In January 2012, Geoff Colvin, a longtime editor at Fortune magazine and a respected commentator on economics and infotech, agreed to play a special game of Jeopardy. The occasion was the annual convention of the National Retail Federation in New York, and Colvin's opponents were a woman named Vicki and an empty podium with the name tag "Watson." Watson's sponsors at IBM wanted to show retailers how smart Watson is. "I wasn't expecting this to go well," recalls Colvin, who knew that Watson had already defeated Jeopardy's two greatest champions. As it turned out, it was even worse than he had expected. "I don't remember the score," says Colvin, "but at the end of our one round I had been shellacked."'

Obviously, Watson isn't your average Jeopardy savant. It's a cognitive computing system that can handle complex problems in which there is ambiguity and uncertainty and draw inferences from data in a way that mimics the human brain. In short, it can deal with the kinds of problems faced by real people. Watson, explains Colvin, "is not connected to the Internet. It's a freestanding machine just like me, relying only on what it knows.... So let's confront reality: Watson is smarter than I am."

Watson is also smarter than anyone who's ever been on Jeopardy, but it's not going to replace human game show contestants any time soon. Watson, however, has quite an impressive skill set beyond its game-playing prowess. For example, it has a lot to offer medical science. At the University of Texas, Watson is employed by the M.D. Anderson Cancer Center's "Moon Shots" program, whose stated goal is the elimination of cancer. This version of Watson, says John Kelly, who oversees the development of IBM's micro-electronics technologies, including Watson, is already "dramatically faster" than the one that was introduced on Jeopardy back in February 2011 (about three times as fast).

Already, reports Kelly, "Watson has ingested a large portion of the world's medical information," and its currently "in the final stages of learning the details of cancer." Then what? "Then Watson has to be trained," explains Kelly. Here's how it works:

Watson is presented with complex healthcare problems where the treatment and outcome are known. So you literally have Watson try to the best diagnosis or therapy and then you look to see whether that was the proper outcome. You do this several times, and the learning engines in Watson begin to make connections between pieces of information. The system learns patterns, it learns outcomes, it learns what sources to trust (emphasis added).

Working with Watson, doctors at the Anderson Center, who are especially interested in leukemia, have made significant headway in their efforts to understand and treat the disease. Watson's role in this process has been twofold:

1. Expanding capacity: It helps to make sense out of so-called big data—the mountain of text, images, and statistics which, according to Kelly, "is so large that traditional databases and query systems can't deal with it." Moreover, says Kelley. big data is "unstructured" and flows "at incredible speeds.... With big data. we're not always looking for precise answers; we're looking for information that will help us make decisions."

2 Increasing speed: Kelley also points out that "Watson can do in seconds what would take people years." The system can, for example, process 500 GB of information—the equivalent of a million books—per second. When it comes to making sense out of the enormous amount of data concerning the genetic factors in cancer, says Kelly; "Watson is like big data on steroids."

Clearly, however, Watson is not replacing "knowledge workers" (doctors) at the Anderson Center. Rather, its being used to facilitate their knowledge work. In this respect, argues Thomas H. Davenport, a widely recognized specialist in knowledge management, Watson is confirming "one of the great cliches of cognitive business technology—that it should be used not to replace knowledge workers, but rather to augment them." On the one hand, even Davenport admits that some jobs have been lost to cognitive technology. In the field of financial services, for instance, "many lower-level" decision makers—loan and insurance-policy originators, credit-fraud detectors—have been replaced by automated systems. At the same time, however, Davenport observes that "experts" typically retain the jobs that call for "reviewing and refining the rules and algorithms [generated byl automated decision systems."

Likewise, human data analysts can create only a few statistical models per week, while machines can churn out a couple of thousand. Even so, observes Davenport, "there are still hundreds of thousands of jobs open for quantitative analysts and big data specialists." Why? "Even though machine learning systems can do a lot of the grunt work," suggests Davenport, "data modeling is complex enough that humans still have to train the systems in the first place and check on them occasionally to see if they're making sense?

Colvin, however, isn't sure that these trends will hold true for much longer. Two years after he competed against Watson, Colvin reported that "Watson is (now] 240 percent faster. I am not He adds that by 2034—when Watson will probably bean antiquated curiosity—its successors will be another 32 times more powerful. "For over two centuries," says Colvin, "practically every advance in technology has sparked worries that it would destroy jobs, and it did.... But it also created even more new jobs, and the improved technology made those jobs more productive and higher paying.... Technology has lifted living standards spectacularly."

