Top Read Articles in Information & Technology : July 2021

Top Read Articles in
Information & Technology
International Journal of Information
Technology, Control and Automation
(IJITCA)
ISSN : 1839-6682
http://airccse.org/journal/ijitca/ijitca.html

PROCESS AUTOMATION OF CEMENT PLANT
Akash Samanta1, Ankush Chowdhury 2, Arindam Dutta3
1Electrical Department, West Bengal University of Technology, Kolkata, India
2
Commissioning Engineer, Axim Automation Technology Pvt. Ltd., Bangalore, India
3
Indian Institute of Social Welfare and Business Management, Kolkata, India
ABSTRACT
Cement is an essential component of infrastructure development. It is also the most important
input of construction industry, mainly in case of the government’s infrastructure and housing
programs, which are necessary for the country’s socio-economic growth and development.
Due to increasing population, various constructional activities are increasing day by day. As a
result the market demand of cement is also increasing continuously but still now most of those
plants aren’t up to the mark technologically. They are very inefficient, not so eco-friendly and
have very low production speed. Keeping in mind the importance of those industries, an
integrated solution of material handling in cement plant is presented in this paper to meet the
increasing production needs. This innovative thinking will help to reduce energy consumption
and improve operational efficiency as most of the energy is consumed to transfer the bulk
materials between intermediate stages. This PLC or HMI based controls are not only cost-
effective method but also improves the control system longevity and ultimately reduces the
total cost of operation over the life of the system.The whole automation process is done using
programmable logic controller (PLC) which has number of unique advantages like speed,
reliability, less maintenance cost and re programm ability. The whole system has been
designed and tested using GE, FANUC PLC.
KEYWORDS
PLC, Level Detector, VRM, Silo, Kiln, ESP, Clinker, Blending.
Full Text: https://wireilla.com/papers/ijitca/V2N2/2212ijitca06.pdf
Volume Link: http://airccse.org/journal/ijitca/vol2.html

REFERENCES
[1] “WP. No: UDE(CAS)25/(9)/3/2008, Documentation Sheet” Performance Of Indian
Cement Industry The Competitive Landscape, L. G. Burange, Shruti Yamini, April 2008,
pages(3-17).
[2] Cement manufacturing process description[Online]. Available:
www.inece.org/mmcourse/chapt6.pdf
[3] Katja Schumacher and Jayant Sathaye, “India’s cement industry productivity, energy
efficiency and carbon emissions”, Energy Analysis Program Environmental Energy
Technologies Division Lawrence Berkeley National Laboratory Berkeley, CA 94720, July
1999, LBNL-41842,pages(1-9).
[4] Arindam Dutta, Ankush Chowdhury, Sabhyasachi karforma, Subhabrata Saha, Saikat
Kundu, Dr. Subhasis Neogi, “Automation of coal handling plant”, in Pro.of conf. on control
communication and power Engineering 2010,ACEEE, paper- 67-146-149,p (147-149).
[5] Vinicius de Oliveira, Michael Amrhein and Alireza Karimi, “Robust gain-scheduled
blending control of raw-mix quality in cement industries”pp.1-6.[Online]. Available:
infoscience.epfl.ch/record/169885/files/blending.pdf
[6] A.K. Swain, “Material mix control in cement plant automation”, 0272- 1708/95/$04.00@1
9951EEE, August 1995.pages(23-27).
[7] Shaleen Khurana, Rangan Banerjee , Uday gaitonde. “Energy balance and cogeneration for
a cement plant”, Applied Thermal Engineering vol. 22, pp. 485–494, 2002. Available:
www.elsevier.com/locate/apthermeng
[8] “Record Growth and Modernisation in Indian Cement Industry”, A quarterly information
carrier of ncb services to the industry, VOL IX NO 4 DECEMBER 2007, seminar special,
ISSN 0972-3412.
[9] Madhuchanda Mitra and Samarjit Sen Gupta, Programmable Logic Controllers and
Industrial Automation an Introduction, ISBN-81-87972-17-3, 2009, pages(1-51).

