Special Issue No. – 5, January, 2020

Abstract:

In this paper, Corporate Happiness is introduced as a tool to enhance the productivity and efficiency of the employees at work. Starting from the apologetic endeavours to happiness the ideology of rights of people to be happy is canvassed from the historical review of the literature. Defining formally the Corporate Happiness, attempts of the people for happiness is described. Further, emerging ideas specifically for Corporate Happiness and the various measures for Corporate Happiness are detailed.

Keywords:

Corporate Happiness,Eudemonic well-being,Hedonic Happiness,Transparent lasting relationships,

Refference:

I. C. D. Ryff, B. H. Singer, “Know thyself and become what you are: a
eudaimonic approach to psychological well-being”, Journal of Happiness
Studies, Vol.: 9, pp: 13–39, 2006.
II. F. D. Cynthia, “Happiness at Work”, International Journal of Management
Reviews, Vol.: 12, Issue: (4), pp. 384–412, 2010.
III. G. H. Joanne, O. M. Richard, “The Virtuous Organization: The Value of
Happiness in the Workplace”, Organizational Dynamics. Healthy, Happy,
Productive Work: A Leadership Challenge, Vol.: 33, Issue: (4), pp. 379–392,
2004.
IV. https://en.wikipedia.org/wiki/Happiness_at_work#Definition
V. https://www.yesmagazine.org/happiness/a-history-of-happiness
VI. https://en.wikipedia.org/wiki/Happiness_at_work#Definition
VII. http://digital_collect.lib.buu.ac.th/dcms/files/53910262/chapter2.pdf
VIII. https://onlinelibrary.wiley.com/doi/10.1111/j.1744-6198.2008.00091.x
IX. https://www.researchgate.net/publication/270882208_Happiness_beyond_Wel
l_Being_Some_Reflections_of_Canadian_Society
X. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4345401/#SD1
XI. https://www.researchgate.net/publication/232053321_Happiness_and_Mental
_Health_Policy_A_Sociological_Critique.
XII. https://www.tandfonline.com/doi/abs/10.1080/14623940903525207
XIII. https://www.science.gov/topicpages/h/happiness.html
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with_a_Single-Item_Scale
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times-jessica-pryce-jones

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HandDevelopment/36.GNH&development.pdf
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happiness-at-work.pdf
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schedule”.
XXXI. Warr, “Work, happiness, and unhappiness”, Mahwah, NJ: lawrenceerlbaum,
2007

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Abstract:

This paper proposes Genetic algorithm based multistage fuzzy DC voltage regulator (GAMSFDCVR) for unified power flow controller (UPFC) for damping low frequency oscillations. The DC voltage regulator is combination of two single stage fuzzy controllers and performing like PID fuzzy. Genetic algorithm is an optimization algorithm and used for tuning of fuzzy bounds of multistage fuzzy voltage regulator based on the error minimization. The error used for optimization of fuzzy bounds is an integral time area error caused by the deviations of capacitor voltage of UPFC. This method is tested on single machine infinite bus system (SMIB) and the performance is compared with conventional controllers. Results demonstrated that the proposed controller is effectively improving the dynamic stability compared with conventional controllers.

Keywords:

Unified power flow controller (UPFC),genetic algorithm based multistage fuzzy DC voltage regulator (GAMSFDCVR),Conventional controllers (CC.),

Refference:

I. A. Kazemi, M. V. Sohrforouzani, “Power system damping controlled
facts devices”, Electrical Power and Energy Systems, Vol.: 28, pp. 349-
357, 2006.
II. B. C. Pal, “Robust damping of interarea oscillations with unified power
flow controller”, IEE Proc. On Generation, Transmission and
Distribution, Vol.: 149, Issue: 6, pp. 733-738, 2002.
III. H. Shayeghi, A. Jalili, “A Hybrid Fuzzy AGC in a competitive
electricity environment”, Int. Journal of Electrical Systems Science and
Engineering, Vol.: 1, Issue: 3, pp. 184-195, 2008.
IV. IEEE Power Engineering Society and CIGRE, FACTS overview, IEEE
Publication, Issue: 95 TP 108, 1995.

