PROBLEM 3: Given the following relational database table: Patients(ID, name, symptom, days_in_hospital) The following insertions are performed on the table Patients: Insert record <20, Johnson, cough, 3> Insert record <10, Black, fever, 5> Insert record <30, Miller, fever, 10> Insert record <70, Brown, fatigue, 2> Insert record <60, Grant, headache, 4> Insert record <50, Miller, nausea, 15> Insert record <90, Brown, cough, 8 > Assume each block in the Patients file can store up to 2 patient records. Do the following: 1. Assuming that Patients is organized as a heap file, show the contents of the file after the last insertion. 2. Assuming that Patients is organized as a sequential file with days_in_hospital as the ordering field, show the contents (i.e. the data values as well as the associated block/bucket/record addresses) of the file after the last insertion. 3. Assuming that Patients is organized as an index-sequential file on the search key days_in_hospital and assuming that the primary index, the secondary index on ID, and the secondary index on name have been created, show the contents of Patients, the primary index, and the two secondary indices after the last insertion. 4. Given the index-sequential file organization as described in (3), explain step-by-step how the DBMS would conduct search on this file organization to answer the following SQL query: select name from Patients where ID between 30 and 60

“So much Fake News. Never been more voluminous or more inaccurate,” tweeted President Trump. A database of Trump remarks contains 320 references to fake news, named as term of the year in 2017. Leading news channels are not immune, for example in 2016 a story claiming HH Shaikh Mohammad Bin Zayed Al Nayhan had chanted a Hindu prayer went viral in India and was tweeted by main news channels. Fake news has been blamed for causing tension between countries, for example the Deputy Chairman of Dubai Police blamed Al Jazeera for deepening the crisis between Qatar and the UAE. Fake news has also resulted in tighter regulation of social media, and is now seen as a threat to democracy and free debate.

Historically, political interests have always misrepresented facts, but the identification, categorization and concept of fake news has become more complex and challenging. One team of students from Berkeley identified four classifications; clickbait, propaganda, commentary and humour and built a tool www.classify.news which scores the truth of information based on its URL. Their site claims 84% accuracy but the sample is based on only 5000 articles. IBM tested a prototype Question Answering Machine (QAM) called Watson to separate fact from fiction, and Google funded a fact checking operation called Full Fact to develop an automated fact-checking system. However, the successful implementation of fact checking models requires a constantly updated corpus of knowledge which is verified.

There are different data science architectures to check facts. The traditional NLP method of fake news detection is used by Thomson Reuters, a trusted global news source. Tracer News is a sensitive algorithmically driven system which filters news stories and social feeds for truth, and assigns a veracity score. It’s claimed to be 84% accurate, and with a sample of 5 tweets the system achieves 78% accuracy on distinguishing rumour and fact.

Research has shown that tweets containing false news spread faster and wider on Twitter than those with valid news. One estimate claims that in the month before the 2016 US election people read up to 3 articles of fake news. How this may possibly effect our attitudes is unknown, and psychologists have taken an interest in fake news. The Cognitive Reflection Test (CRT) was used to measure the ability to think analytically and consequently to predict people who can distinguish fake news from real news. Research has shown that if people agree with a message then they are more likely to believe it.

Social platforms such as Facebook are attempting to crack down on fake news in response to pressure. Facebook was accused of publishing fake posts using the name Lewis, who is a financial expert. Many people were thereby scammed to trust a financial product. Lewis pursued legal action to force social media to change their policy on advertising and be liable for hosting scams. Facebook are now playing an editorial role by changing the way News Feed functions. CEO Zuckerberg commented that sensationalism, misinformation and polarization are too common.

Countries such as Malaysia are making fake news punishable with up to 10 years in prison in an effort to protect national security. The law penalizes those who create, offer, circulate, print or publish fake news, which is defined as “any news, information, data and reports which is, or are, wholly or partly false whether in the form of features, visuals or audio recordings or in any other form capable of suggesting words or ideas”. Opponents call this an attack on freedom of speech and fear the new law could be used to penalize critical attacks on the government.

