Solar Oven Final Report

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Solar Oven Final Report

University  of  Arizona   Tucson,  AZ,  85716

S.A.C.R.A.W Solar Oven Prepared for: Dr. Stanley Pau

 

 

 

Jack Speelman Rebecca Nelson Paola “Andy” Lopez Lorin Greenwood Stephanie Gilboy October 21st 2012

Figure 1: Shows the team members of Team S.A.C.R.A.W standing alongside the final solar oven on Solar Oven Testing Day.

 

 

 

Team S.A.C.R.A.W Solar Oven 2

 

Table of Contents

 

 

Cover 1 Table of Contents 2 Executive Summary 3 Introduction – Motivation/Background/Key Terms 4-5 – Criteria and Constraints 5-6 Main Body – Functional and Design Requirements 6-7 – Design Theory and System Model 7-10 – Design Description – Conceptual Design 11-13 – Design Description – Final Design 14-17 – Design Justification 17-18 – Evaluation of Results 18-19 – Test Procedure 19-20 Design Critique and Summary 20-22 Appendix – First Oven Spreadsheet Data and Design/Drawing 22-24 – Final Oven Spreadsheet Data and Design/Drawing 25-27 – References 28

 

 

 

Team S.A.C.R.A.W Solar Oven 3

Executive Summary

The objective of the solar oven project was to design, build, and test a productive solar oven that

could reach an interior temperature of 100˚C. This was obtained through converting solar energy,

also known as electromagnetic energy, into thermal energy. The first law of thermodynamics

was utilized by understanding that energy cannot be created or destroyed but could be

transformed and used to heat the interior of the oven.

 

Two solar ovens were constructed in order to fully maximize the temperature inside the oven

chamber. The first oven was used as a prototype and research tool in order to build an oven that

could reach the optimum temperature calculated. The initial oven was predicted at 170.26˚C but

only reached an interior temperature of 85.6˚C. This produced a preforming index number of

1.02 and a cost index of 6.05˚C/dollar. The improved oven had a predicted temperature of

176.58˚C using the ambient air temperature and solar density provided. The oven reached an

interior temperature of 99.6˚C. The performing index for the second oven was calculated to be

1.28 and a cost index of 4.34˚C/dollar.

 

 

 

Team S.A.C.R.A.W Solar Oven 4

Introduction

Motivation:

• Learn the concept of team work and how to work together with other people to

achieve a common goal

• Gain proficiency in Excel, Solid Works, and basic solar oven knowledge.

• Acquire knowledge of the transformation of solar energy to heat.

• Learn the basics of the design and construction process

Background:

The main goal of the solar oven project was to find out the best way to change solar

energy into thermal energy. To do this, teams needed to know the first law of thermodynamics.

The first law states that energy cannot be created or destroyed, but can be changed from one

form to another. In the Solar Oven Theory, the energy that is put into the oven should equal the

energy that comes out (Ein=Eout). Therefore, the solar energy in joules should equal the thermal

energy in joules. The oven does this by taking the energy from the sunlight and transferring it

into heat. Since the energy in equals the energy out it allows the equation stated above to be

true. Knowing that the power is equal allows Team S.A.C.R.A.W. to find the temperature of the

oven chamber.

Mathematics for the Solar Oven with Key Terms:

Predicted Temperature:

 

 

 

Team S.A.C.R.A.W Solar Oven 5

€

Tio = Tambient + IoAw ⋅ G⋅ τ

n ⋅ a Usb ⋅ Asb +Uw ⋅ Aw( )

 

Variables:

Tio =the temperature inside the cooking chamber

Tambient= the outdoor temperature on the day tested

G= the gain from the reflectors

Uw= the heat transfer coefficient of the window

Aw= the area of the window

Usb= the heat transfer coefficient of the sides and bottom of the cooking chamber

Asb= the total area of the sides and bottom of the cooking chamber

Constants:

a= absorption coefficient of the cavity walls

τ= the optical transmission coefficient of the cavity walls

Io= the incident solar power density

Performing Index:

 

Variables:

Tio =the temperature inside the cooking chamber

Tambient= the outdoor temperature on the day tested

Tpredicted= the predicted temperature of the oven

Cost= the amount of money and labor for the solar oven in dollars

(Source: “Solar Oven Basics” Engineering 102)

 

 

 

Team S.A.C.R.A.W Solar Oven 6

Criteria and Constraints:

• Cooking oven must be equal to 1000 cm3

o Length (L) and height (h) need to be a minimum of 5cm

• The cooking oven window needs to be a square (W=L)

• The oven must have access for a digital thermometer and have a rack to support a biscuit

• There must be two calculated Performing Index’s calculated PISTOD and PIcost

• The maximum M/L ratio is 3

• The minimum final oven temperature is 100ᵒ C

• Optimal final temperature is over 200ᵒ C

• Focusing lenses and parabolic designs are not allowed

(Source: Solar Oven Design Project and Report Guidelines)

Main Body

Functional and Design Requirements The overall purpose of constructing the solar oven is to convert the absorbed solar energy into

heat. Different requirements of the oven were given in order to fulfill the purpose of constructing

and designing the solar oven. Functional requirements of the oven are needed in order for the

oven to actual work. Functional Requirements for the project include:

• The oven chamber must reach a minimum temperature of at least 100 degrees Celsius.

This is the minimum temperature that is needed to cook the biscuit inside the solar oven

chamber

 

 

 

Team S.A.C.R.A.W Solar Oven 7

• Using exactly four reflectors, sunlight needs to deflect into the Mylar windows at a

certain angle in order to achieve maximum temperature.

• Insulation is needed to surround the chamber to avoid loosing any form of heat.

• The four reflectors given need to be placed at a certain angle to not let any of the sunlight

be steered away from the Mylar window.

• An object or stand supporting the oven may be used in order to have the window be

exactly perpendicular to the sunlight. This way, all the sunlight can directly enter the

window.

Design requirements are given to avoid any advantage towards any oven. These requirements are

given in order for every oven to be at the same advantage. Design Requirements for the project

include:

• The oven chamber dimension should equal exactly 1000 cm3.

• Access to the inside of the solar oven should be fairly simple. Different methods to access

the oven include: lifting the top, door-opening mechanism, the sliding tray mechanism,

and many other methods.

• A hole or small opening for the thermometer to have access to the oven chamber

• The ratio of the reflectors and the width of the widow (M/L) should have a ratio of three

or less.

• The reflectors should be flat and straight; not parabolic. Having parabolic curves could

result in an explosion in the solar oven.

Design Theory and System Model

To conquer the solar oven, Team S.A.C.R.A.W. had to learn more about the theory

behind the solar oven. The knowledge learned can be implemented into constructing the most

 

 

 

Team S.A.C.R.A.W Solar Oven 8

efficient solar oven. The different dimensions of the oven are variables that affect how much

solar energy is converted heat inside the solar oven chamber. By knowing how these variables

affect the temperature allowed Team S.A.C.R.A.W. to reach optimum temperature inside the

oven. The equation predicting the temperature inside the chamber is:

Figure 2: Shows the equation to predict the temperature inside the solar oven chamber

 

 

In the equation above, the variables that have the most effect on the predicted temperature (Tio)

are the variables that are related to the dimensions of the solar oven chamber (Asb and Aw). Asb

represents the total surface areas of the side and bottoms of the solar oven chamber. Aw

represents the surface area of the window that heat is transferred through. Since a given

constraint of the oven is that the volume has to equal 1000 cm3, increasing the Aw would result in

decreasing the Asb. Since Aw appears in both the denominator and numerator in the equation,

increasing the value would have no affect in the Tio , but decreasing the Asb would result in a

higher Tio since the variable only appears in the denominator.

In the equation, G represents the gain of heat that the solar oven reflectors acquire. The

following equation is used to calculate the value of G:

Figure 3: Shows the equation to solve for G, and the variables that affect the value

 

As shown in Figure 3, the number of reflectors (represented by r) affects the overall gain.

Without any reflectors, the gain would equal just one. A higher M/L ratio for the oven would

also increase the gain value. The maximum value of M/L that is allowed is three, and as shown

€

Tio = Tambient + IoAw⋅ G⋅ τ

n⋅ a Usb⋅ Asb +Uw⋅ Aw( )

 

 

 

Team S.A.C.R.A.W Solar Oven 9

in Figure 3, the highest M/L would be most ideal. However, as shown in the table below, having

a higher M/L ratio results in a smaller alpha value.

Table 1: Shows the M/L ratio and the alpha and omega angle associated with each ratio

M/L α Ω 3 16.31° 106.31° 2 21.47° 111.47° 1 30° 120°

 

The alpha angle in the higher M/L ratio is smaller than the smallest M/L ratio, which is one.

However, when multiplying the M/L ratio by the sin (α), the highest value still comes out for the

M/L value that equals three. The highest M/L value is preferred for constructing the oven

because it will allow for the largest reflector gain for the oven.

Two values in the solar oven predicted temperature equation depend on the weather:

temperature (Tambient) and the solar irradiance of the sun (Io) at that time of day. If the

temperature outside is low, the Tambient will also be low, which would result in a lower Tio. If the

sky is cloudy and hardly any sunlight is penetrating through, the solar density will be low, which

would also result in a lower Tio. The weather is a major component in a higher Tio. Because

Arizona relatively tends to have high temperatures and large amounts of sunlight, both values

should be high.

Two other given constraints in the solar oven predicted temperature equation are τ

(optical transmission coefficient of window) and a (absorption coefficient of the cavity walls).

Team S.A.C.R.A.W wanted as much power to be absorbed into the solar oven chamber as

possible, which would result in a higher Tio To achieve such results, both τ and a have to be as

close to one as possible. The optical coefficient of the window depends on the type of window

material used. An ideal window material used for higher τ would have to be highly transparent

 

 

 

Team S.A.C.R.A.W Solar Oven 10

across the visible and near-infrared spectrum. The absorption coefficient of the cavity walls (a)

depends on the color used. The color black absorbs the highest amount of sunlight in comparison

with others colors, and thus has a higher absorption coefficient.

In the solar oven chamber predicted temperature equation, having a low U (overall heat

transfer coefficient) would result in a higher predicted temperature. The value of U is inversely

related to the thermal resistance to the flow of heat energy (R). The equation below shows the

relationship between both values:

Figures 4: Shows the relationship between the heat transfer coefficient and the thermal resistance

 

The equation shows that having multiple materials with higher thickness (x) and higher thermal

conductivity (k) values result in a higher R-value, which results in a lower U value. Having more

insulation materials (such as cardboard, foam, newspaper) decreases the overall heat transfer and

increases the Tio.

One of the main goals of Team S.A.C.R.A.W for constructing the solar oven chamber is

to have the actual temperature acquired equal to the predicted temperature calculated. However,

the task is nearly impossible. Different sources of error can prohibit Team S.A.C.R.A.W from

achieving the desired goal. One of the main errors is not having the dimensions of the solar oven

match up with the ones calculated. For example, if Team S.A.C.R.A.W calculated the area of the

window to be 0.02 m2 and instead constructed a window with an area of 0.018 m2, the result

would be an actual value of Tio that differs from the calculated Tio. Another source of error

includes the deterioration of the materials due to the heat. The materials to construct the oven

must be careful considered. If the materials used are not able to withstand the heat and melt, the

solar oven’s durability will also decrease.

