Battleship Program C++ NEED HELP

For many of us old school gamers, we started out playing good old fashioned board games. Many of us learned strategy from games like Risk and Battleship. For your project, you will be developing a simple battleship type game to test your knowledge of the concepts we have learned in Object Oriented Programming.

 

The purpose of this project is to have you design of a fairly complicated project using concepts we have learned and then implement the solution using some of the code that we wrote in the previous projects along with new code, and then test your game.

 

You need to first start with the design of the project. The design documentation, due as shown on the syllabus, will be worth one homework grade and when corrected and submitted will be 20% of your final project grade. If your design is carefully thought through, the coding of the game should be relatively straightforward since many of the classes and concepts closely match previous assignments. You will need to first read these requirements and make a design document (ensuring that all the requirements are met in the design). A sample design document is posted in Canvas and should be used as your design TEMPLATE (example). Create a design document complete with the class diagram and activity (flow) diagram, as well as any decisions you made on the best use of classes, inheritance, polymorphism, and exception handling.

 

After you have completed your design, then you will be ready to implement the game and test. I cannot stress enough that a good design document and understanding of the requirements will make the actual coding of the game much faster and more simple.

 

Please don’t leave things until the last two weeks. Get started now, and please ask your instructor for help BEFORE you get too lost. Get the big picture done first. Worry about the structure and implementation of the major functionality. Then if you have time, work on the little details, and minor error checking.

 

So now onto the requirements. You sunk my battleship!….

 

For your CSCI 2312 Project, you will develop a simple battleship game. Battleship is a guessing game for two players. It is played on four grids. Two grids (one for each player) are used to mark each players’ fleets of ships (including battleships). The locations of the fleet (these first two grids) are concealed from the other player so that they do not know the locations of the opponent’s ships. Players alternate turns by ‘firing torpedoes’ at the other player’s ships. The objective of the game is to destroy the opposing player’s entire fleet. In our game, ‘firing a torpedo’ will be allowing the player to take a guess at where on the grid their opponent may have placed a ship.

 

In the requirements, we will set forth other simplifying rules to limit the scope of this project.

 

Requirements

 

Given the requirements as a rough specification, you are to design the classes and implement the game. In our imaginary game company, the requirements below were developed by the Product Development Team and your instructor is the Product Owner. You are in full control of the choice of classes (please use classes appropriately or points will be deducted), data structures, algorithms, internal file format, detailed user interface scheme, or any other pertinent design decisions you need to make. As the Product owner, I care that it compiles and runs like it is supposed to, meets all the functionality and requirements I have set forth, and is easy to play and understand.

 

The Battleship game you are designing and implementing is a simplified version of the electronic Battleship game played in one player mode.

 

The game is played on four grids, two for each player. The grids are typically square and in our case will be 10 by 10. The individual squares in the grid are identified by the x coordinate (indicated by a letter) followed by the y coordinate (indicated by a number). The following is an example of a 5 by 4 grid with an X in the position B3.

 

A B C D E

         
         
   

X

     
         

 

1

 

2

 

3

 

4

 

 

 

Each player uses two grids. Each player uses one of their grids to arrange their ships and record the torpedoes fired by the opponent. On the other grid, the player records their own shots and whether they hit or missed.

 

Before play begins, each player secretly arranges their ships on their primary grid. Each ship occupies a certain number of consecutive squares on the grid (sizes of ships are in the following table), arranged either horizontally or vertically. The number of squares for each ship is determined by the type of the ship. The ships cannot overlap so only one ship can occupy any given square in the grid. The types and numbers of ships allowed are the same for each player.

 

Ship Type Number of Grid Squares
Carrier 5
Battleship 4
Cruiser 3
Submarine 3
Detroyer 2

 

 

The game is played in rounds. In each round, each player takes a turn to fire a torpedo at a target square in the opponent’s grid. The opponent then indicates whether the shot was a hit (a ship occupied the square) or a miss (there was not ship in the square). If the shot is a “miss”, the player marks their primary grid with a white peg (X in our game); if a “hit” they mark this on their own primary grid with a red peg (O in our game). The attacking player then indicates the hit or miss on their own “tracking” grid with the appropriate color peg (red (0) for “hit”, white (X) for “miss”) so that they can understand where the opponent’s ship might be.

 

In the board game, once all of the coordinates of a ship have been hit, the ship is sunk, and the ship’s owner announces “You sunk my battleship! (Or whatever the particular ship that was destroyed). For our purposes, we will consider a battleship sunk if the opponent has a single hit. When all of one player’s ships are sunk, the other player wins the game.

 

For your game, you will create a one-person version of the game where ‘the computer’ will play for the second player.

 

At the beginning of the game, you will read a file called ship_placement.csv which contains the type of ship, the first grid square for the ship placement, and whether the ship is placed vertically or horizontally (V or H in the field). The file will be in csv format (comma separated values). This is a common format and is comma separated (instead of being on separate lines). There will be commas between the values. Blank values will just have a comma noting to go to the next field (the game input should not have blank fields so you should handle the case where a field is blank). If you want to view the file, often this will be opened by a spreadsheet unless you specifically open it with a text editor. Do not open it with Microsoft Word, as this may change the format. The first line of a CSV file notes the data descriptions as follows:

TypeOfShip,Location,HorizOrVert

 

I have provided several sample files which contain good scenarios and scenarios with placement issues that you will need to handle using exception handling. Your game should run with any of these files, but should also be able to run with any valid file in the correct format. You will need to check whether all ships were included in the input file (and appropriate action to take if not), whether all ships have been placed, whether they fit on the board in the configuration given, and whether more than one ship occupies a space (which is not allowed) when you read the input file from the user and how to recover if an error occurs.

 

You will then need to randomly position the computer’s ships on the grid taking into consideration the same factors as you did for the player’s input.

 

You will need to prompt for and allow for the user to input their next guess in the form of a letter (A through J) and a number (1 – 10) indicating where they are targeting for their torpedo and you should error check the input. In our simplified game, you will determine if the torpedo shot was a hit or a miss. If the shot was a hit, consider the ship to be sunk. You should display a hit or miss, whether the ship was sunk and which one, and display their tracking grid so they know what they have guessed and where they have made hits. The entire ship which was hit will display as sunk.

 

After the user takes their turn, you must have the computer randomly select a shot that they have not previously taken. Then you must display to the user what the computer guessed, whether it hit any of the player’s ships, whether a ship was sunk, and then display the player’s placement grid showing where ships are located and what has been hit.

 

You should continue this until someone wins or quits the game – meaning you should allow the player to gracefully quit at any turn.

 

At the end of the game, you should indicate the game is over and who the winner was. You should also allow the user to quit the game by entering a Q when prompted for their next guess. If a player decides to quit the game, the grid with all of their guesses and the locations of the computer’s ships should be displayed.

Overall System Design

1. You must have two different classes in your design.

2. You must use inheritance in one of the classes.

3. When reading from a data file, your program should test the input file to ensure that data is of valid format (basic error detection) using Exception Handling.

4. You should consider using the Grids from Assignment 2 to make this easier. You do not need to have 4 grids for this but if you decide to use only two grids, you need to make sure you do not show the player the computer’s ship location when you display the grid after each turn.

5. Each component of the overall program should be modular.

1. Program should be fairly fault tolerant of user input and the appropriate user prompts and on-screen directions should be displayed

1. Split the program into multiple files based on the roughly categorized functionality or classes.

Extra Challenge / Extra Credit

Some of you may want an extra challenge to boost your abilities and have some interesting resume material. If you have completed all of the requirements above and want an additional challenge, you can incorporate fully sinking the ships and additional logic to be used by the computer when it makes a hit. After determining whether the shot was a hit or miss, you will then need to determine if the ship was sunk. In the simplified version of the game above, one torpedo hit sunk the ship. For the extra credit, you will need to accurately track all hits on a ship to determine if it was sunk. If it was sunk, you will need to tell the player, “you sunk my XXXship” where XXX indicates which type of ship and then displays the information as described in the simplified version above. Additionally, you will need to add logic to the random selection of torpedo shots for the computer. When the computer takes a random shot that hits a ship, the next series of shots will need to be logically selected until the hit ship is sunk.

 

If you do the extra credit, please note this in your documentation and make it clear in the running of the program, so we can give you up to 15% extra credit. (meaning you could get 115% on the project). Note: Since this is extra credit, it needs to meet a higher standard for full extra credit).

 

 

 

 

 

1

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

ND Wk8

Network Defense and

Countermeasures

by Chuck Easttom

Chapter 14: Physical Security and Disaster Recovery

 

 

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 2

Objectives

 Understand Physical Security

 Implement Physical Security

 Understand Disaster Recovery

 Understand Business Continuity

 

 

Definition: Physical Security

 The physical measures and their associated

procedures to safeguard and protect against:

 Damage

 Loss

 Theft

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 3

 

 

Required Physical Controls

 Perimeter and Building Grounds

 Building Entry Points

 Inside the Building – Building Floors / Offices

 Data Centers or Server Room Security

 Computer Equipment Protection

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 4

 

 

Examples of Threats

 Emergencies

 Fire and Smoke Contaminants

 Building Collapse or Explosion

 Utility Loss (Power, AC, Heat)

 Water Damage (Broken Pipes)

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 5

 

 

Fire Prevention

 Use Fire Resistant Materials for Walls, Doors, Furnishings, etc.

 Reduce the Amount of Combustible Papers Around Electrical Equipment

 Provide Fire Prevention Training to Employees  REMEMBER: Life Safety is the Most Important

Issue!

 Conduct Fire Drills on All Shifts So that Personnel Know How to Exit A Building

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 6

 

 

Fire Detection

 Automatic Dial-Up Fire Alarm

 System Dials the Local Fire or Police Department and

Plays a Prerecorded Message When a Fire is

Detected

 Usually Used in Conjunction with One of the Other

Type of Fire Detectors

 This Type of System Can Be Easily/Intentionally

Subverted

 Combinations are Usually Used for The Best

Effectiveness in Detecting a Fire

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 7

 

 

Fire Suppression

 Carbon Dioxide (CO2), Foam, Inert Gas and

Dry Power Extinguishers DISPLACE Oxygen

to Suppress a Fire

 CO2 Is a Risk to Humans (Because of

Oxygen Displacement)

 Water Suppresses the Temperature

Required to Sustain a Fire

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 8

 

 

Fire Suppression – Halon

 Halon Banned for New Systems Under 1987

Montreal Protocol on Substances that Deplete

the Ozone Layer

 Began Implementation of Ban in 1992

 Any New Installations of Fire Suppression systems

Must Use Alternate Options

 EU Requires Removal of Halon for Most Applications

 Halon Replacements:

 FM200,

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 9

 

 

Safety Fire Extinguishers

 Class A – Ordinary combustibles such as

wood or paper.

 Class B – Flammable liquids such as grease,

oil, or gasoline.

 Class C – Electrical Equipment

 Class D – Flammable Metals

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 10

 

 

Fire Suppression – Water

 Wet Pipe  Always Contains Water

 Most Popular and Reliable

 165° Fuse Melts  Can Freeze in Winter

 Pipe Breaks Can Cause Floods

 Dry Pipe  No Water in Pipe

 Preferred for Computer Installations

 Water Held Back by Clapper

 Air Blows Out of Pipe, Water Flows

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 11

 

 

Fire Suppression – Water

 Deluge

 Type of Dry Pipe

 Water Discharge is Large

 Not Recommended for Computer Installations

 Preaction

 Most Recommended for Computer Room

 Combines Both Dry and Wet Pipes

 Water Released into Pipe First Then After Fuse Melts in Nozzle the Water is Dispersed

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 12

 

 

What Is a Disaster

 Any natural or man-made event that disrupts

the operations of a business

in such a significant way that a considerable

and coordinated effort is required to achieve

a recovery.

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 13

 

 

How BCP and DRP

Support Security  BCP (Business Continuity Planning) and

DRP (Disaster Recovery Planning)

 Security pillars: C-I-A

 Confidentiality

 Integrity

 Availability

 BCP and DRP directly support availability

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 14

 

 

BCP and DRP Differences

and Similarities  BCP

 Activities required to ensure the continuation of

critical business processes in an organization

 Alternate personnel, equipment, and facilities

 Often includes non-IT aspects of business

 DRP

 Assessment, salvage, repair, and eventual

restoration of damaged facilities and systems

 Often focuses on IT systems

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 15

 

 

The Role of Prevention

 Not prevention of the disaster itself

 Prevention of surprise and disorganized response

 Reduction in impact of a disaster

 Better equipment bracing

 Better fire detection and suppression

 Contingency plans that provide [near] continuous

operation of critical business processes

 Prevention of extended periods of downtime

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 16

 

 

Running a BCP / DRP Project

 Main phases

 Pre-project activities

 Perform a Business Impact Assessment (BIA)

 Develop business continuity and recovery

plans

 Test resumption and recovery plans

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 17

 

 

Performing a Business

Impact Analysis  Asset Analysis

 Purchase cost, development cost, administrative

cost, maintenance cost.

 Survey critical processes

 Perform risk analyses and threat assessment

 Determine Maximum Tolerable Downtime

(MTD)

 Establish key recovery targets

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 18

 

 

RAID

 RAID 0 (striped disks) distributes data across multiple disks in a way that gives improved speed at

any given instant. NO fault tolerance

 RAID 1 mirrors the contents of the disks, making a form of 1:1 ratio realtime backup. Also called

mirroring

 RAID 3 or 4 (striped disks with dedicated parity) combines three or more disks in a way that protects

data against loss of any one disk. Fault tolerance is achieved by adding an extra disk to the array and

dedicating it to storing parity information. The storage capacity of the array is reduced by one disk

 RAID 5 (striped disks with distributed parity) combines three or more disks in a way that protects data

against the loss of any one disk. It is similar to RAID 3 but the parity is not stored on one dedicated

drive, instead parity information is interspersed across the drive array. The storage capacity of the

array is a function of the number of drives minus the space needed to store parity

 RAID 6 (striped disks with dual parity) combines four or more disks in a way that protects data against

loss of any two disks.

 RAID 1+0 (or 10) is a mirrored data set (RAID 1) which is then striped (RAID 0), hence the “1+0”

name. A RAID 1+0 array requires a minimum of four drives: two mirrored drives to hold half of the

striped data, plus another two mirrored for the other half of the data.

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 19

 

 

Backups

 Full – all changes

 Differential – all changes since last full backup

 Incremental – all changes since last backup of

any type

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 20

 

 

Summary

 Physical security involves lighting, locks,

fences, and physical access control.

 Fire suppression systems are an important

part of physical security.

 A Business Impact Analysis must be done

before disaster recovery.

 RAID is a fundamental part of fault tolerance.

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 21

 

 

Summary cont.

 Disaster Recovery Plans are aimed at

restoring full normal operations.

 Business Continuity Plans are designed to

maintain some level of operations until full

recovery can be achieved.

 Data backups are a significant part of fault

tolerance and disaster recovery.

© 2014 by Pearson Education, Inc. Chapter 14 Physical Security and Disaster

Recovery 22

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

Excel Test

QUESTION 1

  1. The ways that HLOOKUP formula works is searching down instead of across data. True
    False

0.9 points  

QUESTION 2

  1. The AND formula takes a list of Booleans and returns TRUE if all of them are true, and FALSE otherwise. True
    False

0.9 points  

QUESTION 3

  1. How would Excel evaluate the following formula? =OR(7<5, A2=6,NOT(“zebra”<=”tree”))? Assume that the formula is in cell D4, the workbook contains no circular references, and outside of cell D4 the workbook contains no errors.TRUEFALSEIt would return an errorThere is insufficient information to answer this question

1.4 points  

QUESTION 4

  1. One of the benefits of using the Table feature is that you’ll be able to see the column titles at every moment. True
    False

0.9 points  

QUESTION 5

  1. Use the brewery.xlsx file to answer the following question: How many total transactions took place at Beerland Amherst?3527425844258542194315939

0.9 points  

QUESTION 6

  1. Use the file Code_Enforcement_-_Building_and_Property_Violations.xlsx for this question.
    What is the total dollar amount of penalties for closed cases in Charlestown due to residents’ improper storage of trash (improper storage trash:res)?