Fractional Order PID Controller Tuning Based on IMC
Mohammad Reza Rahmani Mehdi Abadi1 and Ali Akbar Jalali2
1,2
Electrical Engineering Department, Iran University of Science and Technology, Tehran,
Iran.
ABSTRACT
In this work, a class of fractional order controller (FOPID) is tuned based on internal model
control (IMC). This tuning rule has been obtained without any approximation of time delay.
Moreover to show usefulness of fractional order controller in comparison with classical integer
order controllers, an industrial PID controller tuned in a similar way, is compared with FOPID
and then robust stability of both controllers is investigated. Robust stability analysis has been
done to find maximum delayed time uncertainty interval which results in a stable closed loop
control system. For a typical system, robust stability has been done to find maximum time
constant uncertainty interval of system. Two clarify the proposed control system design
procedure, three examples have been given.
KEYWORDS
Fractional order PID, IMC, Robust Stability.

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Authors
Mohammad Reza Rahmani Mehdi Abadi was born in Yazd, Iran, in 1987. He received
his B.S. degree in electronics engineering from Yazd University in 2008, and the M.S.
degree in control engineering from Iran University of science and technology, in 2011. His
main area of interest includes robust control.
Ali Akbar Jalali was born in Damghan, Iran, in 1954. He received his B.Sc. degree in
Electronics Engineering from Khajeh Nasiredin Toosi University of Technology, Tehran, Iran,
May 1985. He obtained his M.Sc. degree in Electrical Engineering from Oklahama University,
Norman, US, in 1988. Then, he earned his Ph.D. and Post Doctoral in Electrical Engineering,
from West Virginia University, Morgantown, US, in 1993 and 1994 respectively.Dr. Jalali
became a member of the Lane Department of Computer Science and Electrical Engineering,
Collage of Engineering and Mineral Resources, West Virginia University, as an adjunct
Professor in 2002. Currently, he is working in the Department of Electrical Engineering, Iran
University of Science and Technology (IUST) where he has been since 1994 as an associate
professor. His research field interests include mainly Extended Kalman Filtering, Robust
Control, H-infinity and Fractional order control. Furthermore, study of Information Technology
and its applications like: Virtual Learning, Virtual Reality, Internet City, Rural ICT
developments and Designing ICT Strategic Plan are his other research interests.

Neural Network Control Based on Adaptive Observer for
Quadrotor Helicopter
Hana Boudjedir1, Omar Bouhali1 and Nassim Rizoug2
1LAJ Lab, Automatic department, Jijel University, Algeria
2Mecatronic Lab, ESTACA School, Laval, France.
ABSTRACT
A neural network control scheme with an adaptive observer is proposed in this paper to
Quadrotor helicopter stabilization. The unknown part in Quadrotor dynamical model was
estimated on line by a Single Hidden Layer network. To solve the non measurable states
problem a new adaptive observer was proposed. The main purpose here is to reduce the
measurement noise amplification caused by conventional high gain observer by introducing
some changes in observer’s original structure that can minimize the variance and the amplitude
of the noisy signal without increasing tracking error. The stability analysis of the overall
closed-loop system/ observer is performed using the Lyapunov direct method. Simulation
results are given to highlight the performances of the proposed scheme
KEYWORDS
OFDM, pilot-based channel estimation, pilot allocation, direct decision, interpolation channel
estimation, LS, MMSE, MATLab

