Running head: FINANCIAL PERFORMANCE CITY OF DORAL 1 FINANCIAL PERFORMANCE CITY OF DORAL 3 Financial Performance City of Doral Name Institutional Affiliation Financial Performance City of Doral History of City of Doral Two real estate developers called Doris and Alfred Kaskel who bought 2400 acres of land in late 1950s established City of Doral in the state of Florida. The land was swampy between NW 36 and 74 streets and from NW 79 to NW 117 avenues; they bought the land for $ 49,000 with the aim of building a hotel and a golf course. The Kaskel’s constructed the Carillon Hotel and Doral Beach Hotel on Miami Beach. On the bought land, they constructed a country club and established a hotel, which they named as Doral, which is a combination of their names. So guests at the Miami Beach would be transported to the country club, which featured blue, red and par 3 golf courses. Among the events that were hosted at the country club was Florida’s major PGA event, which was the first Doral Open Invitational (City of Doral, 2020). Subsequently, guests frequented the hotels and the country club. Between 1980 and 2000, Doral’s grandson called Bill built Doral estates and engaged in a joint venture to build the Doral park. Because of building the estate, younger families flooded the area for shopping sprees because the area had not parks, stores, or schools. The tenants and buyers of the Doral estate came together as a community; whereas there were no traffic problems the rapid construction of the estate and the attraction of many buyers and tenants due to the low cost led the county to impose a building moratorium (City of Doral, 2020). The high population and lack of amenities led to increase in the cost of services. The community in the area established a West Dade Federation of Homeowner Associations in 1989 to safeguard the welfare of the community. As a result of the federations’ effort, there was establishment of police station, lighting, landscaping and roads in the area. Over time, the ownership of Doral country club and hotel changes when Donald Trump bought the club in 2012 for $150 million. Due to change in ownership, the name of the club changed to Trump National Doral Gold Club. The reputation of the club for its golf courses continued and expanded internationally; for example, the Blue Monster continued to host PGA Tour Tournament until 2016. Apparently, the City of Doral attracts many companies, families, businesses and retires (City of Doral, 2020). Between 2010 and 2016, the population of City of Dorol increased by 26.1% by 12,000 people to 58,000 residents. When the city incorporated in 2003, the population was 22,709, which is half its current population (Madan, 2017). Financial Developments since 2014 During the last four years, the City of Doral experienced increased construction of buildings and gro ...

1. Running head: FINANCIAL PERFORMANCE CITY OF
DORAL 1
FINANCIAL PERFORMANCE CITY OF DORAL
3
Financial Performance City of Doral
Name
Institutional Affiliation
Financial Performance City of Doral
History of City of Doral
Two real estate developers called Doris and Alfred Kaskel
who bought 2400 acres of land in late 1950s established City of
Doral in the state of Florida. The land was swampy between NW
36 and 74 streets and from NW 79 to NW 117 avenues; they
bought the land for $ 49,000 with the aim of building a hotel
and a golf course. The Kaskel’s constructed the Carillon Hotel
and Doral Beach Hotel on Miami Beach. On the bought land,
they constructed a country club and established a hotel, which
they named as Doral, which is a combination of their names. So
guests at the Miami Beach would be transported to the country