1.4 points  

QUESTION 7

  1. Use the Brewery.xlsx file to answer the following question: What s the name of the beer with the highest Alcohol by Volume (ABV)?Half LordGear ShiftSheep MojoRed Salty HoserGnu Breath

0.9 points  

QUESTION 8

  1. The PivotTable functionality is located in the Data tab. True
    False

0.9 points  

QUESTION 9

  1. Use the Brewery.xlsx file to answer the following question: How many beers product names have order quantities between 3000 and 12000?75689

1.4 points  

QUESTION 10

  1. Which of the following functions returns a range of cells?OFFSETCOUNTAMATCHREDEFINENone of the given choices

0.9 points  

QUESTION 11

  1. A named range can be usedwhen creating chartsin formulasin functionsnone of the given choicesall of the given choices

0.9 points  

QUESTION 12

  1. Which of the following statements is correct if new data will be attached as a new row to the existing table?OFFSET( base cell, 0, 0, 1, COUNTA (larger range in row where potential data may appear) )OFFSET( base cell, 0, 0, COUNTA (larger range in row where potential data may appear),1)OFFSET( base cell, COUNTA (larger range in row where potential data may appear), 0, 0,1)OFFSET( base cell, 0, COUNTA (larger range in row where potential data may appear), 0,1)None of the given choices

1.4 points  

QUESTION 13

  1. One of the primarily characteristics of Solver is the mathematical relationship between the objective, the constraints, and the decision variables. True
    False

0.9 points  

QUESTION 14

  1. The Solver and Analysis Toolpak Add-ins are not built in to Excel. True
    False

0.9 points  

QUESTION 15

  1. Use solver to answer the following question: A manufacturing concern wishes to minimize its shipping costs between its 4 factories and 3 warehouses. Factory 1 supplies 1000 units per week and costs $5, $3, and $4 to ship each unit to Warehouses 1, 2, and 3 respectively. Factory 2 supplies 1200 units each week and costs $4, $3, and $3 to ship to Warehouses 1, 2, and 3. Factory 3 supplies 1500 units and costs $6, $2, and $5 to ship to the three warehouses. Factory 4 supplies 1800 units and costs $6, $2, and $4.
    If Warehouse 1 requires 3000 units per week, Warehouse 2 demands 1000, and Warehouse 3 demands 1500, what is the minimum it would cost them in shipping to fulfill each warehouse’s demand?
 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

Visio Networking Diagrams

I need three network diagrams made from Visio.  I have attached the base of the network diagram that was turned in for the first assignment.  Here is the information about the company that I am creating the networking diagram for:

 

ABOUT US

Bit Consulting Services is a small computer consulting company with 15 employees that consult computer solutions with a variety of small to medium sized companies. Bit Consulting specializes in Cloud services and mobile technologies for companies wanting to be at the forefront of technology for their customer solutions. Contact us and we will show you why Bit Consulting Services is the best in business!

 

This first diagram has to add:

Update your corporate network diagram to include branch offices and remote sites.  If your company only has one site, you must assume that at least one executive insists on operating a home office. Also, assume that any manufacturing operations are located in a separate building/site.
Update your network infrastructure using Cisco Packet Tracer to reflect VPN technologies.
Update your network diagram to reflect VPN technologies.

The second diagram has to add:

Update your network diagram to include separate subnets for all major departments in your corporation. You will need to subnet appropriately to account for all workstations, printers, and servers for each network and subnet.

Ensure that all manufacturing systems are appropriately airgapped by including a separate router and VLAN for those departments.

 

The third diagram has to add:

Update your network diagram to include IPv6 network addresses and subnets.

 

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

Homework Of Computer Networking

CSE422 Section 002 – Computer Networking Fall 2018

Homework 2 – 50 points Sockets (10 points)

1. For a client-server application over TCP, why must the server program be executed before the client program?

2. For a client-server application over UDP, why may the client program be executed before the server program?

3. The UDP server shown in the course slides needed only one socket, whereas the TCP server needed two sockets. Why?

4. If the TCP server were to support N simultaneous connections, each from a different client host, how may sockets would the TCP server need?

5. You are creating an event logging service that will be handling event messages from multiple remote clients. This service can suffer delays in message delivery and even the loss of some event messages. Would you implement this using TCP or UDP? Why?

The HTTP GET message (10 Points) Consider the figure below, where a client is sending an HTTP GET message to a web server, gaia.cs.umass.edu.

Suppose the client-to-server HTTP GET message is the following:

GET /kurose_ross/interactive/quotation1.htm HTTP/1.1

Host: gaia.cs.umass.edu

Accept: text/plain, text/html, image/gif, image/jpeg, audio/basic,

audio/vnf.wave, video/mp4, video/wmv, application/*, */*

Accept-Language: en-us, en-gb;q=0.5, en;q=0.1, fr, fr-ch, zh, cs

If-Modified-Since: Wed, 10 Jan 2018 13:13:03 -0800

User Agent: Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML,

like Gecko) Chrome/17.0.963.56 Safari/535.11

Answer the following questions:

1. What is the name of the file that is being retrieved in this GET message?

2. What version of HTTP is the client running?

 

 

CSE422 Section 002 – Computer Networking Fall 2018

3. What formats of text, images, audio, and video does the client browser prefer to receive? [Note: for this and the following questions on browser media and language preferences, you will need to do a bit of additional reading on the Web. Here is a good place to start.]

4. What do the strings “application/*” and “*/*” signify in the Accept: header?

5. What languages is the browser indicating that it is willing to accept? [Note: you can look at your own browser preferences to get a listing of language codes.]

6. What is the meaning of the “relative quality factor,” q, associated with the various version of English? [Note: Here is a good place to start. See also [RFC 2616].]

7. What is the client’s preferred version of English? What is the browser’s least preferred version of English?

8. Does the browser sending the HTTP message prefer Swiss French over traditional French? Explain.

9. Does the client already have a (possibly out-of-date) copy of the requested file? Explain. If so, approximately how long ago did the client receive the file, assuming the GET request has just been issued?

10. What is the type of client browser and the client’s operating system? [Note: To answer this, you’ll need to understand the User Agent: header field. Here is a good place to start.]

The HTTP RESPONSE message (10 Points) Consider the figure below, where the server is sending a HTTP RESPONSE message back the client.

 

Suppose the server-to-client HTTP RESPONSE message is the following:

HTTP/1.1 200 OK

Date: Wed, 10 Jan 2018 21:23:35 +0000

Server: Apache/2.2.3 (CentOS)

Last-Modified: Wed, 10 Jan 2018 21:35:35 +0000

ETag:17dc6-a5c-bf716880.

Content-Length: 77385

Keep-Alive: timeout=41, max=92

Connection: Keep-alive

Content-type: image/html

Answer the following questions:

 

 

CSE422 Section 002 – Computer Networking Fall 2018

1. Is the response message using HTTP 1.0 or HTTP 1.1? Explain.

2. Was the server able to send the document successfully? Explain

3. At what date and time was this response sent?

4. When was the file last modified on the server?

5. How many bytes are there in the document being returned by the server?

6. What is the default mode of connection for HTTP protocol? Is the connection in the reply persistent or non-persistent? Explain.

7. What is the type of file being sent by the server in response?

8. Does the response message use separate keep-alive messages?

9. What is the name of the server and its version? List the advantages of the server used.

10. What is the timeout value for the response message?

DNS and HTTP delays (10 points) Before doing this question, you might want to review sections 2.2.1 and 2.2.2 on HTTP (in particular the text surrounding Figure 2.7) and the operation of the DNS (in particular the text surrounding Figure 2.19).

Suppose within your Web browser you click on a link to obtain a Web page. The IP address for the associated URL is not cached in your local host, so a DNS lookup is necessary to obtain the IP address. Suppose that four DNS servers are visited before your host receives the IP address from DNS. The first DNS server visited is the local DNS cache, with an RTT delay of RTT0 = 1 msecs. The second, third and fourth DNS servers contacted have RTTs of 31, 47, and 25 msecs, respectively. Initially, let’s suppose that the Web page associated with the link contains exactly one object, consisting of a small amount of HTML text. Suppose the RTT between the local host and the Web server containing the object is RTTHTTP = 14 msecs.

1. Assuming zero transmission time for the HTML object, how much time elapses from when the

client clicks on the link until the client receives the object?

 

 

CSE422 Section 002 – Computer Networking Fall 2018

2. Now suppose the HTML object references 7 very small objects on the same web server. Neglecting transmission times, how much time elapses from when the client clicks on the link until the base object and all 7 additional objects are received from web server at the client, assuming non-persistent HTTP and no parallel TCP connections?

3. Repeat 2. above but assume that the client is configured to support a maximum of 5 parallel TCP connections, with non-persistent HTTP.

4. Repeat 2. above but assume that the client is configured to support a maximum of 5 parallel TCP connections, with persistent HTTP.

5. What do you notice about the overall delays (taking into account both DNS and HTTP delays) that you computed in cases 2., 3. and 4. above?

Question: Reliable UDP data transfer (5 points) Is it possible for an application to enjoy reliable data transfer even when the applications run over UDP? If so, how?

Question: NAK-only vs ACK-only (5 points) Consider a reliable data transfer protocol that uses only negative acknowledgments. Suppose the sender sends data only infrequently. Would a NAK-only protocol be preferable to a protocol that uses ACKs? Why? Now suppose the sender has a lot of data to send and the end-to-end connection experiences few losses. In this case, would a NAK-only protocol be preferable to a protocol that uses ACKs? Why?

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

1. How Many Different Estimating Techniques Were Discussed In The Case? 2. If Each Estimate Is Different, How Does A Project Manager Decide That One Estimate Is Better Than Another? 3. If You Were The Project Manager, Which Estimate Would You Use?

APA FORMATE

ADD REFERENCES      AT END

Barbara just received the good news: She was assigned as the project manager for a project that her company won as part of competitive bidding. Whenever a request for proposal (RFP) comes into Barbara’s company, a committee composed mainly of senior managers reviews the RFP. If the decision is made to bid on the job, the RFP is turned over to the Proposal Department. Part of the Proposal Department is an estimating group that is responsible for estimating all work. If the estimating group has no previous history concerning some of the deliverables or work packages and is unsure about the time and cost for the work, the estimating team will then ask the functional managers for assistance with estimating.

Project managers like Barbara do not often participate in the bidding process. Usually, their first knowledge about the project comes after the contract is awarded to their company and they are assigned as the project manager. Some project managers are highly optimistic and trust the estimates that were submitted in the bid implicitly unless, of course, a significant span of time has elapsed between the date of submittal of the proposal and the final contract award date. Barbara, however, is somewhat pessimistic. She believes that accepting the estimates as they were submitted in the proposal is like playing Russian roulette. As such, Barbara prefers to review the estimates.

One of the most critical work packages in the project was estimated at twelve weeks using one grade 7 employee full time. Barbara had performed this task on previous projects and it required one person full time for fourteen weeks. Barbara asked the estimating group how they arrived at this estimate. The estimating group responded that they used the three-point estimate where the optimistic time was four weeks, the most likely time was thirteen weeks, and the pes- simistic time was sixteen weeks.

Barbara believed that the three-point estimate was way off of the mark. The only way that this work package could ever be completed in four weeks would be for a very small project nowhere near the complexity of Barbara’s project. Therefore, the estimating group was not con- sidering any complexity factors when using the three-point estimate. Had the estimating group used the triangular distribution where each of the three estimates had an equal likelihood of occurrence, the final estimate would have been thirteen weeks. This was closer to the fourteen weeks that Barbara thought the work package would take. While a difference of 1 week seems small, it could have a serious impact on Barbara’s project and incur penalties for late delivery.

 

1. ©2010 by Harold Kerzner. Reproduced by permission. All rights reserved.

 

Case Study 735 

 

Barbara was now still confused and decided to talk to Peter, the employee that was assigned to do this task. Barbara had worked with Peter on previous projects. Peter was a grade 9 employee and considered to be an expert in this work package. As part of the discussions with Barbara, Peter made the following comments:

I have seen estimating data bases that include this type of work package and they all esti- mate the work package at about 14 weeks. I do not understand why our estimating group prefers to use the three point estimate.

“Does the typical data base account for project complexity when considering the esti- mates?” asked Barbara. Peter responded:

Some data bases have techniques for considering complexity, but mostly they just assume an average complexity level. When complexity is important, as it is in our project, analogy estimating would be better. Using analogy estimating and comparing the complexity of the work package on this project to the similar works packages I have completed, I would say that 16–17 weeks is closer to reality, and let’s hope I do not get removed from the project to put out a fire somewhere else in the company. That would be terrible. It is impossible for me to get it done in 12 weeks. And adding more people to this work package will not shorten the schedule. It may even make it worse.

Barbara then asked Peter one more question:

Peter, you are a grade 9 and considered as the subject matter expert. If a grade 7 had been assigned, as the estimating group had said, how long would it have taken the grade 7 to do the job?

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

Module 6 Discussion

 

Module 6 Discussion Forum

Include at least 250 words in your posting and at least 250 words in your reply.  Indicate at least one source or reference in your original post. Please see syllabus for details on submission requirements.

Module 6 Discussion Question

Search “scholar.google.com” or your textbook. Include at least 250 words in your reply.  Indicate at least one source or reference in your original post.  Discuss ways organizations have built a CSIRT. What are the components to building an effective and successful CSIRT team?

Reply-1(Vindhya)

 

In the building, an effective and successful CSIRT the steps involved are as follows:

1. Buy-In and support of management are obtained: the creation of an effective incident response team becomes problematic and difficult without the support of the management. The support includes time, funding, and provision of resources to the team (D. Penedo, 2006). The important responsibility and function of the CSIRTs are obtaining managements perceptions and expectations.

2. The strategic plan of CSIRT development is determined: by dealing with the administrative issues and addressing the project management issues the development of CSIRT is to be managed.

3. Relevant information is gathered: the service needs of the organization and to determine the incident response the information is gathered. In gathering the information the resources available are inventories of assets and critical system, for enterprise the organization charts and functions of specific business, networks, and systems organizational topologies, plans of business-continuity or existing disaster recovery, the physical security breach of organization is notified by existing guidelines, existing plans of incident-management, regulations of institution or parental, and existing security policies and procedures.

4. CSIRT vision is designed: The key components of the CSIRT are identified by bringing the gathered information to incident response constituency needs. For creating, CSIRT vision the points to be followed are (Z. Yunos, 2016): Constituency identification, the goals, objectives, and mission of CSIRT are defined, CSIRT services are selected and provided to the constituency, the organizational model is determined, required resources are identified, and CSIRT funding is determined.

5. The vision of CSIRT is communicated: the operational plan and vision are communicated to constituency, management, and others involved in the operation and feedbacks are obtained. Communicating vision before implementation helps in identification of problems.

6. CSIRT implementation begins: the steps involved in implementation are the CSIRT staff is hired and trained, in supporting team the necessary infrastructure is built and equipment are bought, the initial set of CSIRT procedures and policies are developed, the specifications of incident-tracking system are defined and the forms and guidelines of incident-reporting are developed for a constituency.

7. CSIRT announcement: broadly announce to constituency when CSIRT is operational also include the operation hours and contact information.

8. The effectiveness of CSIRT is evaluated: information on effectiveness is gathered by including against other CSIRTs the benchmark, with constituency representatives the general discussions involved, on a periodic basis the surveys of evaluation are distributed to members of the constituency, and in evaluating the team the quality parameters or set of criteria created by an audit.

References:

D. Penedo (2006), Optimal Policy for Software Vulnerability Disclosure. Good practice guide for CERTs in the area of Industrial Control Systems – Computer Emergency Response Capabilities considerations for ICS.

Z. Yunos (2016), Creating and Managing Computer Security Incident Handling Teams (CSIRTs), CERT Training and Education Networked Systems Survivability Software Engineering Institute Carnegie Mellon University.

Reply-2 ( Glad)

 

CSIRT (Computer Security Incident Response Team) is a team within an organization which responds to threats or incidents as they occur within the organization. Their responsibilities include,

–          Maintaining and creating an incident response plan

–          Identifying, troubleshoot and remediation of any incidents

–          Communication methods for incident responses

–          Combing the organization and proactively identifying and physical or network security threats.

–          Recommending technologies, policy updates, governance updates based off the past threats

Keeping in mind the roles and responsibilities of this team, to build a team to perform these activities and own the responsibilities, the first step towards creating this team would be to buy management support to ensure they are in agreement with the creation of such a team and are on board to sign off on the resource allocation and budget as well as procedural aspects of building a CSIRT team.

The next step would be to create a strategic development plan on the various facets the team should possess and within which time frame team should be formed. The plan should be feasible and the timelines realistic and also care has to be taken to ensure the plan aligns with overall objectives of the organization.

After the strategic plan is developed, information should be gathered to ensure all aspects of the CSIRT team is covered based on the types of policies formulated, types of threats assessed and the services that are to be offered. The team will have to be picked based on the information at this stage.

Once the team is aligned and the vision is set, the vision of this team and its operations will have to be communicated within the organization to bring about an awareness on what this team could do.

Post the organizational wide announcement and policy implementation, the team goes live into operations and implements all the guidelines and procedures thereby serving the organization.

References:

Fuertes, W., Reyes, F., Valladares, P., Tapia, F., Toulkeridis, T., & Pérez, E. (2017). An Integral Model to Provide Reactive and Proactive Services in an Academic CSIRT Based on Business Intelligence. Systems5(4), 52. doi: 10.3390/systems5040052

Möller, K. (2007). Setting up a Grid‐CERT: experiences of an academic CSIRT. Campus-Wide Information Systems24(4), 260-270. doi: 10.1108/10650740710834644

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

CS 210 Project 3 Grocery C++ And Python

Hello,

Can anyone help me?  I am completely lost.

Competency

In this project, you will demonstrate your mastery of the following competency:

  • Utilize various programming languages to develop secure, efficient code

Scenario

You are doing a fantastic job at Chada Tech in your new role as a junior developer, and you exceeded expectations in your last assignment for Airgead Banking. Since your team is impressed with your work, they have given you another, more complex assignment. Some of the code for this project has already been completed by a senior developer on your team. Because this work will require you to use both C++ and Python, the senior developer has given you the code to begin linking between C++ and Python. Your task is to build an item-tracking program for the Corner Grocer, which should incorporate all of their requested functionality.