Today, however, Colvin is among many experts who question the assumption that the newest generations of technologies will conform to the same pattern. "Until a few years ago: acknowledges former Treasury Secretary Larry Summers, "I didn't think (technological job loss) was a very complicated subject. I'm not so completely certain now." Microsoft founder Bill Gates, on the other hand, is not quite so ambivalent: "Twenty years from now," predicts Gates. "labor demand for lots of skill sets will be substantially lower. I don't think people have that in their mental model."

According to Colvin, today's technology already reflects a different pattern in job displacement: It's "advancing steadily into both ends of the spectrum" occupied by knowledge workers, replacing both low-and high-level positions and "threatening workers who thought they didn't have to worry." Take lawyers, for instance. In the legal-discovery process of gathering information for a trial, computers are already performing the document-sortirg process that can otherwise require smai armies of attorneys. They can scan legal literature for precedents much more thoroughly and will soon be able to identify relevant mat-ters of law without human help. Before long, says Colvin, they "will move nearer to the heart of what lawyers do" by offering better advice on such critical decisions as whether to sue or settle or go to trial.

So what appears to be the long-term fate of high-end knowledge workers? Davenport thinks that the picture is "still unclear," but he suggests that, in order to be on the safe side, would-be knowledge workers should consider reversing the cliché about technology as a means of augmenting human activity: "If there is any overall lesson" to be learned from current trends "it is to make sure you are capable of augmenting an automated system. If the decisions and actions that you make at work are remarkably similar to those made by a computer. that computer will probably be taking your paycheck before long."

Questions:

I. These clays. according to more and more experts. "every worker is a knowledge worker? Consider the definition of knowledge workers in the text: "workers whose contributions to an organization are based on what they know." In what sense might just about any employee qualify as a "knowledge worker"? For example, what qualifies as "knowledge" in an organization's operational activities (that is, in the work of creating its products and services)? What's the advantage to an organization of regarding all employees as knowledge workers?

2. Why are computers, especially cognitive computing systems, so effective in assisting the decision-making process? In particular, how can they increase the likelihood of good decisions under conditions of risk and uncertainty?

3. "The overwhelming message," says Geoff Colvin, seems lo be that no one is safe. "Technological unemployment may finally be here. But even if that's true... it will also be true that, as always, technology is making some skills more valuable and others less so.... Which skills will be the winners?" Colvin supplies one at least one answer to his own question: "it just seems common sense that the skills that computers cant acquire—forming emotional bonds, making human judgments—will be valuable." Thomas Davenport agrees: "It's probably not a bad idea," he suggests. "to improve your human-relationship skills."

Think of a few jobs in which the application of "human-relationship skills" is important—even absolutely necessary. Explain why these jobs require more than just decision-making skills. How about you? Does the job that you want require good human-relationship skills? Do your human-relationship skills need sonic improvement? What sorts of things can you do to improve them?

4. Science journalist Patrick J. Eiger reports that students of the future are likely to have it a lot easier because digital textbooks equipped with artificial intelligence capabilities will guide them along with the patience and perceptiveness of their favorite kindly professors. Take the newly developed Inquire intelligent biology textbook for the iPad. It allows students to stop and type in a question like "What does a protein do? and then presents them with a page full of information specific to whatever concept they're stuck on."

Using "What does a protein do as a model, think of three questions that you would like to ask this book about topics in this chapter. Explain why you chose the questions that you did and what sort of information you'd find helpful in response to each of your questions.

The inventory of Work in Process—Rolling on September 1 and debits to the account during September were as follows:

During September, 800 units in process on September 1 were completed, and of the 17,920 units entering the department, all were completed except 1,500 units that were 60% completed. Charges to Work in Process—Rolling for October were as follows:

During October, the units in process at the beginning of the month were completed, and of the 20,600 units entering the department, all were completed except 1,000 units that were 90% completed.

Required:

1. Enter the balance as of September 1 in a four-column account for Work in Process—Rolling. Record the debits and the credits in the account for September. Construct a cost of production report and present computations for determining (a) equivalent units of production for materials and conversion, (b) costs per equivalent unit, (c) cost of goods finished, differentiating between units started in the prior period and units started and finished in September, and (d) work in process inventory. If an amount box does not require an entry, leave it blank.

If an amount is zero, enter in a zero "0". Round cost per unit answers to the nearest cent.

2. Provide the same information for October by recording the October transactions in the four-column work in process account. Construct a cost of production report, and present the October computations (a through d) listed in part (1). If an amount box does not require an entry, leave it blank.