2. club, which featured blue, red and par 3 golf courses. Among
the events that were hosted at the country club was Florida’s
major PGA event, which was the first Doral Open Invitational
(City of Doral, 2020). Subsequently, guests frequented the
hotels and the country club.
Between 1980 and 2000, Doral’s grandson called Bill built
Doral estates and engaged in a joint venture to build the Doral
park. Because of building the estate, younger families flooded
the area for shopping sprees because the area had not parks,
stores, or schools. The tenants and buyers of the Doral estate
came together as a community; whereas there were no traffic
problems the rapid construction of the estate and the attraction
of many buyers and tenants due to the low cost led the county to
impose a building moratorium (City of Doral, 2020). The high
population and lack of amenities led to increase in the cost of
services. The community in the area established a West Dade
Federation of Homeowner Associations in 1989 to safeguard the
welfare of the community. As a result of the federations’ effort,
there was establishment of police station, lighting, landscaping
and roads in the area.
Over time, the ownership of Doral country club and hotel
changes when Donald Trump bought the club in 2012 for $150
million. Due to change in ownership, the name of the club
changed to Trump National Doral Gold Club. The reputation of
the club for its golf courses continued and expanded
internationally; for example, the Blue Monster continued to host
PGA Tour Tournament until 2016. Apparently, the City of Doral
attracts many companies, families, businesses and retires (City
of Doral, 2020). Between 2010 and 2016, the population of City
of Dorol increased by 26.1% by 12,000 people to 58,000
residents. When the city incorporated in 2003, the population
was 22,709, which is half its current population (Madan, 2017).
Financial Developments since 2014
During the last four years, the City of Doral experienced
increased construction of buildings and growth of investments
that increased the city’s tax base. In 2018, the corporation

3. raised $12.081 billion; the expansion in the tax base arose due
to diversification of investments in areas such as retail and
wholesale trade, light manufacturing, construction and tourism
(City of Doral, 2018). Generally, the corporation’s assets
exceeded its deferred inflows of resources and liabilities. The
table below shows the a summary of the net position of City of
Doral
2015
2016
2017
2018
Total assets
315,068,814
337,519,822
346,143,957
356,376,077
Total liabilities
41,585,954
57,775,513
57,672,302
55,528,269
Net Position
276,044,345
291,877,613
300,590,734
311,036,836
Based on the summary of the net position, the
corporation’s liabilities reduced during the last two years;
namely 2018 and 2017. However, its total assets increased
leading to increase in its net position. Based on the positive
financial performance of the corporation, it can meet its budget
estimates and effectively plan for future development activities.
Notably, during the budget making process, the city of Doral
engages the public through public participation policy in order

4. prioritize development areas and ways of expanding or
maintaining its revenue base. Among the corporation’s assets
that are, the highest are transport, energy and buildings.
Financial ratios of the City
Among the financial ratios that would be considered in
this section are total-debt-to-total-assets ratio, debt-to-net
assets ratio, and ratio of general bonded debt outstanding. It is
important to consider the ratio because it shows the financial
leverage of the corporation. Specifically, it considers all the
total assets of the corporation including tangible and intangible
assets. The ratio measures how much of the corporation’s assets
are financed by debt. The ratio indicates how the corporation
has grown its assets over time. It helps planners to determine if
the corporation has enough assets to meet its debt obligations.
Conclusion
The above overview gives a brief history of City of Doral,
how it incorporated and its current financial performance. The
city makes its annual budgets by involving its resident who
priorities which projects and programs should be funded based
on the projected revenue. Based on the comprehensive financial
reports, the corporation continues to register increase in assets;
however, during the last two years, it registered a reduction in
its liabilities. Such trend is beneficial for the financial stability
of the corporation.
References
City of Doral, (2020). Doral History. Web. Accessed on
14/3/2020.
City of Doral, (2018). 2018 Comprehensive Annual Financial
Report. Web. Accessed on 14/3/2020.
Madan, M. O (2017). Why is Everyone Moving to Doral?
Census says it’s the Fastest Growing City in Florida. Web.
Accessed on 14/3/2020.