The Corner Grocer needs a program that analyzes the text records they generate throughout the day. These records list items purchased in chronological order from the time the store opens to the time it closes. They are interested in rearranging their produce section and need to know how often items are purchased so they can create the most effective layout for their customers. The program that the Corner Grocer is asking you to create should address the following three requirements for a given text-based input file that contains a list of purchased items for a single day:

  1. Produce a list of all items purchased in a given day along with the number of times each item was purchased.
  2. Produce a number representing how many times a specific item was purchased in a given day.
  3. Produce a text-based histogram listing all items purchased in a given day, along with a representation of the number of times each item was purchased.

As you complete this work, your manager at Chada Tech is interested to see your thought process regarding how you use the different programming languages, C++ and Python. To help explain your rationale, you will also complete a written explanation of your code’s design and functionality.

Directions

One of Python’s strengths is its ability to search through text and process large amounts of data, so that programming language will be used to manage internal functions of the program you create. Alternatively, C++ will be used to interface with users who are interested in using the prototype tracking program.

Grocery Tracking Program
Begin with a Visual Studio project file that has been set up correctly to work with both C++ and Python, as you have done in a previous module. Remember to be sure you are working in Release mode, rather than Debug mode. Then add the CS210_Starter_CPP_Code and CS210_Starter_PY_Code files, linked in the Supporting Materials section, to their appropriate tabs within the project file so that C++ and Python will be able to effectively communicate with one another. After you have begun to code, you will also wish to access the CS210_Project_Three_Input_File, linked in the Supporting Materials section, to check the functionality and output of your work.

As you work, continue checking your code’s syntax to ensure your code will run. Note that when you compile your code, you will be able to tell if this is successful overall because it will produce an error message for any issues regarding syntax. Some common syntax errors are missing a semicolon, calling a function that does not exist, not closing an open bracket, or using double quotes and not closing them in a string, among others.

  1. Use C++ to develop a menu display that asks users what they would like to do. Include options for each of the three requirements outlined in the scenario and number them 1, 2, and 3. You should also include an option 4 to exit the program. All of your code needs to effectively validate user input.
  2. Create code to determine the number of times each individual item appears. Here you will be addressing the first requirement from the scenario to produce a list of all items purchased in a given day along with the number of times each item was purchased. Note that each grocery item is represented by a word in the input file. Reference the following to help guide how you can break down the coding work.
    • Write C++ code for when a user selects option 1 from the menu. Select and apply a C++ function to call the appropriate Python function, which will display the number of times each item (or word) appears.
    • Write Python code to calculate the frequency of every word that appears from the input file. It is recommended that you build off the code you have already been given for this work.
    • Use Python to display the final result of items and their corresponding numeric value on the screen.
  3. Create code to determine the frequency of a specific item. Here you will be addressing the second requirement from the scenario to produce a number representing how many times a specific item was purchased in a given day. Remember an item is represented by a word and its frequency is the number of times that word appears in the input file. Reference the following to help guide how you can break down the coding work.
    1. Use C++ to validate user input for option 2 in the menu. Prompt a user to input the item, or word, they wish to look for. Write a C++ function to take the user’s input and pass it to Python.
    2. Write Python code to return the frequency of a specific word. It will be useful to build off the code you just wrote to address the first requirement. You can use the logic you wrote but modify it to return just one value; this should be a fairly simple change (about one line). Next, instead of displaying the result on the screen from Python, return a numeric value for the frequency of the specific word to C++.
    3. Write a C++ function to display the value returned from Python. Remember, this should be displayed on the screen in C++. We recommend reviewing the C++ functions that have already been provided to you for this work.
  4. Create code to graphically display a data file as a text-based histogram. Here you will be addressing the third requirement from the scenario: to produce a text-based histogram listing all items purchased in a given day, along with a representation of the number of times each item was purchased. Reference the following to help guide how you can break down the coding work:
    1. Use C++ to validate user input for option 3 in the menu. Then have C++ prompt Python to execute its relevant function.
    2. Write a Python function that reads an input file (CS210_Project_Three_Input_File, which is linked in the Supporting Materials section) and then creates a file, which contains the words and their frequencies. The file that you create should be named frequency.dat, which needs to be specified in your C++ code and in your Python code. Note that you may wish to refer to work you completed in a previous assignment where you practiced reading and writing to a file. Some of your code from that work may be useful to reuse or manipulate here. The frequency.dat file should include every item (represented by a word) paired with the number of times that item appears in the input file. For example, the file might read as follows:
      • Potatoes 4
      • Pumpkins 5
      • Onions 3
    3. Write C++ code to read the frequency.dat file and display a histogram. Loop through the newly created file and read the name and frequency on each row. Then print the name, followed by asterisks or another special character to represent the numeric amount. The number of asterisks should equal the frequency read from the file. For example, if the file includes 4 potatoes, 5 pumpkins, and 3 onions then your text-based histogram may appear as represented below. However, you can alter the appearance or color of the histogram in any way you choose.
      • Potatoes ****
      • Pumpkins *****
      • Onions ***
  5. Apply industry standard best practices such as in-line comments and appropriate naming conventions to enhance readability and maintainability. Remember that you must demonstrate industry standard best practices in all your code to ensure clarity, consistency, and efficiency. This includes the following:
    1. Using input validation and error handling to anticipate, detect, and respond to run-time and user errors (for example, make sure you have option 4 on your menu so users can exit the program)
    2. Inserting in-line comments to denote your changes and briefly describe the functionality of the code
    3. Using appropriate variable, parameter, and other naming conventions throughout your code

Programming Languages Explanation
Consider the coding work you have completed for the grocery-tracking program. You will now take the time to think more deeply regarding how you were able to combine two different programming languages, C++ and Python, to create a complete program. The following should be completed as a written explanation.

  1. Explain the benefits and drawbacks of using C++ in a coding project. Think about the user-focused portion of the grocery-tracking program you completed using C++. What control does this give you over the user interface? How does it allow you to use colors or formatting effectively?
  2. Explain the benefits and drawbacks of using Python in a coding project. Think about the analysis portions of the grocery-tracking program you completed using Python. How does Python allow you to deal with regular expressions? How is Python able to work through large amounts of data? What makes it efficient for this process?
  3. Discuss when two or more coding languages can effectively be combined in a project. Think about how C++ and Python’s different functions were able to support one another in the overall grocery-tracking program. How do the two function well together? What is another scenario where you may wish to use both? Then, consider what would happen if you added in a third language or switched Python or C++ for something else. In past courses, you have worked with Java as a possible example. What could another language add that would be unique or interesting? Could it help you do something more effectively or efficiently in the grocery-tracking program?

#include <Python.h>
#include <iostream>
#include <Windows.h>
#include <cmath>
#include <string>

using namespace std;

/*
Description:
To call this function, simply pass the function name in Python that you wish to call.
Example:
callProcedure(“printsomething”);
Output:
Python will print on the screen: Hello from python!
Return:
None
*/
void CallProcedure(string pName)
{
char *procname = new char[pName.length() + 1];
std::strcpy(procname, pName.c_str());

Py_Initialize();
PyObject* my_module = PyImport_ImportModule(“PythonCode”);
PyErr_Print();
PyObject* my_function = PyObject_GetAttrString(my_module, procname);
PyObject* my_result = PyObject_CallObject(my_function, NULL);
Py_Finalize();

delete[] procname;
}

/*
Description:
To call this function, pass the name of the Python functino you wish to call and the string parameter you want to send
Example:
int x = callIntFunc(“PrintMe”,”Test”);
Output:
Python will print on the screen:
You sent me: Test
Return:
100 is returned to the C++
*/
int callIntFunc(string proc, string param)
{
char *procname = new char[proc.length() + 1];
std::strcpy(procname, proc.c_str());

char *paramval = new char[param.length() + 1];
std::strcpy(paramval, param.c_str());

PyObject *pName, *pModule, *pDict, *pFunc, *pValue = nullptr, *presult = nullptr;
// Initialize the Python Interpreter
Py_Initialize();
// Build the name object
pName = PyUnicode_FromString((char*)”PythonCode”);
// Load the module object
pModule = PyImport_Import(pName);
// pDict is a borrowed reference
pDict = PyModule_GetDict(pModule);
// pFunc is also a borrowed reference
pFunc = PyDict_GetItemString(pDict, procname);
if (PyCallable_Check(pFunc))
{
pValue = Py_BuildValue(“(z)”, paramval);
PyErr_Print();
presult = PyObject_CallObject(pFunc, pValue);
PyErr_Print();
}
else
{
PyErr_Print();
}
//printf(“Result is %d\n”, _PyLong_AsInt(presult));
Py_DECREF(pValue);
// Clean up
Py_DECREF(pModule);
Py_DECREF(pName);
// Finish the Python Interpreter
Py_Finalize();

// clean
delete[] procname;
delete[] paramval;

return _PyLong_AsInt(presult);
}

/*
Description:
To call this function, pass the name of the Python functino you wish to call and the string parameter you want to send
Example:
int x = callIntFunc(“doublevalue”,5);
Return:
25 is returned to the C++
*/
int callIntFunc(string proc, int param)
{
char *procname = new char[proc.length() + 1];
std::strcpy(procname, proc.c_str());

PyObject *pName, *pModule, *pDict, *pFunc, *pValue = nullptr, *presult = nullptr;
// Initialize the Python Interpreter
Py_Initialize();
// Build the name object
pName = PyUnicode_FromString((char*)”PythonCode”);
// Load the module object
pModule = PyImport_Import(pName);
// pDict is a borrowed reference
pDict = PyModule_GetDict(pModule);
// pFunc is also a borrowed reference
pFunc = PyDict_GetItemString(pDict, procname);
if (PyCallable_Check(pFunc))
{
pValue = Py_BuildValue(“(i)”, param);
PyErr_Print();
presult = PyObject_CallObject(pFunc, pValue);
PyErr_Print();
}
else
{
PyErr_Print();
}
//printf(“Result is %d\n”, _PyLong_AsInt(presult));
Py_DECREF(pValue);
// Clean up
Py_DECREF(pModule);
Py_DECREF(pName);
// Finish the Python Interpreter
Py_Finalize();

// clean
delete[] procname;

return _PyLong_AsInt(presult);
}

void main()
{
CallProcedure(“printsomething”);
cout << callIntFunc(“PrintMe”,”House”) << endl;
cout << callIntFunc(“SquareValue”, 2);

}

import re

import string

def printsomething():

print (“Hello from python!”)

def PrintMe(v):

print(“You sent me: ” + v)

return 100;

def SquareValue(v):

return v * V

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

Artificial Inteligence Assignment

Unit 3 A

Be sure to carefully follow the syntax and semantics of each representational scheme.

 

For pictorial/graphical representations, you may hand draw them, scan them, and import them into your document. Or, you may use the drawing tools available in your software app.

 

For quantifiers in predicate logic, feel free to use A and E if you are unable to produce the specialized symbols (∀ and ∃)

 

For help with logic, review the handout online. There are many other resources available on predicate logic, for example: http://www.cs.odu.edu/~toida/nerzic/content/logic/pred_logic/intr_to_pred_logic.html

 

1)

Represent the following facts as a set of frames:

“The aorta is a particular kind of artery which has a diameter of 2.5 cm.

An artery is a kind of blood vessel.

An artery always has a muscular wall, and generally has a diameter of 0.4 cm.

A vein is a kind of blood vessel, but has a fibrous wall.

Blood vessels all have tubular form and contain blood.”

 

2)

Represent the following facts in the language of predicate logic:

Every apple is either green or yellow.

No apple is blue.

If an apple is green then it is tasty.

Every man likes a tasty apple.

 

3)

“Herbert is a small hippopotamus who lives in Edinburgh zoo.  Like all hippopotamuses he eats grass and likes swimming.” Represent the above:

· as a semantic network;

· in predicate logic

For quantifiers, feel free to use “A” and “E” if you are unable to produce the specialized symbols

 

 

Unit 3 B

1. Develop a simple set of rules for diagnosing respiratory symptom diseases given patient symptoms, using the following knowledge of typical symptoms. Describe how a simple backward chaining interpreter could be used to go through the possible diagnoses, asking the user questions about their symptoms. If you have an expert system shell available, try implementing a simple diagnosis system based on the above.

· Influenza: Symptoms include a persistent dry cough and a feeling of general malaise.

· Hayfever: Symptoms include a runny nose and sneezing. The patient will show a positive reaction to allergens, such as dust or pollen.

· Laryngitis: Symptoms include a fever, a dry cough, and a feeling of general malaise. A “laryngoscopy” will reveal that the person has an inflamed larynx.

· Asthma: Symptoms include breathlessness and wheezing. If it is triggered by an allergen, such as dust or pollen, it is likely to be “extrinsic asthma”. “Intrinsic asthma” tends to be triggered by exercise, smoke or a respiratory infection.

2. What do you think are the main problems and limitations of the rule-set developed for the question above? What additional knowledge might be useful to deal with more complex or subtle diagnoses?

 

 

 

 

 

 

 

Unit 3 E

 

 

In exercise 1, create the parse tree for each sentence. Sentences which can be recognized will have a complete parse tree while unrecognized sentences will have incomplete parse trees. Be sure to indicate which sentences are recognized.

 

In exercise 2, list the full DCG notation for the extended grammar. Test your grammar by using Amzi prolog.

 

Amzi Prolog allows DCG to be input directly. Therefore, you can enter your grammar exactly as you would create it for problem #2, page 123. For example, you can enter:  sentence –> np(N), vp(N).  etc.

The only “trick” is how to specify the sentence to check for proper grammar. Here’s how:

?- sentence([word1,word2,word3,etc],[]).

note the use of square brackets within the parentheses, each word of the sentence is entered between commas, and the final argument [] (open bracket, close bracket). Thus to check whether “All rabbits eat carrots” is syntactically correct, enter

?- sentence([all,rabbits,eat,carrots],[]).

 

Examples:

?- sentence([the,rabbit,eats,the,carrot],[]).

yes

?- sentence([rabbit,the,carrot,eats,the],[]).

no

 

Submit the .pro file as text copied within the document you submit here. Please upload one document with all exercise answers along with your name and ID#

 

The following is a grammar of a subset of English in DCG notation:

· sentence –> np(N), vp(N).

· np(N) –> det, noun(N).

· vp(N) –> verb(N), np(_).

· noun(s) –> [carrot].

· noun(s) –> [rabbit].

· noun(p) –> [rabbits].

· verb(s) –> [eats].

· det –> [the].

1. Which of the following sentences can be recognized with this Grammar?

· The carrot eats the carrot.

· The rabbits eats the carrot.

· The rabbit eats carrots.

For each sentence which is recognized by the grammar, show its parse tree.

2. Extend the grammar to handle sentences like the following. “All” and “some” should be treated as kinds of determiner (det).

· All rabbits eat carrots.

· Some rabbits eat the carrot.

· The rabbit eats every carrot.

The grammar should NOT allow sentences that are grammatically incorrect because a plural noun (e.g. carrots) is used with a determiner that can only be used with singular nouns (e.g., a, every) or vice versa, e.g.,

· All rabbit eat the carrot.

· A rabbits eat the carrot

· Every rabbits eat the carrots.

Try out your grammar using Prolog.

 

Unit 4 B

Apply the difference operator mask on page 129 to the image on page 128. Notes: use a threshold of 2; use the absolute value of the difference operation; the resulting matrix will be 7×7 rather than 8×8 (as the original is).

 

List the resulting matrix and show your work in computing it. This is a difficult assignment; don’t panic, but work carefully and deliberately.

Please find another attachment for text book

 

Unit 1 D

After you have thoroughly read sections 11.1 – 11.3 in chapter 11 of Computer Science: An Overview. Answer the following questions:

https://eembdersler.files.wordpress.com/2010/09/computer_science_an_overview_11th1.pdf

1. Draw the search tree that is generated by a breadth-first search in an attempt to solve the eight-puzzle from the following start state without the assistance of any heuristic information.  Continue the tree for 5 levels or until a solution is obtained.

  1 3
4 2 5
7 8 6

2. Draw the search tree that is generated by the best-fit algorithm below in an attempt to solve the eight-puzzle from the state shown in the first problem if the number of tiles out of place is used as a heuristic.

. Establish the start node of the state graph as the root of the search tree and record its heuristic value.

. While(the goal note has not been reached)do

2. [Select the leftmost leaf node with the smallest heuristic value of all leaf notes.

2. To this selected node attach as children those nodes that can be reached by a single production.

2. Record the heuristic of each of these new nodes next to the node in the search tree]

. Traverse the search tree from the goal node up to the root, pushing the production associated with each arc traversed onto a stack..

. Solve the original problem by executing the productions as they are popped off the stack.

· Draw the search tree that is generated by the best-fit algorithm as detailed in the previous question in an attempt to solve the eight-puzzle from the following start state, assuming the heuristic used is as follows: Measure the distance each tile is from its destination and add these values to obtain a single quantity.

 1 2 3
5 7 6
4   8

· When solving the eight-puzzle, why would the number of tiles out of place not be as good a heuristic as the one described in the question above.

 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!

