7COM1084: Advanced Research Topics in Computer Science - Report

This report explores several advanced research topics within computer science, including human-robot interaction (HRI), data science, machine learning, and cloud computing. The HRI section defines the field, its relation to computer science, and discusses research questions and methodologies, particularly focusing on survey methods to assess the negative implications of HRI. The data science segment highlights its relevance to businesses, research methods, and its connection to data mining and big data. The machine learning section covers its relation to computer science and research methods. The cloud computing section discusses its relation to computer science, research questions, and its general relevance. Each section provides an overview of the research area, its relation to computer science, research questions, and general relevance, offering insights into the current state and potential future developments within these fields.

Running head: 7COM1084: ADVANCED RESEARCH TOPICS IN COMPUTER
SCIENCE
7COM1084: ADVANCED RESEARCH TOPICS IN COMPUTER SCIENCE
Name of student
Name of university
Author’s note:

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7COM1084: ADVANCED RESEARCH TOPICS IN COMPUTER SCIENCE
Table of Contents
Human robot interaction................................................................................................2
Research area.............................................................................................................2
Relation to Computer Science....................................................................................3
Research questions and methods................................................................................4
General relevance.......................................................................................................6
Data science...................................................................................................................7
Research area.............................................................................................................7
Relation to Computer Science....................................................................................7
Research questions and methods................................................................................7
General relevance.......................................................................................................9
Machine learning..........................................................................................................10
Research area...........................................................................................................10
Relation to Computer Science..................................................................................11
Research questions and methods..............................................................................11
General relevance.....................................................................................................13
Cloud computing..........................................................................................................14
Research area...........................................................................................................14
Relation to Computer Science..................................................................................14
Research questions and methods..............................................................................14
General relevance.....................................................................................................15
References....................................................................................................................16

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Human robot interaction
Research area
Human robot interaction could be described as the sector of the study that has been
primarily dedicated in understanding, designing, as well as the evaluating the robotic systems
for utilisation by or with the humans (Sheridan 2016). The methods of interaction, by
accurate definition mainly needs efficient communication among the humans as well as the
robots (Cherubini et al. 2016). The methods of communication among the humans as well as
any robot could take place in several forms but these particular forms are mainly influenced
by the decision of the proximity of the human and the robot (Polygerinos et al. 2017).
Therefore, the communication as well as the interaction could be easily separated by into two
major categories:
Proximate interactions: The robots and the humans have been co-located
Remote interaction: The robots as well as the humans are not primarily co-located and
have been separated spatially or even temporarlly.
Dividing the interaction in these two categories, it could be significantly useful in
distinguishing among the applications that needs mainly mobility, physical manipulation or
even any social interaction (Lemaignan et al. 2017). The remote interaction with any mobile
robots frequently could be referred as the teleoperation or the supervisory control as well as
any remote interaction with any physical manipulator that is frequently referred as the
telemanipulation (Admoni and Scassellati 2017). The proximate interaction with the mobile
robots might take main form of the robot assistant, as well as the proximate interaction might
include any physical interaction (Lasota, Fong and Shah 2017).

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Relation to Computer Science
In the present times, it has been observed that the HRI has significantly strong
connections to the previous as well as ongoing works in the sectors of telerobotics, human
computer interaction and the vehicle systems (Haddadin and Croft 2016). The main link that
this sector has it with the telerobotics and teleoperation, automation science and human
factors, air traffic control and aviation, intelligent vehicle systems, human computer
interaction and cybernetics as well as artificial intelligence. The sector of human factors
mainly emerged as confluence of the engineering psychology as well as the accident analysis.
The literature of the human factors mainly produced the crucial concepts of the interaction
like mental workload, situation awareness, trust in the automation and the mental models
(Tsarouchi, Makris and Chryssolouris 2016). It mainly includes various themes, models as
well as the frameworks that offers significantly solid base for appropriately describing as well
as the predicting the responses to the interaction among the human and robots (Kanda and
Ishiguro 2016). The activity analysis and the cognitive models are specifically interesting to
the sector of HRI due to the fact that it could be easily used not solely as the models of any
existing processes, but as the tools for generating behaviours like planning and the
perspective-taking (Thomaz, Hoffman and Cakmak 2016).
The modern aircraft could be observed as the most able semi-autonomous systems
that are presently being used. Mainly because of significant nature of safety critical of the
aviation industry, it is required that the aviation systems are significantly dependable and
robust.
As the sector of HRI is achieving significant growth, it has observed significant
contributions from the researchers from the sector of HCI and it is nurtured by the
organisations of HCI. It has been observed that the HRI research is significantly attractive for