5. AI: Artificial Intelligence
1
Reading response
Peter Dormer, “Craft and the Turing Test for Practical
Thinking,” in The Challenge of Technology.
What is personal know-how? What is distributed knowledge?
How do they relate to the Turing test?
Give one example of your own how these concepts matter today
to artists and makers, or better yet, in your own experience?
Journal homework
Keep a record (text and drawings) of events in daily life where
human and machine intersect and interact. Fill at least two
pages with your observations.
Mary Shelley, Frankenstein, or The Modern Prometheus, 1818
Boris Karloff in Frankenstein in 1931 directed by James Whale
Mary Shelley first published Frankenstein, or the Modern
Prometheus 1818. the novel allegorizes the Romantic obsession
with discovering the power or principle of life. Ideas about a
life power were consistent with the scientific understanding of
the day. Darwin himself spoke of an organizing “spirit of
animation” in his Zoonomia; or, The Laws of Organic Life, in

6. which he stated “the world itself might have been generated,
rather than created.”
Dr. Frankenstein picked all the parts for his monster based on
their beauty, but when it comes to life, the monster is
unbearably ugly. “I had worked hard for nearly two years, for
the sole purpose of infusing life into an inanimate body…the
beauty of the dream vanished, and breathless horror and disgust
filled my heart. Unable to endure the aspect of the being I had
created, I rushed out of the room”.
4
Two definitions of AI:
“The use of computer programs and programming techniques to
cast light on the principles of intelligence in general and human
thought in particular.
--Margaret Boden
“The science of making machines do things that would require
intelligence if done by humans.”
-Marvin Minsky
BOTH OF THESE STATEMENTS ORIGINATE IN ALAN
TURING’S FIRST COMPUTER SCIENCE ARTICLE
Working assumption: all cognition is computable

7. Question:
Is what’s not yet known to be computable actually computable?
if so, then what?
if not, why not, and what does that tell us about cognition?
7
Who was Alan Turing?
B. 1912 London, attended King’s College, Cambridge and
Princeton University. He studied mathematics and logic (he
hadn’t invented computer science yet)
At 23, he invented the “Turing machine” and published “On
Computable Numbers in 1936, the first and most important
paper in comp. sci.
During WWII, solved the German Enigma code by use of
electromechanical devices—a precursor to the computer
Laid the foundation for major subfields of comp sci: theory of
computation, design of hardware and software, and the study of
artificial intelligence
“The Imitation Game,”
aka
“The Turing Test”
In 1950, Turing posited a way to test machine intelligence: a
person in a room before a screen. S/he would correspond with
two agents and based on their responses, decide which was a
machine and which was human. If the machine can pass for
human, the machine is intelligent.
This is still a question. Is passing the Turing Test necessary for
AI? Or desirable? Stuart Watt (1996) has proposed an “inverted
Turing Test”: have the computer as the interrogator,
distinguishing between a machine and human. This would prove
a theory of mind for the computer.

8. Currently, “reverse Turing Tests” are used when contacting
companies or signing up for email services to filter out bots
(spell a word out of deformed letters, or click on images with
signs in them)
Turing hypothesized that in fifty years (year 2000), it would be
“pointless” to asking if machines can think==we can think of
this in the same way we say planes “fly” and submarines
“swim.”
9
The idea of putting a computer through a test already implies
some agency on the part of the machine. It’s the same process
that Descartes recommended for determining if other beings
have a mind.
11
blade runner
What's more, the Turing Test has been referenced many times in
popular-culture depictions of robots and artificial life – perhaps
most notably inspiring the polygraph-like Voight-Kampff Test
that opened the movie Blade Runner.
12
But more often than not, these fictional representations
misrepresent the Turing Test, turning it into a measure of

9. whether a robot can pass for human. The original Turing Test
wasn’t intended for that, but rather, for deciding whether a
machine can be considered to think in a manner
indistinguishable from a human - and that, even Turing himself
discerned, depends on which questions you ask.
What’s more, there are many other aspects of humanity that the
test neglects – and that’s why several researchers have devised
new variants of the Turing Test that aren’t about the capacity to
hold a plausible conversation.
13
Take game-playing, for example. To rival or surpass human
cognitive powers in something more sophisticated than mere
number-crunching, Turing thought that chess might be a good
place to start – a game that seems to be characterised by
strategic thinking, perhaps even invention.
Deep Blue won its first game against a world champion on 10
February 1996, when it defeated Garry Kasparov in game one of
a six-game match. However, Kasparov won three and drew two
of the following five games, defeating Deep Blue by a score of
4–2. Deep Blue was then heavily upgraded, and played
Kasparov again in May 1997.[1] Deep Blue won game six,
therefore winning the six-game rematch 3½–2½ and becoming
the first computer system to defeat a reigning world champion
in a match under standard chess tournament time
controls.[2] Kasparov accused IBM of cheating and demanded a
rematch. IBM refused and retired Deep Blue.