 

 

 

Team S.A.C.R.A.W Solar Oven 11

Design Description – Conceptual Design

Figure 5: Shows the outer view of the first oven Figure 6: Shows the inside view (the insulation) of the first solar oven constructed

 

constructed.

 

 

 

 

The first goal for Team S.A.C.R.A.W was to generate a solar oven that met the minimum requirements given by the instructor. Since every solar oven group had two official

trials to test out the ovens, Team S.A.C.R.A.W.s’ main focus was to achieve the optimum

temperature possible with the given constraints. The variables in our oven focused around the

dimensions of the oven chamber. The following table lists the variables that were adjusted for the

first solar oven.

Table 2: Shows the design variables and measurements for the first solar oven constructed

Design Variables Measurements

Aw 0.01 m2

0.92

a 0.9

r 0.7

40

Usb 0.642192854

Asb 0.05 m2

 

 

 

Team S.A.C.R.A.W Solar Oven 12

Io 691 W/m2

40 degrees

Tambient 29.4 degrees Celsius

G 5.205335351

 

The materials that were given by the instructor to construct the oven include:

cardboard, Mylar sheets, black paper, scissors, and a thermometer. The cardboard given was

used to construct the four reflectors, the solar oven chamber, and the outer box where the solar

oven chamber and insulation was kept. Black Duct tape was used to connect the solar oven

chamber to the lid of the outer box. To get to the oven chamber, the reflectors and Mylar sheets

where lifted from a hole centered in the top lid. Inside the chamber, there was a rack that was

intended to hold to biscuit in place. To position the angle of the oven in order for the oven

chamber to absorb optimum heat, backpacks and notebooks were used.

Two Mylar sheets were used and were on top of one another. They were placed

directly above the solar oven chamber and were connected to the reflectors. Having more Mylar

sheets minimized heat losses through the window, while still allowing solar energy to be

transmitted into the oven chamber.

Four reflectors were used and were covered with aluminum foil. Aluminum foil was

used because the material is low-cost and effective. Despite trying to have a smooth aluminum

foil covering the reflectors, Team S.A.C.R.A.W had to take into account the wrinkled sheets,

which affects the overall temperature inside the oven. The shape of the four reflectors was a

trapezoid, and to keep things simple, the height of each reflector was 30 cm. Having a trapezoid

shape for the reflectors allowed no gaps between the reflectors, a problem that would arise if

rectangular reflectors were used. The base of the reflectors was 10 cm wide, conforming to the

 

 

 

Team S.A.C.R.A.W Solar Oven 13

dimensions of the width of the mylar windows. In order to maintain a M/L ratio of 3 or less, the

area of the window had to be 10 cm by 10 cm. To keep with the constraint of having a solar oven

chamber with a volume of 1000 cm3, the solar oven ended up being a cube.

To maximize insulation, Team S.A.C.R.A.W built a huge outer oven to store all of

the insulation. The dimensions of the outer box were 0.62×0.62×0.1 all measured in meters.

However, the insulation material used – newspaper and printer paper – was all wrinkled up and

was not arranged in an organized matter (as shown in Figure 4). However, having high

insulation, allowed for a higher Uxb value, which increases the Tio value overall. Also, to not let

any heat escape the sides of the oven, the thermometer was placed inside the oven. Having that

particular setup prevents obstruction of window and loss of heat through mylar window.

To obtain the dimensions for the oven, Team S.A.C.R.A.W worked from the inside

out, starting with the dimension of the solar oven chamber. To keep things simple, the solar oven

chamber was made into a cube, and from those dimensions, the height of the reflectors was

determined. Having a maximum volume of 1000 cm3 and a M/L ratio of less than three put a

constraint on the oven since it prohibited from further increasing the height of the reflector.

 

 

 

 

Team S.A.C.R.A.W Solar Oven 14

Design Description – Final Design

Figure 7: Shows the construction of the new reflectors Figure 8: Shows the side view of the for the final oven final solar oven on Solar Oven Testing Day

 

 

 

 

 

 

The first solar oven testing allowed Team S.A.C.R.A.W to see what adjustments were

needed for the second oven. Needless to say, many adjustments were done. A new goal was

created – to reach the minimum temperature required, which was 100 degrees Celsius. Also, the

group strived to try to achieve a higher Performance index by reducing the total materials used,

thus reducing the total performing index. To decrease the cost without falling under the

minimum temperature required (100 degrees Celsius), Team S.A.C.R.A.W. took the following

steps: create a smaller insulation box, create smaller and more efficient reflectors, and improve

the design of cooking chamber in order to maximize the total volume. The following variables in

the table below show the values used to calculate the predicted temperature

Table 3: Shows the list of variables used to predict the temperature inside the oven chamber.

Design Variables Measurements

Aw 0.013225 m2

0.92

a 0.9

 

 

 

Team S.A.C.R.A.W Solar Oven 15

40

Usb 0.642192854

Asb 0.0219206522 m2

Io 619 W/m2

40 degrees

Tambient 29.4 degrees Celsius

G 5.205335351

 

Somehow, the first solar oven had dimensions that did not match up with the dimensions

that Team S.A.C.R.A.W. calculated. The group that dissected the oven noticed that the alpha

angle did not match up with the value that Team S.A.C.R.A.W had calculated. The angle value

that Team S.A.C.R.A.W that used based off of the M/L value, which was equal to three. The

group that dissected Team S.A.C.R.A.W.s’ oven measured out the angle to be 15.687 degrees.

The angle that Team S.A.C.R.A.W. calculated based off the M/L ratio was 16.31. Also, the M/L

ratio (that the group who dissected Team S.A.C.R.A.Ws’ oven measured out) was higher than

three. Knowing that these dimensions were inaccurate from the proposed dimensions given by

Team S.A.C.R.A.W, Team S.A.C.R.A.W focused more on accurately measuring out the

dimensions of the oven and making sure that all of the dimensions calculated for the oven

matched up to the actual oven.

Instead of constructing a cubic oven chamber, a rectangular-shaped oven was generated.

Team S.A.C.R.A.W decreased the height of the oven chamber to increase the area of the top and

bottom sides of the oven chamber. Since the width and length of the Mylar sheets are correlated

with the dimensions of the top lid of the chamber oven, the area of the window also increased by

making the oven chamber rectangular. The length of the square Mylar sheet for the new oven

 

 

 

Team S.A.C.R.A.W Solar Oven 16

was determined to be 11.5 cm, which also increased the height of the trapezoidal reflectors to

34.5 cm (to keep in with the M/L ratio of 3).

During the trial for the first solar oven, Team S.A.C.R.A.W noted that tape used did not

properly hold the oven in its place. A new brand of tape was bought, Gorilla duct-tape, which

withstood the heat and did not melt or peel off when exposed to the sun. Although it increased

the Performance Index cost since it was more expensive than the previous adhesive, this new

duct-tape improved structural rigidity and high-temperature performance. The duct-tape was

applied along the sides and corners of any joint component of the oven, which resulted in a

stronger structure and prohibited any air from escaping.

Instead of using wrinkled up newspaper and printer paper for insulation, Polyurethane

insulation foam was used. This foam did a better job of trapping heat and hardly left any room

for letting heat escape. The foam also had greater thickness than the newspaper and higher

thermal conductivity, thus increasing the resistance to escaping heat. However, it was discovered

afterwards that the foam expanded during testing. This increased the dimensions of the outer box

and may have possibly decreased the volume of the solar oven chamber.

The last improvement done on the final solar oven would be the dimensions of the

reflectors. Since the alpha angle was off in the first solar oven, a protractor was used to insure

that the angle matches to the one calculated by Team S.A.C.R.A.W. These new reflectors were

longer, were angled correctly to match the alpha angle calculated (16.31 degrees Celsius), and

had a higher reflectivity (aluminum foil was much smoother). Also to avoid loosing more heat,

the chambers’ sides were still connected with the reflectors when they were cut out. This way,

instead of loosing heat between the gaps of the reflectors and chamber, hardly any heat would be

lost. To have access to the insides of the chamber, the chamber and reflectors were lifted (since

 

 

 

Team S.A.C.R.A.W Solar Oven 17

they were connected). The Mylar sheets were placed from the top and were put at the bottom of

the reflectors. The cut out of the Mylar sheets had a slightly larger area than the window

dimensions, allowing the extra surface area on the Mylar sheets to connect the mylar window to

the top of the solar chamber (area where the solar chamber and reflectors meet).

Much more care and accuracy was placed into constructing the final oven in comparison

with the first oven. Also, to absorb more heat, the inside solar chamber was painted black. Black

is known to absorb the most amount of heat in comparison with other colors. Team

S.A.C.R.A.W also made the outer chamber more aesthetically pleasing by decorating it with red

paint.

Design Justification

To keep the first solar oven simple, Team S.A.C.R.A.W. made the solar oven chamber,

the basis for the construction of the oven, a cube. Team S.A.C.R.A.W.s’ main focus was on

simplicity and the performance of the oven, thus generating an oven with large reflectors and a

cubic solar oven chamber. With those factors in mind, Team S.A.C.R.A.W designed the oven

and constructed the oven based on those parameters. An example of a performance-orientated

component of the oven was the insulation. Team S.A.C.R.A.W decided to use as much insulation

as possible to achieve optimum temperature and a greater performance overall. Unfortunately,

having more insulation in the outer box chamber resulted in more material usage and more open

space for heat to escape (a factor that was not thought of until the day of solar oven testing). In

addition, the size of the reflectors was maximized in relations with the width of the window

(M/L = 3). Both actions were done without a thought about the performance index cost.

 

 

 

Team S.A.C.R.A.W Solar Oven 18

Once the oven was tested and dissected by another team, Team S.A.C.R.A.W noticed that

keeping the oven simple was not a method to achieve maximum performance. The overuse of

materials and lack of accuracy of the dimensions made the performance index relatively low. As

a result, the oven had the lowest temperature acquired out of all the other ovens in the class. For

the second oven, the team decided to replace many materials with more durable options and

made sure that the oven matched the dimensions that were calculated. Less cardboard was used

on the solar chamber and outer chamber, and also, different insulation was used. However, to

obtain a higher temperature, the size of the reflectors was increased. Increasing reflector size

resulted in a higher area of window and a lower surface area of the sides and bottom of the

chamber. The outer chamber box was decreased to reduce the insulation and the new insulation,

foam, did a better job of not letting heat escape than the newspaper and printer paper. The

performance index cost reduced with the usage of less material for the first oven. Also, the

overall performing index of the new solar oven was higher than the first solar oven.

 

Evaluation of Results

Due to the cloudy day and lack of sunlight, the final test did not yield results consistent

with the teams’ expectations and did not verify the final design process. The solar power density

given before the Solar Oven Throw down did not match up with the actual solar density value of

the weather. The result caused the predicted temperature calculated beforehand to be much

higher than the one actually calculated on that day (calculated to be around 109 degrees). The

temperature of the final oven was 99.6 degrees Celsius with a performing index of 1.28. The

predicted temperature of the oven on that day was calculated to be 176.58 degrees Celsius. The

large difference in predicted and actual temperature resulted in a lower performing index.