Data Analytics Lab 1

Data – Q-#12-Page 53-P02_12

School Overall
albright: Overall score
Peers
albright: Score by peer schools (5.0 is highest score)
Recruiters
albright: Score by recruiters (5.0 is highest score)
GPA
albright: Average undergrad GPA (4.0 is highest)
GMAT
albright: Average GMAT score
Accept Rate
albright: Acceptance rate
Salary
albright: Average starting salary and bonus
Employed1
albright: Percentage of graduates employed at graduation time
Employed2
albright: Percentage of graduates employed 3 months after graduation
Out of State
albright: Out-of-state tuition and fees
Enrollment
albright: Total full-time enrollment
Harvard University (MA) 100 4.8 4.5 3.66 720 11.5% $144,261 87.0% 93.3% $50,830 1,801
Stanford University (CA) 99 4.8 4.5 3.64 726 7.5% $140,771 82.5% 92.6% $48,921 740
Northwestern University (Kellogg) (IL) 93 4.7 4.3 3.51 710 19.4% $130,365 89.3% 94.4% $46,791 1,254
University of Pennsylvania (Wharton) 93 4.8 4.3 3.50 714 16.3% $136,676 84.6% 89.1% $53,030 1,611
Massachusetts Institute of Technology (Sloan) 92 4.8 4.3 3.54 708 15.0% $131,087 79.0% 90.3% $47,034 788
University of Chicago 92 4.7 4.3 3.50 713 21.9% $130,839 87.4% 92.2% $47,938 1,144
University of California–Berkeley (Haas) 89 4.6 4.0 3.56 714 11.7% $126,886 85.1% 91.2% $40,605 500
Dartmouth College (Tuck) (NH) 87 4.3 4.1 3.44 712 16.0% $133,407 85.0% 93.6% $45,900 506
Columbia University (NY) 86 4.5 4.1 3.40 709 15.1% $130,281 78.2% 92.2% $48,566 1,234
Yale University (CT) 85 4.3 4.0 3.52 718 14.4% $117,366 75.6% 94.8% $47,300 382
New York University (Stern) 83 4.3 3.9 3.43 708 13.6% $128,968 82.0% 91.7% $43,942 841
Duke University (Fuqua) (NC) 82 4.4 4.0 3.40 696 30.4% $122,742 83.3% 91.7% $45,813 875
University of Michigan–Ann Arbor 81 4.4 4.0 3.32 706 20.1% $125,773 82.4% 85.3% $45,439 843
University of California–Los Angeles (Anderson) 80 4.2 3.9 3.50 711 19.5% $117,253 74.2% 88.9% $38,563 731
Carnegie Mellon University (PA) 79 4.0 3.8 3.35 690 28.3% $122,944 94.0% 96.2% $48,204 392
University of Virginia (Darden) 79 4.1 4.0 3.35 693 24.6% $126,362 85.1% 90.8% $45,500 644
Cornell University (Johnson) (NY) 78 4.2 3.9 3.30 697 20.6% $122,776 80.7% 90.7% $46,510 593
University of Texas–Austin (McCombs) 74 4.0 3.8 3.39 681 26.7% $116,484 82.4% 88.7% $40,900 540
Georgetown University (McDonough) (DC) 71 3.6 3.6 3.35 678 30.2% $114,463 87.9% 98.2% $41,934 522
University of North Carolina–Chapel Hill (Kenan-Flagler) 70 4.0 3.8 3.30 678 34.3% $110,202 78.5% 86.5% $42,239 562
University of Southern California (Marshall) 70 3.9 3.5 3.32 692 23.0% $104,382 80.1% 93.7% $44,502 426
Emory University (Goizueta) (GA) 69 3.8 3.7 3.40 680 28.1% $108,107 70.7% 86.0% $41,428 373
Georgia Institute of Technology (DuPree) 69 3.3 3.5 3.40 681 30.1% $105,266 92.7% 100.0% $32,076 154
Indiana University–Bloomington (Kelley) 69 3.8 3.7 3.35 663 34.0% $109,329 82.3% 89.7% $38,221 474
Washington University in St. Louis (Olin) 69 3.8 3.6 3.42 681 33.8% $103,184 76.6% 90.4% $41,586 294
Ohio State University (Fisher) 67 3.6 3.3 3.41 674 30.5% $101,146 80.8% 97.1% $37,845 277
University of Washington 67 3.4 3.6 3.38 688 30.9% $98,192 83.5% 96.2% $32,451 223
University of Wisconsin–Madison 65 3.6 3.3 3.36 666 33.1% $100,907 83.5% 94.2% $26,568 231
Arizona State University–Main Campus (W. P. Carey) 64 3.5 3.4 3.43 676 24.2% $94,599 72.9% 91.5% $29,856 170
Brigham Young University (Marriott) (UT) 64 3.1 3.5 3.52 673 56.4% $102,026 77.3% 94.5% $9,240 314
University of Rochester (Simon) (NY) 64 3.3 3.3 3.50 675 32.9% $97,206 79.3% 91.7% $40,005 352
Purdue University–West Lafayette (Krannert) (IN) 63 3.6 3.5 3.40 662 29.9% $96,470 78.4% 86.3% $34,940 293
Texas A&M University–College Station (Mays) 62 3.3 3.2 3.39 643 26.1% $96,485 91.2% 98.2% $28,022 164
University of Minnesota–Twin Cities (Carlson) 62 3.5 3.5 3.31 663 39.1% $104,745 78.6% 85.7% $39,238 199
University of Notre Dame (Mendoza) (IN) 62 3.4 3.4 3.30 677 34.1% $102,028 78.0% 90.7% $37,740 315
Vanderbilt University (Owen) (TN) 62 3.5 3.5 3.30 656 35.7% $103,262 75.5% 90.2% $40,917 390
University of Florida (Hough) 61 3.3 3.4 3.34 687 31.4% $84,990 82.3% 93.5% $24,066 142
Rice University (Jones) (TX) 60 3.3 3.2 3.29 667 31.1% $108,596 79.2% 89.6% $38,234 250
University of Illinois–Urbana-Champaign 60 3.5 3.3 3.40 639 34.9% $97,725 75.0% 88.8% $30,352 198
Michigan State University (Broad) 59 3.4 3.3 3.24 642 26.9% $104,445 81.7% 91.5% $29,183 214
Penn State University–University Park (Smeal) 59 3.4 3.4 3.20 646 27.8% $99,655 82.6% 92.8% $31,128 187
University of California–Davis 59 3.3 3.1 3.40 675 24.9% $93,712 76.3% 89.5% $36,894 120
University of Maryland–College Park (Smith) 59 3.5 3.1 3.34 660 27.8% $93,927 76.3% 89.2% $42,305 257
Boston College (Carroll) 58 3.4 3.2 3.30 661 27.9% $93,581 70.8% 90.8% $66,304 202
University of Iowa (Tippie) 58 3.2 3.1 3.37 653 38.7% $90,714 81.0% 95.2% $26,167 140
Boston University 57 3.1 3.1 3.38 680 27.8% $100,322 74.6% 83.3% $37,456 315
Southern Methodist University (Cox) TX 55 3.2 3.2 3.23 642 35.7% $94,361 76.8% 94.6% $39,308 171
Tulane University (Freeman) (LA) 54 3.1 2.9 3.30 655 59.7% $91,844 82.6% 93.5% $45,748 175
Babson College Olin) (MA) 53 3.4 3.3 3.18 630 47.8% $105,470 60.9% 84.8% $38,500 387
University of Texas–Dallas 53 2.8 3.2 3.70 651 32.7% $67,011 65.5% 89.7% $37,265 83

Data – Q-#34-Page70-P02_07

Employee Gender
Christopher J. Zappe, Ph.D.: CODING: 1 for female, 0 for male.
Age
Christopher J. Zappe, Ph.D.: Age at last birthday (in years).
Prior Experience
Christopher J. Zappe, Ph.D.: Number of years of relevant professional experience prior to hiring at Beta Technologies.
Beta Experience
Christopher J. Zappe, Ph.D.: Number of years of professional experience at Beta Technologies.
Education
Christopher J. Zappe, Ph.D.: Number of years of post-secondary education.
Annual Salary
1 1 39 5 12 4 57700
2 0 44 12 8 6 76400
3 0 24 0 2 4 44000
4 1 25 2 1 4 41600
5 0 56 5 25 8 163900
6 1 41 9 10 4 72700
7 1 33 6 2 6 60300
8 0 37 11 6 4 63500
9 1 51 12 16 6 131200
10 0 23 0 1 4 39200
11 0 31 5 4 6 62900
12 1 27 0 8 0 26200
13 0 47 11 9 4 74500
14 1 35 5 5 6 64800
15 1 29 5 4 0 21600
16 0 46 4 15 6 81900
17 1 50 10 17 4 115400
18 0 30 3 6 4 57800
19 1 34 10 1 4 55800
20 1 42 11 8 4 76100
21 1 51 10 15 8 135700
22 0 63 16 20 4 140400
23 0 28 0 5 4 55400
24 1 32 4 1 4 49700
25 0 55 11 16 6 134800
26 1 45 20 2 4 76900
27 0 34 2 12 2 28700
28 0 33 2 7 4 58800
29 1 23 0 1 4 43100
30 0 40 4 13 6 82400
31 1 48 6 15 4 80100
32 1 27 0 6 0 27000
33 1 36 5 5 6 58800
34 0 58 9 22 4 133100
35 0 31 1 1 6 53700
36 1 21 0 1 2 26700
37 0 47 5 16 4 81300
38 1 35 3 7 4 55400
39 1 52 12 14 8 139900
40 0 29 3 3 2 33200
41 1 42 11 7 4 75000
42 0 60 10 21 4 128200
43 1 50 8 13 4 76800
44 1 33 1 2 6 54200
45 0 26 0 5 2 32600
46 0 38 6 6 6 59200
47 1 44 7 12 4 74800
48 0 25 0 3 4 45500
49 1 37 8 5 4 46500
50 0 53 13 13 6 136300
51 0 46 7 18 4 86900
52 1 20 0 1 0 23900
53 1 34 5 1 6 52700
54 1 60 12 13 4 92700
55 1 36 6 7 4 59500
56 0 41 6 3 6 69400
57 1 33 3 1 6 46600
58 0 29 3 8 4 61700
59 0 48 11 9 4 88200
60 1 43 0 4 6 45000
61 1 61 10 5 0 52200
62 0 30 5 1 6 61400
63 1 36 5 19 4 87500
64 1 48 7 23 4 103700
65 1 29 5 6 4 54000
66 0 26 11 23 4 125100
67 1 49 5 11 2 45900
68 0 28 10 2 6 79300
69 1 44 20 5 6 108600
70 1 48 0 13 6 68200
71 0 50 0 21 2 65200
72 1 48 12 14 4 95600
73 1 30 16 12 4 103100
74 1 41 20 23 4 143500
75 0 35 11 5 4 78200
76 1 28 3 3 4 40200
77 1 33 8 5 4 60500
78 1 61 0 7 4 40500
79 1 53 10 8 4 73800
80 1 48 4 4 4 45300
81 0 47 9 1 4 61400
82 1 48 4 7 6 64800
83 1 55 11 3 6 75600
84 0 32 1 19 6 95800
85 0 60 11 4 8 126700
86 0 50 10 2 4 67000
87 1 49 16 12 4 102600
88 0 22 4 3 4 52000
89 1 51 9 10 4 76000
90 1 22 0 3 8 83000
91 1 47 8 13 4 80800
92 1 41 10 10 6 91100
93 0 24 3 1 0 30100
94 1 64 5 7 4 55700
95 1 43 0 11 4 51400
96 0 22 3 1 4 43800
97 1 59 0 1 4 25000
98 0 32 10 15 2 80600
99 1 45 8 5 2 39600
100 0 47 0 1 2 13400
101 1 29 6 18 4 88200
102 0 61 9 15 6 109100
103 1 57 3 1 4 34200
104 1 65 4 9 4 57800
105 0 34 6 7 4 68100
106 0 54 6 13 6 94900
107 1 30 5 5 6 63200
108 1 39 6 16 4 82700
109 0 32 7 8 6 85600
110 1 24 2 7 2 27100
111 0 40 10 3 4 69800
112 0 52 13 4 4 81300
113 0 28 11 5 4 78400
114 0 53 20 9 6 127300
115 0 43 0 24 4 93700
116 0 30 5 6 6 74400
117 0 46 3 3 4 48300
118 1 38 10 13 6 98900
119 0 28 0 16 4 73300
120 1 46 11 19 6 117300
121 1 30 5 5 0 37800
122 1 43 6 14 4 77400
123 1 29 11 1 8 111200
124 0 48 11 4 4 75300
125 0 42 7 17 4 96900
126 0 18 10 19 6 123600
127 0 35 6 2 4 55200
128 1 22 0 1 0 12400
129 1 44 4 15 4 73900
130 1 47 20 4 4 94100
131 1 34 10 8 4 74300
132 1 37 11 4 4 66900
133 1 49 0 4 2 12500
134 0 32 0 18 6 90200
135 1 37 5 8 4 59000
136 1 29 10 19 6 114700
137 0 24 7 15 2 71700
138 0 43 20 18 0 125500
139 1 54 11 17 4 100200
140 1 26 0 4 6 45400
141 0 47 10 4 4 72200
142 1 31 5 12 4 69500
143 0 33 11 1 4 67900
144 0 42 2 7 6 67500
145 1 34 2 1 4 31800
146 1 59 0 10 2 27800
147 1 43 5 4 6 60200
148 1 30 2 2 4 34500
149 1 45 7 12 6 87000
150 1 50 0 4 2 12500
151 0 23 0 15 8 122700
152 1 44 5 7 4 56200
153 0 48 10 6 2 56900
154 1 47 4 12 4 66000
155 0 20 11 4 4 76000
156 1 31 0 16 2 44100
157 0 30 0 18 4 78500
158 1 42 5 13 4 71800
159 1 25 9 7 6 80700
160 1 24 2 15 2 47800
161 0 36 13 13 4 105000
162 0 32 6 15 6 100700
163 1 27 2 1 0 18300
164 0 55 12 12 6 110600
165 0 36 0 2 4 36800
166 1 22 0 4 6 45500
167 1 25 0 14 6 71400
168 1 47 5 14 4 74300
169 0 43 16 11 8 160600
170 1 53 0 7 6 52500
171 0 38 5 7 4 65000
172 0 39 12 14 4 104500
173 1 35 5 18 4 85000
174 1 23 3 10 8 110200
175 0 43 10 7 4 80100
176 1 33 3 3 4 40000
177 1 44 10 1 4 55900
178 1 33 0 16 4 64600
179 1 31 0 13 6 68600
180 1 36 7 8 4 65100
181 1 45 13 19 4 111700
182 1 45 12 1 4 62000
183 0 39 2 7 4 55800
184 0 45 5 11 2 54600
185 0 25 1 1 4 37600
186 1 34 0 7 4 41200
187 1 53 0 6 6 49900
188 0 35 4 6 4 59400
189 1 52 3 13 4 65500
190 1 33 10 3 6 73200
191 1 49 0 3 4 30500
192 1 59 6 17 4 84800
193 1 35 16 9 4 95200
194 1 44 11 11 4 84900
195 1 61 11 18 4 102600
196 1 43 11 1 4 59000
197 0 30 0 5 4 44800
198 0 32 11 2 4 70500
199 0 57 10 4 6 83700
200 1 44 10 18 4 100000
201 1 44 2 4 4 39300
202 1 45 0 7 2 20400
203 0 43 0 12 6 74300
204 0 33 11 19 4 114500