V. J. C. Seo, S.-I. Moon, J.-K. Park, J.-W. Choe, “Design of a robust UPFC
controller for enhancing the small signal stability in the multi-machine
power systems”, Proc. of the IEEE PES Winter Meeting, Vol.: 3, pp.
1197-1202, 2001.
VI. K. L. Lo, Y. J. Lin, “Strategy for the control of multiple series
compensators in the enhancement of interconnected power system
stability”, IEE Proc. On Generation, Transmission and Distribution,
Vol.: 146, Issue: 2, pp. 149-158, 1999.
VII. K. R. Padiyar, H. V. Saikumar, “Coordinated design and performance
evaluation of UPFC supplementary modulation controllers”, Electrical
Power and Energy System., Vol.: 27, pp. 101-111, 2005.
VIII. L. Gyugyi, “Unified power-flow control concept for flexible ac
transmission systems”, IEE Proc. On Generation, Transmission and
Distribution, Vol.: 139, Issue: 4, pp. 323-31, 1992.
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control inputs for damping inter-area oscillations”, IEEE Trans. On
Power Systems, Vol.: 19, Issue: 2, pp. 1135-43, 2004.
XIII. M. Vilathgamuwa, X. Zhu, S. S. Choi, “A robust control method to
improve the performance of a unified power flow controller”, Electric
Power Systems Research, Vol.: 55, pp.103-111, 2000.
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technology of flexible AC transmission systems”, Wiley-IEEE Press,
1999.
XV. N. Tambey, M. L. Kothari, “Damping of power system oscillations with
unified power flow controller (UPFC)”, IEE Proc. On Generation,
Transmission and Distribution, Vol.: 150, Issue: 2, pp. 129-40, 2003.
XVI. P. C. Stefanov., A. M. Stankovic, “Modeling of UPFC operation under
unbalanced conditions with dynamic phasors”, IEEE Trans. On Power
Systems, Vol.: 17, Issue: 2, pp. 395-403, 2002.

XVII. P. K. Dash, S. Mishra, G. Panda, “A radial basis function neural network
controller for UPFC”, EEE Trans. On Power Systems, Vol.: 15, Issue:
4, pp. 1293-1299, 2000.
XVIII. P. K. Dash, S. Mishra, G. Panda, “Damping multimodal power system
oscillation using hybrid fuzzy controller for series connected FACTS
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XXI. S. Limyingcharone, U. D. Annakkage, N. C. Pahalawaththa, “Fuzzy
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Inc.,London, 1983.

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Abstract:

This effort recommends‘ PV based 3-Φ (Multi Level Inverter) MLI with 3Phase induction motor (PVTPMLITPIM) using PI& Fractional Order PID(FOPID) controller closed loop system’. These exertions intend Re Boost Converter (RBC) between PV and MLI, also intended FOPID for control of PVTPMLITPIM system. “PI &FOPID controlled frame works” are composed & recreated utilizing MATLAB. The standards of operation & simulation comes about are observed. The simulation consequences of PI & FOPID controlled PVTPMLITPIM frameworks are evaluated in terms of time domain parameters & association table were analyzed and exhibited. The outcomes show FOPID controlled PVTPMLITPIM system is speedier than that of PI controlled PVTPMLITPIM system.

Keywords:

Multi Level Inverter,Re Boost Converter,simulation,

Refference:

I. B. Yang , T.Yu, H. Shu, Y. H. P. Cao, L. Jiang, “Adaptive fractional order
PID control of PMSG based wind energy conversion system for MPPT using
linear observers” Int. Trans Electr Energ Syst, Vol.: 29, Issue: 1, pp. e2735,
2019.
II. D. Yang, L. Yin, S. X. N. Wu, “Power and voltage control for single phase
cascaded h bridge multilevel converters under unbalanced loads”, Energies,
Vol.: 11, 2435, 2018.
III. L. Chu, Y. Jia, D. Chen, N. Xu, Y. Wang, X. Tang, Z. Xu, “ Research on
control strategies of an open end winding permanent magnet synchronous
driving motor (OW PMSM) equipped dual inverter with a switchable
winding mode for electric vehicles”, Energies, Vol.: 10, pp.616, 2017.
IV. M. Fatu, F. Blaabjerg, I. Boldea, “Grid to stand alone transition motion
sensor-less dual inverter control of PMSG with asymmetrical grid voltage
sags & harmonics filtering”, IEEE Trans PE, Vol.: 29, pp. 3463–3472,
2014.
V. O. A. Alavi, A. H. Viki, S. Shamlou, “A comparative reliability study of
three fundamental multilevel inverters using two different approaches”,
electronics, Vol.: 5, pp.18, 2016.
VI. R. Mohammadikia, M. Aliasghary, “A fractional order fuzzy PID for load
frequency control of four area interconnected power system using
biogeography based optimization”, Int. Trans Electr Energ Syst, Vol.: 29,
Issue: 2, pp. e2735, 2019.
VII. R. R. Behra, A. N. Thakur, “An overview of various grid synchronization
techniques for single phase grid integration of renewable distributed power
generation systems”, IEEE international conf. on electrical electronics &
optimization techniques (ICEEOT), pp: 2876-2880, 2016.
VIII. S. Bogarra, L. Monjo, J. Saura, F. Córcoles, J. Pedra, “Comparison of
simplified models for voltage source inverter fed adjustable speed drive
during voltage sags when the during event continue mode of operation is
active”. IET Electr power A ppl, Vol.: 8, pp. 329–341, 2014.