 

 

 

Team S.A.C.R.A.W Solar Oven 19

However, the main focus for the second design of the solar oven was to improve on the

performing index and durability of the oven. The first oven had a performing index of 1.02, a

predicted temperature of 170.26 degrees Celsius, and an actual temperature of 85.8 degrees

Celsius. No issues regarding the weather occurred on the first solar oven trial day – the day was

filled with sunlight and heat. Although the final oven did not reach the desired 100 degree

Celsius temperature, the final oven had a greater performance and better durability than the first

oven, which was the overall goal for Team S.A.C.R.A.W.

 

Test Procedure

Table 4: Shows the values measured in both ovens.

Value Measured First Oven Second Oven

Predicted Temperature (Tio) 170. 26 degrees Celsius 176.58 degrees Celsius

Actual Temperature Acquired 85.8 degrees Celsius 99.6 degrees Celsius

Performing Index 1.02 1,23

Performing Cost 6.05 degrees Celsius/dollar 4.34 degrees Celsius/dollar

 

As shown in Table 4, the measured values are much smaller than the predicted values. For the

first oven, Team S.A.C.R.A.W. identified that the result of disagreement between the predicted

and actual temperature value was because of the lack of accuracy done on the dimensions of the

oven. The angles of the reflectors were not measured accurately – the angles were just assumed

to be correct based off of the dimensions of the reflectors. Also, the insulation was not tightly

packed together; instead there were many openings for heat escape through. For the second oven,

more accuracy was placed on the dimensions of the oven. Also, a different material was used for

 

 

 

Team S.A.C.R.A.W Solar Oven 20

the insulation. However, the reason for the vast difference in degree of the predicted and actual

temperature was because of the weather. The weather on solar oven testing day was much cooler

than predicted. Also, not that much sunlight was penetrating through the clouds, resulting in a

lower solar irradiance value (I0)). The change in weather is out of Team S.A.C.R.A.Ws’ control,

thus no conclusion can be made on what improvements could have been done for the final oven

aside from testing it on a different day that includes more sunlight and less clouds.

 

Design Critique and Summary

Team S.A.C.R.A.W.’s objective was to build a solar oven that met the constraints and

performed at optimum temperature. The team needed to build the oven at a low cost but still able

to withstand the high temperatures made on the day of testing. Teamwork, collaboration, and

attention to detail were implemented to produce an oven that had the potential to reach 176.58°

C. During construction of the first and second oven, the team realized many areas of

improvement that would raise the temperature of their oven and produce a more efficient

product. For example, in the first oven constructed, a flimsy duct tape was used to hold together

the corners of the exterior of the oven. When the first oven was tested, the tape could not

withstand the high temperatures and the adhesives began to fall apart. Because of the error, gaps

began to form around the exterior oven, which allowed heat to escape. To prevent this from

happening again, the second oven was constructed with a heavy-duty black duct tape that was

able to withstand much higher temperatures than what could be reached with the solar oven. If

 

 

 

Team S.A.C.R.A.W Solar Oven 21

another oven was to be built, it should be constructed with the heat resistant tape to minimize the

heat loss. Another area that needed improvement from the first oven to the second was the angle of

the reflectors relative to the oven container. Precise measurements needed to be done in order to

have the optimal angle that would allow the most solar light to be reflected into the cooking

chamber. To fix this problem, S.A.C.R.A.W. used a more accurate protractor and ruler when

measuring the reflectors for the second oven. This way the angle was accurate and allowed the

most light to be reflected into the cooking chamber. If this oven was to be reconstructed it is

recommended that an emphasis is put on the measurement of the angles because this has a direct

impact on the amount of light reflected into the cooking chamber. The more light reflected into

the cooking chamber, the higher the temperature will reach.

The insulating material is a large component of how much heat will be retained and how

much will be lost through the walls of the oven. In the first oven, the team used crumpled up

newspaper and printer paper to insulate the cooking chamber. While the crumpled up paper took

up a lot of room, there was a lot of room for the air to move around between the pieces of paper.

The conductive heat loss was maximized because the molecules had a lot of air to move around

in and therefore they did not hold very much heat. For the second oven constructed, insulating

foam was used inside the oven. The foam sealed all of the edges of the oven to heat was not lost

through those and it also reduced the movement of air inside the chamber. The heat stayed

localized to the chamber instead of freely moving about the oven and escaping. This was

essential for the oven built by S.A.C.R.A.W. because on the day of testing it was very cloudy out

and the ambient air temperature and the incident solar density were not very high. This meant

that the oven only increased temperature when there was direct sunlight. The data oscillated

 

 

 

Team S.A.C.R.A.W Solar Oven 22

because every time the sun would go behind the clouds, the temperature would drop slowly and

when the sun would come back out, the temperature would shoot up. Because of the foam

insulation and the minimal amount of heat escaping the oven, S.A.C.R.A.W.’s oven was able to

maintain a temperature higher than the ambient air temperature when the sun was behind the

clouds so when it did come out and provide direct sunlight, the temperature was able to start at a

higher initial temperature and rise from there. If there had been direct sunlight on the day of

testing, the oven would be considered a viable cooking unit that could be used if desired to cook

food for consumption. Appendix

First Oven Spreadsheet Data and Drawing

Figure 9: Shows the drawing and dimensions for the first solar oven.

 

 

 

 

 

Team S.A.C.R.A.W Solar Oven 23

Table 5: Shows the value of each variable and their value. It also states the variables’ units and description

Variable Value Units Description Io 619 watts/m2 (solar power density)

τ 0.92 (transmissivity for single layer of mylar)

a 0.9 (absorptivity of oven chamber and contents)

r 0.7 (reflectivity of Al foil) Tambient 29.4 C ambient temperature L 0.1 m length of oven window

h 0.1 m height of oven chamber n 2 # of layers of mylar M 0.3 m length of reflectors Aw 0.01 m2 area of the window

Asb 0.05 m2 area of the sides and bottom

Vchamber 0.00099981 m3 volume of the oven chamber

M/L 3 ratio of reflector length to oven window length

Usb 0.642192854 heat transfer coefficient of the chamber

α 0.284602961 angle of the reflectors with respect to the Sun’s rays

G 5.205335351 gain from reflectors Table 7: Shows the dimensions of the oven

Table 6: Shows the materials used for insulation

Wall Element Thickness (m)

Thermal Conductivity (watts/m-C)

Inner cardboard wall x1 0.003 k1 0.064 Insulation (wadded newspaper) x2 0.18 k2 0.123 Outer cardboard wall x3 0.003 k3 0.064

 

Dimension Length (m) Length of window 0.1 Width of window 0.1 Length of oven 0.6096 Width of oven 0.6096 Height of oven 0.1524 Length of chamber 0.1 Width of chamber 0.1 Height of chamber 0.1 Reflector length 0.3

 

 

 

Team S.A.C.R.A.W Solar Oven 24

 

 

 

 

 

 

Tio Uw(single) Uw(double) Table Combo 1

10.1 4.9 66 225.319429 13.9 6.7 93 179.723146 18.7 9 121 145.571651 24.3 11.7 149 121.231541 31.6 15.2 177 101.530964 40.1 19.4 204 87.1142525

Value Measured First Oven Predicted Temperature (Tio)

170. 26 degrees Celsius

Actual Temperature Acquired

85.8 degrees Celsius

Performing Index 1.02 Cost Index 6.05 degrees

Celsius/dollar

Component Amount Cost ($)

Total Cost for Component ($)

Grand Cost ($)

Reflectors $0.31 $1.25 $1.25 Interior Chamber

$0.40 $0.40 $1.59

Exterior Chamber

$1.94 $1.94 $3.73

Mylar Sheets $0.25 $0.50 With Reflectors

Duct Tape $0.50 $0.50 $8.73 Paper $0.03 $0.03 With interior

chamber Newspaper $0.00 $0.00 $8.73 Grand Total $8.73

Table 8: Shows the heat transfer values for the windows

Table 9: Final Results for the First Oven

Table 10: Shows the breakdown of costs for the first oven

Figure 10: Shows the graph and equations of line used to predict the temperature of the fist oven

 

 

 

Team S.A.C.R.A.W Solar Oven 25

Second Oven Spreadsheet Data and Drawing

Figure 11: shows the drawing and dimensions for the final oven

 

 

 

 

Team S.A.C.R.A.W Solar Oven 26

Table 11: Shows the values for the variables used to predict the Tio for the second oven Variable Combo 1 Units Description Io 619 watts/m2 (solar power density)

τ 0.92 (transmissivity for single layer of mylar)

a 0.9 (absorptivity of oven chamber and contents)

r 0.7 (reflectivity of Al foil) Tambient 29.4 C ambient temperature L 0.115 M length of oven window

h 0.115 M height of oven chamber n 2 # of layers of mylar M 0.345 M length of reflectors Aw 0.013225 m2 area of the window

Asb 0.048001 m2 area of the sides and bottom

Vchamber 0.00099981 m3 volume of the oven chamber

M/L 3 ratio of reflector length to oven window length

Usb 0.642192854 heat transfer coefficient of the chamber

α 0.284602961 angle of the reflectors with respect to the Sun’s rays

G 5.205335351 gain from reflectors Table 12: Shows the values for the insulation used. Table 13: Shows the dimensions of the oven

 

Wall Element Thickness (m)

Thermal Conductivity (watts/m-C)

Inner cardboard wall x1 0.003 k1 0.064 Insulation foam x2 0.0925 k2 0.21 Outer cardboard x3 0.003 k3 0.064

Dimension Length (m) Length of Window 0.115 Width of Window 0.115 Length of oven 0.3 Width of oven 0.3 Height of oven 0.197 Length of Chamber

0.115

Width of Chamber 0.115 Height of Chamber 0.0756 Reflector Length 0.345

 

 

 

Team S.A.C.R.A.W Solar Oven 27

 

 

 

Table #16: Shows the breakdown of costs for the final oven

 

 

Tio Uw(single) Uw(double) Table Combo 1

10.1 4.9 66 358.947717 13.9 6.7 93 285.790364 18.7 9 121 229.865253 24.3 11.7 149 189.399928 31.6 15.2 177 156.270352 40.1 19.4 204 131.809152

Value Measured Second Oven Predicted Temperature (Tio)

176.58 degrees Celsius

Actual Temperature Acquired

99.6 degrees Celsius

Performing Index 1,23 Cost Index 4.34 degrees

Celsius/dollar

Component Amount Cost $

Total Cost for Component $

Grand Cost $

Reflectors $0.43 $1.72 $1.72 Interior Chamber

$0.05 $0.05 $1.77

Exterior Chamber

$0.71 $0.71 $2.48

Mylar Sheets $0.25 $0.50 With Reflectors Duct Tape $5.00 $5.00 $7.48 Foam $5.00 $7.50 $14.98 Grand Total $14.98

Figure 12: Shows the graph and equation of lines used to determine the predicted temperature for the final oven

Table 14: Shows the heat transfer values for the windows   Table 15: Shows the final results for the final oven.

 

 

 

Team S.A.C.R.A.W Solar Oven 28

References References from Solar Oven Handout

“Solar Oven Basics” University of Arizona. Engineering 102. 2012

Shawyer, Michael and Avilio F. Medina Pizzali. “FAO Fisheries Technical Paper 436: The use

of ice on small fishing vessels.” FAO Corporate Document Repository. Food and

Agriculture Organization of the United Nations. Rome. 2003. Web. 13 Oct. 2012.