REFERENCES
[1] Henrik Schulze and Christian Luders. Theory and Applications of OFDM and CDMA:
Wideband Wireless Communications. John Wiley & Sons, 2006.
[2] Yong Soo Cho, Jaekwon Kim, Won Young Yang, Chung G. Kang. MIMO-OFDM
Wireless Communications with MATLAB, John Wiley & Sons, August 2010.
[3] Mathuranathan Viswanathan. Digital Modulations using MATLab: Build Simulation
Models from Scratch. E-book, June, 2017.
[4] Srishtansh Pathak and Himanshu Sharma. Channel Estimation in OFDM Systems.
International Journal of Advanced Research in Computer Science and Software Engineering
(IJARCSSE), Vol.3, No.3, pp. 312-327, 2013.
[5] Elizabeth A. Thompson, Charles McIntosh, James Isaacs, Eric Harmison, Ross Sneary.
Robot Communication Link Using 802.11n or 900 MHz OFDM. Journal of Network and
Computer Applications (JNCA), Vol. 52, Issue 6, pp. 37-51, June 2015.
[6] Jeffrey G. Andrews, Arunabha Ghosh, and Rias Muhamed. Fundamentals of WiMAX-
Understanding Broadband Wireless Networking. Prentice Hall, Second Edition, 2007.
[7] Christopher Cox. An Introduction to LTE: LTE, LTE-Advanced, SAE and 4G Mobile
Communications. John-Wiley & Sons, March 2012.
[8] Mehdi Alasti, Behnam Neekzad, Jie Hui, and Rath Vannithamby. Quality of Service in
WiMAX and LTE Networks. IEEE Communications Magazine, Vol. 48, Issue 5, May 2010.
[9] Deepak Sharma and Praveen Srivastava. OFDM Simulator Using MATLAB. International
Journal of Emerging Technology and Advanced Engineering, Vol. 3, Issue 9, pp. 493-496,
September 2013.
[10] S. S. Ghorpade and S. V. Sankpal. Behavior of OFDM System Using MATLAB
Simulation. International Journal of Innovative Technology and Research (IJITR), Vol., No. 1,
Issue No. 3, pp. 249 – 252, April - May 2013.
[11] S. Sadinov, P. Daneva, and P. Kogias. Description and Simulation of OFDM Reception
Process Journal of Engineering Science and Technology Review, Vol. 7, No. 4, pp. 18-22,
2014.
[12] Orlandos Grigoriadis and H. Srikanth Kamath. BER Calculation Using MATLAB
Simulation for OGDM Transmission. Proceedings of the International Multi-Conference of
Engineers and Computer Scientists (IMECS), Vol II, Hong Kong, 19-21 March 2008.
[13] Kala Praveen Bagadi and Susmita Das. MIMO-OFDM Channel Estimation Using Pilot
Carries. International Journal of Computer Applications (0975 – 888 (IJCA), Vol. 2, No. 3,
May 2010.
[14] H. Sinha, R. Meshram, and G.R. Sinha. BER Performance Analysis of MIMO-OFDM
over Wireless Channel. International Journal of Pure and Applied Mathematics (IJPAM), Vol.
118, No. 5, pp. 195- 206, 2018.