10. The “44th move” per se represents the moment when a human
being (Kasparov) realised he was facing a superior intellect
(Deep Blue).
The IBM vs. Kasparov game taught us not to be naïve about the
advancements in brute force (calculative) computing or
artificial intelligence. Kasparov’s frustration and anger
following the loss against Deep Blue almost feels cute today (I
say this as a huge fan of Garry, it almost pains me to write that
sentence). It’s likely that we underestimate advancements in a
similar manner, due to sheer disbelief or ignorance, the
incapacity of imagining a future where we work in a different
way all-together. It’s a pity.
And we now have algorithms that are all but invincible (in the
long term) for bluffing games like poker – although this turns
out to be less psychological than you might think, and more a
matter of hard maths.
14
What about something more creative and ineffable, like music?
Machines can fool us there too. There is now a music-
composing computer called Iamus, which produces work
sophisticated enough to be deemed worthy of attention by
professional musicians. Iamus’s developer Francisco Vico of the
University of Malaga and his colleagues carried out a kind of
Turing Test by asking 250 subjects – half of them professional
musicians – to listen to one of Iamus’s compositions and music
in a comparable style by human composers, and decide which is
which. “The computer piece raises the same feelings and

11. emotions as the human one, and participants can’t distinguish
them”, says Vico. “We would have obtained similar results by
flipping coins.”
15
Then there’s the “Turing touch test”. Turing himself claimed
that even if a material were ever to be found that mimicked
human skin perfectly, there was little reason to try to make a
machine more human by giving it artificial flesh.
Our current motivation is a little different: We know that
prosthetic limbs that can pass for the real thing may lessen the
psychological and emotional impact that wearers report. To this
end, mechanical engineer John-John Cabibihan at Qatar
University and his colleagues are creating materials that look
and feel indistinguishable from human skin. Earlier this year, he
and his coworkers reported that they had created a soft silicone
polymer that, when heated close to body temperature with sub-
surface electronic heaters, closely resembled real skin. The
researchers created an artificial hand by coating a 3D-printed
resin skeleton with the electrically warmed polymer and used it
to touch the forearms of people while the hand itself was
concealed. The participants proved unable to make any reliable
distinction between the touch of the artificial hand and a real
one.
16
2014
a “supercomputer” program called “Eugene Goostman”—an

12. impersonation of a wisecracking, thirteen-year-old Ukranian
boy—had become the first machine to pass the Turing Test.
Kevin Warwick, a professor of cybernetics at the University of
Reading, who administered the test, wrote, “In the field of
Artificial Intelligence there is no more iconic and controversial
milestone than the Turing Test, when a computer convinces a
sufficient number of interrogators into believing that it is not a
machine but rather is a human.” Warwick went on to call
Goostman’s victory “ a milestone” that “would go down in
history as one of the most exciting” moments in the field of
artificial intelligence.
Developed by PrincetonAI (a small team of programmers and
technologists not affiliated with Princeton University) and
backed by a computer and some gee-whiz algorithms, "Eugene
Goostman" was able to fool the Turing Test 2014 judges 33% of
the time — good enough to surpass the threshold set by
computer scientist Alan Turing in 1950. Turing believed that by
2000, computers would be able to, through five-minute text-
based conversations, fool humans into believing that they were
flesh and blood, at least 30% of the time. Depending on whom
you talk to, Goostman's achievement is either a huge turning
point for technology, or just another blip.
17
Scott: … Do you understand why I’m asking such basic
questions? Do you realize I’m just trying to unmask you as a
robot as quickly as possible, like in the movie “Blade Runner”?
Eugene: … wait
Scott: Do you think your ability to fool unsophisticated judges
indicates a flaw with the Turing Test itself, or merely with the
way people have interpreted the test?