 
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Excel homework help

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Excel homework help

A Skills Approach: Excel 2016 Chapter 4: Formatting Worksheets

and Managing the Workbook

1 | Page Skill Review 4.1 Last Updated 4/15/16

Skill Review 4.1 In this project, you will work on an attendance log for a 16-week college course. For one section of the course,

you will set up the sheet to print as an attendance sign-in sheet. For another section, you will set up the sheet

to print as an attendance report for the administration office. This is a long project. Be sure to save often!

Skills needed to complete this project:

 Naming Worksheets

 Changing the Color of Sheet Tabs

 Moving and Copying Worksheets

 Grouping Worksheets

 Modifying Column Widths and Row Heights

 Changing the Worksheet View

 Adding Headers and Footers

 Applying Themes

 Splitting Workbooks

 Inserting and Deleting Rows and Columns

 Deleting Worksheets

 Freezing and Unfreezing Rows and Columns

 Hiding and Unhiding Rows and Columns

 Changing Worksheet Orientation

 Setting Up Margins for Printing

 Scaling Worksheets for Printing

 Showing and Hiding Worksheet Elements

 Printing Selections, Worksheets, and Workbooks

 Printing Titles

 Inserting Page Breaks

1. Open the start file EX2016-SkillReview-4-1. The file will be renamed automatically to include your

name. Change the project file name if directed to do so by your instructor, and save it.

2. If the workbook opens in Protected View, click the Enable Editing button in the Message Bar at the

top of the workbook so you can modify the workbook.

3. Rename Sheet1 and change the color of the sheet tab.

a. Right‐click on the Sheet1 tab, choose Rename, and type: TTh300

b. Press the ENTER key.

c. Right‐click the sheet tab again, point to Tab Color, and select Green, Accent 6 (the last color in the

first row of theme colors).

4. Make a copy of the TTh300 sheet.

a. Right‐click the sheet tab and select Move or Copy… to open the Move or Copy dialog.

b. In the Before sheet box, select Sheet2.

c. Check the Create a copy check box.

d. Click OK.

 

Step 1

Download start file

 

 

A Skills Approach: Excel 2016 Chapter 4: Formatting Worksheets

and Managing the Workbook

2 | Page Skill Review 4.1 Last Updated 4/15/16

5. Name the new sheet MWF301 and change the tab color.

a. Right‐click the new TTh300 (2) sheet tab, choose Rename, and type: MWF301

b. Press the ENTER key.

c. Right‐click the sheet tab again, point to Tab Color, and select Blue, Accent 5 (the second color

from the right in the first row of theme colors).

6. Group sheets TTh300 and MWF301 so you can apply formatting changes to both sheets at once.

a. Click the TTh300 sheet tab, press and hold the Ctrl key, and click the MWF301 sheet tab. Now any

changes made to one of the sheets will be made to both sheets.

b. Verify that [Group] appears in the title bar, indicating that the selected sheets are grouped.

7. Resize column A in both worksheets at once to best fit the data by double-clicking the right border of

the column heading.

8. Add a header and footer to both worksheets at once.

a. Switch to Page Layout view by clicking the Page Layout button on the status bar.

b. Click in the center section of the header.

c. On the Header & Footer Tools Design tab, in the Header & Footer Elements group, click the File Name

button. The code &[File] will be entered in the center section of the header. Once you click

somewhere else, this will display the name of your file.

d. Click in the right section of the header and type your own name.

e. On the Header & Footer Tools Design tab, in the Navigation group, click the Go to Footer button.

f. Click in the center section of the footer.

g. On the Header & Footer Tools Design tab, in the Header & Footer Elements group, click the Sheet Name

button. The code &[Tab] will be entered. Once you click somewhere else, this will display the name

of the sheet.

h. Click in the right section of the footer.

i. On the Header & Footer Tools Design tab, in the Header & Footer Elements group, click the Current

Date button. Once you click somewhere else, this will display the current date.

j. Click in any cell of the worksheet and click the Normal button on the status bar.

9. Ungroup the sheets by clicking Sheet2. Verify that the same formatting was applied to both sheets and

that they are now ungrouped.

10. Apply the Integral theme to the workbook.

a. On the Page Layout tab, in the Themes group, click the Themes button to display the Themes gallery.

b. Notice that as you hover the mouse pointer over each option in the Themes gallery, Excel updates the

worksheet to display a live preview of how the theme would affect the worksheet.

c. Click the Integral option.

 

 

A Skills Approach: Excel 2016 Chapter 4: Formatting Worksheets

and Managing the Workbook

3 | Page Skill Review 4.1 Last Updated 4/15/16

11. Select the TTh300 sheet. It can be difficult to work with such a wide worksheet. Scroll to the right to see

the end of the semester, and you can no longer see the student names. Split the screen into two views of

different parts of this worksheet.

a. Click cell D1. On the View tab, in the Window group, click the Split button. Now you can scroll each

pane separately, but it is all still the same worksheet. You can drag the split bar to the right or left as

needed.

b. Scroll to show the student names and the last few weeks of the semester on your screen.

c. Click the Split button again to return to normal.

12. Insert a new row to add a new student to the list.

a. Right‐click on the row heading for row number 9 and select Insert.

b. Click the Insert Options button that appears immediately below where you right‐clicked, and select

Format Same As Below.

c. Enter the new student name: Aaron, Kayla

d. Enter her student ID #: 1350679

13. Select the MWF301 sheet. Because this sheet was copied from the TTh300 class worksheet, the student

names and ID numbers are not those of the students in MWF301 class. Copy the student data from

Sheet2, and then delete Sheet2 when it is no longer needed.

a. On sheet MWF301, select cells A9:B29. Press the DELETE key to delete the content.

b. Go to Sheet2 and copy the student names and ID numbers from cells A2:B20.

c. Paste the copied names and ID numbers to cell A9 in the MWF301 sheet.

d. Delete Sheet2 by right-clicking on the sheet name and selecting Delete.

e. When Excel displays the message telling you that you can’t undo deleting sheets, click the Delete

button to complete the action.

14. Jay Parson has decided to drop the class. Remove him from the MWF301 class roster.

a. On worksheet MWF301, delete the entire row for Jay by right-clicking on the row heading for row

number 21 and selecting Delete.

15. Use the Freeze Panes option to keep rows 1:8 and columns A:B visible at all times.

a. Verify that the MWF301 sheet is selected, and click cell C9.

b. On the View tab, in the Window group, click the Freeze Panes button, then click the Freeze Panes

option.

c. Verify that you selected the correct point at which to freeze panes. Scroll down and to the right. Are

rows 1:8 and columns A:B visible regardless of where you scroll?

 

 

 

A Skills Approach: Excel 2016 Chapter 4: Formatting Worksheets

and Managing the Workbook

4 | Page Skill Review 4.1 Last Updated 4/15/16

Modify sheet MWF301 to print as an attendance sign-in sheet.

16. First, hide the student ID numbers by right‐clicking on the column B heading and selecting Hide.

17. Set the page layout options.

a. On the Page Layout tab, in the Page Setup group, click the Orientation button, and select Landscape.

b. On the Page Layout tab, in the Page Setup group, click the Margins button, and select Narrow.

c. On the Page Layout tab, in the Scale to Fit group, expand the Width list and select 1 page, and expand

the Height list and select 1 page.

d. On the Page Layout tab, in the Sheet Options group, click the Print check box under Gridlines.

18. Print only the part of the worksheet to use as the attendance sign‐in sheet.

a. Select the appropriate cells to print as an attendance sign-in by selecting cells A1:C26.

b. Click the File tab to open Backstage view, and then click Print to display the Print page.

c. Under Settings, click the Print Active Sheets button to expand the options, and select Print

Selection.

d. If your instructor has directed you to print the attendance sign-in list, click the Print button.

e. Click the Back arrow to exit Backstage view.

At the end of the semester you will need to print all the attendance records to turn in to the administration

office. Let’s set this up for the TTh300 class worksheet.

19. Select the TTh300 worksheet, and hide the attendance sign-in column by right-clicking the column C

heading and selecting Hide.

20. Modify the worksheet so column A and rows 1 through 8 will print on every page.

a. On the Page Layout tab, in the Page Setup group, click the Print Titles button.

b. Click in the Rows to repeat at top box, and then click and drag with the mouse to select rows 1:8.

When you release the mouse button, you should see $1:$8 in the box.

c. Click in the Columns to repeat at left box, and then click with the mouse to select column A. When

you release the mouse button, you should see $A:$A in the box.

d. Click OK.

21. Preview how the worksheet will look when printed and make adjustments from the Print page to keep

the report to four or fewer pages.

a. Click the File tab to open Backstage view, and then click Print.

b. If necessary, select Print Active Sheets under Settings.

c. Note that the current settings will cause the worksheet to print on five pages.

d. Under Settings, click the Portrait Orientation button and switch to Landscape Orientation instead.

e. Under Settings, click the Normal Margins button, and select Custom Margins… to set your own

margins.

 

 

 

A Skills Approach: Excel 2016 Chapter 4: Formatting Worksheets

and Managing the Workbook

5 | Page Skill Review 4.1 Last Updated 4/15/16

 

f. In the Page Setup dialog, on the Margins tab, change the Top, Bottom, Left, and Right values to 0.5.

Click OK.

g. Under Settings, click the No Scaling button, and select Fit All Rows on One Page.

22. Modify the worksheet page breaks so weeks 1-8 print on the first page and weeks 9-16 print on the

second page.

a. Click the Back arrow to exit Backstage.

b. If necessary, scroll to the right so columns T:V are visible. Note the current page break in the file.

c. Click cell T1.

d. On the Page Layout tab, in the Page Setup group, click the Breaks button, and select Insert Page

Break. This inserts a page break to the left of the selected cell (after week 8).

e. Click the File tab to open Backstage view, and then click Print to preview how the change will affect

the printed pages.

f. If your instructor has directed you to print the worksheet, click the Print button.

g. Click the Back arrow to exit Backstage view.

23. Save and close the workbook.

24. Upload and save your project file.

25. Submit project for grading.

Step 2

Upload & Save

Step 3

Grade my Project

 
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Data Mining assignment Help

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Data Mining assignment Help

Question 1

Suppose that you are employed as a data mining consultant for an Internet search engine company. Describe how data mining can help the company by giving specific examples of how techniques, such as clustering, classification, association rule mining, and anomaly detection can be applied.

Question 2

Identify at least two advantages and two disadvantages of using color to visually represent information.

Question 3

Consider the XOR problem where there are four training points: (1, 1, −),(1, 0, +),(0, 1, +),(0, 0, −). Transform the data into the following feature space:

Φ = (1, √ 2×1, √ 2×2, √ 2x1x2, x2 1, x2 2).

Find the maximum margin linear decision boundary in the transformed space.