[15] Pratima Manhas and M.K Soni. OFDM Performance Evaluation under Different Fading
Channels using Matlab Simulink. Indonesian Journal of Electrical Engineering and Computer
Science, Vol. 5, No. 2, pp. 260-266, 2017.
[16] A. Z. M. Touhidul Islam. A Comparative Performance Study of OFDM System with the
Implementation of Comb Pilot-Based MMSE Channel Estimation. International Journal on
Computational Sciences & Applications (IJCSA), Vol.3, No.6, pp. 45-53, December 2013.
[17] D. Khosla, S. Singh, R. Singh, and S. Goyal. OFDM Modulation Technique & its
Applications: A Review. Proceedings of the International Conference on Innovations in
Computing (ICIC 2017), pp. 101-105, 2017.
[18] Fateme Salehi, Mohammad‐Hassan Majidi, and Naaser Neda. Channel Estimation Based
on Learning Automata for OFDM Systems. International Journal of Communication Systems,
Vol. 321, Issue 12, August, 2018.
[19] Navjot Kaur and Neetu Gupta. Simulation and Analysis of OFDM and SC-FDMA with
STBC using Different Modulation Techniques. International Journal of Advanced Research in
Computer Engineering & Technology (IJARCET), Vol. 4, Issue 11, pp. 4184-4189, November
2015.
[20] Himanshi Jain and Vikas Nandal. A Comparison of Various Channel Estimation
Techniques to Improve Fading Effects in MIMO over Different Fading Channels. International
Journal of Current Engineering and Technology (IJCET), Vol. 6, No. 4, pp. 1382-1386, 2016.
[21] Kussum Bhagat and Jyoteesh Malhotra. Performance Evaluation of Channel Estimation
Techniques in OFDM-based Mobile Wireless System. International Journal of Future
Generation Communication and Networking (IJFGCN), Vol. 8, No. 3, pp. 53-60, 2015.
[22] Vishal Sharma and Harleen Kaur. On BER Evaluation of MIMO-OFDM Incorporated
Wireless System. International Journal for Light and Electron Optics, Vol. 127, Issue 1, pp.
203-205, January 2016.
[23] N. Kumar and Anuradha. BER Analysis of Conventional and Wavelet Based OFDM in
LTE using Different Modulation Techniques. IEEE Engineering and Computational Sciences,
March 2014.
[24] M Divya. Bit Error Rate Performance of BPSK Modulation and OFDM-BPSK with
Rayleigh Multiple Channel. International Journal of Engineering and Advanced Technology
(IJEAT), Vol. 2, Issue 4, April 2013.
[25] Song Wang, Jinli Cao, Jiankun Hu. A Frequency Domain Subspace Blind Channel
Estimation Method for Trailing Zero OFDM Systems. Journal of Network and Computer
Applications (JNCA), Vol. 34, Issue 1, pp. 116-120, January 2011.
[26] Li Li. Advanced Channel Estimation and Detection Techniques for MIMO and OFDM
Systems. PhD Thesis, University of York, UK, 2013.

[27] S. Patil and A. N. Jadhav. Channel Estimation Using LS and MMSE Estimators. KIET
International Journal of Communications & Electronics, Vol. 2, No.1, pp. 51-55, April 2014.
[28] Anwar Yousef Al-Tarawneh. An Improved Performance OFDM Channel Estimation
Using PilotSymbol-Aided Technique. MSc Thesis, Mutah University, Jordan, 2015.

KEY SWAP OVER AMONG GROUP OF
MULTILAYERPERCEPTRONS FOR ENCRYPTION IN WIRELESS
COMMUNICATION (KSOGMLPE)
Arindam Sarkar1 and J. K. Mandal2
1
Department of Computer Science & Engineering, University of Kalyani, W.B, India
2
Department of Computer Science & Engineering, University of Kalyani, W.B, India
ABSTRACT
In this paper, a key swap over mechanism among group of multilayer perceptrons for
encryption/decryption (KSOGMLPE) has been proposed in wireless communication of
data/information. Two parties can swap over a common key using synchronization between
their own multi layer perceptrons. But the problem crop up when group of N parties desire to
swap over a key. Since in this case each communicating party has to synchronize with other
for swapping over the key. So, if there are N parties then total number of synchronizations
needed before swapping over the actual key is O(N2). KSOGMLPE scheme offers a novel
technique in which complete binary tree structure is follows for key swapping over. Using
proposed algorithm a set of N parties can be able to share a common key with only O(log2 N)
synchronization. Parametric tests have been done and results are compared with some existing
classical techniques, which show comparable results for the proposed technique.
KEY WORDS
Multi layer Perceptron, Encryption, Swap Over, Wireless Communication.
Volume Link: https://wireilla.com/ijitca/vol3.html