13. Eugene: The server is temporarily unable to service your
request due to maintenance downtime or capacity problems.
Please try again later.
certainly it doesn’t obviously justify claims that the Turing Test
has been passed. As computer scientist Scott Aaronson of the
Massachusetts Institute of Technology has said, “Turing’s
famous example dialogue, involving Mr. Pickwick and
Christmas, clearly shows that the kind of conversation Turing
had in mind was at a vastly higher level than what any chatbot,
including Goostman, has ever been able to achieve.”
More to the point, Aaronson’s splendid conversation with
Eugene, after he decided to probe further into all the publicity
surrounding “him”, demonstrates the limitations rather
graphically:
Scott: … Do you understand why I’m asking such basic
questions? Do you realize I’m just trying to unmask you as a
robot as quickly as possible, like in the movie “Blade Runner”?
Eugene: … wait
Scott: Do you think your ability to fool unsophisticated judges
indicates a flaw with the Turing Test itself, or merely with the
way people have interpreted the test?
Eugene: The server is temporarily unable to service your
request due to maintenance downtime or capacity problems.
Please try again later.
18
Two theories of AI:
Base of knowledge
Neural networks

14. The base of knowledge idea—basically filling a machine with
encyclopedic knowledge is the “bottom-up” method. It
establishes a base of knowledge from which the machine can
operate
The neural net idea constructs a system that will analyze huge
amounts of data. This is the “top-down” method. For example,
through analyzing millions of images of cats, a neural net will
“learn” to recognize a cat.
19
Google’s Deep Dream
Google’s Deep Dream is an example of a neural net. Given an
input image, it analyzes and classifies the image according to
millions of images it’s seen before. The results so far have been
these kaleidoscopic/psychedelic outputs that cram as much
information into one space as possible. It’s job is essentially to
find the sound in noise
https://www.youtube.com/watch?v=egk683bKJYU see esp min
18:00—25:00 for google dream architecture; 32:30—36:00
“shore of portraits”
20
Asked to find bananas, Google’s Deep Dream will find bananas
within a set of noise
21
SketchRNN (recurrent neural network)

15. Google’s Project Magenta includes SketchRNN, in which the
network has “learned” to draw. It is interactive—the user starts
a drawing and the network will finish it
22
What is the most important difference between humans and
artificial intelligence-- what makes us human? Is it thinking?
Learning? Creativity? Emotion? Would it be possible for
machines to achieve this function? How would it be tested? Is
there a good reason to create machines that can perform in this
way? Conversely, is there a reason to prevent this technology?
23
Terence Broad, Blade Runner-Autoencoded
and
Koyaanisqatsi Autoencoded Through Blade Runner
Is this a machine “memory”?
Blade Runner Autoencoded was a research project for Broad’s
dissertation in the Creative Computing program at Goldsmiths.
He trained a type of artificial neural network called an
autoencoder to reconstruct individual frames from Blade
Runner, which he then re-sequenced into a video. The technique
was first proposed in 2015 by Larsen et al at the International
Conference on machine Learning (ICML).
Running Koyaanisqatsi through the nerual net trained on Blade