IX. S. Lee, J. Kim, “Optimized modeling and control strategy of the single phase
photovoltaic grid connected cascaded h bridge multilevel inverter”,
Electronics, Vol.: 7, pp. 207, 2018.
X. S. Leng, A. Haque, N. Perera, A. M. Knight, J. Salmon, “ Smart grid
connection of an induction motor using a three phase floating h bridge
system as a series compensator”, IEEE Trans. PE, Vol.: 31, pp.7053–7064,
2016.
XI. V. F. Pires, D. Foito, J. F. Silva, “Fault tolerant multilevel topology based
on three phase h bridge inverters for open end winding induction motor
drives”, IEEE Trans, Energy Converters, Vol.: 32, pp.895–902, 2017.
XII. Y. Zhou, W. Huang, F. Hong, “Single phase input variable speed ac motor
system based on an electronic capacitor less single stage boost three phase
inverter”, IEEE Trans. PE, Vol.: 31, pp.7043–7052. 2016.

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Abstract:

A novel method proposed for the reduction of switching operations (SOs) of voltage controlled devices (VCDs) and system power loss in the presence of dispatchable distributed generation (DDG). In this method reactive power of DDG coordinated with voltage controlled devices (VCDs) like under load tap changers (ULTCs) and shunt capacitors (SCs) in order to curtail switching operations (SOs) of VCDs together with power loss. Reactive power coordination and power loss is formulated as a multi objective function (MOF), Grey wolf optimizer (GWO) algorithm is proposed for optimizing MOF with the aid of forecasted load one day in advance. Proposed method was tested on 10kv 16 nodes system in Matlab environment at different locations of DDG with different output profiles. The efficacy of proposed scheme is compared with conventional (CO) and particle swarm optimization (PSO) methods.

Keywords:

Dispatchable distributed generation (DDG),,Voltage controlled devices (VCDs),switching operations (SOs),Grey wolf optimizer (GWO),Dynamic programming (DP),

Refference:

I. A. Askarzadeh, A. Rezazadeh, “A new heuristic optimization algorithm
for modelling of proton exchange membrane fuel cell: Bird mating
optimizer”, International Journal of Energy Research, Vol. 37, No. 10,
pp. 1196-1204, 2013.
II. A. H. Gandomi, A. H. Alavi, “Krill herd: a new bio inspired
optimization algorithm”, Communications in Nonlinear Simulations,
Vol. 17, No. 12, pp. 4831-4845, 2012.
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regional active network management system”, IEEE Power & Energy
Society General Meeting, pp. 1-7, 2009.
IV. C. J. Dent, L. F. Ochoa, G. P. Harrison, “Network distributed generation
capacity analysis using OPF with voltage step constraints”, IEEE
Transactions on Power Systems, Vol. 25, No. 1, pp. 296-304, 2010.
V. E. Bonabeau, M. Doriga, G. Theraulaz, “Swarm intelligence: from
natural to artificial systems”, IEEE Transactions on Evolutionary
Computation, Vol. 4, No. 2, pp. 192-193, 2000.
VI. F. A. Vivan, D. Karlsson, “Combined local and remote voltage and
reactive power control in the presence of induction machine distributed
generation”, IEEE Transactions on Power Systems, Vol. 22, No. 4, pp.
2003-2012, 2007.
VII. F. A. Vivan, D. Karlsson, “Voltage and reactive power control in
systems with synchronous machine based distributed generation”, IEEE
Transactions on Power Delivery, Vol. 23, No. 2, pp. 1079-1087, 2008.

VIII. F. A. Vivan: “Voltage control and voltage stability of power distribution
systems in the presence of distributed generation”, Doctoral Dissertation,
U.T. Sweden, 2008.
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with distributed energy sources: Algorithm, theoretical analysis,
simulation, and field test verification”, IEEE Transactions on Power
Systems, Vol. 25, No. 3, pp. 1638-1647, 2010.
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networks”, IEEE International Conference on Neural Networks, Perth,
Australia, December 1995.
XIII. J. O. Donnel: “Voltage management of networks with distributed
generation”, Doctoral Dissertation, U.K. Edinburgh, 2007.
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algorithm with bacterial foraging optimization”, IEEE International
Conference on Cyber Technology in Automation, Control, and
Intelligent Systems, Shenyang, China, June 2015.
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XVI. M. Sankaraiah, S. Suresh Reddy, M. Vijaya Kumar, “DFIG and voltage
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optimization”, IEEE International Conference for Convergence in
Technology, Manglore, India, Oct 2018.
XVII. M. Sankaraiah, S. Suresh Reddy, M. Vijaya Kumar, “Particle Swarm
Optimization based reactive power coordinated Control of distributed
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XVIII. M. Sankaraiah, S. Suresh Reddy, M. Vijaya Kumar, “PSO based reactive
power coordination of PV system and voltage controlled devices”, Third
International Conference on Emerging Trends in Electrical,
Communications and Information Technology (Springer conference),
Ananthapuramu, India, Dec 2018.
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capacitors in a distribution system”, IEEE Transactions on Power
Delivery, Vol. 16, No. 4, pp. 625-630, 2001.