REFERENCES
[1] Atul Kahate, Cryptography and Network Security, 2003, Tata McGraw-Hill publishing
Company Limited, Eighth reprint 2006.
[2] Sarkar Arindam, Mandal J. K, “Artificial Neural Network Guided Secured Communication
Techniques: A Practical Approach” LAP Lambert Academic Publishing ( 2012-06-04 ), ISBN:
978-3-659-11991-0, 2012
[3] Sarkar Arindam, Karforma S, Mandal J. K, “Object Oriented Modeling of IDEA using GA
based Efficient Key Generation for E-Governance Security (OOMIG) ”, International Journal
of Distributed and Parallel Systems (IJDPS) Vol.3, No.2, March 2012, DOI :
10.5121/ijdps.2012.3215, ISSN : 0976 - 9757 [Online] ; 2229 - 3957 [Print]. Indexed by:
EBSCO, DOAJ, NASA, Google Scholar, INSPEC and WorldCat, 2011.
[3] Mandal J. K., Sarkar Arindam, “Neural Session Key based Traingularized Encryption for
Online Wireless Communication (NSKTE)”, 2nd National Conference on Computing and
Systems, (NaCCS 2012), March 15-16, 2012, Department of Computer Science, The
University of Burdwan, Golapbag North, Burdwan –713104, West Bengal, India. ISBN 978-
93-808131-8-9, 2012.
[4] Mandal J. K., Sarkar Arindam, “Neural Weight Session Key based Encryption for Online
Wireless Communication (NWSKE)”, Research and Higher Education in Computer Science
and Information Technology, (RHECSIT- 2012) ,February 21-22, 2012, Department of
Computer Science, Sammilani Mahavidyalaya, Kolkata , West Bengal, India. ISBN 978-81-
923820-0-5,2012
[6] Mandal J. K., Sarkar Arindam, “An Adaptive Genetic Key Based Neural Encryption For
Online Wireless Communication (AGKNE)”, International Conference on Recent Trends In
Information Systems (RETIS 2011) BY IEEE, 21-23 December 2011, Jadavpur University,
Kolkata, India. ISBN 978-1-4577-0791-9, 2011
[7] Mandal J. K., Sarkar Arindam, “An Adaptive Neural Network Guided Secret Key Based
Encryption Through Recursive Positional Modulo-2 Substitution For Online Wireless
Communication (ANNRPMS)”, International Conference on Recent Trends In Information
Technology (ICRTIT 2011) BY IEEE, 3-5 June 2011, Madras Institute of Technology, Anna
University, Chennai, Tamil Nadu, India. 978-1-4577-0590-8/11, 2011
[8] Mandal J. K., Sarkar Arindam, “An Adaptive Neural Network Guided Random Block
Length Based Cryptosystem (ANNRBLC)”, 2nd International Conference on Wireless
Communications, Vehicular Technology, Information Theory And Aerospace & Electronic
System Technology” (Wireless Vitae 2011) By IEEE Societies, February 28- March 03,
2011,Chennai, Tamil Nadu, India. ISBN 978-87- 92329-61-5, 2011
[9] Mandal J. K., Sarkar Arindam, “Neural Network Guided Secret Key based Encryption
through Cascading Chaining of Recursive Positional Substitution of Prime Non-Prime
(NNSKECC)”, International Conference on Computing and Systems, ICCS – 2010, 19–20
November, 2010,Department of Computer Science, The University of Burdwan, Golapbag
North, Burdwan –713104, West Bengal, India.ISBN 93-80813-01-5, 2010