Question 4

Consider the following set of candidate 3-itemsets: {1, 2, 3}, {1, 2, 6}, {1, 3, 4}, {2, 3, 4}, {2, 4, 5}, {3, 4, 6}, {4, 5, 6}

Construct a hash tree for the above candidate 3-itemsets. Assume the tree uses a hash function where all odd-numbered items are hashed to the left child of a node, while the even-numbered items are hashed to the right child. A candidate k-itemset is inserted into the tree by hashing on each successive item in the candidate and then following the appropriate branch of the tree according to the hash value. Once a leaf node is reached, the candidate is inserted based on one of the following conditions:

Condition 1: If the depth of the leaf node is equal to k (the root is assumed to be at depth 0), then the candidate is inserted regardless of the number of itemsets already stored at the node.

Condition 2: If the depth of the leaf node is less than k, then the candidate can be inserted as long as the number of itemsets stored at the node is less than maxsize. Assume maxsize = 2 for this question.

Condition 3: If the depth of the leaf node is less than k and the number of itemsets stored at the node is equal to maxsize, then the leaf node is converted into an internal node. New leaf nodes are created as children of the old leaf node. Candidate itemsets previously stored in the old leaf node are distributed to the children based on their hash values. The new candidate is also hashed to its appropriate leaf node.

How many leaf nodes are there in the candidate hash tree? How many internal nodes are there?

Consider a transaction that contains the following items: {1, 2, 3, 5, 6}. Using the hash tree constructed in part (a), which leaf nodes will be checked against the transaction? What are the candidate 3-itemsets contained in the transaction?

Question 5

Consider a group of documents that has been selected from a much larger set of diverse documents so that the selected documents are as dissimilar from one another as possible. If we consider documents that are not highly related (connected, similar) to one another as being anomalous, then all of the documents that we have selected might be classified as anomalies. Is it possible for a data set to consist only of anomalous objects or is this an abuse of the terminology?

You will need to ensure to use proper APA citations with any content that is not your own work.

with zero plagiarism needed.

 
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Uses Of Efficient Frontier Analysis In SRM assignment Help

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Uses Of Efficient Frontier Analysis In SRM

Discussion1

Explaining the results of Efficient Frontier Analysis to non-technical decision-makers

The implementation of Efficient Frontier Analysis in an organization helps the process of strategic risk management to encompass and advanced analytical technique. The outcomes derived from it can easily be acknowledged and utilised by the non-technical decision-makers of the organisation as well. With the private utilization of Efficient Frontier Analysis, the decision-maker can easily consider identifying Complex property and developing casualty risk profiles. It has been observed in the considered case study that the most convincing organizational decision-making practices to determine efficient risk management need extensive acknowledgement of the governance structure followed by the processes and the varieties of tools used in it. In addition to it, they are also subjected to be developed on the basis of the guidance and principles of ISO 31000 followed by the guidance of implementation empowered by Australian and New Zealand handbook HB 436 (Fraser, Simkins & Narvaez, 2014). The consideration of Efficient Frontier Analysis emphasizes the hierarchical roles within an internal audit function as well as the organization and risk management function.

The results of implementing Efficient Frontier Analysis depend in-depth assessment of the risk portfolio volatility followed by the pricing structure acknowledged through decision-making. Furthermore, the considered case study also explains that the implementation of Efficient Frontier Analysis also needs to analyze the insurance layering efficiency to determine the risk portfolio application in order to ensure the catastrophic loss potential within the decision-making practices of strategic risk management (Rezaeiani & Foroughi, 2018). Additionally, a business organization implementing it can also become capable of analyzing and resolving the control break down easily with the identification of risk origins, actors, causes and consequences precisely. With the help of proper strategic management, the non-technical decision-making practices can be functional through a risk appetite framework that influences risk control framework. both these further impact on the emergence of the dynamic risks followed by integrated enterprise risk profile and scenario and stress testing by enabling untapped opportunities.

Recommendations assuming the risk appetite

The notion of risk appetite is strongly aligned with risk tolerance to influence the scenario and stress testing abilities to develop an analytical framework. The fundamental purpose of this Framework is to drive multiple sets of discussions based on analytical information to help the decision-makers in determining the risk profile and lead the organization to constitute competitive opportunities. It has been observed that the risk appetite in association with the risk tolerance helps them in categorizing the risks and further reframe them as opportunities (Zhou & Xu, 2016). The decision-makers are recommended to acknowledge this concern in order to determine the position control framework.

Identifying risk appetite also enables control actions for the decision-makers considering the components of market share, product or service provision, market profit, social impact, stakeholder levels and other benefits (Hillson & Murray-Webster, 2017). The decision-makers are also recommended to acknowledge SRM over the traditional risk assessment in order to two distinct advantages risk profiles from the exploitable with a profile in order to determine sustainable efficiency and preventing competitively noisy environment by foreseeing the risk dynamics categorically through risk appetite.

 

Discussion2

For an organization to access risk versus return of each proposed project, their project lead should use the concept of efficient frontier analysis. If the frontier analysis is used efficiently, a company can easily understand and find the high profitable project to invest in. In addition, the information, which is gathered during this process, can be used to develop decision structure, which is eventually used by the project managers to assess a project. As per (Fraser, 2014), the idea of using the idea of using the concept of efficient frontier analysis is to help investors to invest in a project that gives high returns against risks. This process is usually represented by a graph. The value on the X-Axis of the graph is risk and the value on the Y-Axis of the graph is investment returns.  A line is drawn to connect the highest portfolio return that a project can give with the existing risks factors.  This line is the efficient frontier line and the analysis.

I would prefer using a simple graph, so that a non-technical person can easily understand the point. Additionally, this is a simple approach too, not all the points that fall under the efficient frontier line is optimal, therefore making it a not-a-good-idea-to-implement kind of project. Further, dumping a bunch of statics and random facts is going to be less fascinating to a non-techie.

The first and foremost recommendation from my end is, making sure the information is well recorded in the graph, so that we can obtain accurate information. If not, the main purpose of the analysis will never be achieved.

 

Discussion3

Most investment choices involve the trade-off between risk and reward. The “Efficient frontier” is a modern portfolio theory tool that shows investors the best possible return they can expect from their portfolio, given the level of volatility they are willing to accept. The chart here demonstrates the influence of concept. The vertical axis represents the expected rate of return. The horizontal axis signifies the investors’ risk tolerance. The frontier is a line curve, which shows the potential yield of portfolio given a degree of risk. Optimal portfolios should lie on this curve. In addition, the portfolios that fall below the frontier curve represent the less ideal mix of investment because with the same risk one could achieve a greater return. Any portfolio above this curve is impossible.

Take Chris who owns portfolio A. Currently, his investment generates the combined yield of 8%. Based on the efficient frontier, however, Chris can be achieving the same level of return with a considerably safer mix of investments with portfolio B. Both portfolio offer the same level of return but portfolio B has less risk. The job of investment advisor who uses modern portfolio theory is to identify the basket of securities that get as close as possible to the frontier. Investors should realize there is no preferred point on the frontier. A young professional probably is willing to accept a high level of risk and will therefore want to be somewhere near to the right of the curve. For an older adult, nearing retirement, a portfolio further to the left maybe ideal.

What is important is to get as close as possible to the efficient frontier whatever your risk profile may be. The effort to take advantage of complex data techniques was, in part, stimulated by the evolving risk management framework integration into what is now being modestly referred to as enterprise risk management (ERM) or strategic risk management (SRM).

Within the 2013 Risk and Insurance Management Society (RIMS) SRM Implementation Guide, the concept of strategic risk management is defined as a “business discipline that drives the deliberations and actions surrounding business- related uncertainties, while uncovering untapped opportunities reflected in an organization’s strategy and execution.”

What distinguishes this definition from previous descriptions of enterprise wide risk management (ERM) approaches is the effort to sustainably deliver a robust fact-based strategic dialogue across the entire organization. This new strategic dialogue requires an analytical framework that is dynamic and encompasses all areas of an enterprise. In this chapter, we demonstrate how the use of efficient frontier analysis (EFA), and many of its derivative techniques, provides a robust portfolio approach to hazard, operational, market, and reputational risk domains.

 
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Artificial Intelligence ( Computer Science, Python) assignment Help

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Artificial Intelligence ( Computer Science, Python) assignment Help

Homework 2 (10% of total course weight) – Multiagent Search

California State University San Bernardino, School of Computer Science and Engineering (CSE)

 

Date of Issue: February 24, 2020, Date of submission: March 10, 2021 – 11:59 pm (PST)

Module: CSE 5120 Introduction to Artificial Intelligence

Assessment brief: The code and resources provided in this homework are drawn from UC Berkeley which are part of their recent offering. Thanks, and credit to the authors (particularly Dan Klein, Pieter Abbeel, John DeNero, and others) at UC Berkeley for making these projects available to the public.

Pacman lives in a shiny blue world of twisting corridors and tasty round treats. Navigating this world efficiently will be Pacman’s first step in mastering his domain.

The code for this project consists of several Python files, some of which you will need to read and understand in order to complete the assignment, and some of which you can ignore. You can download all the code and supporting files as a zip folder from homework 2 link given on Blackboard (multiagent.zip).

Your homework is based on two parts as given below:

1. Code implemented for multiagent algorithms in given multiAgents.py file (in specific sections as indicated in detail below)

2. A brief report on what you did for each algorithm (i.e., how you implemented with screenshots from autograder script given in the folder)

 

File Name Description
multiAgents.py Where all of your multi-agent search agents will reside.
pacman.py The main file that runs Pacman games. This file describes a Pacman GameState type, which you use in this project.
game.py The logic behind how the Pacman world works. This file describes several supporting types like AgentState, Agent, Direction, and Grid.
util.py Useful data structures for implementing search algorithms.

 

After downloading the code, unzipping it, and changing to the directory, you should be able to play a game of Pacman by running the following command.

python pacman.py

pacman.py supports a number of options (e.g. –layout or -l). You can see the list of all options and their default values via python pacman.py -h.

You can use Spyder (installed through Anaconda from week 1 Thursday’s lecture) or other IDE for this work.

Files to Edit and Submit: You will need to edit and submit (multiAgents.py) file to implement your algorithms. Once you have completed the homework, you are welcome to run automated tests using an autograder.py given in the folder before you submit them for accuracy. You do not need to submit autograder.py file in your code submission but will need to test your algorithms with autograder.py to copy screenshots in your report. Please do not change the other files in this distribution or submit any of the original files other than these files.

 

Academic Dishonesty: Your code will be checked against other submissions in the class for logical redundancy. If you copy someone else’s code and submit it with minor changes, they will be detected easily, so please do not try that and submit your own work only. In case of cheating, the University’s academic policies on cheating and dishonesty will strictly apply which may result from the deduction in your grade to expulsion.

 

Getting Help: If you are having difficulty in implementing the algorithms from the pseudocodes provided in this homework, contact the course staff for help. Office hours and Slack are there for your support. If you are not able to attend office hours, then please inform your instructor to arrange for additional time. The intent is to make these projects rewarding and instructional, not frustrating and demoralizing. You can either complete this homework on your own or discuss the problem and collaborate with another member of the class (or different section). Please clearly acknowledge and mention your group member in your homework report submission who you will collaborate with in this homework. Your report and program (search.py file) will be separately submitted by yourself on Blackboard irrespective of your collaboration with your group member. Group discussions are encouraged but copying of programs is NOT recommended. Programming based on your own skills is encouraged.