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XXIV. W. Sheng, K. Y. Liu, Y. Liu, X. Ye, H. Kaiyuan, “A reactive power
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&Biologically inspired Computing”, World Congress on Nature and
Biologically Inspired Computing, Coimbatore, India, December 2009.
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XXX. Y. Shiqin, J. Jianjun, Y. Guangxing, “A Dolphin Partner
Optimization”;World Congress on Nature and Biologically Inspired
Computing, Coimbatore, India, December 2009.

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Abstract:

The firefly optimization technique gives the reduced order model for the higher-order interval system. Stimulated by sporadic behavior of fireflies to act as the signal system to impress other fireflies. The fitness function is developed using   Routh approximation and cross multiplication of transfer function. The stability is analyzed through Routh-Hurwitz stability.

Keywords:

Firefly Algorith,Integral Square Error,Routh-Hurwitz,Lower order,Higher order,

Refference:

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1999

VI. D. Gorinevsky, S. Boyd, G. Stein, “Design of Low-Bandwidth Spatially
Distributed Feedback,”IEEE Transactions on Automatic Control, Vol.: 53,
Issue: 1, pp. 257-272, 2008.
VII. D. K. Kumar,S. K. Nagar, J. P. Tiwari, “A New Algorithm for model order
reduction of interval systems,”Bonfring International Jornal of Data Mining,
Vol.: 3, Issue: 1, 2013
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Abstract:

Nowadays, text mining research has become one of the broad areas of research of natural language documents. A comprehensive overview of text mining and existing research status are discussed in the results of this study. The discovery of relevant patterns and trends for analyzing text documents from a huge volume of information is a major issue. Text mining is an extract from a huge number of text documents for interesting and nontrivial trends. Various methods and tools exist to determine the text and identify valuable information for future analysis and decisionmaking. The right and effective techniques for text mining help to speed up the extraction of valuable information and decrease the time and effort required. This document describes and reports the methods and applications of text mining in various fields of life. In addition, issues are identified in the field of text mining that affect the accurate and relevant results.

Keywords:

Text mining,Information extraction,Information Retrieval,Applications,Patterns,

Refference:

I. A. M. Cohen, W. R. Hersh, “A survey of current work in biomedical text
mining”, Briefings in bioinformatics, Vol.: 6, Issue: 1, pp. 57–71, 2005.
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Breast Cancer Data using Data Mining Techniques”, International Journal of
innovations in Engineering and Technology, Vol.: 2 , Issue: 4, Pages: 139-
144, 2013.
III. G. R. Kumar, K. Nagamani, “A Framework of Dimensionality Reduction
utilizing PCA for Neural Network Prediction”, Proceedings of the
International Conference on Data Science and Management(ICDSM-2019),
Published in the book series Lecture Notes on Data Engineering and
Communications Technologies of Springer Publishing House.
IV. G. R. Kumar, K. Nagamani, “Banknote Authentication System utilizing
Deep Neural Network with PCA and LDA Machine Learning Techniques”,
International Journal of Recent Scientific Research, Vol.: 9, Issue: 12(D) ,
2018.
V. K. Sumathy, M. Chidambaram, “Text mining: Concepts, applications, tools
and issues-an overview,” International Journal of Computer Applications,
Vol.: 80, Issue: 4, 2013.
VI. M. V. Lakshmaiah, G. R. Kumar, G. Pakardin, “Frame work for Finding
Association Rules in Bid Data by using Hadoop Map/Reduce Tool”,
International Journal of Advance and Innovative Research, Vol.: 2, Issue:
1(I), PP:6-9, ISSN 2394 -7780, 2015.

