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52 pages including cover
Knowledge Digest for IT Community
50/-
0970-647X
Volume No. 42
41 | Issue No. 2
7 | May
October
20182017
0970-647X
Internet of
ISSN ISSN
SMART CITY Everything (IoE)
Applications
SMART
education
www.csi-india.org
www.csi-india.org
SMART AGRICULTURE
COVER STORY Article
Sensors based Internet of Everything Importance of Sensor Fusion in the
Applications and related issues 8 Internet of Everything (IoE) 21
Technical Trends SECURITY CORNER
An IoE Application: Pattern Discovery for
Smart parking solution 11 Insider Threat Detection 31
RESEARCH FRONT Practitioner Workbench
Pattern recognition in Bioinformatics 13 Efficient Handling of Data Structures using
Python with Minimum Lines of Code 37
Know Your CSI
Executive Committee (2017-18/19)
President Vice President Hon. Secretary
Mr. Sanjay Mohapatra Mr. Gautam Mahapatra Prof. A. K. Nayak
D/204, Kanan Tower, Vailla No: 8, Maithri Enclave, Director, Indian Institute of Business
Patia Square, Bhubaneswar Near Tulsi Gardens, Yapral Kapra, Management, Budh Marg, Patna
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CSI Communications Volume No. 42 • Issue No. 2 • May 2018
Contents
Chief Editor
S S Agrawal
KIIT Group, Gurgaon
Editor Cover Story
Prashant R Nair Sensors based Internet of Everything Applications and related issues 8
Amrita Vishwa Vidyapeetham, Coimbatore Dharmendra Patel & Atul Patel
Published by An IoE Application: Smart parking solution 11
AKSHAYA KUMAR NAYAK C Jagadees
Hony. Secretary
Research Front
For Computer Society of India Pattern recognition in Bioinformatics 13
Sherin K, Suma L S, Vijayalakshmi B, Arya K R and Achuthsankar S Nair
Editorial Board: Person re-identification with content and context re-ranking 18
Arun B Samaddar, NIT, Sikkim Reshma O S & Reshma Sheik
Bhabani Shankar Prasad Mishra,
KIIT University, Bhubanewar
Articles
Importance of Sensor Fusion in the Internet of Everything (IoE) 21
Debajyoti Mukhopadhyay, MIT, Pune Dipesh Vaya & Teena Hadpawat
J Yogapriya, Kongunadu Engg. College, Trichy Medical Internet of Thing (MIoT) for Healthcare using cloud 24
M Sasikumar, CDAC, Mumbai, Sunil Gupta & Shivank Singh
Sensors for Internet of Everything (IOET): Smart Irrigation System 31
R Subburaj, SRM University, Chennai
S Pramila, S Shwetha & S Renganathan
R K Samanta, Siliguri Inst. of Tech., West Bengal
R N Behera, NIC, Bhubaneswar
Security Corner
Pattern Discovery for Insider Threat Detection 31
Sudhakar A M, University of Mysore Ratnik Gandhi, Mehul S. Raval & Sanjay Chaudhary
Sunil Pandey, ITS, Ghaziabad State of Research on User Psychology involved in Phishing Attacks 34
Shailesh K Srivastava, NIC, Patna Aniket Bhadane & Sunil B. Mane
Vishal Mehrotra, TCS Practitioner Workbench
Efficient Handling of Data Structures using Python with Minimum Lines of Code 37
Baisa L Gunjal
Design, Print and Dispatch by
GP Offset Pvt. Ltd.
PLUS
Know Your CSI 2nd Cover
Tech Leader Interview with Dr. Gulshan Rai, National Cyber Security Coordinator, 6
Government of India
After Assam, Nagaland and Sikkim, CSI now at Meghalaya 10
Please note:
CSI Communications is published by Computer
Recognition for CSI Communications Editor 20
Society of India, a non-profit organization. Prospective Contributors of CSI Communications 27
Views and opinions expressed in the CSI
Communications are those of individual Call for Paper - CICBA 2018 23
authors, contributors and advertisers and they
may differ from policies and official statements
A Division-IV Report 40
of CSI. These should not be construed as legal Seminar Report on “Cyber Hygiene and Opportunities in Cyber Security”
or professional advice. The CSI, the publisher,
the editors and the contributors are not CSI Divisional Event First International Conference on “Contemporary 41
responsible for any decisions taken by readers Advances in Innovative and Applicable Information Technology” (ICCAIAIT 2018)
on the basis of these views and opinions.
Although every care is being taken to ensure I.T.S National IT Convention – 2018 – A Report 42
genuineness of the writings in this publication,
CSI Communications does not attest to the
CSI Student Conventions 43
originality of the respective authors’ content. One Week Awareness programme on ICT Standards, Benchmarks and Guidelines 44
© 2012 CSI. All rights reserved. organized at VIT Vellore by CSI Student Branch
Instructors are permitted to photocopy isolated
articles for non-commercial classroom use Chapter Activities News 45
without fee. For any other copying, reprint or
republication, permission must be obtained
Student Branch News 47
in writing from the Society. Copying for other Printed and Published by Akshaya Kumar Nayak on behalf of Computer Society of India, Printed GP Offset Pvt. Ltd.
than personal use or internal reference, or of
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269, 2nd Floor, A-2, Shah & Nahar Indl. Estate, Sitaram Jadhav Marg, Lower Parel, Mumbai 400 013 and Published from
without explicit permission of the Society or Samruddhi Venture Park, Unit No. 3, 4th Floor, Marol Industrial Area, Andheri (East), Mumbai 400 093. • Email : hq@csi-india.org
the copyright owner is strictly prohibited. Editor: Prashant R. Nair
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C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8
Editorial
Dear Fellow CSI Members,
“IoT is transforming the everyday physical objects that surround us into an ecosystem of information that will
enrich our lives. From refrigerators to parking spaces to houses, the IoT is bringing more and more things
into the digital fold every day, which will likely make the IoT a multi-trillion dollar industry in the near future.”