 

Tasks for homework 2

 

1. Minimax search (3%)

Write an adversarial agent in the provided MinimaxAgent class in multiAgents.py. Your minimax agent should work with any number of ghosts, so your algorithm should be a more generalized version of the standard Minimax algorithm that we have studied in the class. Your minimax tree will have multiple min layers (one for each ghost) for each max layer. Your code should also be able to expand the tree to an arbitrary depth which can be accessed from self.depth and score your nodes with the supplied self.evaluationFunction. Make sure your Minimax program refers to these variables since these are populated in response to the command line options.

Important:  A single search ply is considered to be one Pacman move and all the ghosts’ responses, so depth 2 search will involve Pacman and each ghost moving two times. For further reading and understanding of Minimax (including alpha-beta pruning), please see this short video tutorial with pseudo code.

Hints and Observations

· Hint: Implement the algorithm recursively using helper function(s).

· The correct implementation of minimax will lead to Pacman losing the game in some tests. This is not a problem: as it is correct behavior, it will pass the tests.

· The evaluation function for the Pacman test in this part is implemented for you (self.evaluationFunction). You should not change this function but recognize that now we are evaluating states rather than actions, as compared to the reflex agent. Look-ahead agents evaluate future states whereas reflex agents evaluate actions from the current state.

· Pacman is always agent 0, and the agents move (take turns) in order of increasing agent index.

· All states in minimax should be GameStates, either passed in to getAction or generated via GameState.generateSuccessor. In this project, you will not be abstracting to simplified states.

Evaluation: Your code will be checked to determine whether it explores the correct number of game states. This is the only reliable way to detect some very subtle bugs in implementations of minimax. As a result, the autograder will be very picky about how many times you call GameState.generateSuccessor. If you call it any more or less than necessary, the autograder will complain. Please note that q1 relates to ReflexAgent which is not a part of this homework and can be skipped. We will start with q2 in this homework. To test and debug your code, run

python autograder.py -q q2

This will show what your algorithm does on a number of small trees, as well as a pacman game. To run it without graphics, use:

python autograder.py -q q2 –no-graphics

Figure 1: Pseudo-code for the implementation of Minimax algorithm. Please use this as a guide only. You will still need to carefully read multiAgents.py file for helper functions given in the comments and think/reason about the implementation of Minimax in Pacman scenario.

 

Figure 2: Pseudo-code for general-purpose implementation of Minimax algorithm. Please use this as a guide only. You will still need to carefully read multiAgents.py file for helper functions given in the comments and think/reason about the implementation of Minimax in Pacman scenario.

 

2. Alpha-beta pruning (2%)

write an adversarial agent in the provided AlphaBetaAgent class in multiAgents.py to more efficiently explore the minimax tree. Your agent should work with any number of ghosts, so your algorithm should be a generalized version of the standard Alpha-Beta Pruning algorithm. The AlphaBetaAgent minimax values should be identical to the MinimaxAgent minimax values, although the actions it selects can vary because of different tie-breaking behavior.

Note: The correct implementation of alpha-beta pruning will lead to Pacman losing some of the tests. This is not a problem: as it is correct behavior, it will pass the tests.

Evaluation: Your code will be checked to determine whether it explores the correct number of game states. Therefore, it is important that you perform alpha-beta pruning without reordering children. In other words, successor states should always be processed in the order returned by GameState.getLegalActions. Again, do not call GameState.generateSuccessor more than necessary. Additionally, in order to match the set of states explored by the autograder, you must not prune on equality: that is, stop generating children for a max (min) node only if a child’s value is strictly greater than (less than) β (α). To test and debug your code, run

python autograder.py -q q3

This will show what your algorithm does on a number of small trees, as well as a pacman game. To run it without graphics, use:

python autograder.py -q q3 –no-graphics

Figure 3: Pseudo-code for the implementation of the algorithm you should implement for this question. Please use this as a guide only. You will still need to carefully read multiAgents.py file for helper functions given in the comments and think/reason about the implementation of Minimax in Pacman scenario.

3. Expectimax Search (2%)

Implement the ExpectimaxAgent, which is useful for modeling probabilistic behavior of agents who may make suboptimal choices. As with the search and constraint satisfaction problems covered in CSE 5120, the impressive feature of this algorithm is its general applicability.

Note: The correct implementation of expectimax will lead to Pacman losing some of the tests. This is not a problem: as it is correct behavior, it will pass the tests.

 

Evaluation: You can debug your implementation on small the game trees using the command:

python autograder.py -q q4

Debugging on these small and manageable test cases is recommended and will help you to find bugs quickly. Once your algorithm is working on small trees, you can observe its success in Pacman. Random ghosts are not optimal minimax agents, and so modeling them with minimax search may not be appropriate. ExpectimaxAgent, does not take the min over all ghost actions, but the expectation according to the agent’s model of how the ghosts act. To simplify your code, assume you will only be running against an adversary which chooses amongst their getLegalActions uniformly at random (read about uniform distribution for further understanding). To see how the ExpectimaxAgent behaves in Pacman, run:

python pacman.py -p ExpectimaxAgent -l minimaxClassic -a depth=3

You should now observe a more cavalier approach in close quarters with ghosts. In particular, if Pacman perceives that he could be trapped but might escape to grab a few more pieces of food, he will at least try. Investigate the results of these two scenarios:

python pacman.py -p AlphaBetaAgent -l trappedClassic -a depth=3 -q -n 10

python pacman.py -p ExpectimaxAgent -l trappedClassic -a depth=3 -q -n 10

You should find that your ExpectimaxAgent wins about half the time, while your AlphaBetaAgent always loses. Make sure you understand why the behavior here differs from the minimax case.

4. Constraint satisfaction problems (3%)

1. (1.5%) Consider the problem of placing k knights on an n×n chess board such that no two knights are attacking each other, where k is given and k ≤ n2.

· Choose a CSP formulation. What are the variables in your formulation?

· What are the possible values of each variable in your formulation?

· What sets of variables are constrained, and how?

2. (1.5%) Class scheduling (items to answer are at the end in green font)

You are given a problem of class scheduling for the computer science department at CSUSB. The class timings are Tuesdays, Thursdays, and Fridays. There are 5 different classes on these given days and 3 professors who are qualified for teaching these classes.

Problem constraint: Each professor can teach only one class at a time.

Classes:

C1 – CSE 5120 Introduction to Artificial Intelligence: Time: 1:00 – 2:15pm

C2 – CSE 4600 Operating Systems: Time: 9:00 – 10:15am

C3 – CSE 4550 Software Engineering: Time: 10:30-11:45am

C4 – CSE 5720 Database Systems: Time: 10:30 – 11:45am

C5 – CSE 5160 Machine Learning: Time: 2:30 – 3:45pm

Professors:

Professor A: Qualified to teach Classes 1, 2, and 5.

Professor B: Qualified to teach Classes 3, 4, and 5.

Professor C: Qualified to teach Classes 1, 3, and 4.

1. Formulate this problem as a CSP where there is one variable per class, reporting the domains and constraints (e.g., for each class, the entry in the table should be <class number (e.g., C1)> <Domains (unary constraints)>). Also, list binary constraints on the classes . Your constraints should be specified formally which can be implicit rather than explicit

2. Draw the constraint graph for your problem in item 1

3. Make sure your CSP looks nearly tree-structure. Provide a one paragraph description of why the solution to CSP via tree structured CSPs is preferred. Review lecture slides and videos for help.

 

 

1

 

Homework 2 (10%)

 

 

 

 

 

CSE 5120 (Section ##) – Introduction to Artificial Intelligence – Spring 2021

 

 

 

 

 

 

Submitted to 

 

Department of Computer Science and Engineering California State University, San Bernardino, California

 

 

by

 

Student name (CSUSB ID)

(Your collaborator in this homework (if any))

 

 

 

 

 

Date: Month Day, Year

 

 

 

 

 

 

Email:

· Your email

· Your collaborator’s email (if you collaborated with any)

 

 

Report

Brief description of your work here acknowledging your collaboration with your class fellow (or a friend from other CSE 5120 section), and the capacity at which he/she collaborated with you, followed by the algorithms you implemented.

1. Minimax algorithm

Your brief explanation of the problem, your code solution, and any documentation with screenshots of your code Evaluation (results from autograder.py)

2. Alpha-beta pruning

Your brief explanation of the problem, your code solution, and any documentation with screenshots of your code Evaluation (results from autograder.py)

3. Expectimax Search

Your brief explanation of the problem, your code solution, and any documentation with screenshots of your code Evaluation (results from autograder.py)

4. Constraint satisfaction problems

Your explanation and drawings, wherever necessary, numbered according to how the questions are defined in the questions.

 

α-βImplementationdef min-value(state, α, β):initialize v = +∞for each successor of state:v = min(v, value(successor, α, β))if v ≤ αreturn vβ = min(β, v)return vdef max-value(state, α, β):initialize v = -∞for each successor of state:v = max(v, value(successor, α, β))ifv ≥ βreturn vα= max(α, v)return vα: MAX’s best option on path to rootβ:MIN’s best option on path to root

Minimax Implementationdef value(state):if the state is a terminal state: return the state’s utilityif the next agent is MAX: return max-value(state)if the next agent is MIN: return min-value(state)def min-value(state):initialize v = +∞for each successor of state:v = min(v, value(successor))return vdef max-value(state):initialize v = -∞for each successor of state:v = max(v, value(successor))return v

 
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Lab5 – Legal Regulations, Compliance, And Investigation

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Lab5 – Legal Regulations, Compliance, And Investigation

35

 

Introduction

When consumers provide personal information for a product or service, the assumption is the

receiving company will exercise due diligence to protect their information. Bear in mind there is

no all-purpose federal law mandating personal data should be protected, only certain industry-

specific laws, for example, health care and financial. But even without an overarching mandate,

most companies will attempt to protect your personal data just to avoid a charge of negligence

should a privacy breach occur.

One nonprofit organization that monitors how well companies guard personal data—among

other missions—is the Electronic Frontier Foundation (EFF). EFF’s purpose is to defend free

speech, privacy, innovation, and consumer rights. This lab takes a look at a class-action lawsuit

filed by EFF.

In this lab, you will explain the privacy issues related to an EFF case study, you will identify

U.S. privacy law violations and their implications, and you will assess the impact of those

violations on consumer confidential information.

Learning Objectives

Upon completing this lab, you will be able to:

Explain the mission statement of the Electronic Frontier Foundation (EFF).

Relate privacy issues in the case study to any personal or individual laws in the United

States.

Identify U.S. citizen privacy law violations and their implications for privacy and

confidential information in the case study.

Assess the impact of these violations on consumers’ confidential information from a legal,

ethical, and information systems security perspective.

Lab #5 Case Study on Issues Related to Sharing Consumers’ Confidential Information

 

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36 | LAB #5 Case Study on Issues Related to Sharing Consumers’ Confidential Information

 

Deliverables

Upon completion of this lab, you are required to provide the following deliverables to your

instructor:

1. Lab Report file; 2. Lab Assessments file.

Instructor Demo

The Instructor will present the instructions for this lab. This will start with a general discussion

about privacy law and how this is different from information systems security as well as how

they are related. The Instructor will then present an overview of the Electronic Frontier

Foundation (EFF) and the case study in this lab.