An endocrinologist was interested in exploring the relationship between the level of a steroid (Y) and age (X) in healthy subjects whose ages ranged from 8 to 25 years. She collected a sample of 27 healthy subject in this age range. The data is located in the file problem01.txt, where the first column represents X = age and the second column represents Y = steroid level. For all R programming, print input and output codes and values.

(a) Read the file problem01.txt into R using the read.table() function. You’ll need to set the working directory to the file location. Make a scatterplot of steroid (Y) versus age (X). Include the plot.

(b) Use R to fit a simple linear regression. Write down the fitted equation and multiple R² from the summary() output. Also comment on the p-value for the ?₁

coefficient

Y_i = ?₀ + ?₁X_i + ?_i

(c) Make a scatterplot of the fitted values versus the standardized residuals for the model in part (b). Are there any violation of assumptions? Include a copy of your plot.

(d) Create a quadratic regression in R. Write down the fitted equation, multiple R², and the p-value for ?₁ from the summary()output. Compare to part (b).

Y_i = ?₀ + ?₁X_i + ?₂X_i² + ?_i

problem01.txt

"age" "steroid"

15 14.1

10 8.5

13 10.8

16 18.4

10 4.7

18 23.3

16 16.4

10 9.4

16 17.7

23 35.8

19 25.4

18 24.9

24 42.1

19 26.5

24 40

12 10.7

13 11.6

10 3.6

23 37.9

17 16.8

19 24

23 37.7

20 29.6

14 13.7

19 23.1

11 8.3

17 19.6

9 7.8

11 7.1

13 13.3

18 20.8

25 44.4

9 9.7

12 12.5

22 34.9

8 4.3

9 5.9

8 6

22 36.2

15 11.7

10 5.3

15 15.6

9 6.6

14 15.7

13 10.5

17 20.7

23 36.8

23 37.2

8 5

16 19.6

16 18.9

15 16.1

10 7.7

14 11.9

12 9

8 4.4

8 2.7

8 5.2

16 19.3

20 27.5

20 27.8

13 12.9

12 12.8

13 9.3

15 16.1

19 25

13 10.5

13 9

18 22.3

22 33.6

9 4.9

19 28.4

15 14

21 30.6

19 24.8

R Outline Sample

########################

####### Part (a) #######

########################

# First save the file 'problem01.txt' on your computer.

# Next, set the working directory to the file location by doing the following:

# 1) Click on 'Session' on the top menu

# 2) Select 'Set Working Directory' > 'Choose Directory'

# 3) Select the folder where 'problem01.txt' is saved

# Read in data using the read.table() function.

dat <-

attach(dat)

# Create a scatterplot of age (X) vs steroid (Y)

# Write code here

########################

####### Part (b) #######

########################

# Fit a simple linear regression, then display the summary

fit <- # Enter code for simple linear regression

summary(fit)

########################

####### Part (c) #######

########################

# Plot the fitted values versus the standardized residuals for the fitted

# equation in part (b). Use the functions: sigma(), resid(), and predict()

y.hat <-

e.std <-

plot(y.hat, e.std, main = "Standardized Residuals vs. Fitted Value")

########################

####### Part (d) #######

########################

In this homework, you will practice and reinforce the basics of socket programming for TCP connections in Python: how to create a socket, bind it to a specific address and port, as well as send and receive a HTTP packet. You will also learn some basics of HTTP header format. The requirements for this homework are specified below.

1. Function Requirement: You will develop a web server that handles one HTTP request at a time. Your web server should accept and parse the HTTP request, get the requested file from the server’s file system, create an HTTP response message consisting of the requested file preceded by header lines, and then send the response directly to the client. If the requested file is not present in the server, the server should return an HTTP 404 “Not Found” msg.

2. Security Requirement: Note that this Web server will allow its clients to access ANY file that they can name. To prevent strangers from snooping on your files, you should include some basic protections: 1. If the request goes to “/grades/students.html”, your server should return an HTTP 403 “Forbidden” response. 2. Additionally, to prevent directory listing, the same 403 message needs to be returned if the request goes to “/grades/” folder.

Skeleton Code

Below you will find the skeleton code for the Web server. You are to complete the skeleton code. The places where you need to fill in code are marked with #Fill in. Each place may require one or more lines of code.