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several members of community due to the distinct challenges that are posed by this particular
field.
Research questions and methods
What are the negative implications of human-robot interaction in the modern times
and future?
The methods that could be used for evaluating the above mentioned research question
is survey. Survey could be defined as the research method that is mainly used to collect
effective data from any pre-defined group of respondents for gaining insights as well as
information on several interesting topics. Survey possesses variety of purposes and could be
easily executed in several methods depending on methodology chosen as well as the
objectives that are required to be achieved. All the data is commonly gained using the method
of standardised processes whose sole intention is ensuring that each of the respondents is
easily able to answer question at level stage for avoiding any biased opinion that might
influence the required outcome of study or the research. Any survey includes inquiring
people for information using questionnaire that could be easily distributed using paper, even
though with the introduction of innovative technology, it has become significantly common
in distributing the question using the digital media like the social networks, QR codes, email
or the URLs.
For conducting the survey for the research question, it is important to create a
questionnaire and then provide it to the common people for sharing their views. The various
advantages and the disadvantages of the human-robot interaction in the modern times could
be listed in the questionnaire and then the common people choose from the various options.
The option that has been chosen by the people frequently could be considered as the
prominent challenge associated with the human-robot interaction. An appropriate sample size

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could be determined to whom the questionnaire could be provided and then the views could
be analysed. The selection of sample size mainly depends on end objective of the research
study. It must comprise of efficient series of respondents of survey data with the needed
demographic features who could accurately answer the survey questions and then provide
their most appropriate insights. For conducting the surveys, there are mostly two types of
sampling methods, which are the probability sampling as well as the non-probability
sampling. Even though sampling could be easily conducted at discretion of researcher, the
main two methods that could be used are:
Non probability sampling: This kind of sampling method could be described as the
sampling method where any researcher chooses appropriate sample of the respondents solely
on basis of their respective discretion.
Probability sampling: This sampling method could be described as the method where
any respondent could be chosen on the basis of the theory of probability. The main feature of
this particular method is that each of the individual in any population has the equivalent
probability of being chosen.
For conducting the survey for the research question of human-robot interaction, the
most appropriate sampling method is the probability sampling. It would provide the equal
chance to the considered population in being chosen for the survey.
Using any survey software for administering the survey research could be considered
as the powerful tool that is used by the market researchers for collecting data. The providers
of advanced survey software offers the survey solutions for several modes of survey research
that includes the paper survey, online survey as well as phone survey. It could be analysed
that the survey methods are significantly effective as it provides the survey team with the
accurate data of various respondents. Surveys could be considered as significantly useful in