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37

 

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www.jblearning.com Student Lab Manual

 

 

Hands-On Steps

Note: This is a paper-based lab. To successfully complete the deliverables for this lab, you will need access to Microsoft® Word or another compatible word processor. For some labs, you may also need access to a graphics line drawing application, such as Visio or PowerPoint. Refer to the Preface of this manual for information on creating the lab deliverable files.

 

1. On your local computer, create the lab deliverable files.

2. Review the Lab Assessment Worksheet. You will find answers to these questions as you proceed through the lab steps.

3. Review the following case study on issues related to sharing consumers’ confidential information. Note that this information originated from the following Electronic Frontier

Foundation Web pages: https://www.eff.org/about, https://www.eff.org/cases/hepting, and

https://www.eff.org/nsa/hepting.

From the Internet to the iPod, technologies transform society and empower us as

speakers, citizens, creators, and consumers. When freedoms in the networked world come

under attack, the Electronic Frontier Foundation (EFF) is the first line of defense. EFF

broke new ground when it was founded in 1990—well before the Internet was on most

people’s radar—and continues to confront cutting-edge issues defending free speech,

privacy, innovation, and consumer rights today. From the beginning, EFF has

championed the public interest in every critical battle affecting digital rights.

Blending the expertise of lawyers, policy analysts, activists, and technologists, EFF

achieves significant victories on behalf of consumers and the general public. EFF fights

for freedom primarily in the courts, bringing and defending lawsuits even when that

means taking on the U.S. government or large corporations. By mobilizing more than

61,000 concerned citizens through the Action Center, EFF beats back bad legislation. In

addition to advising policymakers, EFF educates the press and public.

EFF is a donor-funded nonprofit and depends on support to continue successfully

defending digital rights. Litigation is particularly expensive. Because two-thirds of EFF’s

budget comes from individual donors, every contribution is critical to helping EFF

fight—and win—more cases (https://www.eff.org/about).

EFF Case Study Information

The Electronic Frontier Foundation (EFF) filed a class-action lawsuit against AT&T on

January 31, 2006, accusing the telecom giant of violating the law and the privacy of its

customers by collaborating with the National Security Agency (NSA) in its massive, illegal

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38 | LAB #5 Case Study on Issues Related to Sharing Consumers’ Confidential Information

 

program to wiretap and data-mine Americans’ communications. In May 2006, many other

cases were filed against a variety of telecommunications companies. Subsequently, the

Multi-District Litigation Panel of the federal courts transferred approximately 40 cases to

the Northern District of California federal court.

In Hepting v. AT&T, EFF sued the telecommunications giant on behalf of its customers

for violating privacy law by collaborating with the NSA in the massive, illegal program

to wiretap and data-mine Americans’ communications. Evidence in the case includes

undisputed evidence provided by former AT&T telecommunications technician Mark

Klein showing AT&T routed copies of Internet traffic to a secret room in San Francisco

controlled by the NSA.

In June of 2009, a federal judge dismissed Hepting and dozens of other lawsuits against

telecoms, ruling that the companies had immunity from liability under the controversial

Foreign Intelligence Surveillance Act Amendments Act (FISAAA), which was enacted in

response to court victories in Hepting. Signed by President Bush in 2008, the FISAAA

allows the attorney general to require the dismissal of the lawsuits over the telecoms’

participation in the warrantless surveillance program if the government secretly certifies

to the court that the surveillance did not occur, was legal, or was authorized by the

president—certification that was filed in September of 2008.

Note: To read the full order from the federal judge who dismissed the many EFF lawsuits, the order is available here: http://www.eff.org/files/filenode/att/orderhepting6309_0.pdf.

 

EFF plans to appeal the decision to the 9th U.S. Circuit Court of Appeals, primarily

arguing that FISAAA is unconstitutional in granting to the president broad discretion to

block the courts from considering the core constitutional privacy claims of millions of

Americans (http://www.eff.org/cases/hepting; https://www.eff.org/nsa/hepting).

Note: Public proof regarding the case study came in June 2013 when British newspaper The Guardian first published news of massive electronic data collection by the NSA, a U.S. spy agency. Revelations from former NSA contractor and whistleblower Edward Snowden have detailed the extensiveness of data collection.

 

4. In your Lab Report file, describe the EFF’s mission statement.

5. In your Lab Report file, explain the privacy issues in the case study.

6. In your Lab Report file, identify the U.S. citizen privacy law violations in the case study and the implications those violations have on privacy and confidential information.

Note: This completes the lab. Close the Web browser, if you have not already done so.

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39

 

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www.jblearning.com Student Lab Manual

 

 

Evaluation Criteria and Rubrics

The following are the evaluation criteria for this lab that students must perform:

1. Explain the mission statement of the Electronic Frontier Foundation (EFF). – [25%] 2. Relate privacy issues in the case study to any personal or individual laws in the United

States. – [25%]

3. Identify U.S. citizen privacy law violations and their implications for privacy and confidential information in the case study. – [25%]

4. Assess the impact of these violations on consumers’ confidential information from a legal, ethical, and information systems security perspective. – [25%]

 

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40 | LAB #5 Case Study on Issues Related to Sharing Consumers’ Confidential Information

 

Lab #5 – Assessment Worksheet

Case Study on Issues Related to Sharing Consumers’ Confidential Information

Course Name and Number: _____________________________________________________ Student Name: ________________________________________________________________ Instructor Name: ______________________________________________________________ Lab Due Date: ________________________________________________________________

Overview

In this lab, you explained the privacy issues related to an EFF case study, you identified U.S.

privacy law violations and their implications, and you assessed the impact of those violations on

consumer confidential information.

Lab Assessment Questions & Answers

1. What is the Electronic Frontier Foundation’s mission statement?

 

2. Did the U.S. government violate the constitutional rights of U.S. citizens by ordering the NSA to review consumer confidential privacy information?

 

 

3. Why is the Hepting v. AT&T case crucial to the long-term posture of how the U.S. government can or cannot review consumer confidential information?

 

 

4. If Hepting v. AT&T results in “Big Brother” being allowed to eavesdrop and/or review the local and toll telephone dialing and bills of individuals, will U.S. citizens and consumers have any

privacy rights left regarding use of communication technologies?

 

 

5. What are the legal implications of consumer privacy information being shared?

 

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41

 

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www.jblearning.com Student Lab Manual

 

 

6. What are the ethical implications of consumer privacy information being shared?

 

7. What are the information systems security implications of consumer information being shared?

 

8. What law allowed a federal judge to dismiss Hepting v. AT&T and other lawsuits against telecommunication service providers participating in the warrantless surveillance program

authorized by the president?

 

 

9. True or false: EFF claimed that the ruling set forth by FISAAA was unconstitutional.

 

 

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Computer Science homework help

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Computer Science homework help

Adjust your audio

This is a narrated slide show. Please adjust your audio so you can hear the lecture.

If you have problems hearing the narration on any slide show please let me know.

 

1

 

Chapter 1 The Information Systems Strategy Triangle

2

 

Kaiser Permanente (KP) Opening Case

What was KP’s business strategy in 2015?

On what were bonuses to doctors based under the “fix me” system?

What would the new idea be called instead of a “fix me” system?

What is the new basis for end-of-year bonuses?

What goal alignment has helped KP’s success?

What IS components are part of this?

Could only the IS components be changed to achieve their success?

Could only the strategy be changed to achieve their success?

© 2016 John Wiley & Sons, Inc.

3

To promote better health care at lower cost

Billings

Proactive health system

Improved health of patients

Alignment between business strategy, organizational design, and information systems strategy

Fast communication with patients outside of face-to-face appointments; automatic email reminders to patients for exercise or medications

No, the business strategy must be aligned with the IS, in addition to incentives

No, without the new incentives and new IS, employees would not wish to cooperate, nor would they be able to do so.

3

4

The Information Systems Strategy Triangle

These need to be balanced.

 

Business Strategy

Organizational Strategy

Information Strategy

© 2016 John Wiley & Sons, Inc.

4

 

What is a “Strategy?”

Coordinated set of actions to fulfill objectives, purposes, or goals

It sets limits on what the organization seeks to accomplish

Starts with a mission

Company Mission Statement
Zappos To provide the best customer service possible. Internally we call this our WOW philosophy.
Amazon We seek to be Earth’s most customer-centric company for three primary customer sets: consumer customers, seller customers and developer customers.
L.L. Bean Sell good merchandise at a reasonable profit, treat your customers like human beings and they will always come back for more.

© 2016 John Wiley & Sons, Inc.

5

What is a business strategy?

It is where a business seeks to go and how it expects to get there

It is not a business model, although it includes business models as one component of a business strategy

Business models include subscriptions, advertising, licenses, etc.

Business models do not include where the business seeks to go, and only the revenue portion of how it expects to get there

 

© 2016 John Wiley & Sons, Inc.

6

Generic Strategies Framework

Michael Porter: How businesses can build a competitive advantage

Three primary strategies for achieving competitive advantage:

Cost leadership – lowest-cost producer.

Differentiation – product is unique.

Focus – limited scope – can accomplish this via cost leadership or differentiation within the segment

7

© 2016 John Wiley & Sons, Inc.

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Three Strategies for Achieving Competitive Advantage

Strategic Advantage
Strategic Target Uniqueness Perceived by Customer Low Cost Position
Industry Wide Differentiation Cost Leadership
Particular Segment Only Focus

© 2016 John Wiley & Sons, Inc.

8

Three Strategies for Achieving Competitive Advantage Examples

Strategic Advantage
Strategic Target Uniqueness Perceived by Customer Low Cost Position
Industry Wide Differentiation Cost Leadership
Particular Segment Only Focus

Apple

Wal-Mart

Marriott

Ritz Carlton

© 2016 John Wiley & Sons, Inc.

9

Dynamic Strategies

Beware of Hypercompetition

Can lead to a “red ocean” environment

Cutthroat competition – zero sum game

Every advantage is eroded—becoming a cost.

Sustaining an advantage can be a deadly distraction from creating new ones.

D’Avenis says: Goal of advantage should be disruption, not sustainability

Initiatives are achieved through series of small steps. Get new advantage before old one erodes.

Better to adopt a “blue ocean” strategy

Change the industry; create new segments/products

10

© 2016 John Wiley & Sons, Inc.

10

 

Creative Destruction

GE’s Approach under Jack Welch

Ask people to imagine how to destroy and grow your business

DYB: Imagine how competitors would want to destroy your business.

GYB: Counteract that by growing the business in some way to:

Reach new customers/markets

Better serve existing customers

© 2016 John Wiley & Sons, Inc.

11

Summary

Strategic Approach Key Idea Application to Information Systems
Porter’s generic strategies Firms achieve competitive advantage through cost leadership, differentiation, or focus. Understanding which strategy is chosen by a firm is critical to choosing IS to complement the strategy.
Dynamic environment strategies Speed, agility, and aggressive moves and countermoves by a firm create competitive advantage. The speed of change is too fast for manual response making IS critical to achieving business goals.

© 2016 John Wiley & Sons, Inc.

12

Organizational Strategy

What is organizational strategy?

Organizational design and

Choices about work processes

How do you manage organizational, control, and cultural variables?