[10] R. Mislovaty, Y. Perchenok, I. Kanter, and W. Kinzel. Secure key-exchange protocol with
an absence of injective functions. Phys. Rev. E, 66:066102,2002.
[11] A. Ruttor, W. Kinzel, R. Naeh, and I. Kanter. Genetic attack on neural cryptography.
Phys. Rev. E,73(3):036121, 2006.
[12] A. Engel and C. Van den Broeck. Statistical Mechanics of Learning. Cambridge
University Press,Cambridge, 2001.
[13] T. Godhavari, N. R. Alainelu and R. Soundararajan “Cryptography Using Neural Network
” IEEE Indicon 2005 Conference, Chennai, India, 11-13 Dec. 2005.gg
[14] Wolfgang Kinzel and ldo Kanter, "Interacting neural networks and cryptography",
Advances in Solid State Physics, Ed. by B. Kramer (Springer, Berlin. 2002), Vol. 42, p. 383
arXiv- cond-mat/0203011, 2002
[15] Wolfgang Kinzel and ldo Kanter, "Neural cryptography" proceedings of the 9th
international conference on Neural Information processing(ICONIP 02).h
[16] Dong Hu "A new service based computing security model with neural
cryptography"IEEE07/2009.J

Authors
Arindam Sarkar
INSPIRE Fellow (DST, Govt. of India), MCA (VISVA BHARATI, Santiniketan, University
First Class First Rank Holder), M.Tech (CSE, K.U, University First Class First Rank Holder).
Total number of publications 13.
Jyotsna Kumar Mandal
M. Tech.(Computer Science, University of Calcutta), Ph.D.(Engg., Jadavpur University) in the
field of Data Compression and Error Correction Techniques, Professor in Computer Science
and Engineering, University of Kalyani, India. Life Member of Computer Society of India since
1992 and life member of cryptology Research Society of India. Dean Faculty of Engineering,
Technology & Management, working in the field of Network Security, Steganography, Remote
Sensing & GIS Application, Image Processing. 25 years of teaching and research experiences.
Eight Scholars awarded Ph.D. one submitted and 8 are pursuing. Total number of publications
230.

MOBILE PHONE –BASED PARKING SYSTEM
Karari Ephantus Kinyanjui1
and Andrew Mwaura Kahonge2
1Department of Computer Science, Dedan Kimathi University of Technology
2
School of Computing and Informatics, University of Nairobi
ABSTRACT
Traffic flow, allocation and availability of parking space within the streets of Nairobi is a
major concern to every motorist. The availability of the mobile phone and its increased
affordability has led to its adoption as the main gadget and technology for contemporary
communication in most developing countries. Furthermore, the convenience it offers to users
and its cost effectiveness has made it the technology driver not just in developing world but
also in the developed countries. One area where its application has born fruits in some
countries is in mobile parking. By use of mobile communication, cities in countries such as
Singapore and Germany have experienced increased efficiency in traffic management and
parking fees collection. The technology also depends on banking models used in these
countries; a fact that makes it necessary for any similar solution been developed elsewhere to
consider the local system environment.
KEYWORDS
Parking, Mobile, Sensor, Camera, Fee, Council
Full Text: http://wireilla.com/papers/ijitca/V3N1/3113ijitca03.pdf
Volume Link: https://wireilla.com/ijitca/vol3.html

REFERENCES
[1] Irungu, King'ori Zachariah (). Decongesting Nairobi-Urban Transportation Challenges.
Internet: http://www.scribd.com/doc/2382775/Decongesting-Nairobi-City-Kenya, Nov.
2007[Apr.15, 2010]
[2] Gerd Müller, Introducing a mobile parking system, Internet:
http://www.civitas.eu/index.php?id=79&sel_menu=16&measure_id=18, Apr. 2007 [Apr.15,
2010]
[3] Fact sheet mobile parking system, Internet:
http://www.google.co.ke/url?sa=t&rct=j&q=mobile%20parking%20system%20berlin%20gmb
h&source=web&cd=4&cad=rja&ved=0CEwQFjAD&url=https%3A%2F%2Fblue-sea-697d.quartiers047.workers.dev%3A443%2Fhttp%2Fwww.stadtentwic
klung.berlin.de
%2Finternationales_eu%2Fverkehr%2Farchiv%2Ftellus%2Fwww.telluscities.net%2Fmedia%
2Fen%2FFactsheet%2520Berlin%2520WP%25206.4%2520Oktober%2520200
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