VII. N. Padhy, D. Mishra, R. Panigrahi, “The survey of data mining applications
and feature scope,” arXiv preprint arXiv:1211.5723, 2012.
VIII. P. J. Joby, J. Korra, “Accessing accurate documents by mining auxiliary
document information,” in Advances in Computing and Communication
Engineering (ICACCE), Second International Conference on. IEEE, pp.
634–638, 2015.
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techniques”, International Journal of Computational Engineering Research,
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Applications, Vol.: 39, Issue: 12, pp. 11 303–11 311, 2012.
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methods for analyzing unstructured information”, Springer Science and
Business Media, 2010.
XII. S. R. Basha, J. K. Rani, “A Comparative Approach of Dimensionality
Reduction Techniques in Text Classification”, Engineering, Technology &
Applied Science Research, Vol.: 9, Issue: 6, pp. 4974-4979, 2019.
XIII. S. R. Basha, J. K. Rani, J. J. C. P. Yadav, “A Novel Summarization-based
Approach for Feature Reduction Enhancing Text Classification Accuracy”,
Engineering, Technology & Applied Science Research, Vol.: 9, Issue: 6, pp.
5001-5005, 2019.
XIV. S. R. Basha, J. K. Rani, J. J. C. P. Yadav, G. R. Kumar , “Impact of
featureselection techniques in Text Classification: An Experimental study”,
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XV. W. Fan, L. Wallace, S. Rich, Z. Zhang, “Tapping the power of text mining,”
Communications of the ACM, Vol.: 49, Issue: 9, pp. 76–82, 2006.
XVI. Z. Wen, T. Yoshida, X. Tang, “A study with multi-word feature with text
classification,” in Proceedings of the 51st Annual Meeting of the ISSS-2007,
Tokyo, Japan, Vol.: 51, p. 45, 2007.

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Abstract:

Over the internet and other network applications, the need for security is increasing each day due to its wide usage. There are a number of algorithms that have been developed for the secure transmission of data. This paper presents a novel approach for the generation of key using the Advanced Encryption Standard (AES) algorithm along with the Flower Pollination Algorithm (FPA). This combination is termed as Modified AES (MAES). Initially, a plain text of 128 bits is the input to this algorithm. This text is converted into a cipher text. The key generation is important for the generation of the S-Box (substitution box). The key generation in the proposed work is done using the Flower Pollination Algorithm. This step is done to generate the keys in such a way that the complexities of the S-Box enhances. This improves the security of the proposed approach for data transmission in a network. Then encryption is done. This is followed by decryption. Finally, the 128-bit plain text is retrieved at the receiver’s side. The MAES algorithm was compared with other traditional cryptographic algorithms. The proposed MAES algorithm yielded outstanding results.

Keywords:

Modified Advanced Encryption Standard Algorithm,Flower Pollination Algorithm,Security,Encryption,Decryption,Key,

Refference:

I. A. A. Yavuz, F. Alagöz, E. Anarim, “A new multi-tier adaptive military
MANET security protocol using hybrid cryptography and
signcryption.” Turkish Journal of Electrical Engineering & Computer
Sciences, Vol.: 18, Issue: 1, pp. 1-22, 2010.
II. A. Kushwaha, H. R. Sharma, A. Ambhaikar, “Selective Encryption Using
Natural Language Processing for Text Data in Mobile Ad Hoc Network.”
In Modeling, Simulation, and Optimization, pp. 15-26, 2018
III. B. Bala, L. Kamboj, P. Luthra, “Secure File Storage in Cloud Computing
using Hybrid Cryptography, International Journal of Advanced Research in
Computer Science, Vol.: 9, Issue: 2, pp. 773-776, 2018.
IV. B. Pradhan, S. Sengupta, “Chaotic-cipher based memory efficient symmetric
key cryptosystem.” In 2018 Emerging Trends in Electronic Devices and
Computational Techniques, 2018.
V. Ç. Ünal, S. Kaçar, A. Zengin, I. Pehlivan, “A novel hybrid encryption
algorithm based on chaos and S-AES algorithm.” Nonlinear Dynamics 92,
Issue: 4, pp. 1745-1759, 2018.