Managerial Levers

13

© 2016 John Wiley & Sons, Inc.

13

 

14

Managerial Levers

© 2016 John Wiley & Sons, Inc.

14

 

IS Strategy

What is an IS Strategy? – The plan an organization uses in providing information services.

Four key IS infrastructure components

15

© 2016 John Wiley & Sons, Inc.

15

 

16

Information systems strategy matrix.

What Who Where
Hardware The physical devices of the system System users and managers Physical location of devices (cloud, datacenter, etc.)
Software The programs, applications, and utilities System users and managers The hardware it resides on and physical location of that hardware
Networking The way hardware is connected to other hardware, to the Internet and to other outside networks. System users and managers; company that provides the service Where the nodes, wires, and other transport media are
Data Bits of information stored in the system Owners of data; data administrators Where the information resides

© 2016 John Wiley & Sons, Inc.

16

 

What Who Where
Hardware Laptops, servers to store info and back up laptops Consultants have laptops, managed by the IS Dept. Laptops are mobile; servers are centralized
Software Office suite; collaboration tools Software is on consultants’ laptops but managed centrally Much resides on laptops; some only resides on servers
Networking Internet; hard wired connections in office; remote lines from home, satellite, or client offices ISP offers service; Internal IS group provides servers and access Global access is needed; Nodes are managed by ISPs
Data Work done for clients; personnel data Data owned by firm but made available to consultants as needed Resides on cloud and copies “pulled” into laptops as needed.

17

Illustration in a Consulting Firm

© 2016 John Wiley & Sons, Inc.

17

 

One IS Strategy: Social Strategy

Collaboration

Extend the reach of stakeholders to find and connect with one-another

Engagement

Involve stakeholders in the business via blogs; communities

Innovation

Identify, describe, prioritize new ideas

© 2016 John Wiley & Sons, Inc.

18

Summary

After you have listened to this lecture and read Chapter 1 of your text

Go to Discussion Board 2 and answer the discussion prompt

Finally complete Quiz 1

© 2016 John Wiley & Sons, Inc.

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Personal Reflection Assignment

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Personal Reflection Assignment

Provide a reflection of at least 600 words (or 2 pages double spaced ) of how the knowledge, skills, or theories of this course have been applied or could be applied, in a practical manner to your current work environment. If you are not currently working, share times when you have or could observe these theories and knowledge could be applied to an employment opportunity in your field of study.

 

Requirements:

Provide a 600 word (or 2 pages double spaced) minimum reflection.

Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited.

 

Share a personal connection that identifies specific knowledge and theories from this course.

 

Demonstrate a connection to your current work environment. If you are not employed, demonstrate a connection to your desired work environment.

 

You should NOT provide an overview of the assignments assigned in the course. The assignment asks that you reflect how the knowledge and skills obtained through meeting course objectives were applied or could be applied in the workplace.

The assignment will be graded using the following criteria:

(Maximum # of Points Per Area)

Grammar/Spelling/Citation: Make sure all work is grammatically correct, spelling is 100% accurate, and cite all sources in-text/at the end of the paper where applicable.

 

Technical Connection: Make the paper relevant to the course and its connection with your current classwork. Discuss how what you have learned can be applied to your work or future work.

 

Word Count: The minimum word count is 600 words. 350-500 will receive 50% credit. Anything below will receive a minimum number of points.

 

Personal Connection – 4 Points: How does this course and the experiences you have been taught in BLCN-635 ONLY impact your personal work.

 
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Project On Access 2013 Assignment Help

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Project On Access 2013 Assignment Help

Access 2013 Chapter 3 Creating and Using Queries Last Updated: 2/27/15 Page 1

USING MICROSOFT ACCESS 2013 Independent Project 3-5

Independent Project 3-5 The State of New York Department of Motor Vehicles wants to create three queries. The first query provides summary data on the number of tickets by city and violation. The second query summarizes the total tickets by violation. The third query provides summary data for the total fines assessed against each driver who has had a ticket. To ensure consistency, the starting file is provided for you. Use Design view to create the summary queries. Edit the queries to add fields, aggregate functions, and sorting. Finally, save and run the queries.

Skills Covered in This Project  Create a summary query in Design view.

 Edit a query in Design view.

 Add fields to a query.

 Execute a query.

 Save a query.

 Sort query results.

 Add aggregate functions.

 

 

1. Open the NewYorkDMV-03.accdb start file.

2. The file will be renamed automatically to include your name. Change the project file name if

directed to do so by your instructor, and save it.

3. If needed, enable content in the security warning.

4. Create a new summary query in Design view. The

query counts the number of tickets issued by city

and violation.

a. Add the Ticket table into the Query

Design window.

b. Increase the size of the table object to

display all of the fields.

c. Add the following fields into the query: City,

PrimaryFactor, and TicketNumber.

d. Add the Total row to the query.

e. Group By the City and PrimaryFactor fields

and Count the TicketNumber field.

5. Save the query as

TicketCountByCityAndFactor.

6. Run the query. The datasheet should display

20 records.

7. Widen the field column widths to the Best Fit

(Figure 3-104).

8. Save the changes to the query.

9. Save a copy of the query as

TicketCountByFactor.

10. Edit the TicketCountByFactor query in Design

view. The query should show the total tickets

issued for each violation factor, sorted in

descending order by count.

a. Delete the City field.

b. Sort the TicketNumber field in

descending order.

11. Save and run the query. The datasheet should

match Figure 3-105.

Step 1

Download start file

 

 

 

Access 2013 Chapter 3 Creating and Using Queries Last Updated: 2/27/15 Page 2

USING MICROSOFT ACCESS 2013 Independent Project 3-5

12. Close the query.

13. Create a new summary query in Design view. The query provides summary data on the total fines

assessed against

each driver.

a. Add both tables into the Query

Design window.

b. Increase the size of the table

objects to display all of the fields.

c. Add the following fields into the

query: LicenseNumber,

FirstName, LastName, Fine, and

TicketNumber.

d. Add the Total row to the query.

e. Group By the LicenseNumber,

FirstName, and LastName fields,

Sum the Fine field and Count the

TicketNumber field.

f. Sort the Fine field in descending

order.

14. Save the query as TicketsByDriver.

15. Run the query. The datasheet should

display 21 drivers who have received

tickets, sorted in descending order

by the total dollar amount of their

fines (Figure 3-106).

16. Save and close the database.

17. Upload and save your project file.

18. Submit project for grading. Step 3

Grade my Project

Step 2

Upload & Save

 
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Python 3.6 Assignment

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Python 3.6 Assignment

Hello,

Hope this email finds you well.

I have an important assignment worth 100% of my grade that I really need your help with. Kindly find below the set of questions:

Assignment
Answer all parts of the following question. Marks allocated to each part in square
brackets.
Data source for Questions 2 through 5 needs to be the same, and has to be mentioned at
the beginning of your report
1) Many people find it difficult to understand blockchain because it requires the
coordination of many components for it to function, and it’s hard to see the full picture
until all the individual components are fully understood. In brief, please explain the
following from a technological standpoint: What are the basics of interaction of
cryptography and economics? What is your fundamental understanding of blockchain
technology? [10]
2) What were the key events for Cryptocurrencies from January 31, 2018 till January 31,
2019? Create and present a graphical timeline with the key dates and the key events.
What was the reaction in Bitcoin trading (BTC) on these dates? Did the BTC price go up
or down? By how much? What was the mean return on key events dates? What was the
median return? What was the standard deviation? Plot the distribution of the daily
percentage change on key events dates. Create a variable that takes the value 0 on days
without key events and 1 on days with key events. Calculate the correlation matrix on key
events dates and non-key events dates between the behaviour of Bitcoin, Ethereum
(ETH), Ripple (XRP) and Nasdaq. Perform a regression analysis between the previous
variables and briefly comment on the results.
[25]
3) Create a function called assess_portfolio() that takes as input an asset allocation of a
cryptocurrency asset portfolio and computes important statistics about the portfolio. You
are given the following inputs for analysing a portfolio:
• A date range to select the historical data to use (specified by a start and end date).
You should consider performance from close of the start date to close of the end
date on a daily basis, if you choose intraday data then please use daily median
price.
• Symbols for each cryptocurrency asset (e.g., BTC, ETH, XRP, LTC).
• Portfolio allocations for each asset at the beginning of the simulation (e.g., 0.2,
0.3, 0.4, 0.1) which should sum to 1.0.
• Total starting value of the portfolio (e.g. $1,000,000)
Your goal is to create a programme to compute and visualise the daily portfolio value
over the given date range within a sample period from: February 15, 2017 to February 15,
2019, and then the following statistics for the overall portfolio:
• Cumulative return for the chosen date range from the sample period
• Plot the average period return (if sampling frequency == 252 trading days then
this is average daily return for the portfolio)
• Calculate the standard deviation of daily returns
• Calculate the annualised Sharpe ratio of the daily returns of the portfolio, given
daily risk-free rate (usually average of overnight LIBOR rate), and yearly
sampling frequency (usually 252 days, the number of trading days in a year)
• Plot the moving historical volatility with a minimum rolling period of 30 days
(i.e. moving historical standard deviation of the log returns)
• Ending value of the portfolio
Are these returns all positive? Or not? What is your explanation for what you observe?
[25]
4) Create an event study profile of a specific market event in the Cryptocurrency market,
and compare its impact on two relatively liquid cryptocurrencies. The event is defined as
when the daily median price / daily close price of the cryptocurrency is 10% lower than
the previous day. Evaluate this event for the time period: February 15, 2017 to February
15, 2019. Create and describe your own trading strategy based on the findings, to include
writing the code for your trading strategy and execution of the strategy with relevant
visual output in plots for this sample period. [20]
5) Now that you’ve got your trading strategy at hand, it’s a good idea to also backtest it and
optimise its performance. However, when you’re backtesting, it’s a good idea to keep in
mind that there are some pitfalls. For example, external events such as market regime
shifts, which are regulatory changes or macroeconomic events. Also, liquidity constraints,
could affect your backtesting heavily. Create your own ‘market event’ and experiment
with it using your trading strategy developed in the previous question for a
cryptocurrency portfolio. Consider answering these questions:
? Explain why the event chosen is a relevant ‘market event’ for cryptocurrency assets?
? Is it possible to make money using your event?
? If it is possible, what is your trading strategy? Think about details of entry (buy), exit
(sell) and how many days would you hold?
? Is this a risky strategy?
? How much do you expect to make on each trade?
? How many times do you expect to be able to act on this opportunity each year?
? Is there some way to reduce the risk? [20]
For questions 2, 3, 4 and 5, you will need to write code in Python 3.6 using Python functions, libraries
and classes. You will need to respect the good programming practices such as commenting your code
so that it is clear (to you and other programmers that might read it) as to what it attempts to execute.
Assessment Criteria
Your work will be assessed in terms of how well you have carried out the various parts of the
assignment, in terms of: appropriate understanding of key concepts / principles discussed in class
(programming code, functions, classes, commenting); correctness, clarity, completeness and
relevance of your interpretations and commentaries.
The marks assigned to each part of the assignment are given in square brackets at the end of each part.

Kindly reply to me the soonest if you could help me out.
you need to use   python 3.6

Many thanks

 
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