Data – Q-#28-Page60-P02_28

Month Seasonally Adjusted Sales Seasonal Index Total Retail Sales
Chris: Each value is expressed in millions of dollars.
Jan-1992 146,913 0.893 131,193
Feb-1992 147,270 0.891 131,218
Mar-1992 146,831 0.972 142,720
Apr-1992 148,082 0.994 147,194
May-1992 149,015 1.023 152,442
Jun-1992 149,821 1.016 152,218
Jul-1992 150,809 1.013 152,770
Aug-1992 151,064 1.011 152,726
Sep-1992 152,595 0.971 148,170
Oct-1992 153,577 1.016 156,034
Nov-1992 153,605 1.006 154,527
Dec-1992 155,504 1.226 190,648
Jan-1993 157,525 0.874 137,677
Feb-1993 156,292 0.86 134,411
Mar-1993 154,774 0.988 152,917
Apr-1993 158,996 0.996 158,360
May-1993 160,624 1.019 163,676
Jun-1993 160,171 1.018 163,054
Jul-1993 162,832 1.011 164,623
Aug-1993 162,491 1.011 164,278
Sep-1993 163,285 0.977 159,529
Oct-1993 164,711 0.995 163,887
Nov-1993 166,593 1.019 169,758
Dec-1993 168,101 1.23 206,764
Jan-1994 167,504 0.87 145,728
Feb-1994 169,652 0.861 146,070
Mar-1994 172,775 0.996 172,084
Apr-1994 173,099 0.989 171,195
May-1994 172,340 1.019 175,614
Jun-1994 174,307 1.025 178,665
Jul-1994 174,801 0.992 173,403
Aug-1994 177,289 1.028 182,253
Sep-1994 178,776 0.98 175,200
Oct-1994 180,569 0.99 178,763
Nov-1994 180,695 1.019 184,128
Dec-1994 181,492 1.224 222,146
Jan-1995 182,423 0.869 158,526
Feb-1995 179,472 0.864 155,064
Mar-1995 180,996 1.004 181,720
Apr-1995 181,702 0.97 176,251
May-1995 183,543 1.037 190,334
Jun-1995 186,088 1.029 191,485
Jul-1995 185,470 0.987 183,059
Aug-1995 186,814 1.035 193,352
Sep-1995 187,338 0.973 182,280
Oct-1995 186,546 0.988 184,307
Nov-1995 189,052 1.023 193,400
Dec-1995 190,809 1.194 227,826
Jan-1996 189,167 0.883 167,034
Feb-1996 192,269 0.904 173,811
Mar-1996 193,993 0.986 191,277
Apr-1996 194,712 0.983 191,402
May-1996 196,210 1.05 206,021
Jun-1996 196,127 1.006 197,304
Jul-1996 196,229 1.003 196,818
Aug-1996 196,215 1.04 204,064
Sep-1996 198,843 0.954 189,696
Oct-1996 200,488 1.006 201,691
Nov-1996 200,200 1.017 203,603
Dec-1996 201,191 1.182 237,808
Jan-1997 202,414 0.893 180,756
Feb-1997 204,273 0.872 178,126
Mar-1997 204,965 0.986 202,095
Apr-1997 203,372 0.984 200,118
May-1997 201,676 1.051 211,961
Jun-1997 204,666 1.007 206,099
Jul-1997 207,049 1.008 208,705
Aug-1997 207,643 1.02 211,796
Sep-1997 208,298 0.966 201,216
Oct-1997 208,064 1.008 209,729
Nov-1997 208,982 0.994 207,728
Dec-1997 209,379 1.195 250,208
Jan-1998 209,684 0.894 187,457
Feb-1998 209,532 0.877 183,760
Mar-1998 210,792 0.989 208,473
Apr-1998 213,623 0.991 211,700
May-1998 214,619 1.031 221,272
Jun-1998 216,324 1.02 220,650
Jul-1998 214,853 1.013 217,646
Aug-1998 213,669 1.016 217,088
Sep-1998 215,712 0.967 208,594
Oct-1998 219,465 1.004 220,343
Nov-1998 221,150 0.991 219,160
Dec-1998 223,226 1.198 267,425
Jan-1999 224,020 0.878 196,690
Feb-1999 226,240 0.881 199,317
Mar-1999 227,407 1.007 228,999
Apr-1999 228,978 0.995 227,833
May-1999 231,238 1.027 237,481
Jun-1999 231,926 1.021 236,796
Jul-1999 233,933 1.012 236,740
Aug-1999 236,589 1.016 240,374
Sep-1999 237,516 0.971 230,628
Oct-1999 237,560 0.982 233,284
Nov-1999 240,462 1.003 241,183
Dec-1999 245,498 1.2 294,598
Jan-2000 243,483 0.877 213,535
Feb-2000 247,133 0.915 226,127
Mar-2000 249,847 1.019 254,594
Apr-2000 245,789 0.973 239,153
May-2000 246,225 1.042 256,566
Jun-2000 248,178 1.028 255,127
Jul-2000 247,184 0.99 244,712
Aug-2000 247,601 1.04 257,505
Sep-2000 251,812 0.967 243,502
Oct-2000 251,267 0.975 244,985
Nov-2000 250,225 1.009 252,477
Dec-2000 250,603 1.172 293,707
Jan-2001 252,736 0.892 225,441
Feb-2001 252,730 0.883 223,161
Mar-2001 250,346 1.019 255,103
Apr-2001 254,759 0.974 248,135
May-2001 255,262 1.048 267,515
Jun-2001 254,020 1.021 259,354
Jul-2001 253,015 0.993 251,244
Aug-2001 254,570 1.046 266,280
Sep-2001 249,856 0.95 237,363
Oct-2001 268,072 0.988 264,855
Nov-2001 260,363 1.01 262,967
Dec-2001 256,552 1.165 298,883
Jan-2002 256,376 0.9 230,738
Feb-2002 257,677 0.883 227,529
Mar-2002 257,060 0.999 256,803
Apr-2002 261,320 0.989 258,445
May-2002 257,616 1.052 271,012
Jun-2002 259,815 1.002 260,335
Jul-2002 262,811 1.011 265,702
Aug-2002 264,975 1.046 277,164
Sep-2002 260,650 0.948 247,096
Oct-2002 262,011 0.993 260,177
Nov-2002 263,559 1.003 264,350
Dec-2002 265,802 1.162 308,862
Jan-2003 267,276 0.905 241,885
Feb-2003 263,199 0.882 232,142
Mar-2003 267,842 0.994 266,235
Apr-2003 267,240 0.992 265,102
May-2003 267,347 1.052 281,249
Jun-2003 270,432 1.001 270,702
Jul-2003 273,393 1.021 279,134
Aug-2003 277,901 1.027 285,404
Sep-2003 276,413 0.96 265,356
Oct-2003 274,779 0.996 273,680
Nov-2003 278,322 0.983 273,591
Dec-2003 277,567 1.178 326,974
Jan-2004 278,884 0.905 252,390
Feb-2004 280,966 0.901 253,150
Mar-2004 286,232 1.009 288,808
Apr-2004 282,971 1.001 283,254
May-2004 288,250 1.029 296,609
Jun-2004 284,146 1.017 288,976
Jul-2004 287,341 1.027 295,099
Aug-2004 287,909 1.022 294,243
Sep-2004 293,177 0.966 283,209
Oct-2004 295,055 0.973 287,089
Nov-2004 296,178 0.994 294,401
Dec-2004 299,766 1.188 356,122
Jan-2005 297,728 0.885 263,489
Feb-2005 299,986 0.882 264,588
Mar-2005 299,958 1.016 304,757
Apr-2005 304,710 0.996 303,491
May-2005 301,572 1.031 310,921
Jun-2005 311,171 1.023 318,328
Jul-2005 314,562 1.007 316,764
Aug-2005 309,404 1.036 320,543
Sep-2005 310,084 0.968 300,161
Oct-2005 311,034 0.968 301,081
Nov-2005 313,282 0.995 311,716
Dec-2005 313,107 1.185 371,032
Jan-2006 322,795 0.887 286,319
Feb-2006 319,887 0.884 282,780
Mar-2006 321,428 1.021 328,178
Apr-2006 322,769 0.978 315,668
May-2006 321,283 1.049 337,026
Jun-2006 322,795 1.027 331,510
Jul-2006 325,038 1.002 325,688
Aug-2006 324,913 1.04 337,910
Sep-2006 323,029 0.961 310,431
Oct-2006 322,747 0.966 311,774
Nov-2006 323,367 1.002 324,014
Dec-2006 327,600 1.16 380,016
Jan-2007 326,922 0.903 295,211
Feb-2007 327,893 0.885 290,185
Mar-2007 330,819 1.022 338,097
Apr-2007 329,256 0.977 321,683
May-2007 333,889 1.056 352,587
Jun-2007 331,164 1.021 338,118
Jul-2007 332,620 1 332,620
Aug-2007 333,824 1.041 347,511
Sep-2007 336,431 0.942 316,918
Oct-2007 337,090 0.98 330,348
Nov-2007 340,383 1.006 342,425
Dec-2007 336,829 1.155 389,037
Jan-2008 337,274 0.912 307,594
Feb-2008 334,469 0.923 308,715
Mar-2008 334,559 1 334,559
Apr-2008 336,101 0.993 333,748
May-2008 337,383 1.058 356,951
Jun-2008 338,832 1.002 339,510
Jul-2008 336,771 1.02 343,506
Aug-2008 334,481 1.017 340,167
Sep-2008 327,779 0.953 312,373
Oct-2008 314,828 0.989 311,365
Nov-2008 302,285 0.986 298,053
Dec-2008 293,959 1.169 343,638
Jan-2009 298,565 0.917 273,784
Feb-2009 297,933 0.889 264,862
Mar-2009 292,857 1.002 293,443
Apr-2009 293,419 1 293,419
May-2009 297,060 1.037 308,051
Jun-2009 301,671 1.013 305,593
Jul-2009 302,901 1.02 308,959
Aug-2009 309,581 1.011 312,986
Sep-2009 301,199 0.955 287,645
Oct-2009 303,962 0.988 300,314
Nov-2009 307,190 0.987 303,197
Dec-2009 308,501 1.174 362,180
Jan-2010 309,140 0.901 278,535
Feb-2010 308,807 0.892 275,456
Mar-2010 316,242 1.021 322,883
Apr-2010 318,115 1.004 319,387
May-2010 315,985 1.03 325,465
Jun-2010 315,379 1.013 319,479
Jul-2010 315,716 1.017 321,083
Aug-2010 317,501 1.01 320,676
Sep-2010 320,346 0.961 307,853
Oct-2010 324,941 0.97 315,193
Nov-2010 327,271 1.003 328,253
Dec-2010 329,974 1.176 388,049
Jan-2011 332,752 0.896 298,146
Feb-2011 334,679 0.893 298,868
Mar-2011 338,207 1.03 348,353
Apr-2011 339,991 1 339,991
May-2011 339,664 1.028 349,175
Jun-2011 341,859 1.017 347,671
Jul-2011 342,554 0.996 341,184
Aug-2011 342,093 1.027 351,330
Sep-2011 345,332 0.965 333,245
Oct-2011 348,631 0.967 337,126
Nov-2011 349,723 1.006 351,821
Dec-2011 349,714 1.173 410,215
Jan-2012 352,598 0.893 314,870
Feb-2012 357,278 0.927 331,197
Mar-2012 359,189 1.033 371,042
Apr-2012 356,541 0.983 350,480
May-2012 356,256 1.049 373,713
Jun-2012 352,397 1.012 356,626
Jul-2012 354,292 0.991 351,103
Aug-2012 358,479 1.04 372,818
Sep-2012 362,886 0.945 342,927
Oct-2012 362,014 0.983 355,860
Nov-2012 363,393 1.017 369,571
Dec-2012 365,669 1.143 417,960
Jan-2013 367,676 0.908 333,850
Feb-2013 372,573 0.893 332,708
Mar-2013 369,575 1.012 374,010
Apr-2013 368,614 0.996 367,140
May-2013 370,671 1.054 390,687
Jun-2013 372,894 0.994 370,657
Jul-2013 374,280 1.007 376,900
Aug-2013 372,768 1.041 388,051
Sep-2013 373,610 0.946 353,435
Oct-2013 374,196 0.99 370,454
Nov-2013 374,691 1.012 379,187
Dec-2013 377,425 1.142 431,019
Jan-2014 373,036 0.908 338,717
Feb-2014 377,666 0.89 336,123
Mar-2014 382,356 1.008 385,415
Apr-2014 385,855 0.992 382,768
May-2014 385,572 1.056 407,164
Jun-2014 388,226 0.994 385,897
Jul-2014 387,963 1.016 394,170
Aug-2014 390,353 1.024 399,721
Sep-2014 388,462 0.96 372,924
Oct-2014 389,672 0.995 387,724
Nov-2014 391,741 0.996 390,174
Dec-2014 387,188 1.159 448,751
Jan-2015 383,889 0.903 346,652
Feb-2015 381,432 0.89 339,474
Mar-2015 387,665 1.005 389,603
Apr-2015 387,235 0.997 386,073
May-2015 392,268 1.037 406,782
Jun-2015 392,010 1.009 395,538
Jul-2015 394,199 1.022 402,871