VI. D. Parashar, S. Roy, N. Dey, V. Jain, U. S. Rawat, “Symmetric Key
Encryption Technique: A Cellular Automata Based Approach.” In
Proceedings of CSI Cyber Security, pp. 59-67, 2018.
VII. E. B. Kavun, H. Mihajloska, T. Yalçin, “A Survey on Authenticated
Encryption–ASIC Designer’s Perspective”, ACM Computing Surveys ,
Vol.: 50, Issue: 6, pp. 1-21, 2017.
VIII. G. J. Krishna, R. Vadlamani, S. N. Bhattu, “Key Generation for Plain Text
in Stream Cipher via Bi-Objective Evolutionary Computing”, Applied Soft
Computing, 2018.
IX. G. Kalpana, P. V. Kumar, S. Aljawarneh, R. V. Krishnaiah, “Shifted
Adaption Homomorphism Encryption for Mobile and Cloud
Learning”, Computers & Electrical Engineering , Vol.: 65, pp.178-195,
2018.
X. J. Liu, C. Fan, X. Tian, Q. Ding, “Optimization of AES and RSA Algorithm
and Its Mixed Encryption System.” In International Conference on
Intelligent Information Hiding and Multimedia Signal Processing, pp. 393-
403, 2017.
XI. K. S. Reddy, V. U. Kumar, “A Practical Approach for Secured Data
Transmission using Wavelet based Steganography and Cryptography”,
International Journal of Computer Applications, Vol.: 67, Issue: 10, 2013.
XII. K. S. Reddy, V. U. Kumar, “Secured Data Transmission using Wavelet
based Steganography and Cryptography”, International Journal of
Computers & Technology, Vol.: 6, Issue: 1, 2013.
XIII. K. V. N. Rao, P. K. Budda, K. Sruthi, “Authentication and Encryption Using
Modified Elliptic Curve Cryptography with Particle Swarm Optimization
and Cuckoo Search Algorithm.” Journal of The Institution of Engineers
(India): Series B, pp.1-9, 2018.
XIV. M. E. Hameed, M. M. Ibrahim, N. A. Manap, “Review on Improvement of
Advanced Encryption Standard (AES) Algorithm based on Time Execution,
Differential Cryptanalysis and Level of Security.” Journal of
Telecommunication, Electronic and Computer Engineering, Vol.: 10, Issue:
1, pp.139-145, 2018.
XV. M. Elhoseny, G. R. González, O. M. A. Elnasr, S. A. Shawkat, N.
Arunkumar, A. Farouk, “Secure medical data transmission model for IoTbased
healthcare systems.” IEEE Access, Vol.: 6. pp. 20596-20608, 2018.
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cryptography protocals in Network Security”, International journal of Advanced Research computer science and Software Engineering, Vol.: 2,
Issue: 6, 2012.
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Mobile Agent Network Security”, Journal of Electronic science and
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Security”, International Journal of computational Engineering & research,
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auditing for securing big data storage in cloud computing”, Information
Sciences , Vol.: 380 , pp.101-116, 2017.
XX. M. U. Bokhari, Q. M. Shallal, Y. K. Tamandani, “Reducing the Required
Time and Power for Data Encryption and Decryption Using K-NN Machine
Learning.” IETE Journal of Research, pp.1-9, 2018.
XXI. P. Dixit, A. K. Gupta, M. C. Trivedi, V. K. Yadav. “Traditional and Hybrid
Encryption Techniques: A Survey”, In Networking Communication and Data
Knowledge Engineering, pp. 239-248, 2018.
XXII. P. Li, K. T. Lo, “A Content-Adaptive Joint Image Compression and
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pp. 1960-1972, 2018.
XXIII. R. D. Gill, N. Kapur, H. S. Gill, “Increase Security of Data With Respect to
Both Confidentiality and Integrity over Cloud”, International Journal of
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XXIV. T. Hanqi, Q. T. Sun, X. Yang, K. Long, “A Network Coding and DES Based
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XXV. Ü. Çavuşoğlu, A. Zengin, I. Pehlivan, S. Kaçar, “A novel approach for
strong S-Box generation algorithm design based on chaotic scaled
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(PKI).” International Journal of Information Management , Vol.: 38, Issue: 1,
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Subexpression Elimination Algorithm.” Journal of Circuits, Systems and
Computers, Vol.: 27, Issue: 11, pp.1-11, 2018.

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Abstract:

Oscillators are used to convert Direct Current (DC) from power supply to an Alternating Current (AC) signal. Oscillatory behavior is ubiquitous in all physical systems, especially in electronic and optical. This paper present a inverter based (three stage) and delay cell based (three and five stage) Ring Oscillators (ROs).ROs was simulated using Cadence tools and its performance was evaluated based on different parameters having with 7.79GHz frequency (90nm technology), wide tuning- range from 11.58 GHz to 16.62 GHz (90 nm technology), Phase noise of - 101dBc/Hz (90 nm technology) and average power of 8.83μW (45 nm technology) .All these parameters are analyzed using CMOS technologies in 45nm, 90nm and 180nm technologies.

Keywords:

Ring oscillator,Voltage Controlled Oscillator,PLL,Communication systems,

Refference:

I. B. Razavi, R. F. Microelectronics, Prentice Hall PTR, 1997.
II. H. Yoon, Y. Lee, J. J. Kim, J. Choi, “A wideband dual-mode LC-VCO with a
switchable gate-biased active core”, IEEE Trans. Circuits Syst. II, Exp.
Briefs, Vol.: 61, Issue: 5, pp. 289–293, 2014.
III. J. A. Hou, Y. H. Wang, “A 5 GHz differential colpitts CMOS VCO using the
bottom PMOS cross-coupled current source”, IEEE Microw.Wireless
Component Lett., Vol.: 19, Issue: 6, pp. 401–403, 2009.