– Pricewaterhouse Coopers report
“The global industrial sector is poised to undergo a fundamental structural change akin to the industrial
revolution as we usher in the IoT. Equipment is becoming more digitized and more connected, establishing
Prof. (Dr.) S. S. Agrawal
Chief Editor
networks between machines, humans, and the Internet, leading to the creation of new ecosystems that enable
higher productivity, better energy efficiency, and higher profitability. While we are still in the nascent stages
of adoption, we believe the IoT opportunity for Industrials could amount to $2 trillion by 2020. The IoT has the
potential to impact everything from new product opportunities, to shop floor optimization, to factory worker
efficiency gains that will power top-line and bottom-line gains”
– Goldman Sachs Report
The theme for the Computer Society of India (CSI) Communications (The Knowledge Digest for IT
Community) May 2018 issue is ‘Applications of Internet of Everything’. We are continuing with the issue on
Sensors for IoE with this applications of IoE feature.
For the benefit of giving our CSI members more time to present their original research and empirical
results, we are extending the announced research theme of CSI Communications May 2018 viz. Digital
Revolution in Speech and Language Processing for Efficient Communication and Sustaining Knowledge
Prof. Prashant R. Nair
Editor Diversity to June 2018 issue
We have 1 cover story which covers the entire gamut of application domains of IoE, “Sensors based Internet
of Everything Applications and related issues” by Dharmendra Patel and Atul Patel
There are 2 research front articles which highlights original research results in Image processing and pattern recognition.
These are
• “Pattern recognition in Bioinformatics” by Sherin K, Suma L S, Vijayalakshmi B, Arya K R and Achuthsankar S Nair.
Achuthsankar S Nair, a distinguished computer science researcher is also a past editor of CSI Communications .
• “Person re-identification with content and context re-ranking” by Reshma O.S and Reshma Sheik.
The technical trends featured is “IoE Sensor Connectivity Technologies - An overview” by C. Jagadees from Oil and Natural Gas
Corporation Limited, Chennai.
We have 3 articles providing us applications of IoE and IoT in healthcare, agriculture and information security domains.
The articles are:
¬¬ “Importance of Sensor Fusion in the Internet of Everything (IoE)” by Dipesh Vaya and Teena Hadpawat
¬¬ “Medical Internet of Thing (MIoT) for Healthcare using cloud’ by Sunil Gupta and Shivank Singh
”Sensors for Internet of Everything; Smart Irrigation System” by S. Pramila, S. Shwetha and S. Ranganathan
The Security Corner contribution is “Pattern Discovery for Insider Threat Detection” by Ratnik Gandhi, Mehul S. Raval and Sanjay
Chaudhary and “State of Research on User Psychology involved in Phishing Attacks” by Aniket Bhadane and Sunil B. Mane
In Practioners Workbench, we have “Efficient Handling of Data Structures using Python with Minimum Lines of Code” by Baisa
L. Gunjal
Both of these sections are reappearing after a gap.
This issue also contains reports of national, regional and state student conventions & CSI activity reports from divisions, chapters
& student branches.
In our Tech Leader interview series in this issue, we are very proud to present an interview of Dr. Gulshan Rai, National Cyber
Security Coordinator, Government of India. In this interview, he nicely outlined what professional societies like CSI as well as
academic institutions, who are our institutional members and student branches can contribute towards promoting cyber security
through skilling, research and innovation
We seek the support of all CSI members for suggestions and support for this next exciting section of CSI Communications.
We are thankful to entire ExecCom for their continuous support in bringing this issue successfully.
We wish to express our sincere gratitude to the CSI publications committee, editorial board, authors and reviewers for their
contributions and support to this issue.
We look forward to receive constructive feedback and suggestions from our esteemed members and readers at csic@csi-india.
org.
With kind regards,
Prof. (Dr.) S. S. Agrawal Prof. Prashant R. Nair
Chief Editor Editor
www.csi-india.org
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C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8
Computer Society of India
TM
http://www.csi-india.org
Mr. Sanjay Mohapatra Shri.Gautam Mahapatra Prof. A. K. Nayak Mr. Manas Ranjan Pattnaik Dr Anirban Basu
President Vice President Hon. Secretary Hon. Treasurer Immd. Past President
President’s Message
From : President, Computer Society of India
Date : 01 May, 2018
Email : president@csi-india.org / Cell : (91) 9861010656
CSI Incubation Centre
As you are aware, the launch of the CSI Incubation Centre is a great milestone for CSI in the spirit of the national mission, “Start-
up India”. I take this opportunity to call upon all CSI members, both professional and students or graduates who are venturing
into the start-up space to make use of this facility. Our diverse talent of CSI fellows and senior members will also be available for
guidance and mentoring of start-ups in this facility. I request for the support of all CSI fellows, past presidents, office bearers,
executive committee members, chapter & student branch office bearers to support his centre with your expertise, contacts and
support.
CSI General Body Meeting
CSI General Body meeting and Special AGM will be held on 20th May, 2018 at India Islamic Cultural Centre, New Delhi. Along with
regular agenda issues such as administrative and financial matters, we will be taking a decision on the CSI National elections and
the calendar for the same. I look forward to the participation of each of one of you to strengthen CSI.
CSI Tech Leader Interview with Dr. Gulshan Rai
Cyber security is becoming a huge concern in India in the wake of NSA snooping, worldwide company hacks and government
websites including Supreme Court, various ministries etc. CSI is privileged to publish an interview of Dr. Gulshan Rai, National
Cyber Security Coordinator of India in this issue of CSI Communications. Here, he has nicely outlined what professional societies
like CSI as well as academic institutions, who are our institutional members and student branches can contribute towards
promoting cyber security through skilling, research and innovation.
Divisional Events
It is heartening to note the organizing of various high quality divisional events of CSI. First International Conference on
“Contemporary Advances in Innovative and Applicable Information Technology” (ICCAIAIT 2018) at Kingston Educational Institute,
Kolkata in collaboration CSI Division IV (Communication) and national level Seminar on “Cyber Hygiene and Opportunities in
Cyber Security” organized by CSI Division IV (Communication) along with CSI-Vijayawada & Koneru Chapters at 4 institutions and
universities in the region.
Student Conventions
CSI Student branch activities and initiatives are at a record high. We have had maximum number of CSI Student Conventions.
CSI National Student Convention, Regional Student Conventions in regions 2 and State Student Convention at Telangana have
been recently conducted with funding from CSI HQ and active participation from CSI student members and high quality technical
contests and competitions.