Data-Q-#48-Pg75-Baseball Salar

Player Team Position Salary
A.J. Burnett Pittsburgh Pirates Pitcher $8,500,000
A.J. Ellis Los Angeles Dodgers Catcher $4,250,000
A.J. Griffin Oakland Athletics Pitcher $517,500
A.J. Pierzynski Atlanta Braves Catcher $2,000,000
A.J. Pollock Arizona Diamondbacks Center Fielder $519,500
A.J. Ramos Miami Marlins Pitcher $530,000
Aaron Barrett Washington Nationals Pitcher $514,200
Aaron Crow Miami Marlins Pitcher $1,975,000
Aaron Harang Philadelphia Phillies Pitcher $5,000,000
Aaron Hill Arizona Diamondbacks Second Baseman $12,000,000
Aaron Loup Toronto Blue Jays Pitcher $527,000
Aaron Sanchez Toronto Blue Jays Pitcher $510,800
Aaron Thompson Minnesota Twins Pitcher $520,000
Adam Eaton Chicago White Sox Center Fielder $560,000
Adam Jones Baltimore Orioles Center Fielder $13,355,106
Adam LaRoche Chicago White Sox First Baseman $12,000,000
Adam Lind Milwaukee Brewers First Baseman $7,500,000
Adam Ottavino Colorado Rockies Pitcher $1,300,000
Adam Rosales Texas Rangers First Baseman $900,000
Adam Wainwright St. Louis Cardinals Pitcher $19,500,000
Adam Warren New York Yankees Pitcher $572,600
Addison Reed Arizona Diamondbacks Pitcher $4,875,000
Adeiny Hechavarria Miami Marlins Shortstop $1,925,000
Adrian Beltre Texas Rangers Third Baseman $16,000,000
Adrian Gonzalez Los Angeles Dodgers First Baseman $21,857,142
Al Alburquerque Detroit Tigers Pitcher $1,725,000
Albert Pujols Los Angeles Angels First Baseman $24,000,000
Alberto Callaspo Atlanta Braves Second Baseman $3,000,000
Alcides Escobar Kansas City Royals Shortstop $3,000,000
Alejandro De Aza Baltimore Orioles Left Fielder $5,000,000
Alex Avila Detroit Tigers Catcher $5,400,000
Alex Cobb Tampa Bay Rays Pitcher $4,000,000
Alex Colome Tampa Bay Rays Pitcher $510,800
Alex Gordon Kansas City Royals Left Fielder $13,750,000
Alex Guerrero Los Angeles Dodgers Second Baseman $6,500,000
Alex Rios Kansas City Royals Right Fielder $9,500,000
Alex Rodriguez New York Yankees Third Baseman $22,000,000
Alex Torres New York Mets Pitcher $522,900
Alex Wood Atlanta Braves Pitcher $520,000
Alexei Ramirez Chicago White Sox Shortstop $10,000,000
Alexi Amarista San Diego Padres Third Baseman $1,150,000
Alexi Ogando Boston Red Sox Pitcher $1,500,000
Alfredo Simon Detroit Tigers Pitcher $5,550,000
Allen Craig Boston Red Sox Left Fielder $5,500,000
Andre Ethier Los Angeles Dodgers Center Fielder $18,000,000
Andrelton Simmons Atlanta Braves Shortstop $3,142,857
Andres Blanco Philadelphia Phillies Shortstop $850,000
Andrew Cashner San Diego Padres Pitcher $4,050,000
Andrew Chafin Arizona Diamondbacks Pitcher $507,500
Andrew Lambo Pittsburgh Pirates Left Fielder $515,000
Andrew McCutchen Pittsburgh Pirates Center Fielder $10,208,333
Andrew McKirahan Atlanta Braves Pitcher $507,500
Andrew Miller New York Yankees Pitcher $9,000,000
Andrew Romine Detroit Tigers Shortstop $520,000
Angel Nesbitt Detroit Tigers Pitcher $507,500
Angel Pagan San Francisco Giants Center Fielder $10,250,000
Anibal Sanchez Detroit Tigers Pitcher $16,800,000
Anthony Bass Texas Rangers Pitcher $725,000
Anthony DeSclafani Cincinnati Reds Pitcher $507,500
Anthony Gose Detroit Tigers Center Fielder $515,000
Anthony Recker New York Mets Catcher $517,880
Anthony Rendon Washington Nationals Third Baseman $2,500,000
Anthony Rizzo Chicago Cubs First Baseman $5,285,714
Anthony Swarzak Cleveland Indians Pitcher $900,000
Anthony Varvaro Boston Red Sox Pitcher $576,500
Antoan Richardson Texas Rangers Right Fielder $600,000
Antonio Bastardo Pittsburgh Pirates Pitcher $3,100,000
Aramis Ramirez Milwaukee Brewers Third Baseman $14,000,000
Archie Bradley Arizona Diamondbacks Pitcher $507,500
Arismendy Alcantara Chicago Cubs Second Baseman $510,000
Aroldis Chapman Cincinnati Reds Pitcher $8,050,000
Arquimedes Caminero Pittsburgh Pirates Pitcher $515,500
Asdrubal Cabrera Tampa Bay Rays Second Baseman $7,500,000
Asher Wojciechowski Houston Astros Pitcher $507,500
Austin Adams Cleveland Indians Pitcher $507,700
Austin Jackson Seattle Mariners Center Fielder $7,700,000
Avisail Garcia Chicago White Sox Right Fielder $523,000
Bartolo Colon New York Mets Pitcher $11,000,000
Ben Revere Philadelphia Phillies Center Fielder $4,100,000
Ben Zobrist Oakland Athletics Second Baseman $7,750,000
Billy Burns Oakland Athletics Center Fielder $507,500
Billy Butler Oakland Athletics Designated Hitter $6,666,666
Billy Hamilton Cincinnati Reds Center Fielder $545,000
Blaine Boyer Minnesota Twins Pitcher $750,000
Blake Treinen Washington Nationals Pitcher $512,800
Bobby Parnell New York Mets Pitcher $3,700,000
Bobby Wilson Tampa Bay Rays Catcher $700,000
Boone Logan Colorado Rockies Pitcher $5,500,000
Brad Boxberger Tampa Bay Rays Pitcher $521,400
Brad Brach Baltimore Orioles Pitcher $523,000
Brad Hand Miami Marlins Pitcher $520,000
Brad Miller Seattle Mariners Shortstop $527,600
Brad Peacock Houston Astros Pitcher $515,800
Brad Ziegler Arizona Diamondbacks Pitcher $5,000,000
Brandon Beachy Los Angeles Dodgers Pitcher $2,500,000
Brandon Belt San Francisco Giants First Baseman $3,600,000
Brandon Crawford San Francisco Giants Shortstop $3,175,000
Brandon Cumpton Pittsburgh Pirates Pitcher $520,500
Brandon Guyer Tampa Bay Rays Left Fielder $515,800
Brandon League Los Angeles Dodgers Pitcher $8,500,000
Brandon McCarthy Los Angeles Dodgers Pitcher $12,500,000
Brandon Morrow San Diego Padres Pitcher $2,500,000
Brandon Moss Cleveland Indians Right Fielder $6,500,000
Brandon Phillips Cincinnati Reds Second Baseman $12,083,333
Brayan Pena Cincinnati Reds Catcher $1,400,000
Brendan Ryan New York Yankees Second Baseman $2,000,000
Brennan Boesch Cincinnati Reds Left Fielder $1,250,000
Brett Anderson Los Angeles Dodgers Pitcher $10,000,000
Brett Cecil Toronto Blue Jays Pitcher $2,475,000
Brett Gardner New York Yankees Left Fielder $12,500,000
Brett Lawrie Oakland Athletics Second Baseman $1,925,000
Brett Oberholtzer Houston Astros Pitcher $515,800
Brian Dozier Minnesota Twins Second Baseman $2,000,000
Brian Duensing Minnesota Twins Pitcher $2,700,000
Brian Matusz Baltimore Orioles Pitcher $3,200,000
Brian McCann New York Yankees Catcher $17,000,000
Brock Holt Boston Red Sox Third Baseman $530,500
Bronson Arroyo Arizona Diamondbacks Pitcher $9,500,000
Brooks Brown Colorado Rockies Pitcher $509,500
Bruce Rondon Detroit Tigers Pitcher $510,000
Bryan Morris Miami Marlins Pitcher $531,500
Bryan Shaw Cleveland Indians Pitcher $1,550,000
Bryce Harper Washington Nationals Right Fielder $2,500,000
Bud Norris Baltimore Orioles Pitcher $8,800,000
Buddy Carlyle New York Mets Pitcher $725,000
Burke Badenhop Cincinnati Reds Pitcher $1,000,000
Buster Posey San Francisco Giants Catcher $17,277,777
C.J. Cron Los Angeles Angels Designated Hitter $512,500
C.J. Wilson Los Angeles Angels Pitcher $18,500,000
Caleb Joseph Baltimore Orioles Catcher $515,000
Cameron Maybin Atlanta Braves Center Fielder $7,100,000
Cameron Rupp Philadelphia Phillies Catcher $508,000
Carl Crawford Los Angeles Dodgers Left Fielder $21,357,142
Carlos Beltran New York Yankees Right Fielder $15,000,000
Carlos Carrasco Cleveland Indians Pitcher $2,337,500
Carlos Corporan Texas Rangers Catcher $975,000
Carlos Gomez Milwaukee Brewers Center Fielder $8,000,000
Carlos Gonzalez Colorado Rockies Left Fielder $16,428,571
Carlos Martinez St. Louis Cardinals Pitcher $520,000
Carlos Quentin Atlanta Braves Left Fielder $8,000,000
Carlos Ruiz Philadelphia Phillies Catcher $8,500,000
Carlos Sanchez Chicago White Sox Second Baseman $510,000
Carlos Santana Cleveland Indians First Baseman $6,200,000
Carlos Torres New York Mets Pitcher $582,125
Carlos Villanueva St. Louis Cardinals Pitcher $2,000,000
Carson Smith Seattle Mariners Pitcher $509,500
Casey Fien Minnesota Twins Pitcher $1,375,000
Casey Janssen Washington Nationals Pitcher $3,500,000
Casey McGehee San Francisco Giants Third Baseman $4,800,000
CC Sabathia New York Yankees Pitcher $23,000,000
Cesar Hernandez Philadelphia Phillies Second Baseman $510,000
Cesar Jimenez Philadelphia Phillies Pitcher $575,000
Cesar Ramos Los Angeles Angels Pitcher $1,312,500
Chad Billingsley Philadelphia Phillies Pitcher $1,500,000
Chad Qualls Houston Astros Pitcher $3,000,000
Charlie Blackmon Colorado Rockies Right Fielder $517,500
Charlie Culberson Colorado Rockies Second Baseman $512,500
Charlie Furbush Seattle Mariners Pitcher $1,300,000
Charlie Morton Pittsburgh Pirates Pitcher $8,000,000
Chase Anderson Arizona Diamondbacks Pitcher $512,500
Chase Headley New York Yankees Third Baseman $13,000,000
Chase Utley Philadelphia Phillies Second Baseman $10,000,000
Chasen Shreve New York Yankees Pitcher $510,275
Chris Archer Tampa Bay Rays Pitcher $1,166,666
Chris Capuano New York Yankees Pitcher $5,000,000
Chris Carter Houston Astros Designated Hitter $4,175,000
Chris Coghlan Chicago Cubs Left Fielder $2,505,000
Chris Davis Baltimore Orioles First Baseman $12,000,000
Chris Denorfia Chicago Cubs Right Fielder $2,600,000
Chris Dominguez Cincinnati Reds Third Baseman $510,000
Chris Hatcher Los Angeles Dodgers Pitcher $522,500
Chris Herrmann Minnesota Twins Catcher $510,000
Chris Iannetta Los Angeles Angels Catcher $5,525,000
Chris Johnson Atlanta Braves Third Baseman $6,000,000
Chris Martin New York Yankees Pitcher $511,025
Chris Owings Arizona Diamondbacks Shortstop $512,500
Chris Sale Chicago White Sox Pitcher $6,000,000
Chris Stewart Pittsburgh Pirates Catcher $1,225,000
Chris Taylor Seattle Mariners Shortstop $512,400
Chris Tillman Baltimore Orioles Pitcher $4,315,000
Chris Withrow Los Angeles Dodgers Pitcher $522,500
Chris Young Kansas City Royals Pitcher $675,000
Chris Young New York Yankees Center Fielder $2,500,000
Christian Bergman Colorado Rockies Pitcher $509,500
Christian Bethancourt Atlanta Braves Catcher $507,500
Christian Colon Kansas City Royals Shortstop $509,525
Christian Friedrich Colorado Rockies Pitcher $512,500
Christian Vazquez Boston Red Sox Catcher $512,500
Christian Yelich Miami Marlins Left Fielder $651,000
Clay Buchholz Boston Red Sox Pitcher $12,250,000
Clayton Kershaw Los Angeles Dodgers Pitcher $31,000,000
Cliff Lee Philadelphia Phillies Pitcher $25,000,000
Cliff Pennington Arizona Diamondbacks Second Baseman $3,275,000
Clint Barmes San Diego Padres Shortstop $1,300,000
Clint Robinson Washington Nationals First Baseman $525,000
Coco Crisp Oakland Athletics Center Fielder $11,000,000
Cody Allen Cleveland Indians Pitcher $547,100
Cody Asche Philadelphia Phillies Left Fielder $517,500
Cody Martin Atlanta Braves Pitcher $507,500
Colby Lewis Texas Rangers Pitcher $4,000,000
Colby Rasmus Houston Astros Center Fielder $8,000,000
Cole Hamels Philadelphia Phillies Pitcher $23,500,000
Collin Cowgill Los Angeles Angels Center Fielder $995,000
Collin McHugh Houston Astros Pitcher $516,300
Colt Hynes Toronto Blue Jays Pitcher $510,800
Conor Gillaspie Chicago White Sox Third Baseman $555,000
Corey Dickerson Colorado Rockies Center Fielder $512,500
Corey Hart Pittsburgh Pirates Right Fielder $2,500,000
Corey Kluber Cleveland Indians Pitcher $1,000,000
Cory Luebke San Diego Padres Pitcher $5,375,000
Cory Rasmus Los Angeles Angels Pitcher $513,000
Cory Spangenberg San Diego Padres Second Baseman $508,500
Craig Breslow Boston Red Sox Pitcher $2,000,000
Craig Gentry Oakland Athletics Center Fielder $1,600,000
Craig Kimbrel San Diego Padres Pitcher $9,250,000
Craig Stammen Washington Nationals Pitcher $2,250,000
Curtis Granderson New York Mets Right Fielder $16,000,000
Dale Thayer San Diego Padres Pitcher $1,375,000
Dallas Beeler Chicago Cubs Pitcher $508,500
Dallas Keuchel Houston Astros Pitcher $524,500
Dalton Pompey Toronto Blue Jays Right Fielder $508,500
Dan Haren Miami Marlins Pitcher $10,000,000
Dan Jennings Chicago White Sox Pitcher $523,000
Dan Otero Oakland Athletics Pitcher $512,500
Dan Uggla Washington Nationals Second Baseman $13,250,000
Daniel Descalso Colorado Rockies Shortstop $1,500,000
Daniel Hudson Arizona Diamondbacks Pitcher $800,000
Daniel Murphy New York Mets Second Baseman $8,000,000
Daniel Nava Boston Red Sox Right Fielder $1,850,000
Daniel Norris Toronto Blue Jays Pitcher $508,700
Daniel Winkler Atlanta Braves Pitcher $507,500
Danny Duffy Kansas City Royals Pitcher $2,425,000
Danny Espinosa Washington Nationals Second Baseman $1,800,000
Danny Farquhar Seattle Mariners Pitcher $527,000
Danny Santana Minnesota Twins Shortstop $530,000
Danny Valencia Toronto Blue Jays Third Baseman $1,675,000
Darin Ruf Philadelphia Phillies Left Fielder $515,000
Darren O`Day Baltimore Orioles Pitcher $4,250,000
Darwin Barney Los Angeles Dodgers Second Baseman $2,525,000
David Buchanan Philadelphia Phillies Pitcher $512,500
David Carpenter New York Yankees Pitcher $1,275,000
David DeJesus Tampa Bay Rays Left Fielder $5,114,378
David Freese Los Angeles Angels Third Baseman $6,425,000
David Hale Colorado Rockies Pitcher $512,500
David Hernandez Arizona Diamondbacks Pitcher $2,000,000
David Lough Baltimore Orioles Left Fielder $525,500
David Murphy Cleveland Indians Right Fielder $6,000,000
David Ortiz Boston Red Sox Designated Hitter $16,000,000
David Peralta Arizona Diamondbacks Right Fielder $512,000
David Phelps Miami Marlins Pitcher $1,400,000
David Price Detroit Tigers Pitcher $19,750,000
David Robertson Chicago White Sox Pitcher $10,000,000
David Ross Chicago Cubs Catcher $2,500,000
David Wright New York Mets Third Baseman $19,347,170
Dee Gordon Miami Marlins Second Baseman $2,500,000
Delino DeShields Jr. Texas Rangers Center Fielder $507,500
Dellin Betances New York Yankees Pitcher $507,500
Delmon Young Baltimore Orioles Left Fielder $2,250,000
Denard Span Washington Nationals Center Fielder $9,000,000
Derek Holland Texas Rangers Pitcher $7,400,000
Derek Norris San Diego Padres Catcher $545,000
Desmond Jennings Tampa Bay Rays Center Fielder $3,100,000
Devin Mesoraco Cincinnati Reds Catcher $2,525,000
Devon Travis Toronto Blue Jays Second Baseman $507,500
Dexter Fowler Chicago Cubs Center Fielder $9,500,000
Didi Gregorius New York Yankees Shortstop $553,900
Dillon Gee New York Mets Pitcher $5,300,000
Dioner Navarro Toronto Blue Jays Catcher $5,000,000
DJ LeMahieu Colorado Rockies Second Baseman $517,500
Domonic Brown Philadelphia Phillies Right Fielder $2,500,000
Don Kelly Miami Marlins Third Baseman $1,250,000
Donovan Solano Miami Marlins Shortstop $531,500
Doug Fister Washington Nationals Pitcher $11,400,000
Drew Butera Los Angeles Angels Catcher $987,500
Drew Hutchison Toronto Blue Jays Pitcher $520,100
Drew Pomeranz Oakland Athletics Pitcher $517,500
Drew Rucinski Los Angeles Angels Pitcher $507,500
Drew Smyly Tampa Bay Rays Pitcher $2,650,000
Drew Storen Washington Nationals Pitcher $5,700,000
Drew Stubbs Colorado Rockies Left Fielder $5,825,000
Dustin Ackley Seattle Mariners Left Fielder $2,600,000
Dustin McGowan Philadelphia Phillies Pitcher $600,000
Dustin Pedroia Boston Red Sox Second Baseman $12,142,348
Eddie Butler Colorado Rockies Pitcher $509,500
Edgar Olmos Seattle Mariners Pitcher $512,500
Edinson Volquez Kansas City Royals Pitcher $7,500,000
Eduardo Escobar Minnesota Twins Shortstop $532,500