IV. J. C. Chien, L. H. Lu, “Design of wide-tuning-range millimeter-wave CMOS
VCO with a standing-wave architecture”, IEEE J. Solid-State Circuits, Vol.:
42, Issue: 9, pp. 1942–1952, 2007.
V. J. L. González, F. Badets, B. Martineau, D. Belot, “A 56-GHz LC-tank VCO
with 17% tuning range in 65-nm bulk CMOS for wireless HDMI”, IEEE
Trans. Microw. Theory Techn., Vol.: 58, Issue: 5, pp. 1359–1366, 2010.
VI. M. T. Hsu, P. H. Chen, “5G Hz low power CMOS LC VCO for IEEE
802.11a application”, in Proc. Asia-Pacific Microw. Conf, pp. 263–266,
2011.
VII. N. Ramanjaneyulu, D. Satyanarayana, K. S. Prasad, “Design of a 3.4 GHz
Wide-Tuning-Range VCO in 0.18 μm CMOS”, Lecture Notes in Networks
and Systems, Vol.: 5, pp-227-234, 2017.
VIII. N. Ramanjaneyulu, D. Satyanarayana, K. S. Prasad, “Design of a Three Stage
Ring VCO in 0.18 μm CMOS under PVT Variations”, International Journal
of Computer Applications, Vol.: 170, Issue: 8, pp. 35-39, 2017.
IX. P. H. Hsieh, J. Maxey, C. K. Yang, “Minimizing the supply sensitivity of a
CMOS ring oscillator through jointly biasing the supply and control
voltages”, IEEE J. Solid-State Circuits, Vol.: 44, Issue: 9, pp. 2488–2495,
2009.
X. P. K. Tsai, T. H. Huang, “Integration of current-reused VCO and frequency
tripler for 24-GHz low-power phase-locked loop applications”, IEEE Trans.
Circuits Syst. II, Exp. Briefs, Vol.: 59, Issue: 4, pp. 199–203, 2012.
XI. Q. Wu, S. Elabd, T. K. Quach, A. Mattamana, S. R. Dooley, J. McCue, P. L.
Orlando, G. L. Creech, W. Khalil, “A–189 dBc/Hz FOMT wide tuning range
Ka-band VCO using tunable negative capacitance and inductance
redistribution”, Proc. IEEE Radio Freq. Integr. Circuits (RFIC) Symp, pp.
199–202, 2013.
XII. Y. J. Moon, Y. S. Roh, C. Y. Jeong, C. Yoo, “A 4.39–5.26 GHz LC-tank
CMOS voltage-controlled oscillator with small VCO-gain variation”, IEEE
Microw. Wireless Compon. Lett., Vol.: 19, Issue: 8, pp. 524–526, 2009.
XIII. Z. Z. Chen, T. C. Lee, “The design and analysis of dual-delay-path ring
oscillators”, IEEE Trans Circuits Syat.I, Vol.: 58, Issue: 3, pp. 470-478, 2011.

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Abstract:

In this paper Modelling, position detection and torque ripple analysis of switched reluctance motor(SRM) is investigated under variable loads. SRM is gaining popularity over conventional induction motors with its simple structure, high reliability and high speed operations. Nonlinear mathematical model of a 8/6 SRM is developed in this paper. Operation of asymmetrical converter fed to SRM is also elucidated. Proposed drive is controlled by a PI controller, the need of rotor position in flux estimation is also presented in this paper. The proposed drive is simulated in MATLAB Simulink under variable load conditions. In simulation effect of load on source current, torque, torque error, speed, and speed error is analysed.

Keywords:

SRM,PI controller,Torque ripples,Modelling,

Refference:

I. E. G. Shehata, “Speed sensoreless torque control of an IPSM drive with online
stator resistance estimation using reduced order EKF. Electr.Power Energy
Syst, Vol.: 47, pp. 378–386, 2013.
II. H. Majid, F. Mohammad, “Adaptive intelligent speed control of switched
reluctance motors with torque ripple reduction. Energy Convers.Manage, Vol.:
48, pp. 1028–1038, 2008.
III. I. Hussain, “Minimization of torque ripple in SRM drives. IEEE Trans. Ind.
Electron, Vol.: 49, pp. 28–39, 2002.
IV. J. Faiz, G. H. S. Khosroshahi, “Torque ripple reduction in switched reluctance
motor by optimal commutation strategy using a novelreference torque. Electr.
Power Compon. Syst, Vol.: 30, pp. 769–782, 2002.
V. K. M. Rahman, M. Ehsami, “Performance analysis of electric motor drives for
electric and hybrid electric vehicle applications. IEEE Trans. Power Electron,
Vol.: 1, pp. 49–56, 1996.
VI. M. N. Anwar, I. Hussain, A.V. Radun, “Comprehensive design methodology
for switched reluctance machines”, IEEE Trans Ind. Appl, Vol.: 37, pp. 1684–
1692, 2001.
VII. M. R. Harris, “Comparison of design and performance parameters in switched
reluctance and induction motors”, Fourth Int. Conf. Electrical Machines and
Drives, pp. 303–307, 1989.
VIII. M. Rodrigues, P. J. C. Branco, W. Suemitsu, “Fuzzy logic torque ripple
reduction by turn-off angle compensation for switched reluctancemotors. IEEE
Trans. Ind. Electron, Vol.: 48, pp. 711–715, 2001.
IX. N. C. Sahoo, S. K. Panda, P. K. Dash, “A current modulation scheme for
direct torque control of switched reluctance motor using fuzzy
logic.Mechatronics, Vol.: 10, pp. 353–370, 2000.

X. R. Krishnan, “Switched Reluctance Motor Drives. Modeling, Simulation,
Analysis, Design and Applications. CRC Press, Boca Raton, 2001.
XI. T. J. E. Miller, “Electronic control of switched reluctance motors,”Newness
power engineering series, Oxford, UK, 2001.
XII. V. P. Vujicic, “Minimization of torque ripple and copper losses in SR drives.
IEEE Trans. Power Electron, Vol.: 27, pp. 388–399, 2012.
XIII. Z. Lin, S. Reay, W. Williams, “Torque ripple reduction in switched reluctance
motor drives using B-spline neural networks. IEEE Trans. Ind.Appl, Vol.: 2,
pp. 1445–1453, 2006.

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Abstract:

For expanding their business portfolios, organisations using strategy of mergers and amalgamations. It employs a significant impact on internal and external stakeholders. Hence, before making investment decisions shareholders should consider the announcements of corporate restructuring. This study suggests to evaluate the impact of merger announcement on corporate performance and investment decisions of investors.

Keywords:

Mergers,Acquisitions,Profitability,

Refference:

For expanding their business portfolios, organisations using strategy of
mergers and amalgamations. It employs a significant impact on internal and external
stakeholders. Hence, before making investment decisions shareholders should
consider the announcements of corporate restructuring. This study suggests to
evaluate the impact of merger announcement on corporate performance and
investment decisions of investors.I. A. Shukla, M. G. Gekara, “Effects of Multinational Mergers and Acquisitions
on Shareholders’ Wealth and Corporate Performance”, The IUP Journal of
Accounting Research & Audit Practices, Vol.: 9, Issue: 1, pp: 44-62, 2010.
II. F. Schiavone, “Mergers, Acquisitions and the Determinants of national
competitiveness in the European Electricity Industry: An Empirical Test”,
Journal of General Management, Vol.: 37, Issue: 4, pp: 71-85, 2012.
III. F. Singh, M. Mogla, “Impact of Mergers on Profitability of Acquiring
Companies”, The Icfai University Journal of Mergers & Acquisitions, Vol.:
5, Issue: 2, pp: 60.-76, 2010.
IV. F. Singh, M. Mogla, “Profitability Analysis of Acquiring Companies”, The
IUP Journal of Applied Finance, Vol.: 16, Issue: 5, pp: 72-83, 2010.
V. G. M. Dhinaiya, “Impact of Mergers & Acquisitions on the Performance of
Companies”, International Journal of Research in Commerce and
Management, Vol.: 3, Issue: 9, pp: 102-106, 2012.
VI. N. M. Leepsa, C. S. Mishra, “Post Merger Financial Performance: A Study
with reference to Selected Manufacturing Companies in India”, Journal of
Finance and Economics, Vol.: 8, Issue: 3, pp: 6-17, 2012.
VII. N. Rani, S. S.Yadav, P. K Jain, “Post-Merger & Amalgamations Operating
Performance of Indian Acquiring Firms: A Du Point Analysis”, International
Journal of Economics and Finance, Vol.: 5, Issue: 8, pp: 65-73, 2013.
VIII. R. C. Ferrer, “An Empirical Investigation of the Impact of Merger and
Acquisition on the Firms Activity Ratios”, Journal of International
Management Studies. Vol.: 12, Issue: 2, pp: 68-73, 2012.
IX. R. Kouser, I. Saba, “Effects of Business Combination on Financial
Performance: Evidence from Pakistan Banking Sector”, Australian Journal of
Business and Management Research, Vol.: 1, Issue: 8, pp: 54-64, 2011.

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