Please write your valuable ideas for growth of CSI at president@csi-india.org
With kind regards
Sanjay Mohapatra
President, CSI
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C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8
Interview
Tech Leader Interview with
Dr. Gulshan Rai, National Cyber Security
Coordinator, Government of India
Q :
As the national cyber security coordinator, what are
the agenda items for the country as such? The major
initiatives so as to speak?
A :
My objective is to enable secure cyber transactions
so that we achieve the overall objective, i.e., the vision
of the Honourable Prime Minister of India. Now, in that
overall vision, my role is to coordinate among different
departments, different ministries, and different sections
of the society so that there’s a synergy and we achieve the
objective set forward by the prime minister.
Q : We’ve been hearing about this national cyber security
policy and I’m told its been reviewed adding the data
privacy aspects and so on. Sir, Is there something on the
Cyber security is becoming a huge concern in India. In the anvil?
wake of NSA snooping and worldwide company hacks, the A : The policy is being reviewed from time to time and it’s a
Indian government has been actively trying for Internet dynamic and regular affair to review the policy and there’s
sovereignty where local Internet traffic remains on servers a intention to bring forward a revised, upgraded policy.
hosted within the country. In the wake of increasing cyber Also, to address the emerging issues of the technology
threats in India, the Narendra Modi government has challenge is also there. Areas like AI, Machine Learning,
appointed Dr. Gulshan Rai, a cyber security expert who has IoT different aspects of these technologies are applicable
over 30 years of experience in different areas of Information to different areas. These apply to many sectors like the IT
Technology as the special secretary for the department in the sector, telecom, critical sector etc. We need to look at it
Prime Minister’s Office. He is designated as Chief Information and we are looking at it.
Security Officer (CISO) performing the role of National Cyber
Q :
That means, every year there are periodic updates
Security Coordinator of the Government of India. Prior to
happening to the policy?
this, he was the director-general of the Indian Computer
Emergency Response Team (Cert-In) and Group Coordinator A : We cannot change a policy by responding to every change
of E-Security and Cyber Law Division in the Ministry of in technology. Policy is a long term affair. As long as
Communications and Information Technology. He has led the an attempt is always there, policy should be agnostic.
team to set up National Watch and Alert System in the country It should be wide enough to be made applicable. And
as part of cyber security initiative and Computer Emergency it is high time that the gaps in the policy addresses the
Team. Several international cooperation agreements have emerging challenges that needs to be reviewed and then
been entered under his leadership. He led a team from the updating of the policy, wherever possible, can address
time to time to draft and bring out National Policies in the these challenges.
area of cyber security and cyber law. Prior to this, he was Q : So, that’s what is expected this year, the change in policy?
executive director of autonomous scientific society, ERNET
India for over seven years, and was instrumental in setting A : The process is on, and I don’t know how much time it will
up of the first large scale education and research network take but certainly the review shouldn’t take much longer.
in the country. Rai has been working since 1998 in the area Q :
What do you think, considering so many issues like
of evolving legal framework to address issues arising out of cyber-crime and cyber terrorism and all. What do you
cyberspace, which resulted in second Technology Legislation think universities and professional societies like CSI can
in the country i.e. Information Technology Act and recent do? I have heard you often say to universities that their
amendments in the Act. cyber security research should address national issues.
Can you throw us some light on that?
Here are excerpts from the interview with Dr. Gulshan
Rai with Prof. Prashant R. Nair, Editor, CSI Communications A : You see, universities play a crucial role. In the sense
and Vice-Chairman, Department of Computer Science & that, the whole cyber part, I’m not talking about cyber
Engineering, Amrita Vishwa Vidyapeetham, Coimbatore security since it includes that. Whole cyber security
www.csi-india.org
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C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8
I N T E R V I E W
has multi-stake holders. They are all different stake
holders there. Today, it not possible to have a structure
or a system which gets into a vertical kind of a double
partnership. A partnership should be there between
industry, academia and the government. These are very
important. So it’s a multi-stake holder, even in the civil
societies. And, in an organisation like computer societies
like Computer Society of India (CSI), it’s very clear. See,
there are different organisations. Computer Society
of India is a very old organization. CSI’s job was to look
after the interest of civil society after the NGOs. You also
are a stake holder in the entire process and every stake
holder has a role to play there. So, academia is a very
powerful kind of a stake holder where they do the capacity
development. They bring the basic foundation; they help
in skilling and educating the people to handle these there. And, CERT, at one point of time was considered a
things. You and I can use skills if we have a good basic contemporary with other CERTs worldwide, including the
foundation. Academia provides that basic foundation. one in the US. So, it was a collective effort, it wasn’t mine
Then of course there’s upgrading your skill set. There’s alone. My colleagues at CERT cooperated with me and
M.Tech, B.Tech, diploma and other programmes. So, each one of them was fantastic person. I used to spend
academia is very important aspect. They can play a role almost ` 2 crore per annum to equip them with their
in the capacity development. They can create courses skills. It was a collective effort of all my colleagues, I was
dynamically to address the challenges which the industry simply facilitating them. It was indeed a good job and we
and the government are facing. A student coming out are all very proud of CERT. We are also very proud that IT
of a university needs to be seasoned out to address the Act was the second technology legislation. So, I’m proud
issues in the industry and the society in all areas – policy, to be a part of it. We started writing it at 1998 and we
maintenance, R&D, diplomacy, legal etc. Academia can brought out the act in 2000 and we were the 12th nation to
play a major role in developing technology and developing do so. There was also an amendment 10 years back. All
short term solutions. We don’t need any large solutions. those issues and concerns that were there then are still
Any solution has many components; they’re all built on valid. And people who are there currently, they are also
components. If anyone requires a proof of concept, then
building it up in the same spirit in which it was created.
academia is the best place to proof your concept. Societies
So yes, I do feel very happy and proud to be associated
like CSI can play an important role in the skilling aspect
with these key projects. Apart from that, I was associated
of capacity-building.
with almost every common computerization projects like
Q : I’ve heard a lot about CERT-in, and how you built it brick income tax, PAN etc. That’s why I say that my luck, or
by brick. rather my fate that I never enjoyed a finished work.
A : I built ERNET and many other things too brick by brick. Q : On a lighter note, I’m told you don’t use WhatsApp or
The position I’m in, that also started out brick by brick. Internet banking?