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accurately describing the features of any large population. The survey is particularly effective
because no other research method could offer the wide capability that ensures accurate
sample gathering for targeted results that could be used for drawing conclusions as well as
provide crucial decisions.
General relevance
There are several benefits of conducting the research on the sector of human-robot
interaction and valuable data could be gained from this particular investigation. The main
benefits and the challenges of human-robot interaction that are already known to the common
people could be easily verified and then analysis could be done on the challenges so that
mitigation solution could be determined. It has been analysed that the HRI has their roots in
significantly general field of the human-machine interaction and particular field of the
human-computer interaction. In comparison to the conventional applications of the robots in
the industrial settings, where the working of the robots was done in significant isolation from
the human beings and solely the trained operators were permitted to operate the robots, the
service robots is being designed for various applications in various non-industrial settings like
schools, home as well as urban areas. HRL could provide various benefits to the society in
various ways. The assistive as well as healthcare robotics could help in improving quality of
life of elderly or the physically impaired people as the aging population is significantly
growing and there is restricted workforce available for the human health care. Robots could
be helpful in searching as well as the rescuing operations for sparing the valuable lives of the
rescue workers in event of any kind of natural or even man-made disasters. It could be
gathered from the data of the survey that the education sector would be significantly
benefitted from the total rollout of the robotics as the robotic teacher could assist the students
and then provide the enhanced experience of learning for children in any classroom. With the
help of survey in any particular demographic location, the most common views and insights

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of the people regarding the technology could be easily analysed and the effectiveness of the
technology could be determined.
Data science
Research area
As the technology, big data has been introduced in the modern times, the requirement
for the storage capacity increased exponentially. This was considered as the major challenge
as well as issue for enterprise industries (Van Der Aalst 2016). The primary emphasis on the
development of the framework as well as the solutions for storing data. Data science could be
considered as future of the artificial intelligence. Data science could be described as the blend
of the various algorithms, tools as well as the machine learning principles with the sole
intention of discovering the hidden patterns from pile of raw data (McIntosh et al. 2016).
Data science is solely used for making the decisions as well as predictions by the proper use
of the predictive casual analytics, machine learning as well as the prescriptive analytics.
Relation to Computer Science
It could be observed that the data science concept is primarily related to the data
mining as well as big data. Data science is the concept of unifying the statistics, machine
learning as well as the data analysis along with the associated methods for understanding and
analysing any actual phenomenon (George et al. 2016). It uses the techniques as well as
theories that are drawn from several fields within context of statistics, mathematics,
information science and computer science. Various models of mathematics is used by the
data scientists for analysing the pile of raw data that is collected (Wickham and Grolemund
2016).
Research questions and methods
How does data science adds value to the businesses?

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The evaluation method that is used for evaluating this research question is researching
the internet for articles and journals. With the use of internet, appropriate resources could be
evaluated and the answer for this question could be determined. With the evaluation of the
research articles on the internet it has been determined that the aspect of knowledge is power
of any business and huge amount of data is considered as the fuel that is used for creating
power in the business. The ability of harnessing the power of the data using data science is
presently considered significantly valuable.
Appropriate scientific processes, methods, systems and algorithms are presently being
used in the data for extracting knowledge from the data that is collected and then leveraging
the data for taking significantly major decisions and this process is presently considered as
the crucial strategic practice in the businesses. Taking the analytical approach on the basis of
the numbers, statistics as well as facts could provide the reasonable solution that may not be
seemed obvious at the initial stages (Bolyen et al. 2018). Due to the insights provided by the
use of data science, significantly more businesses are using the power of the technology of
data science for making evidence based decisions, promoting efficient employee training as
well as understanding the customers. In several research articles, it has been mentioned that
the data science technology allows significantly improved decision making with the
quantifiable evidence. In majority of the businesses, data required to be present at fingertips
of each of the decision makers of the company (Donoho 2017).
It has been considered as problematic as majority of data collected is unstructured and
requires the predictive analytic tools for gaining appropriate insights on this data. With
extracting appropriate numbers as well as statistics using data science, the business could
create appropriate predictive models for simulating variety of possibilities. In the research
articles, it has also been presented that the relevance of the products of the company could be
improved with the use of data science technology (Agrawal and Choudhary 2016). The