Eduardo Nunez Minnesota Twins Third Baseman $1,025,000
Edward Mujica Boston Red Sox Pitcher $4,750,000
Edwin Encarnacion Toronto Blue Jays First Baseman $10,000,000
Edwin Escobar Boston Red Sox Pitcher $508,500
Edwin Jackson Chicago Cubs Pitcher $13,000,000
Efren Navarro Los Angeles Angels First Baseman $511,000
Elvis Andrus Texas Rangers Shortstop $15,333,333
Emilio Bonifacio Chicago White Sox Second Baseman $3,000,000
Ender Inciarte Arizona Diamondbacks Center Fielder $513,000
Erasmo Ramirez Tampa Bay Rays Pitcher $522,800
Eric Hosmer Kansas City Royals First Baseman $5,650,000
Eric O`Flaherty Oakland Athletics Pitcher $6,275,000
Eric Sogard Oakland Athletics Second Baseman $1,075,000
Eric Stults Atlanta Braves Pitcher $2,000,000
Eric Surkamp Chicago White Sox Pitcher $516,000
Eric Young Jr. Atlanta Braves Left Fielder $1,000,000
Erick Aybar Los Angeles Angels Shortstop $8,750,000
Erik Cordier San Francisco Giants Pitcher $650,000
Erik Davis Washington Nationals Pitcher $508,900
Erik Kratz Kansas City Royals Catcher $532,500
Ernesto Frieri Tampa Bay Rays Pitcher $800,000
Ervin Santana Minnesota Twins Pitcher $13,500,000
Esmil Rogers New York Yankees Pitcher $1,480,000
Evan Gattis Houston Astros Catcher $526,500
Evan Longoria Tampa Bay Rays Third Baseman $11,500,018
Evan Marshall Arizona Diamondbacks Pitcher $512,000
Evan Scribner Oakland Athletics Pitcher $512,500
Everth Cabrera Baltimore Orioles Shortstop $2,400,000
Felix Hernandez Seattle Mariners Pitcher $24,857,142
Fernando Abad Oakland Athletics Pitcher $1,087,500
Fernando Rodney Seattle Mariners Pitcher $7,000,000
Fernando Salas Los Angeles Angels Pitcher $1,370,000
Francisco Cervelli Pittsburgh Pirates Catcher $987,500
Francisco Liriano Pittsburgh Pirates Pitcher $11,666,666
Francisco Rodriguez Milwaukee Brewers Pitcher $3,500,000
Frank Garces San Diego Padres Pitcher $508,500
Franklin Morales Kansas City Royals Pitcher $1,850,000
Freddie Freeman Atlanta Braves First Baseman $8,859,375
Freddy Galvis Philadelphia Phillies Shortstop $513,500
Garrett Jones New York Yankees Right Fielder $5,000,000
Garrett Richards Los Angeles Angels Pitcher $3,200,000
Gavin Floyd Cleveland Indians Pitcher $4,000,000
George Kontos San Francisco Giants Pitcher $517,500
George Springer Houston Astros Right Fielder $512,900
Geovany Soto Chicago White Sox Catcher $1,500,000
Gerald Laird Arizona Diamondbacks Catcher $1,000,000
Gerardo Parra Milwaukee Brewers Right Fielder $6,237,500
Gerrit Cole Pittsburgh Pirates Pitcher $531,000
Giancarlo Stanton Miami Marlins Right Fielder $6,500,000
Gio Gonzalez Washington Nationals Pitcher $11,100,000
Glen Perkins Minnesota Twins Pitcher $4,650,000
Gordon Beckham Chicago White Sox Third Baseman $2,000,000
Grady Sizemore Philadelphia Phillies Center Fielder $2,000,000
Grant Balfour Tampa Bay Rays Pitcher $7,315,956
Greg Holland Kansas City Royals Pitcher $8,250,000
Gregor Blanco San Francisco Giants Center Fielder $3,600,000
Gregorio Petit New York Yankees Second Baseman $510,000
Gregory Polanco Pittsburgh Pirates Right Fielder $525,000
Hank Conger Houston Astros Catcher $1,075,000
Hanley Ramirez Boston Red Sox Left Fielder $19,750,000
Hector Gomez Milwaukee Brewers Shortstop $507,500
Hector Noesi Chicago White Sox Pitcher $1,950,000
Hector Rondon Chicago Cubs Pitcher $544,000
Hector Sanchez San Francisco Giants Catcher $800,000
Hector Santiago Los Angeles Angels Pitcher $2,290,000
Henderson Alvarez Miami Marlins Pitcher $4,000,000
Hernan Perez Detroit Tigers Second Baseman $508,500
Hisashi Iwakuma Seattle Mariners Pitcher $7,000,000
Homer Bailey Cincinnati Reds Pitcher $10,000,000
Howie Kendrick Los Angeles Dodgers Second Baseman $9,850,000
Hunter Pence San Francisco Giants Right Fielder $18,700,000
Huston Street Los Angeles Angels Pitcher $7,000,000
Hyun-Jin Ryu Los Angeles Dodgers Pitcher $4,833,333
Ian Desmond Washington Nationals Shortstop $11,000,000
Ian Kennedy San Diego Padres Pitcher $9,850,000
Ian Kinsler Detroit Tigers Second Baseman $16,000,000
Ian Krol Detroit Tigers Pitcher $515,000
Ichiro Suzuki Miami Marlins Right Fielder $2,000,000
Ike Davis Oakland Athletics First Baseman $3,800,000
Ivan Nova New York Yankees Pitcher $3,300,000
J.A. Happ Seattle Mariners Pitcher $6,700,000
J.B. Shuck Chicago White Sox Left Fielder $516,000
J.D. Martinez Detroit Tigers Left Fielder $3,000,000
J.J. Hardy Baltimore Orioles Shortstop $11,209,424
J.J. Hoover Cincinnati Reds Pitcher $535,000
J.P. Howell Los Angeles Dodgers Pitcher $5,500,000
J.R. Graham Minnesota Twins Pitcher $507,500
Jace Peterson Atlanta Braves Shortstop $507,500
Jacob deGrom New York Mets Pitcher $531,875
Jacob Turner Chicago Cubs Pitcher $1,000,000
Jacoby Ellsbury New York Yankees Center Fielder $21,142,857
Jaff Decker Pittsburgh Pirates Left Fielder $510,000
Jaime Garcia St. Louis Cardinals Pitcher $9,375,000
Jake Arrieta Chicago Cubs Pitcher $3,630,000
Jake Diekman Philadelphia Phillies Pitcher $535,500
Jake Lamb Arizona Diamondbacks Third Baseman $508,500
Jake Marisnick Houston Astros Center Fielder $511,200
Jake McGee Tampa Bay Rays Pitcher $3,550,000
Jake Odorizzi Tampa Bay Rays Pitcher $522,000
Jake Peavy San Francisco Giants Pitcher $9,000,000
Jake Petricka Chicago White Sox Pitcher $520,000
Jake Smolinski Texas Rangers Left Fielder $508,500
James Loney Tampa Bay Rays First Baseman $8,666,666
James McCann Detroit Tigers Catcher $507,500
James Paxton Seattle Mariners Pitcher $519,000
James Shields San Diego Padres Pitcher $10,000,000
Jared Hughes Pittsburgh Pirates Pitcher $1,075,000
Jarred Cosart Miami Marlins Pitcher $540,000
Jarrod Dyson Kansas City Royals Center Fielder $1,225,000
Jarrod Parker Oakland Athletics Pitcher $850,000
Jarrod Saltalamacchia Miami Marlins Catcher $7,000,000
Jason Bourgeois Cincinnati Reds Center Fielder $522,500
Jason Castro Houston Astros Catcher $4,000,000
Jason Frasor Kansas City Royals Pitcher $1,250,000
Jason Garcia Baltimore Orioles Pitcher $507,500
Jason Grilli Atlanta Braves Pitcher $4,375,000
Jason Hammel Chicago Cubs Pitcher $9,000,000
Jason Heyward St. Louis Cardinals Right Fielder $8,800,000
Jason Kipnis Cleveland Indians Second Baseman $4,166,666
Jason Marquis Cincinnati Reds Pitcher $1,500,000
Jason Motte Chicago Cubs Pitcher $4,500,000
Jason Vargas Kansas City Royals Pitcher $8,500,000
Javier Lopez San Francisco Giants Pitcher $4,000,000
Javy Guerra Chicago White Sox Pitcher $937,500
Jay Bruce Cincinnati Reds Right Fielder $12,041,666
Jayson Werth Washington Nationals Left Fielder $21,571,428
Jean Machi San Francisco Giants Pitcher $527,500
Jean Segura Milwaukee Brewers Shortstop $534,000
Jeanmar Gomez Philadelphia Phillies Pitcher $800,000
Jed Lowrie Houston Astros Shortstop $8,000,000
Jedd Gyorko San Diego Padres Second Baseman $2,000,000
Jeff Baker Miami Marlins Second Baseman $2,100,000
Jeff Beliveau Tampa Bay Rays Pitcher $513,600
Jeff Francoeur Philadelphia Phillies Right Fielder $925,000
Jeff Locke Pittsburgh Pirates Pitcher $531,000
Jeff Mathis Miami Marlins Catcher $1,500,000
Jeff Samardzija Chicago White Sox Pitcher $9,800,000
Jenrry Mejia New York Mets Pitcher $2,595,000
Jered Weaver Los Angeles Angels Pitcher $18,200,000
Jeremy Affeldt San Francisco Giants Pitcher $6,000,000
Jeremy Guthrie Kansas City Royals Pitcher $9,000,000
Jeremy Hellickson Arizona Diamondbacks Pitcher $4,275,000
Jeremy Jeffress Milwaukee Brewers Pitcher $510,500
Jerome Williams Philadelphia Phillies Pitcher $2,500,000
Jerry Blevins New York Mets Pitcher $2,400,000
Jesse Chavez Oakland Athletics Pitcher $2,150,000
Jesse Hahn Oakland Athletics Pitcher $507,500
Jesus Sucre Seattle Mariners Catcher $509,300
Jeurys Familia New York Mets Pitcher $523,925
Jhonny Peralta St. Louis Cardinals Shortstop $15,000,000
Jim Henderson Milwaukee Brewers Pitcher $512,000
Jim Johnson Atlanta Braves Pitcher $1,600,000
Jimmy Nelson Milwaukee Brewers Pitcher $511,500
Jimmy Paredes Baltimore Orioles Third Baseman $515,000
Jimmy Rollins Los Angeles Dodgers Shortstop $11,000,000
Joakim Soria Detroit Tigers Pitcher $7,000,000
Joaquin Arias San Francisco Giants Second Baseman $1,450,000
Joaquin Benoit San Diego Padres Pitcher $8,232,595
Joba Chamberlain Detroit Tigers Pitcher $1,000,000
Joc Pederson Los Angeles Dodgers Center Fielder $510,000
Joe Kelly Boston Red Sox Pitcher $603,000
Joe Mauer Minnesota Twins First Baseman $23,000,000
Joe Nathan Detroit Tigers Pitcher $10,000,000
Joe Panik San Francisco Giants Second Baseman $522,500
Joe Smith Los Angeles Angels Pitcher $5,250,000
Joe Thatcher Houston Astros Pitcher $1,000,000
Joel Peralta Los Angeles Dodgers Pitcher $2,500,000
Joey Terdoslavich Atlanta Braves Right Fielder $507,500
Joey Votto Cincinnati Reds First Baseman $14,000,000
John Axford Colorado Rockies Pitcher $2,600,000
John Danks Chicago White Sox Pitcher $15,750,000
John Jaso Tampa Bay Rays Catcher $3,175,000
John Lackey St. Louis Cardinals Pitcher $507,500
John Mayberry Jr. New York Mets Center Fielder $1,450,000
John Ryan Murphy New York Yankees Catcher $518,700
Johnny Cueto Cincinnati Reds Pitcher $10,000,000
Johnny Giavotella Los Angeles Angels Second Baseman $516,250
Jon Jay St. Louis Cardinals Center Fielder $4,125,000
Jon Lester Chicago Cubs Pitcher $20,000,000
Jon Niese New York Mets Pitcher $7,050,000
Jonathan Broxton Milwaukee Brewers Pitcher $9,000,000
Jonathan Herrera Chicago Cubs Third Baseman $900,000
Jonathan Lucroy Milwaukee Brewers Catcher $3,100,000
Jonathan Papelbon Philadelphia Phillies Pitcher $13,000,000
Jonathan Pettibone Philadelphia Phillies Pitcher $510,000
Jonathan Schoop Baltimore Orioles Second Baseman $515,000
Jonathan Villar Houston Astros Shortstop $513,000
Jonny Gomes Atlanta Braves Left Fielder $4,000,000
Jordan Lyles Colorado Rockies Pitcher $2,475,000
Jordan Pacheco Arizona Diamondbacks Catcher $900,000
Jordan Schafer Minnesota Twins Center Fielder $1,550,000
Jordan Walden St. Louis Cardinals Pitcher $2,675,000
Jordan Zimmermann Washington Nationals Pitcher $16,500,000
Jordy Mercer Pittsburgh Pirates Shortstop $538,000
Jorge De La Rosa Colorado Rockies Pitcher $12,500,000
Jorge Soler Chicago Cubs Right Fielder $2,666,666
Jose Abreu Chicago White Sox First Baseman $8,666,666
Jose Altuve Houston Astros Second Baseman $2,687,500
Jose Alvarez Los Angeles Angels Pitcher $509,500
Jose Bautista Toronto Blue Jays Right Fielder $14,000,000
Jose Fernandez Miami Marlins Pitcher $651,000
Jose Iglesias Detroit Tigers Shortstop $1,443,750
Jose Lobaton Washington Nationals Catcher $1,200,000
Jose Pirela New York Yankees Second Baseman $510,000
Jose Quintana Chicago White Sox Pitcher $1,000,000
Jose Ramirez Cleveland Indians Shortstop $511,300
Jose Reyes Toronto Blue Jays Shortstop $22,000,000
Josh Collmenter Arizona Diamondbacks Pitcher $1,450,000
Josh Donaldson Toronto Blue Jays Third Baseman $4,300,000
Josh Edgin New York Mets Pitcher $520,625
Josh Fields Houston Astros Pitcher $516,700
Josh Hamilton Los Angeles Angels Left Fielder $25,000,000
Josh Harrison Pittsburgh Pirates Third Baseman $2,800,000
Josh Johnson San Diego Padres Pitcher $1,000,000
Josh Outman Atlanta Braves Pitcher $925,000
Josh Phegley Oakland Athletics Catcher $510,000
Josh Reddick Oakland Athletics Right Fielder $4,100,000
Josh Tomlin Cleveland Indians Pitcher $1,500,000
Juan Jaime Atlanta Braves Pitcher $507,500
Juan Lagares New York Mets Center Fielder $528,696
Juan Nicasio Los Angeles Dodgers Pitcher $2,300,000
Juan Uribe Los Angeles Dodgers Third Baseman $7,925,000
Julio Teheran Atlanta Braves Pitcher $1,166,666
Jumbo Diaz Cincinnati Reds Pitcher $510,000
Jung-Ho Kang Pittsburgh Pirates Shortstop $2,500,000
Junichi Tazawa Boston Red Sox Pitcher $2,250,000
Jurickson Profar Texas Rangers Second Baseman $509,500
Justin De Fratus Philadelphia Phillies Pitcher $528,000
Justin Grimm Chicago Cubs Pitcher $531,500
Justin Masterson Boston Red Sox Pitcher $9,500,000
Justin Maxwell San Francisco Giants Center Fielder $1,000,000
Justin Morneau Colorado Rockies First Baseman $7,250,000
Justin Ruggiano Seattle Mariners Center Fielder $2,505,000
Justin Sellers Pittsburgh Pirates Shortstop $518,500
Justin Smoak Toronto Blue Jays First Baseman $1,000,000
Justin Turner Los Angeles Dodgers Third Baseman $2,500,000
Justin Upton San Diego Padres Left Fielder $14,708,333
Justin Verlander Detroit Tigers Pitcher $28,000,000
Justin Wilson New York Yankees Pitcher $556,000
Kelly Johnson Atlanta Braves Left Fielder $1,500,000
Kelvin Herrera Kansas City Royals Pitcher $1,600,000
Ken Giles Philadelphia Phillies Pitcher $519,000
Kendall Graveman Oakland Athletics Pitcher $507,500
Kendrys Morales Kansas City Royals First Baseman $6,500,000
Kenley Jansen Los Angeles Dodgers Pitcher $7,425,000
Kennys Vargas Minnesota Twins First Baseman $517,000
Keone Kela Texas Rangers Pitcher $507,500
Kevin Gausman Baltimore Orioles Pitcher $522,000
Kevin Gregg Cincinnati Reds Pitcher $1,500,000
Kevin Jepsen Tampa Bay Rays Pitcher $3,025,000
Kevin Kiermaier Tampa Bay Rays Center Fielder $513,800
Kevin Pillar Toronto Blue Jays Center Fielder $512,000
Kevin Siegrist St. Louis Cardinals Pitcher $518,000
Khris Davis Milwaukee Brewers Left Fielder $519,500
Kirby Yates Tampa Bay Rays Pitcher $512,800
Kirk Nieuwenhuis New York Mets Center Fielder $525,415
Koji Uehara Boston Red Sox Pitcher $9,000,000
Kole Calhoun Los Angeles Angels Right Fielder $537,500
Kolten Wong St. Louis Cardinals Second Baseman $520,000
Kris Medlen Kansas City Royals Pitcher $2,000,000
Kristopher Negron Cincinnati Reds Second Baseman $512,500
Kurt Suzuki Minnesota Twins Catcher $6,000,000
Kyle Crockett Cleveland Indians Pitcher $510,900
Kyle Drabek Chicago White Sox Pitcher $518,200
Kyle Gibson Minnesota Twins Pitcher $537,500
Kyle Hendricks Chicago Cubs Pitcher $510,000
Kyle Kendrick Colorado Rockies Pitcher $5,500,000
Kyle Lohse Milwaukee Brewers Pitcher $11,000,000
Kyle Seager Seattle Mariners Third Baseman $4,500,000
Kyuji Fujikawa Texas Rangers Pitcher $1,000,000
Lance Lynn St. Louis Cardinals Pitcher $7,000,000
LaTroy Hawkins Colorado Rockies Pitcher $2,250,000
Leonys Martin Texas Rangers Center Fielder $4,750,000
Liam Hendriks Toronto Blue Jays Pitcher $518,400
Lisalverto Bonilla Texas Rangers Pitcher $508,500
Logan Forsythe Tampa Bay Rays Second Baseman $1,100,000
Logan Morrison Seattle Mariners First Baseman $2,725,000
Logan Schafer Milwaukee Brewers Left Fielder $510,500
Logan Verrett Texas Rangers Pitcher $507,500
Lonnie Chisenhall Cleveland Indians Third Baseman $2,250,000
Lorenzo Cain Kansas City Royals Center Fielder $2,725,000
Lucas Duda New York Mets First Baseman $4,200,000
Luis Avilan Atlanta Braves Pitcher $530,000
Luis Garcia Philadelphia Phillies Pitcher $509,000
Luis Jimenez Milwaukee Brewers Third Baseman $508,500
Luis Valbuena Houston Astros Third Baseman $4,200,000
Luke Gregerson Houston Astros Pitcher $6,000,000
Luke Hochevar Kansas City Royals Pitcher $4,000,000
Madison Bumgarner San Francisco Giants Pitcher $6,916,666
Maicer Izturis Toronto Blue Jays Third Baseman $3,000,000
Manny Machado Baltimore Orioles Third Baseman $548,000