(laughs) I don’t know, I think it’s my bad luck that
wherever I go, my job starts by building brick-by-brick. I A : No no, what I said was that I don’t use international
never got to enjoy a built house. I’ve struggled in my life internet banking. I was misquoted by a Times of India
and I believe that this luck came with me when I came to reporter. If you read the second paragraph in that
this world. interview, I would’ve said that I use a debit card. I do use
Q : Regarding CERT-in, there was something pertaining to debit card for transactions, but I don’t use international
android where there was some vulnerability that was debit cards, because who knows who is internationally
brought out? Is there any major thing that you’re proud of capturing the data and that’s why I don’t use it.
during your time at CERT-in? I don’t use WhatsApp or other social media either, but I
A : First of all, I’m really proud that we were able to lay the do carry out net banking. Today, it’s not possible without
foundation of the emergency response team. That itself net banking. I pay my mobile bills on the net. I also
is a major achievement and it is sustaining by itself encourage people to do so.
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COVER STORY
Sensors based Internet of Everything
Applications and related issues
Dharmendra Patel Atul Patel
Associate Professor at CHARUSAT, Changa Dean and Professor of Faculty of CS and Applications at CHARUSAT, Changa
I. Introduction (Table-1 Key Sensors for Internet of Everything)
Internet of Everything is the popular
Sr. Sensor Subcategories of Sensors Internet of Everything Domains
expression in the industry. It re-imagine
No.
the businesses at three principle
levels : know as PMM implies Process, 1. Temperature Infrared Sensors Manufacturing Processes
Model and Moment. As organizations Semiconductor Health Care
digitalize items and process, totally Thermistors Agriculture
better approaches for working together RTD
in ventures rise. More transformational 2. Pressure Barometer Manufacturing Processes
changes as digitalization re-concocts Pressure gauges Weather Forecasting
enterprises at the plan of action level. Water System
The third level of digital re-imagine Heating System
is made by the need to contend with
unprecedented business speed and 3. Proximity Inductive Retail Industry
dexterity. Millions of new objects and Capacitive Vehicle Industry
sensors play an essential part in Photoelectric Parking System
Internet of Everything that is in charge Ultrasonic Airport
of generating real time data. 4. Gas Gas Detector Manufacturing Processes
Industries have been utilizing Oxygen Sensor Health Care
a different sort of sensors for quite Hydrogen Sensor Agriculture
a while, however the concoct of the Breathalyzer
Internet of Everything has taken part of Air pollution sensor
sensors and developments of sensors
to a totally unique level. Applications 5. Smoke Optical Smoke Sensor Infrastructure
of Internet of Everything combine a Ionization Smoke Sensor Manufacturing
set of sensors and a communication 6. Infrared IR Sensor Smart Devices
network in such a way that the devices Home Appliances
become smarter and share information Health Care
with one another and enhance their
7. Optical Fiber Optic Sensor Health Care
functionalities. Table-1 describes the
Digital Camera
key sensors and their characteristics in
Industrial Automation
the context to Internet of Everything.
Environment
II. Sensors based Smart IOET
8. Level Point Level Fuel Industry
Applications
Continuous Recycling Industry
IOET platforms function and
Alcohol Industry
deliver various kinds of intelligence and
Medical Equipment
data using a variety of sensors. Sensors
collect the data and share them with a 9. Image CCD Digital Camera
whole network of connected devices. CMOS Medical Imaging
The devices function autonomously Radar
due to such platform and become IRIS Device
smarter. There are various IOET based Biometric Device
applications exist in the different 10. Gyroscope Rotary Navigation
ventures that broadly utilize sensors Vibrating Structure Game Controller
and carry on shrewdly. Here we will Optical Cellular and camera device
examine few intriguing and promising MEMS Robotics Control
sensors based keen IOET applications. Drone
1) Smart e-Health Gateway: This
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C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8
COVER STORY
application utilizes sensor hubs, The most common use cases of of any IOET application. Sensors are
remote server and clients that this application are optimizing extremely valuable for gathering
offer more elevated amount operations, enhancing public safety, the continuous information and
administrations, such as local increasing employee productivity, causes an application to go about
storage,real time local data and improving maintenance. as a keen way. However, numerous
processing and embedded data issues are there in sensor in setting
5) Internet of Robotics Things (IoRT):
mining. Empowered by Internet of to IOET applications that should be
The application broadly utilizes
Everything based advancements, delivered in a successful way.
the equipments , for example,
all the entities of health care
robots, sensors, advanced cell, • False Messages: If the sensor
an be monitored and managed is inadequately designed or
vehicles and so forth. Sensors
ceaselessly. It needs repository to hacked may produce false
are the primary segment of an
store sensor and client information. messages to the clients.
application. An assortment of
A few information mining methods
modern sensors is utilized as a • Sensor Interoperability:
like information fusion,aggregation Assortment of sensors is
part of the framework for various
and interpretations are expected utilized as a part of the IOET
functionalities. Primary utilization
to improve the sensor information application so the likelihood
of IoRT is industry automation.
and to produce a constant effective an application may not adjust
yield in view of applying intelligence 6) Smart Mobile Gaming: Present to the information from an
for this information. day advanced mobile phone assortment of sensors.
involves sensors, accelerometers • Security challenges of
2)
S mart Weather Station: The
and a camera. Versatile gaming wireless sensors: Sensors
application gives climate data in
application broadly utilizes these impart secret information to
our neighboring condition.
enhancements for dissecting and the associated gadgets. It is
There are different kinds of following the correct information. plausible that the hacker may
sensors are required in such The sensors catch the outward hack this information
application that detects the appearances, nonverbal signals • The power problem with
genuine circumstances, for and discourse of the player. Savvy sensors: Sensors require
example, temperature,pressure, versatile gaming measures the power for working and that
humidity,light intensity, rain value satisfaction level of the player by is the principle leap for IOET
and so forth. Whenever these utilizing Internet of Everything. application.
values exceed a chosen threshold • Data Transmission issue:
7) Smart Farming: The applications
limit for each an SMS, an E-mail Sensors may collect lots of
in this class comprise of various
and a Tweet post are published data and transmit them with
sensors, associated gadgets and
alerting the owner of the appliance originality is the real issue in
cultivating offices. Sensors assume
to take the necessary measures. IOET application.
a key part in this. Sensors gather
3) Smart Home Automation: The the information from genuine • Breaks in Communications:
application comprises of a server circumstances and help in a Sometimes interrupts are
and different classifications of few routes, for example, remote utilized as a part of the
sensors. Server controls and harvest checking, determining of sensor based application for
monitors the various sensors, and product, atmosphere observing, estimation and that may cause
can be easily configured to deal with livestock following and so forth. the break in communication.
an extensive number of sensors.