16. Runner results in a strange merging of the two.
https://arxiv.org/pdf/1512.09300.pdf
24
From Larsen et all, “Autoencoding beyond pixels using a
learned similarity metric,” 2015
Image illustrating an autoencoding process of reconstructing
dataset samples with visual attribute vectors added to latent
representations
25
Terence Broad, Topological Visualization of Convolutional
Neural Network
Open in safari: http://terencebroad.com/convnetvis/vis.html
This is a simplification of the connections between nodes in a
neural network. The algorithm is a “recursive depth first tree
search.” Starting with an input value, the network classifies the
input along each layer. Convolutional networks are what made
the generation of images possible.
26
Trevor Paglen and Kronos Quartet, Sight Machine,2017
Paglan is interested in machine vision and surveillance. These
are images not meant for us, but for computers. He explores the
mechanics and the implications for aesthetics but also their

17. sociological impact.
In Sight Machine, Paglen worked with Obscura Digital to track
the Kronos quartet in real-time with technology sourced from
open source software that runs neural nets. Paglen wanted to
reveal how the networks “see” and process images.
https://www.youtube.com/watch?v=HEI8cuGKiNk
https://www.wired.com/2017/04/unsettling-performance-
showed-world-ais-eyes/
27
Paglen, Machine-Readable Hito, 2017, part of “A Study of
Invisible Images”
https://qz.com/1103545/macarthur-genius-trevor-paglen-
reveals-what-ai-sees-in-the-human-world/
Paglen turns a face-analyzing algorithm on fellow artist Hito
Steyerl. In hundreds of snapshots, she grimaces, laughs, yawns,
shouts, rages, and smiles. Each picture is annotated with the
AI’s earnest guesstimate of Steyerl’s age, gender, and emotional
state. In one instance, she is evaluated as 74% female.
It’s an absurd but simple way to raise a complicated question:
Should computers even attempt to measure existentially
indivisible characteristics like sex, gender, and personality—
and without asking their subject? (Secondarily, what does 100%
female even look like?)
Computers already and increasingly make decisions about you—
which advertisement to serve, whether or not you’ve committed
a prior crime—based on vast banks of training data and image
libraries basically inaccessible to anyone not already literate in

18. machine-vision research. That could soon complicate traditional
ideas of accountability: In the future, humans working with
computer-vision technologies in corporations and law
enforcement agencies may not themselves be capable of tracing
back how an AI made its decision, much less be able to make
that process transparent to consumers and citizens.
28
William Latham, Mutator, 2014
William Latham calls this series of computer animation Organic
Art. He builds generative algorithms based on geometric
patterns in life to create “living” forms
Latham trained as an artist and became a Research Felow at the
IBM UK Scientific Centre
29
2
2
Title of the Report Goes Here in Bold
Student Name
Masters of Accountancy,
ACG6505 Advance Governmental and Fund Accounting
Dr. Dahli Gray, CPA, CMA, CGMA, CFE
Date
Abstract

19. Start your text at the beginning of this line. The abstract should
be one paragraph in length. The abstract must be a brief
statement of the content of the paper or report. It is to be
presented with a phrase such as the following: This paper
presents the … This included the following conclusions and
recommendations … The abstract a very brief summary of your
paper. A reader should know all the key information by reading
the abstract. Details are presented in the paper. Headings and
subheadings help the reader jump to the information of interest
without having to read the entire paper or report. Headings and
subheadings are required.
Keywords: GASB,
Title of Your Paper in Bold
Without a heading called introduction, type your introduction. It
should be like a table of contents, but in sentences. There
should headings and subheadings throughout the report. While
more headings and subheadings reflecting your topic, at a
minimum the following headings should be included:
History
Example Second Level Heading
Example Third Level Heading
Issues Analyzed
Analysis Methods
Analysis Results
Conclusions
Recommendations
Summary
References
Start your references at the beginning of this line. Type “Enter”
only at the end of each source’s entry information: the cursor
will be repositioned correctly to enter your next source. Notice
that each entry is formatted with a hanging indent, meaning the
lines after the first line are indented as you see with these

20. “paragraphs”.
Your second source entry will begin here once you type “Enter”
at the end of the first source. All subsequent entries will begin
at the correct place after you type “Enter”