Manny Parra Cincinnati Reds Pitcher $3,500,000
Marc Rzepczynski Cleveland Indians Pitcher $2,400,000
Marcell Ozuna Miami Marlins Center Fielder $555,000
Marco Estrada Toronto Blue Jays Pitcher $3,900,000
Marcus Semien Oakland Athletics Second Baseman $510,000
Marcus Stroman Toronto Blue Jays Pitcher $514,700
Mario Hollands Philadelphia Phillies Pitcher $512,500
Mark Buehrle Toronto Blue Jays Pitcher $20,000,000
Mark Canha Oakland Athletics Left Fielder $507,500
Mark Melancon Pittsburgh Pirates Pitcher $5,400,000
Mark Reynolds St. Louis Cardinals First Baseman $2,000,000
Mark Teixeira New York Yankees First Baseman $23,125,000
Mark Trumbo Arizona Diamondbacks Left Fielder $6,900,000
Marlon Byrd Cincinnati Reds Right Fielder $8,000,000
Martin Maldonado Milwaukee Brewers Catcher $825,000
Martin Perez Texas Rangers Pitcher $1,250,000
Martin Prado Miami Marlins Third Baseman $11,000,000
Marwin Gonzalez Houston Astros Shortstop $1,062,500
Masahiro Tanaka New York Yankees Pitcher $22,000,000
Mat Latos Miami Marlins Pitcher $9,400,000
Matt Adams St. Louis Cardinals First Baseman $534,000
Matt Albers Chicago White Sox Pitcher $1,500,000
Matt Andriese Tampa Bay Rays Pitcher $507,500
Matt Belisle St. Louis Cardinals Pitcher $3,500,000
Matt Cain San Francisco Giants Pitcher $20,833,333
Matt Carpenter St. Louis Cardinals Third Baseman $3,750,000
Matt den Dekker Washington Nationals Center Fielder $512,792
Matt Duffy San Francisco Giants Shortstop $509,000
Matt Garza Milwaukee Brewers Pitcher $12,209,424
Matt Harrison Texas Rangers Pitcher $13,200,000
Matt Harvey New York Mets Pitcher $614,125
Matt Holliday St. Louis Cardinals Left Fielder $16,227,957
Matt Joyce Los Angeles Angels Left Fielder $4,750,000
Matt Kemp San Diego Padres Right Fielder $21,250,000
Matt Moore Tampa Bay Rays Pitcher $3,100,000
Matt Shoemaker Los Angeles Angels Pitcher $517,500
Matt Stites Arizona Diamondbacks Pitcher $510,500
Matt Szczur Chicago Cubs Center Fielder $508,500
Matt Thornton Washington Nationals Pitcher $3,500,000
Matt Wieters Baltimore Orioles Catcher $8,275,000
Max Scherzer Washington Nationals Pitcher $17,142,857
Melky Cabrera Chicago White Sox Left Fielder $13,000,000
Melvin Upton Jr San Diego Padres Center Fielder $15,050,000
Micah Johnson Chicago White Sox Second Baseman $507,500
Michael Blazek Milwaukee Brewers Pitcher $508,500
Michael Bourn Cleveland Indians Center Fielder $13,500,000
Michael Brantley Cleveland Indians Left Fielder $5,875,000
Michael Cuddyer New York Mets Right Fielder $8,500,000
Michael McKenry Colorado Rockies Catcher $1,087,600
Michael Morse Miami Marlins First Baseman $7,500,000
Michael Pineda New York Yankees Pitcher $2,100,000
Michael Saunders Toronto Blue Jays Center Fielder $2,875,000
Michael Taylor Washington Nationals Right Fielder $508,700
Michael Wacha St. Louis Cardinals Pitcher $520,000
Miguel Cabrera Detroit Tigers First Baseman $22,000,000
Miguel Castro Toronto Blue Jays Pitcher $507,500
Miguel Gonzalez Baltimore Orioles Pitcher $3,275,000
Miguel Montero Chicago Cubs Catcher $12,000,000
Mike Aviles Cleveland Indians Shortstop $3,500,000
Mike Dunn Miami Marlins Pitcher $2,350,000
Mike Fiers Milwaukee Brewers Pitcher $512,500
Mike Leake Cincinnati Reds Pitcher $9,775,000
Mike Minor Atlanta Braves Pitcher $5,600,000
Mike Morin Los Angeles Angels Pitcher $514,000
Mike Moustakas Kansas City Royals Third Baseman $2,640,000
Mike Napoli Boston Red Sox First Baseman $16,000,000
Mike Olt Chicago Cubs First Baseman $520,000
Mike Pelfrey Minnesota Twins Pitcher $5,500,000
Mike Trout Los Angeles Angels Center Fielder $6,083,333
Mike Zunino Seattle Mariners Catcher $523,500
Mitch Moreland Texas Rangers Designated Hitter $2,950,000
Mookie Betts Boston Red Sox Center Fielder $514,500
Nate Freiman Oakland Athletics First Baseman $512,500
Nate Jones Chicago White Sox Pitcher $660,000
Nate McLouth Washington Nationals Center Fielder $5,000,000
Nathan Eovaldi New York Yankees Pitcher $3,300,000
Nathan Karns Tampa Bay Rays Pitcher $508,800
Neal Cotts Milwaukee Brewers Pitcher $3,000,000
Neftali Feliz Texas Rangers Pitcher $4,125,000
Neil Ramirez Chicago Cubs Pitcher $514,500
Neil Walker Pittsburgh Pirates Second Baseman $8,000,000
Nelson Cruz Seattle Mariners Designated Hitter $14,250,000
Nick Ahmed Arizona Diamondbacks Shortstop $508,500
Nick Castellanos Detroit Tigers Third Baseman $525,000
Nick Franklin Tampa Bay Rays Second Baseman $510,900
Nick Hagadone Cleveland Indians Pitcher $517,100
Nick Hundley Colorado Rockies Catcher $3,100,000
Nick Markakis Atlanta Braves Right Fielder $11,000,000
Nick Martinez Texas Rangers Pitcher $515,000
Nick Swisher Cleveland Indians First Baseman $15,000,000
Nick Vincent San Diego Padres Pitcher $525,300
Nolan Arenado Colorado Rockies Third Baseman $512,500
Norichika Aoki San Francisco Giants Right Fielder $4,000,000
Odrisamer Despaigne San Diego Padres Pitcher $517,300
Odubel Herrera Philadelphia Phillies Center Fielder $507,500
Oliver Perez Arizona Diamondbacks Pitcher $2,500,000
Omar Infante Kansas City Royals Second Baseman $7,500,000
Oscar Hernandez Arizona Diamondbacks Catcher $507,500
Oswaldo Arcia Minnesota Twins Left Fielder $532,500
Pablo Sandoval Boston Red Sox Third Baseman $17,600,000
Paco Rodriguez Los Angeles Dodgers Pitcher $522,500
Pat Neshek Houston Astros Pitcher $5,500,000
Patrick Corbin Arizona Diamondbacks Pitcher $524,000
Paul Goldschmidt Arizona Diamondbacks First Baseman $3,083,333
Paulo Orlando Kansas City Royals Center Fielder $507,500
Pedro Alvarez Pittsburgh Pirates First Baseman $5,750,000
Pedro Baez Los Angeles Dodgers Pitcher $512,500
Pedro Strop Chicago Cubs Pitcher $2,525,000
Pete Kozma St. Louis Cardinals Shortstop $522,000
Peter Bourjos St. Louis Cardinals Center Fielder $1,650,000
Phil Coke Chicago Cubs Pitcher $2,250,000
Phil Gosselin Atlanta Braves Second Baseman $507,500
Phil Hughes Minnesota Twins Pitcher $9,200,000
Phil Klein Texas Rangers Pitcher $509,500
Prince Fielder Texas Rangers First Baseman $24,000,000
R.A. Dickey Toronto Blue Jays Pitcher $12,000,000
R.J. Alvarez Oakland Athletics Pitcher $507,500
Radhames Liz Pittsburgh Pirates Pitcher $1,000,000
Rafael Betancourt Colorado Rockies Pitcher $1,000,000
Rafael Montero New York Mets Pitcher $511,000
Rafael Ynoa Colorado Rockies Second Baseman $509,500
Raisel Iglesias Cincinnati Reds Pitcher $1,714,285
Rajai Davis Detroit Tigers Center Fielder $5,000,000
Randal Grichuk St. Louis Cardinals Right Fielder $510,000
Randall Delgado Arizona Diamondbacks Pitcher $526,000
Randy Choate St. Louis Cardinals Pitcher $3,000,000
Reed Johnson Washington Nationals Left Fielder $1,000,000
Rene Rivera Tampa Bay Rays Catcher $1,200,000
Rick Porcello Boston Red Sox Pitcher $12,500,000
Rickie Weeks Seattle Mariners Second Baseman $2,000,000
Ricky Nolasco Minnesota Twins Pitcher $12,000,000
Rob Scahill Pittsburgh Pirates Pitcher $517,500
Robbie Grossman Houston Astros Left Fielder $515,000
Robbie Ross Jr. Boston Red Sox Pitcher $566,500
Roberto Hernandez Houston Astros Pitcher $1,250,000
Roberto Osuna Toronto Blue Jays Pitcher $507,500
Roberto Perez Cleveland Indians Catcher $508,600
Robinson Cano Seattle Mariners Second Baseman $24,000,000
Robinson Chirinos Texas Rangers Catcher $518,290
Roman Mendez Texas Rangers Pitcher $509,500
Ross Detwiler Texas Rangers Pitcher $3,450,000
Rougned Odor Texas Rangers Second Baseman $513,850
Rubby De La Rosa Arizona Diamondbacks Pitcher $516,000
Ruben Tejada New York Mets Shortstop $1,880,000
Russell Martin Toronto Blue Jays Catcher $7,000,000
Ryan Braun Milwaukee Brewers Right Fielder $13,111,111
Ryan Flaherty Baltimore Orioles Third Baseman $1,075,000
Ryan Hanigan Boston Red Sox Catcher $3,500,000
Ryan Howard Philadelphia Phillies First Baseman $25,000,000
Ryan Madson Kansas City Royals Pitcher $850,000
Ryan Raburn Cleveland Indians Right Fielder $2,500,000
Ryan Rua Texas Rangers Left Fielder $508,500
Ryan Vogelsong San Francisco Giants Pitcher $4,000,000
Ryan Webb Baltimore Orioles Pitcher $2,750,000
Ryan Zimmerman Washington Nationals First Baseman $14,000,000
Salvador Perez Kansas City Royals Catcher $1,750,000
Sam Dyson Miami Marlins Pitcher $507,500
Sam Fuld Oakland Athletics Left Fielder $1,750,000
Samuel Deduno Houston Astros Pitcher $525,100
Sandy Leon Boston Red Sox Catcher $510,400
Santiago Casilla San Francisco Giants Pitcher $5,166,666
Scooter Gennett Milwaukee Brewers Second Baseman $516,500
Scott Atchison Cleveland Indians Pitcher $900,000
Scott Feldman Houston Astros Pitcher $10,000,000
Scott Kazmir Oakland Athletics Pitcher $13,000,000
Scott Van Slyke Los Angeles Dodgers Left Fielder $522,500
Sean Doolittle Oakland Athletics Pitcher $780,000
Sean Gilmartin New York Mets Pitcher $507,500
Sean Marshall Cincinnati Reds Pitcher $6,625,000
Sean Nolin Oakland Athletics Pitcher $507,500
Sean Rodriguez Pittsburgh Pirates Second Baseman $1,900,000
Sergio Romo San Francisco Giants Pitcher $6,000,000
Seth Maness St. Louis Cardinals Pitcher $530,000
Seth Smith Seattle Mariners Left Fielder $6,000,000
Shae Simmons Atlanta Braves Pitcher $508,750
Shane Greene Detroit Tigers Pitcher $515,000
Shane Robinson Minnesota Twins Right Fielder $550,000
Shane Victorino Boston Red Sox Right Fielder $13,000,000
Shawn Kelley San Diego Padres Pitcher $2,835,000
Shawn Tolleson Texas Rangers Pitcher $519,700
Shelby Miller Atlanta Braves Pitcher $535,000
Shin-Soo Choo Texas Rangers Left Fielder $14,000,000
Skip Schumaker Cincinnati Reds Left Fielder $2,500,000
Sonny Gray Oakland Athletics Pitcher $512,500
Starlin Castro Chicago Cubs Shortstop $6,857,142
Starling Marte Pittsburgh Pirates Left Fielder $1,333,333
Stephen Drew New York Yankees Second Baseman $5,000,000
Stephen Strasburg Washington Nationals Pitcher $7,400,000
Stephen Vogt Oakland Athletics Catcher $512,500
Steve Cishek Miami Marlins Pitcher $6,650,000
Steve Clevenger Baltimore Orioles Catcher $514,000
Steve Geltz Tampa Bay Rays Pitcher $508,900
Steve Pearce Baltimore Orioles Left Fielder $3,700,000
Steve Tolleson Toronto Blue Jays Third Baseman $517,300
Steven Souza Jr. Tampa Bay Rays Center Fielder $508,700
Steven Wright Boston Red Sox Pitcher $510,500
T.J. House Cleveland Indians Pitcher $511,900
Taijuan Walker Seattle Mariners Pitcher $513,100
Tanner Roark Washington Nationals Pitcher $529,600
Tanner Scheppers Texas Rangers Pitcher $515,200
Taylor Featherston Los Angeles Angels Shortstop $507,500
Taylor Thompson Oakland Athletics Pitcher $507,500
Thomas Pham St. Louis Cardinals Center Fielder $507,500
Tim Beckham Tampa Bay Rays Shortstop $508,100
Tim Collins Kansas City Royals Pitcher $1,475,000
Tim Federowicz San Diego Padres Catcher $512,400
Tim Hudson San Francisco Giants Pitcher $12,000,000
Tim Lincecum San Francisco Giants Pitcher $18,000,000
Tim Stauffer Minnesota Twins Pitcher $2,200,000
Todd Frazier Cincinnati Reds Third Baseman $3,750,000
Todd Redmond Toronto Blue Jays Pitcher $520,000
Tom Gorzelanny Detroit Tigers Pitcher $1,000,000
Tom Koehler Miami Marlins Pitcher $570,000
Tom Wilhelmsen Seattle Mariners Pitcher $1,400,000
Tommy Hunter Baltimore Orioles Pitcher $4,650,000
Tommy La Stella Chicago Cubs Second Baseman $513,000
Tommy Layne Boston Red Sox Pitcher $557,000
Tommy Milone Minnesota Twins Pitcher $2,775,000
Tony Cingrani Cincinnati Reds Pitcher $525,500
Tony Cruz St. Louis Cardinals Catcher $775,000
Tony Sanchez Pittsburgh Pirates Catcher $518,000
Tony Sipp Houston Astros Pitcher $2,400,000
Tony Watson Pittsburgh Pirates Pitcher $1,750,000
Torii Hunter Minnesota Twins Right Fielder $10,500,000
Travis d`Arnaud New York Mets Catcher $525,424
Travis Ishikawa San Francisco Giants Left Fielder $1,100,000
Travis Snider Baltimore Orioles Right Fielder $2,100,000
Travis Wood Chicago Cubs Pitcher $5,685,000
Trevor Bauer Cleveland Indians Pitcher $1,940,000
Trevor Cahill Atlanta Braves Pitcher $12,200,000
Trevor Plouffe Minnesota Twins Third Baseman $4,800,000
Trevor Rosenthal St. Louis Cardinals Pitcher $535,000
Troy Tulowitzki Colorado Rockies Shortstop $20,000,000
Tsuyoshi Wada Chicago Cubs Pitcher $4,000,000
Tuffy Gosewisch Arizona Diamondbacks Catcher $514,500
Tyler Chatwood Colorado Rockies Pitcher $1,000,000
Tyler Clippard Oakland Athletics Pitcher $8,300,000
Tyler Flowers Chicago White Sox Catcher $2,675,000
Tyler Ladendorf Oakland Athletics Second Baseman $507,500
Tyler Matzek Colorado Rockies Pitcher $509,500
Tyler Moore Washington Nationals First Baseman $518,200
Tyler Olson Seattle Mariners Pitcher $507,500
Tyler Skaggs Los Angeles Angels Pitcher $515,000
Tyler Thornburg Milwaukee Brewers Pitcher $510,500
Tyson Ross San Diego Padres Pitcher $5,250,000
Ubaldo Jimenez Baltimore Orioles Pitcher $11,923,102
Vance Worley Pittsburgh Pirates Pitcher $2,450,000
Vic Black New York Mets Pitcher $515,500
Victor Martinez Detroit Tigers Designated Hitter $14,000,000
Vinnie Pestano Los Angeles Angels Pitcher $1,150,000
Wade Davis Kansas City Royals Pitcher $7,000,000
Wade Miley Boston Red Sox Pitcher $3,666,666
Wei-Yin Chen Baltimore Orioles Pitcher $4,750,000
Welington Castillo Chicago Cubs Catcher $2,100,000
Wesley Wright Baltimore Orioles Pitcher $1,700,000
Wil Myers San Diego Padres Right Fielder $519,800
Wil Nieves San Diego Padres Catcher $850,000
Wilin Rosario Colorado Rockies Catcher $2,800,000
Will Harris Houston Astros Pitcher $513,900
Will Middlebrooks San Diego Padres Third Baseman $540,500
Will Smith Milwaukee Brewers Pitcher $512,500
Will Venable San Diego Padres Center Fielder $4,250,000
Willie Bloomquist Seattle Mariners Shortstop $3,000,000
Wilmer Flores New York Mets Shortstop $513,543
Wilson Ramos Washington Nationals Catcher $3,550,000
Wily Peralta Milwaukee Brewers Pitcher $525,500
Xander Bogaerts Boston Red Sox Shortstop $543,000
Xavier Cedeno Washington Nationals Pitcher $516,500
Yadier Molina St. Louis Cardinals Catcher $15,200,000
Yan Gomes Cleveland Indians Catcher $1,083,000
Yangervis Solarte San Diego Padres Second Baseman $516,400
Yasiel Puig Los Angeles Dodgers Center Fielder $6,214,285
Yasmani Grandal Los Angeles Dodgers Catcher $693,000
Yimi Garcia Los Angeles Dodgers Pitcher $510,000
Yoenis Cespedes Detroit Tigers Right Fielder $10,500,000
Yoervis Medina Seattle Mariners Pitcher $527,300
Yonder Alonso San Diego Padres First Baseman $1,650,000
Yordano Ventura Kansas City Royals Pitcher $750,000
Yovani Gallardo Texas Rangers Pitcher $13,000,000
Yu Darvish Texas Rangers Pitcher $10,000,000
Yunel Escobar Washington Nationals Second Baseman $5,000,000
Yusmeiro Petit San Francisco Giants Pitcher $2,100,000
Zach Britton Baltimore Orioles Pitcher $3,200,000
Zach Duke Chicago White Sox Pitcher $4,500,000
Zach McAllister Cleveland Indians Pitcher $520,400
Zach Putnam Chicago White Sox Pitcher $525,000
Zach Walters Cleveland Indians Second Baseman $509,600
Zack Cozart Cincinnati Reds Shortstop $2,350,000
Zack Greinke Los Angeles Dodgers Pitcher $27,000,000
Zack Wheeler New York Mets Pitcher $546,250
 
Do you need a similar assignment done for you from scratch? Order now!
Use Discount Code "Newclient" for a 15% Discount!