8) Intelligent Drones: The uses III. CONCLUSION
The system can be accessed from
of this class basically subject to The Internet of Everything (IoET) is
anywhere using a browser or any
sensors, reception apparatuses an idea that intends to take a gander at
handheld device having internet
and implanted programming to the master plan in which the Internet
connectivity. The system makes an
give two-route correspondences of Things fits. While the Internet of
alarm in view of the circumstance
to remote control and checking. Things today, for the most part draws
of the different sensors.
Movement sensors gather the closer from the point of view of their
4) Intelligent Video Analytics : The data about genuine situations. The detecting capacities. In this article we
application utilizes machine fundamental utilizations of savvy have portrayed the primary classes
learning algorithms to video feeds, Drones are military observation, of sensors with their subtypes and
enabling cameras to perceive distribute to the client’s doorstep their application spaces in Internet of
individuals, objects, and situations and debacle reconnaissance and Everything (IoET). We have portrayed
automatically. Vision sensors with help. a few promising applications where
video ability are the fundamental sensors are to be utilized widely. Finally,
9) Issues of Sensors in IOET
segment of the system. Vision we have talked about issues of sensors
Environment
sensors with video capability are in IOET condition. We concluded
the main component of the system. Sensors are the fundamental piece
Contd. on pg. 10
9
C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8
COVER STORY
After Assam, Nagaland and Sikkim, CSI now at Meghalaya
Inauguration of CSI Student Branch at
NIT Meghalaya, Shillong
The student branch at National Institute of Technology, Meghalaya was
inaugurated on 27 April, 2018 at the NIT Meghalaya’s Shillong campus. The
inauguration ceremony was well attended by the new CSI student members
as well as incumbent CSI members and also attracted faculty participation.
The ceremony was Inaugurated by Prof. A. K. Nayak, Honorary Secretary, CSI.
Prof. D. P. Sinha, Regional Vice President, Region 2 and Mr. Manas Pattnaik,
Treasurer, CSI also graced the occasion. Prof. Nayak emphasized on the need
of professional memberships for students in professional courses like B. Tech
and M. Tech. He also provided the comprehensive list of facilities that student
members can be entitled by means of their CSI memberships. Prof. Sinha
detailed the historical significance of CSI in pioneering computer education
and training in India with a brief
historical perspective and its present-day relevance. Mr. Manas Patnaik ,the
treasurer of CSI advised the students for the upgradetion of their professional
capabilities through the professional Societies like CSI
The session was very interactive with queries and clarifications sought by the
student branch members that were patiently addressed by the dignitaries.
Different Competitions & contests were organised among the students for
which the awards were distributed on this occasion. At the beginning the
Welcome address was delivered by Dr. Diptendu Sinha Roy, Head Dept., of
Computer Science & engineering. & the ceremony concluded with a vote of
thanks by Dr. Alok Chakrabarty, the Student Branch Councellor, NIT Meghalaya.
Contd. from pg. 9
that IOET applications are required IEEE Consumer Communications and [4] https://www.finoit.com/blog/top-15-
in all spaces and if sensor issues Networking Conference (CCNC),At: sensor-types-used-iot/
address legitimately we can plan IOET USA,Volume: 826-834. [5] http://ieeexplore.ieee.org/
[2] Partha Pratim Ray, “Internet of Robotic document/7988038/
applications successfully.
Things: Concept, Technologies, and [6] https://www.electronicshub.org/iot-
References Challenges”, IEEE Translations and project-ideas/
[1] Amir M. Rahmani et.al “Smart e-Health content mining,2017. [7] http://readwrite.com/2016/07/22/
Gateway: Bringing Intelligence to [3] http://www.softwebsolutions.com/ cameras-smart-intelligent-dt2/
Internet-of-Things Based Ubiquitous re s o u rce s / 7 - m u s t - h a v e - s e n s o r-
Health Care Systems”, 12th Annual solutions-for-iot-implementation.html
About the Authors
Dr. Dhrmendra Patel (membership No. 2060000012) received his Master of Computer Application degree from North Gujrat
University. He received his Ph.D degree in computer science from Kadi Sarva Viswavidyalaya. His area of research is Web
Mining, Fog Computing, Image Processing, Interenet of Things etc. He has published 20 papers in national/international
journal of repute. Currently he is working as an associate professor at CHARUSAT, Changa.
Dr. Atul Patel (Life Membership No. 00114194) is working as a Dean and Professor of Faculty of Computer Science and
Applications at CHARUSAT,Changa. He received his Ph.D Degree in computer science from Sardar Patel University. His
area of research is Wireless Communications, Network Security, Cloud Computing, Internet of Things etc. He has published
more than 30 research papers in national/international journal of repute.
www.csi-india.org
10
C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8Technical Trends
An IoE Application: Smart parking solution
C Jagadees
Oil and Natural Gas Corporation Limited, Chennai
Introduction
Internet of Everything (IoE) can be described as the Internet of Everything, moisture levels also could be detected.
defined as the intelligent connection of is what makes smart parking possible. Data collected by the sensor is sent to the
people, process, data and things. This Smart Parking involves the use gateway using any IoE communication
is a concept that extends the Internet of of low cost sensors, real-time data technology. The data is then aggregated
Things (IoT) based machine- to-machine and applications that allow users to and is sent to the Datacentre through
(M2M) communications to describe monitor available and unavailable the internet, where it is analyzed
a more complex system that also parking spots. The goal is to automate using applications. The information is
encompasses people and processes and decrease time spent manually relayed to the traffic control centre for
yielding smart solutions to people. searching for the optimal parking floor, monitoring and control. The information
This paper looks into the aspect of how spot and even lot. Some solutions will is made available to users with web-
IoE concept could be implemented encompass a complete suite of services based applications, so that they can
in the case of smart parking solution such as online payments, parking time select the parking slot without wasting
in an urban scenario. This makes notifications and even car searching much time.