Running the Server

Put an HTML file (e.g., HelloWorld.html) in the same directory that the server is in. Run the server program. Determine the IP address of the host that is running the server (e.g., 128.238.251.26, or 127.0.0.1 if you run your server program locally on your own device). In either case, you can open up a browser on your client machine and type the following URL.

http://127.0.0.1:6789/HelloWorld.html

where 6789 is the port number you hardwired into your server code and ‘HelloWorld.html’ is the name of the file you placed in the server directory (case matters!). The browser should then display the contents of HelloWorld.html. Don’t forget the port number; if you leave it out the browser will use the default HTTP port 80 and you won’t get a result. Then try to get a file that is not present at the server. You should get a 404 “Not Found” message. For security feature testing, you can create a folder named ‘grades’ inside your server directory and test it in your browser by replacing ‘HelloWorld.html’ with ‘grades/students.html’ or ‘grades/’.

Skeleton Python Code for the Web Server

#import socket module

from socket import *
import sys # In order to terminate the program

serverSocket = socket(AF_INET , SOCK_STREAM)

# Prepare a server socket on a particular port # Fill in code to set up the port
while True:

# Establish the connection

print(’Ready to serve...’)
connectionSocket, addr = # Fill in code to get a connection try:

message = # Fill in code to read GET request filename = message.split()[1]
# Fill in security code
f = open(filename)

outputdata = # Fill in code to read data from the file # Send HTTP header line(s) into socket
# Fill in code to send header(s)
# Send the content of the requested file to the client for i in range(0, len(outputdata)):

connectionSocket.send(outputdata[i].encode()) connectionSocket.send("\r\n".encode()) connectionSocket.close()

except IOError:
# Send response message for file not found # Fill in
# Close client socket
# Fill in

serverSocket.close()
sys.exit() # Terminate the program after sending the corresponding data

Please study the article below and choose one specific corporation & business at your choice from the most unstable industries in the U.S. right now, in April 2020 due to corona virus impact and discuss in a word document the following topics (please do a brief research using external internet resources, website of the corporation, annual or quarterly company reports or your required book and OSM 311 power points):

-Company products & services

-The impact on sales or revenue or profit for this corporation of the corona virus effect on customers, supply chain, operation & employees, distribution, shelter in place government & state decision.

-What should you decide on inventory management (Anticipation inventory or Seasonal Inventory and safety inventory) as an operation manager for this company

-How can you reduce the inventory cost (slide 14) and Total cost minimization (slide 22-25).

-Losses & how to maximize the gross profit (review the break-even point)?

-Operations Strategies that your recommend for this business & corporation in this difficult situation of the economy (required book, page 581).

Airlines

With people around the world being asked to stay home and travel bans preventing people from entering and leaving certain countries becoming more common, the airline industry has been suffering major losses. Vertical Research Partners said that passenger revenues could decline to zero by the end of the first quarter and stay there for the whole year, Reuters reported.

Many major airlines have taken a hit. For example, Lufthansa has idled 700 of its 763 aircraft, and Qantas made plans to cut all international flights, which means 30,000 of its workers would need to take paid or unpaid leave.

The airline industry has been asking for government aid to get through the crisis, and on March 27, the U.S.’s coronavirus aid package passed, which would provide $58 billion to the American airline industry, Business Insider reported. The bill protects airline employee jobs through Sept. 30.

Many stakeholders see this as a win, including Delta Airlines and the Association of Flight Attendants.

“This is an unprecedented win for frontline aviation workers and a template all workers can build from,” Association of Flight Attendants president Sara Nelson said in a statement obtained by Business Insider. “The payroll grants we won in this bill will save hundreds of thousands of jobs and will keep working people connected to healthcare many will need during this pandemic.”

However, other experts think the bailout won’t be enough to save the industry, which relies on passengers to make revenue.

“We have an airline industry right now that is flying empty planes,” airline consultant Mike Boyd told CNN. “This isn’t going to save the industry unless we get back in [the] business of flying people.” And it’s unknown when that time might come.

“We’re talking about at least six to eight months down the road before flying starts to resume at anything approaching normal,” Boyd said. “And even then, we’re likely to see a significant reduction. One way or another, we’re going to have a smaller airline industry.”

Auto Manufacturing

Ford, General Motors, Fiat Chrysler, Honda, Toyota, Nissan and Hyundai have all shut down manufacturing plants amid concerns about the spread of the coronavirus, ABC News reported. The closing of  Ford, General Motors and Fiat Chrysler’s Detroit facilities will leave 150,000 workers without jobs, though they are likely to receive supplemental pay in addition to unemployment benefits.