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methodologies of data science could explore the historicals, make effective comparisons to
the competitions, execute the analysis of market and finally generate appropriate suggestions
of the most appropriate markets for selling the products. This kind of consistent analysis as
well as reflection with the use of data science offers significantly deep understanding of the
response of the markets for the services as well as the products of the company (Cao 2017).
By effectively analysis the market where the product of the companies are being used, the
model of the business could be modified for ensuring that the solutions are provided to the
customer.
The research articles present in the internet is also effective in determining the various
troublesome aspects in any business. It has been analysed that the aspect of recruiting has
been considered as troublesome task, but with the introduction of data science, the procedure
could be made to be significantly faster and significantly accurate (Molina-Solana et al.
2017). With the availability of all talent points from the analysis of the social media data, the
corporate databases as well as job companies, the businesses could work extensively through
the data points and then use the analytical models for discovering the appropriate candidates
for the organisations. The recruiting of appropriate staff in the organisation is troublesome
task that is required to be extensively simplified in the organisations. The knowledge as well
as the insights that are gained from the analysis of the data of the business using data could be
used for populating the software of online knowledge base or the software of IT
documentation that mainly holds all the crucial knowledge for the employees.
General relevance
In the present business world, all the data is significantly easily accessible for the
common people. The simple actions such as logging in the social media platforms or even
inputting the private details in the banks as well as the hospitals for the purposes of
compliance could leave various kinds of digital trails. With agreeing to the activity of

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revealing personal data, the right of privacy as well as security is extensively compromised
and the people are significantly susceptible to the data breaches. Majority of the people in the
present world are not aware of the methods by which data is being misused until they are the
victims of some kind of data manipulation or even fraud and theft. While the people could
easily store and access data, the companies commonly analyse the preferences from the
browsing patterns and target the people with specific kinds of advertisements. There is
always the risk of common people to fail at the concepts of data scoring as well as risk
analysis. While the governments are in pursuit of effectively detecting the terrorists, there
might be some situation where they could execute discriminating against the people of any
specific religion or race. Subsequently several innocent lives might fall behind bars. The
major adverse effect of these kinds of stratification cannot be ignored along with the negative
impact of the technology of data science on the innocent people. While the use of data
science is not considered bad, it could have various undesirable effects if people involved in
the use have various kinds of malicious intentions. In the modern times, the data scientists
helps the companies in making several decisions that are primarily data-driven. Moreover, the
data that is used for this process could breach privacy of the customers.
Machine learning
Research area
Machine learning could be considered as sector of study that provides the computers
with ability of learning deprived of being explicitly programmed. The machine learning is
presently considered as the technology that provides the computers with the abilities that
allows similar thinking capability as the humans (Meng et al. 2016). Machine learning could
be described as the application of Artificial intelligence which offers the system with ability
of automatically learn as well as improve from the experience deprived of explicitly
programmed. The machine learning technology mainly emphasises on development of the

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computer programs that could access the data as well as use this data for learning. The main
procedure of learning initiates with various kinds of data or observations like direct
experience, or any kind of instruction for looking for the patterns in available data as well as
making improved decisions in future (Abadi et al. 2016). The main aim of this technology is
allowing the computers in learning automatically deprived of human intervention or even
assistance as well as adjust the actions accordingly.
Relation to Computer Science
In the sector of computer science, the machine learning technology mainly denotes to
kind of data analysis where the algorithms are used who learns from various kinds of data. It
is the kind of artificial intelligence who offers systems with ability of learning deprived of
being programmed (Carrasquilla and Melko 2017). The computer scientists observes machine
learning as the algorithms for executing improved predictions and forecasts. Unlike the
statisticians, the computer scientists are extensively interested in efficiency of majority of
algorithms and frequently blur distinction among model and the methods by which the
models fits. Machine learning has been considered as the black boxes that has the ability of
making predictions. And the use of computer science has major part dominated statistics
when the aspect of making improved predictions is considered. Computer science could be
considered as significantly huge sector and it includes several domains. Machine learning is
presently being implemented using computers and this is the reason why this sector has
managed significant growth over recent times (Witten et al. 2016). Even though there are
major intersections among the sector of computer science and machine learning, it is required
to understand properly the reason behind the introduction of machine learning. The sole
reason of implementation of machine learning is discovering the underlying function or the
hidden relationship among the data with provided observations (Biamonte et al. 2017).