sense when India has jumped into the functionalities for very large lots. There is human to machine
bandwagon of creating 100 smart cities. interaction here, which is the basis
People in cities waste a lot of time in Parking solution of IoE. Somebody looking for a free
getting a parking slot. In addition to In a typical urban scenario, the city parking slot in a particular zone may
waste of time, other side effects of is divided into Zones (Fig-1) and the open the application, search the area
this are increased fuel consumption, parking slots in each Zone are marked. and check the availability of free parking
more green gas release, productivity Smart sensors are placed in each slot. Using the integration of parking
loss, wastage of money etc. This smart parking slot and a group of such sensors solution with Global positioning System,
parking solution would help the people shall be connecting to the nearest the person can navigate the vehicle to
to identify, locate and pre-book parking gateway, which is the aggregation the desired location. Once the parking
slots as per their requirement. Others point for that zone. A typical solution slot is allocated, it would be shown as
on the move can also get to know is shown in Fig-2. The sensor is placed allocated. Once the slot is occupied,
about the nearest parking lot available below the road level and it shall sense the status is shown as occupied and
through this application. The ability to the presence or absence of vehicle in the billing starts as per the rate chart
connect, analyze and automate data that parking slot. Additional information built into the system. Once the person
gathered from devices, powered by and like temperature, noise, visibility and leaves the parking slot, his billing stops
CHENNAI
Datacentre
User
Internet
Traffic control
Sensor Gateway
Fig. 1 : Area demarcation Fig. 2 : Typical smart parking solution
11
C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8Technical Trends
Conclusion
iii) Sensor in
parking slot This IoE based parking
solution offers many benefits like
i) Sensor optimized parking, reduced traffic,
iv) A sample parking area
reduced pollution, enhanced user
experience, new revenue streams,
integrated payments, increased
safety, real-time data and trend
insight, decreased management
Sensors ii) Sensor costs and increased service and
placement brand image. The solution can be
Fig. 4 : Sensor placement made more futuristic by adding
more intelligence and smartness
and the app will pop up the payment monitoring, control and regulation. into the application for a better user
invoice for online payment or may get Each Zone can also be provided with experience. Main issue at present
the payment deducted from the users panels displaying the parking status is the lack of standardisation of
connected e-wallet. and the availability of free slots. A different sensors, which makes
The data could also be used polling frequency is configured as per
compatibility a problem. However,
by the traffic control department to the requirement. A sample frequency is
standardisation agencies and
monitor the traffic conditions, vehicular five minutes, for data updation. These
movements, parking violations, parking sensors could also be integrated with research bodies are working
regulations, redirecting the traffic the Global Positioning System to get on this matter. India has a long
during some specific events etc. accurate location of the parking slot way to go to make these things
Sensors and placement and for navigating to the location. available with Indian technologies.
In a particular Zone, the sensors Connectivity The software and hardware
are buried under the surface of the Sensor to gateway connectivity technologists, technical bodies,
road inside a waterproof casing at every is based on Low Power Wide Area companies and governments
parking slot. A typical scenario is shown Network (LPWAN) technology, which should come together to develop
at Fig-3. One type of sensor is the is designed for low-power, long range Indian technology solutions for
Magnetic field sensor, fitted with smart wireless communication. They are ideal Internet of Things, which is the next
parking sensor board. These sensors for use within large scale deployments
big thing happening now along with
detect the variation of the magnetic of low power IoE devices like wireless
blockchain technology.
field generated by a car parked on it. sensors. LPWAN technologies
A sample sensor is depicted in Fig- include LoRaWAN (Long Range WAN), References
4(i). Placement of sensor below the Haystack, SigFox, LTE-M (Long Term [1] https://iot.ieee.org
surface is shown in Fig-4(ii). A typical Evolution for Machines) and NB-IoT [2] https://www.iotforall.com
[3] https://www.gsma.com/iot/smart-
installation is given in Fig-4(iii). Fig-4(iv) (Narrow Band-IoT). These technologies
cities/smart-parking/
shows a typical parking area provided help to transmit and receive data from [4] www.ijsrp.org/research-paper-1215/
with the sensors. the sensor assembly with low data ijsrp-p4898.pd
The information from the sensors rates, over a long distance using very [5] https://www.sciencedirect.com/science
is relayed to the gateway and in turn is less power. This will help the sensor [6] https://electronicsofthings.com/expert-
sent to the Datacentre. The information to function for a long time, without any opinion/smart-city-solutions-smart-
is then made available to citizens battery replacement. The selection of parking-lots
through their access devices connected the sensor connectivity would depend [7] https://www.researchgate.
net/303842610_IoT_based_Smart_
to the internet using an application. on the range required, number of
Parking_System
The traffic authorities are also provided sensors, number of gateways, data n
with the complete information for traffic size and power available.
About the Author
Mr. C Jagadees (CSI Membership No. 00003986) is a 1982 batch graduate engineer with 36 years of professional
experience in many areas in electronics, instrumentation, communications and IT. He is a lifetime member
of CSI and a Senior member of IEEE. He has written many papers and presented them in various forums. He
is presently looking after the IT requirements of Oil and Natural Gas Corporation Limited (ONGC) at Chennai.
www.csi-india.org
12
C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8R esearch front
Pattern recognition in Bioinformatics
Sherin K*, Suma L S, Vijayalakshmi B, Arya K R and Achuthsankar S Nair
Dept. of Computational Biology and Bioinformatics, University of Kerala
*Corresponding author: E-mail: sherin.cbi@gmail.com
In view of fact that biological data is a huge information resource from which useful knowledge need
to be extracted, pattern recognition gains its significance. Recognizing different patterns from data,
analyzing and interpreting it, is a real challenge to life science researchers and bioinformatics comes
handy with various tools and techniques. Pattern recognition technique reveals molecular and cellular
processes that can enable better understanding of life processes. This article gives an overview on the
steps involved in pattern recognition, tools and techniques used frequently and its application in the field
of bioinformatics.