However, the slowdown in demand for cars as a result of the coronavirus could have major ripple effects. According to one projection, for every seven-day period that consumers stop buying new vehicles, the U.S. economy would lose roughly 94,400 jobs and $7.3 billion in overall earnings, NBC News reported.

Construction

Although the construction industry is pushing to be seen as “essential” to keep their projects running, there could still be some major impacts to the industry. The shutdown of the production of construction materials in China could lead to material delays and more expensive materials stateside, Construction Dive reported. It could also lead to fewer projects, especially in the realm of hospitality, as clients and lenders pull back on funding and expansion in these times of uncertainty.

“My gut tells me we’re going to see higher prices and projects canceled, although I can’t point to the extent of it,” Joe Natarelli, national construction industry leader at accounting services firm Marcum, told Construction Dive.

Cruises

All the major cruise lines have ceased operations as countries continue to close their ports. Thousands of workers have lost their jobs — both those who work on the cruise ships and those who work at the ports — and the values of the three biggest U.S. cruise lines — Carnival, Royal Caribbean and Norwegian — have all plummeted, The Guardian reported.

“This will be a disastrous time for the industry,” Dr. Christopher Muller, a senior professor at Boston University’s School of Hospitality Administration, told The Guardian. “When you have 3,500 people booked on one of these mega cruises and the boat doesn’t go, it’s an enormous expense. Someone’s paying for that boat that’s sitting idle in the harbor and it’s very hard to recapture those ongoing fixed-cost losses.”

However, he believes the industry will be able to bounce back eventually.

“The logical thing is they will have to have very deep discounts, and those deep discounts will be especially present in the next cycle of cruise seasonality in September,” Muller said. “By August and September, the consuming public will be enticed to go back on cruises because the pricing is going to be outrageously good with enormous discounts.”

Film and TV Production

Major networks and film studios have put a halt on production as a result of the coronavirus outbreak. Netflix has stopped production on all shows in the U.S. and Canada, including “Stranger Things” season four; NBC Universal has suspended production on 35 or more shows; and Warner Bros., Disney +, Apple TV +, CBS, AMC and Viacom have all also paused production on their shows, Forbes reported.

The release dates of several major films have also been pushed, including “Wonder Woman 1984,” “In the Heights,” “Black Widow” and “A Quiet Place Part II,” while others have been released straight to streaming.

Over 100,000 entertainment industry workers have lost their jobs, while studios, networks and producers face major losses, the Los Angeles Times reported.

“There may be irrecoverable losses to the movie and entertainment industry,” Brian Kingman, who helps film and television companies find insurance policies, told the Los Angeles Times. “It’s going to take a long time to sort out.”

Gambling

As a result of the coronavirus, 92% of all of the casinos in America are now closed, including those in Las Vegas, the Las Vegas Review-Journal reported. In addition, the legal sports betting industry is also suffering as live sporting events have been canceled or postponed, Business Insider reported.

These closures not only affect the hospitality and gaming employees who are now out of work, but also the U.S. economy as a whole. If casinos remain closed for two months, it would rob the U.S. economy of $43.5 billion in economic activity, the Las Vegas Review-Journal reported.

Gyms

Many gyms and fitness studios have temporarily closed as a result of the coronavirus. But the pandemic hasn’t been bad for all sectors of the fitness industry — it’s actually been good news for Peloton, which has seen an increase in share prices, CNBC reported. But as people invest more in their at-home gyms while traditional gyms and fitness studios are closed, they might be reluctant to go back once they are open, feeling that they need to justify the thousands they just spent on new equipment.

How does Watters explain the process by which the concept of depression gained a foothold in Japan? Is this "globalization of the American psyche" destructive of other cultures? Why would American concepts of mental illness and treatment be especially likely to spread to other countries?

(The Globalization Reader 5th edition)

Considering the mass surveillance that the American people endured from their own government after 9/11, what should be an appropriate threshold that would allow certain governmental agencies to infringe the civil liberties of American citizens when it is claimed to be utilized strictly for the safety of the general public?

17. A new African American lounge in Brooklyn who advertises on social media and websites only accepts African American patrons. Some of Brooklyn’s new Caucasian residents filed injunction suit citing the Commerce Clause. Which case have they cited as precedent to their claim?

The price of a three-month future contract on the S&P 500 index is traded at 2355. Use a 9 step binomial tree model to value an American put on the future contract assuming K=2400, r=1%, s=15%. The price of the American put option is ___________.