Human fact checkers are a rigorous and expensive way to combat fake news. A simple claim could take hours to verify and the manpower required could be considerable. If the responsibility lies with algorithms, false positives and negatives could lead to the suppression of a news story. In the UAE, the Youth Media Council is playing a role in the UAE’s strategy of developing the media sector and verifying credible from fake news. In a Dubai competition the winners research had explored a fake news incident whereby students’ names were spread on social media as soldiers who had died. Workshops to educate and teach young people skills to identify fake news were suggested.

Technology has enabled anyone to create news and for that news to go viral. The success of the message is not reliant on the truth of the contents, and there is too much information to validate. Many questions are raised about the effects of tagging news as fake, susceptibility to fake news, is fake news more real if its viral, and how to identify fake news. How can we create and sustain a global culture which promotes and values truth? What indeed is the truth of an event when multiple perspectives of the same event can hold truth.

1. What is/are the problem/problems here? Is there an underlying fundamental problem?
2. Who are the major stakeholders and what are their perspectives?
3. What are the major ethical, legal, and security aspects associated with the problem.
4. What are the intended and unintended consequences of existing computing solutions? Consider the consequences on individuals, organizations and society within local and global contexts
5. What recommendations would you propose that will lead to potential solutions.

Please answer ASAP

Database

Consider the following relation scheme:
Players = {name, position, year, team, manager}
We use the following abbreviations:
Players = {n, p, y, t, m}
with the following FDs
n --> p
n, y --> t
t, y --> m
(3.a) Is Players in BCNF? Explain why.
(3.b) Find all candidate keys of Players. Show your work.
(3.c) Obtain a decomposition of players using the 3NF decomposition algorithm. Assume the
given FDs are a minimal (canonical) cover. Show your work.
(3.d) Assume the following FD also holds in players (in addition to the FDs listed above).
t, m ! y
Find all candidate keys of Players for this case. Show your work.

Database Design and SQL

Consider the following relations:

Student (snum: integer, sname: string, major: string, level: string, age: integer)
Class (name: string, meets_at: time, room: string, fid: integer)
Enrollment (snum: integer, cname: string)
Faculty (fid: integer, fname: string, deptid: integer)

Write the following queries in SQL. Also, there should be no duplicates printed in any of the answers.

a) Find the names of all students who are enrolled in two classes that meet at the same time.
b) Find the names of faculty members for whom the combined enrollment of the courses that they teach is less than five.
c) Print the Level and the average age of students for that Level, for each Level.
d) Print the Level and the average age of students for that Level, for all Levels except JR.
e) Find the names of students who are enrolled in the maximum number of classes.
f) Find the names of students who are not enrolled in any class.

CASE STUDY SCENARIO 1

GEOLEN VENTURES

GEOLEN VENTURES, a local administrative authority, provides a range of services to individuals, including the provision of welfare. GEOLEN has a total workforce of 1,900.

In the welfare department, GEOLEN employs 30 staff who visits individuals to assess their welfare needs. This job means visiting individuals, who are normally poorly-paid or facing difficult family circumstances, to find out whether they should receive financial assistance (sometimes termed ‘benefits’) from GEOLEN.  

The area covered by GEOLEN has a very low population density. Staff may have to travel many kilometres between each appointment and may not return to their central office for days at a time.

Rules which determine whether people are entitled to financial assistance are complicated, with over 6,500 separate rules and 170 different forms to complete. These rules change frequently, usually three per week. Consistent application of rules is difficult because of benefit fraud, human error, constant changing of rules and time delays inherent in the system itself. Staff retention is low because of poor morale.

The existing IT system is a minicomputer which consists of a central processor supported by a number of peripherals located at the headquarters of GEOLEN. The minicomputer contains a database and other related software showing which benefits are due to which individuals. A list of the benefits due is printed out weekly; and benefits are paid out according to the information on this list. The database is accessed and updated from ten terminals located in the computer room itself. Staff normally updates the database when they return from their visits to individuals requiring benefits.

GEOLEN has decided to establish a decision support system to assist its staff in the application of benefit rules to the situations of individuals. GEOLEN requires that staff have access to the decision support system at any time during their working day.

QUESTIONS 1 RELATES TO  THE CASE STUDY SCENARIO 1 ABOVE.