Introduction
Pattern recognition is one of the microarray data, phylogenetic studies, can be parametric where in the data
key strategies by which brain performs clinical data and drug discovery. is summarised by a set of parameters
analogical reasoning of many life Biomolecules (DNA, RNA, proteins) or can be non-parametric. Linear
problems based on the information in sequence form and structural form discriminant analysis, a parametric
accumulated through its sense contain different patterns that are classification algorithm is used in
organs. In a general perspective, functionally relevant. These patterns testing the significance of gene pathway
pattern recognition involves receiving also known as motifs are very much and gene network models [5].
an input data, analysing it for similar, involved in the characterization of these Classification and Clustering
specific, regular patterns based on biomolecules. In proteins, patterns Classification assigns instances to
which meaningful interpretation is may also occur for the elements found predefined classes based on features.
made. Pattern recognition can be in secondary structure. Helix turn helix It analyses and learns association
employed to make computers execute is a widely studied motif that falls in between the features from the training
tasks like humans, even faster and the category of DNA binding motifs data to classify the unknown variables.
more accurately, by figuring out [2]. Recent studies in drug discovery
actual problems and using a set of The common classification technique,
show that proline rich linear motifs are decision tree, divides the search space
mathematical, statistical, heuristic and excellent mediators for intermolecular
inductive techniques to find solutions into subsets using divide and conquer
interactions seen in many faces of technique. Linear regression is a
[1]. When a computer program is immune response activities, and hence
trained to learn the pattern and simple classification method wherein
these motifs are considered as drug relationship between observed variables
categorize the data, then it is machine targets in immune mediated diseases
learning or machine intelligence. are modeled [6].
[3]. Alignment method, local search, The input data are categorized into
Solutions based on pattern recognition heuristic approach are a few among
may be employed almost everywhere training data and test data. Training
the applied techniques for this pattern data comprises of representative
and anywhere - medicine, health and
identification task. In the field of medical data from a known category and the
pharma industry, agriculture, financial
science, pattern recognition is the basis test data is unknown data. A feature
markets, forensic investigations.
for computer-aided diagnosis (CAD) extractor is used to extract features
During the last few decades, enormous
systems that describe a procedure that from input data. Features are the
amount of biological data in different
supports the doctor’s interpretations parameters or explanatory variables
formats has been generated using
and findings [4]. Detection of patterns most relevant to the problem extracted
advanced technologies. Moreover,
demands computational techniques from observations. It can be either
more databases are also added by
that produce optimum results. categorical, ordinal, integer or real
researchers, which accumulate huge
molecular data. Consequently, demand Pattern Recognition valued and is represented as a vector.
for new computational techniques is Pattern recognition is the process When applied in bioinformatics the vector
also increased for better processing of of efficiently detecting any patterns or consist of frequency of nucleotides such
this data. regularities in the given data. Clustering as A, T, G, C or its 2-mer, 3-mer etc.
Pattern recognition plays key role is an example of unsupervised Dimensionality reduction techniques
in interpreting varied data related to machine learning while classification are implemented to reduce the number
sequence and structure of biomolecules, is supervised learning. The processes of features. Feature selection is
13
C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8R esearch front
another pre- processing methods used of cluster is reached. The instances (NMF) are two major methods coming
to filter features to remove unwanted are assigned to each cluster with under this category.
and redundant data and include most lower Eucledian distance among the Non negative Matrix Factorization
relevant or quality data to produce elements in the same group. The mean is another technique that reduces data
reliable output. A trainer/classifier, of each cluster is calculated iteratively dimension by generating matrix factors
implements any of the clustering or and each instance is assigned to the of lower dimensions. Moreover, these
classification algorithm and maps input cluster with lower distance between lower dimension matrices must satisfy
to the corresponding class. the instance and the mean. Nearest non negativity constraints. Hence NMF
Binary classifiers are used in neighbour, Squared error, PAM, BIRCH is applied for applications where the
predictive models in computational etc are other partitional clustering data can be encoded into non negative
biology. Often prediction may lead techniques[8]. values. The algorithm selects a cost
to identifying normal or diseased Dimensionality Reduction function that reflects the distance
condition. There are several evaluation Enormous amount of gene between the given input matrix and the
measures to analyse these classifiers expression data is available from product of factors. Then update rules
and the measures are obtained from Microarray data analysis. The are applied iteratively so as to minimize
states of output (whether true os false generated data is converted into real this distance.
case) plotted in a contingency table. valued numbers after a series of pre- The amazing power of NMF is
The true predictions of each condition processing steps and stored in a matrix. revealed with mining of biclusters from
is denoted as true positives and true Here, each row corresponds to the gene microarray data. As the microarray data
negatives and false predictions are selected for experiment and column contains expression values of genes in
denoted as false positives and false corresponds to the sample taken for various conditions/samples, similar
negatives. The evaluation measures experiment or a given condition. This genes may not be coexpressed in all
such as sensitivity, specificity and set is of high dimension as it contains experimental conditions or samples.
accuracy are commonly used [7]. expression values of thousands of genes Instead, these co-expressed genes may
The clustering algorithm is an and very challenging to extract useful exhibit similar expression patterns only
exploratory data analysis technique information from this input by reducing in a subset of conditions. In this context,
which groups similar instances on the its dimension without losing any conventional clustering algorithms may
basis of similarities and learns from the information. The principle of dimension fail to extract these biclusters because
grouping rather than from a training reduction is to store data in compressed clustering is to be performed on genes
set. Here no apriori knowledge is form as smaller size vectors and then as well as conditions simultaneously.
available about classes or members. reconstruct the original dataset with This requirement leads to the
Number, size, shape, density absolute minimum error[9]. development of biclustering techniques
and relative position of the clusters are Principal Component analysis and NMF and its variations proved that
all determined by clustering. (PCA) is a popular technique used in a it can reveal the inherent patterns in the
Clustering algorithms are broadly number of problems. Here data set with microarray data[10].
classified into hierarchical and p variables are reduced to a smaller set Feature selection
partitioning algorithms. Hierarchical with k variables without losing relevant Feature selection increases the
clustering builds cluster by merging information. This is facilitated by accuracy of prediction since the features
together or dividing them in various choosing principal components or axes which contribute in decision making
steps and is named respectively that are linear combination of original p is selected for classification. Feature
as agglomerative and divisive. In variables. PCA has been successfully selection reduces complexity and over
agglomerative clustering each applied on gene expression data where fitting and makes the interpretation of
observation starts on its own and the principal components are referred model easier. The selection methods
iteratively merges all clusters till it to as expression vectors or eigen genes. can be filter, wrapper or embedded.