QUESTIONS 1

1. Identify and describe the existing system of GEOLEN which is a minicomputer which consists of a central processor supported by a number of peripherals located at the headquarters. [10 marks]

2. Discuss the merits and demerits of such a system. [4 marks]

3 . A consultant of GEOLEN to the company that the organization can be more efficient in terms of information delivery if a Client/Server system is used instead of the current minicomputer. Discuss the suggestions of the consultant.   

  [6 marks]

The consultant is requesting the IT manager of GEOLEN to consider using some current Networking Operating Systems (NOS) for the Client/Server system.

4. Suggest with reasons two (2) current NOS that the IT manager of GEOLEN could deploy to support its operations.

[10 marks]

b. Discuss the main features of such two (2) Network Operating Systems. [10 marks]

5. Suggest with a diagram and reasons the type of topology that will be suitable for Client/Server system for GEOLEN.

[10 marks]

b. Discuss the merits and demerits of such a topology. [10 marks]

XYZ stock price and dividend history are as follows:

An investor buys four shares of XYZ at the beginning of 2015, buys another two shares at the beginning of 2016, sells one share at the beginning of 2017, and sells all five remaining shares at the beginning of 2018.

a. What are the arithmetic and geometric average time-weighted rates of return for the investor? (Do not round intermediate calculations. Round your answers to 2 decimal places.)

b-1. Prepare a chart of cash flows for the four dates corresponding to the turns of the year for January 1, 2015, to January 1, 2018.

4. Paul and Libby White (both are age 66) are married and together have AGI of $105,000 in 2018. They have two dependents and file a joint return. During the year, they paid $8,000 for medical insurance, $15,000 in doctor bills and hospital expenses, and $1,000 for prescribed medicine and drugs.

(A) In December 2018, the Whites received an insurance reimbursement of $3,500 for hospitalization expenses. Determine the deduction allowable for medical expenses paid during the year.

(B) Assume instead that the Whites received the $3,500 insurance reimbursement in February 2019. Determine the deduction allowable for medical expenses incurred in 2018.

(C) Assume that the Whites received the $3,500 insurance reimbursement in February 2019. Discuss whether the reimbursement will be included in their gross income for 2019.

4. Paul and Libby White (both are age 66) are married and together have AGI of $105,000 in 2018. They have two dependents and file a joint return. During the year, they paid $8,000 for medical insurance, $15,000 in doctor bills and hospital expenses, and $1,000 for prescribed medicine and drugs.

(A) In December 2018, the Whites received an insurance reimbursement of $3,500 for hospitalization expenses. Determine the deduction allowable for medical expenses paid during the year.

(B) Assume instead that the Whites received the $3,500 insurance reimbursement in February 2019. Determine the deduction allowable for medical expenses incurred in 2018.

(C) Assume that the Whites received the $3,500 insurance reimbursement in February 2019. Discuss whether the reimbursement will be included in their gross income for 2019.

Martinez, Inc. acquired a patent on January 1, 2017 for $41,300 cash. The patent was estimated to have a useful life of 10 years with no residual value. On December 31, 2018, before any adjustments were recorded for the year, management determined that the remaining useful life was 7 years (with that new estimate being effective as of January 1, 2018). On June 30, 2019, the patent was sold for $26,300.

Required:

1. Prepare the journal entry to record the acquisition of the patent on January 1, 2017.
2. Prepare the journal entry to record the annual amortization for 2017.
3. Compute the amount of amortization that would be recorded in 2018.
4. Determine the gain (loss) on sale on June 30, 2019.
5. Prepare the journal entry to record the sale of the patent on June 30, 2019.

The following data from Lyre Ltd's accounts relates to two assets at 30 June 2018:

At 30 June 2018 Lyre Ltd decides to adopt the revaluation model for both these assets. On this date land has a fair value of $2,018,000 and plant and equipment has a fair value of $294,000. On 30 June 2019 Lyre Ltd reviews the value of its assets. The fair value of land is reassessed as $2,080,000. Plant and equipment has no change in value on that date.

Prepare the journal entries required to revalue the assets for the year ended 30 June 2018 and the 30 June 2019.