reaches single cluster. It is built in These eigen genes are viewed as major Filter methods is independent of the
a bottom-up approach. In divisive patterns or clusters in the expression classification method used and score
clustering all instances are taken as data. As the number of expression the data depending on its relevance
a single cluster and it is divided to vectors increases, the accuracy of using statistical test based on the
clusters with instances having minimum representation also increases. But, correlation with the output. Examples
distance between them. Hierarchical we must keep an optimum number are chi-square test and correlation
clustering is represented with a tree or of such eigen genes so that the noise coefficient. Wrapper method finds the
dendogram. In partitional clustering, is eliminated sufficiently. Feature best subset based on performance by
clustering is done iteratively and the transformation approach for dimension choosing different combination and
number of clusters required has to be reduction transforms or projects data then comparing and evaluating with
provided beforehand. Considering onto smaller feature space rather than other combination. Embedded methods
K-means clustering, K is the number of eliminating the unwanted features. do feature selection along with the
clusters required and the instances are Singular Value Decomposition (SVD) modelling process and it is included as
moved to each cluster until K number and Non Negative Matrix Factorization a normal functionality or extension [11].
www.csi-india.org
14
C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8R esearch front
Artificial Neural Network accurate results [14]. Apart from this, patterns in their structure. CATH (Class,
Artificial Neural Network is a ANN was a successful tool in various Architecture, Topology, Homology)
classification technique inspired by protein related problems like secondary is a protein-fold database in which
working of neurons in nervous system structure identification, protein binding SSAP (sequential structure alignment
of human brain. The principle behind site prediction, motif detection etc. program), a dynamic program is used
ANN is that knowledge is acquired Drug design is a very dynamic field for structure alignment based on atom
through learning As the neurons in our which demands highly sophisticated to atom vectors in structure space.
brain receives input signals from other tools and techniques in bioinformatics. Phylogenetic Analysis
neurons, artificial neurons facilitates Artificial neural network has been used Phylogenetics is the study of
learning process through weighted successfully in almost all phases-. finding relationship among species
inputs as well as interconnection Discovery and validation of targets, or genes using a branching diagram
among neurons. The input received by hit evaluation, virtual screening of
or tree structure. Classical way
the network of neurons is represented compounds, deciphering quantitative
of representing the evolutionary
as a vector. These inputs are multiplied structure–activity relationships etc. It is
relationship between species is also
with assigned weight values and added also used in the study of various aspects
called as phylogenetic tree. Multiple
up. The whole ANN model has 3 layers- in pharmacokinetics and pharmaco
sequences are considered and a pattern
input layer, output layer and hidden dynamics [15].
matching-based approach is employed
layer. It is the hidden layer that converts Dynamic Programming for the construction of phylogenetic
the given input into an intermediate form The major macromolecules of life network. Some of the methods utilised
to be used by the output layer. Learning DNA/RNA and the proteins are encoded for multiple sequence alignment
methods used in a given ANN model has in large sequences of nucleic acids or (MSA) include dynamic programming,
significance in generating the output. amino acids respectively. Analysis of progressive alignment construction,
Gradient Descent, Back propagation etc this sequence data is crucial for finding iterative methods, consensus methods,
are a few learning algorithms commonly homology, mutation, conserved regions hidden markov models, genetic
used [12]. Among various neural and evolutionary patterns. Pattern algorithms and simulated annealing,
network architectures, Multilayer recognition is used to compute the simulated quantum computing [18].
perceptrons, Self organizing maps, evolutionary distance between two Using dynamic programming technique
Radial basis function network are found or more finite sequences through pairwise alignment of sequences
to be effective in pattern recognition dynamic programming. In principle, followed by a sum-up is adopted . Some
applications. The techniques discussed the technique involves calculating of the commonly used tools include
so far has the limitations of extracting the global alignment (spanning the ClustalW, MAFFT, T-Coffee (based on
and processing huge raw data for entire length of query sequences) or progressive alignment construction),
feature extraction and processing. The local alignments (pairs of intervals in MUSCLE, DIALIGN (based on iterative
limitations are overcome by the deep each of the sequence resemble each methods), M-COFFEE, MergeAlign
learning algorithm with the power of other) using Needle-Wunsch algorithm (based on consensus methods), HMM-
parallel and distributed computing, and and Smith-Watermann algorithm based tools like POA (Partial-Order
sophisticated algorithms. Moreover the respectively. Scoring matrices like Alignment), SAM (Sequence Alignment
limitation of complex feature extraction BLOSUM62, BLOSUM50 are designed to and Modelling System) and HMMER.
is also overcome by deep learning. detect and give penalty for mismatches
Deep learning is ANN with multiple Microarray Analysis
in the sequence. Some of the sequence
non-linear layers. It has been used in Micro array data is subjected to
similarity search tools include BLAST,
protein structure prediction, protein fold change (FC) method or T-test
FASTA, HMMER, SSEARCH.
classification, subcellular localization In case of proteins and sometimes to evaluate the absolute expression
etc RNA, structural data can help in better levels of gene expression based on up
DNA sequences, known as alignment of sequences as structures regulation or down regulation for a
promoters serve as regulators of are more conserved than sequences given set of experimental conditions.
gene expression by interacting with [16]. Protein functions are conditioned Pattern recognition methods such as
RNA polymerase. Recognizing and by their spatial structures, so protein k-means clustering and time series
predicting such promoter regions is structure comparison is important based techniques like Short Time-
an important problem solved efficiently for predicting protein structures from series Expression Miner (STEM), Linear
by ANN [13]. Finding the functionality amino acid sequences, understanding Mixed Model mixtures and Dynamic
of various RNAs is found to be the evolutionary relationships among Time Warping relate gene expression
significant in study of diseases like proteins and predicting protein functions with their phenotypes. In addition
cancer, cardiovascular diseases etc. [17]. DALI is a protein structure to PCA and SVD, more sophisticated
Unsupervised neural network model alignment comparison tool which methods like Bayesian Belief Networks
was created and applied for predicting performs distance matrix alignment for (BBN) are implemented in the analysis.
new pre-miRNAS from coding sequence successive hexapeptides in the query Pattern Recognition Tools
human regions and obtained a very high sequence based on contact similarity There are numerous tools available
15
C S I C o m m u n ic a t i o n s | MA Y 2 0 1 8You can also read
