Malwares : Creation and Avoidance
Review Paper | Journal Paper
Vol.7 , Issue.4 , pp.179-183, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.179183
Abstract
In today’s world, hackers are improvising their various techniques for creating a malware which is usually a malicious software product. These malwares are basically created by hackers and it happens mostly in parts of Russia and Europe. Hackers usually use malicious software or malware to attack victims and enable multiple forms of cyber security. On the other hand, the developers establish different techniques to produce anti-malware systems with effective detection methods for protection on computers. This paper relates with the creation of malware by “Darkcomet RAT-v5.3”. A detailed survey has been conducted on the current status of malware creation and infection and efforts are made to improve anti-malware or malware detection systems.
Key-Words / Index Term
Malwares, hackers, security, malware detection
References
[1] Fan Wu, Hira Narang, Dwayne Clarke. (2014). An Overview of Mobile Malware and Solutions, Journal of Computer and Communications.
[2] Hieu Le Thanh. (2013). Analysis of Malware Families on Android Mobiles: Detection Characteristics Recognizable by Ordinary Phone Users and How to Fix It, Journal of Information Security.
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Citation
Durganath Rajesh, Adnaan Arbaaz Ahmed, M.I. Thariq Hussan, Venkateswarlu Bollapalli, "Malwares : Creation and Avoidance," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.179-183, 2019.
A Comparative Study of Different Machine Learning Tools
Research Paper | Journal Paper
Vol.7 , Issue.4 , pp.184-190, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.184190
Abstract
Machine Learning is the science of making computers learn and act like humans by feeding data and information without being explicitly programmed. It imbibes the philosophy of human learning, i.e. learning from expert guidance and from experience. The objective of this paper is to venture into the arena of machine learning from evolution to types of machine learning. In addition to, this paper also insights the comparison between various programming and non programming tools of machine learning
Key-Words / Index Term
machine learning, supervised, unsupervised, reinforcement, active, semi supervised
References
[1] Dutt S., Chandramouli S. and Das A. K. (2019). Machine Learning, Published by Pearson Indian Education Services.
[2] Jawad F., Choudhury T. U. R., Najeeb A., Fariha M., Nusrat Chamon, R., Rashedur M. (2015). Data mining techniques to analyze the reason for home birth in Bangladesh, IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, pp. 225-230.
[3] Kumar A., Alzubi J. and Nayyar A. (2018). Machine learning from theory to algorithms: An overview, Journal of Physics: Conference Series.
[4] Nithya, B. and Ilango V. (2017).Predictive analytics in health care using machine learning tools and techniques, International Conference on Intelligent Computing and Control Systems (ICICCS) (IEEE Explore).
[5] R Sujatha, S. Sree Dharinya, E P Ephzibah, R Kiruba Thangam (2019).International Journal of Engineering and Advanced Technology (IJEAT), ISSN: 2249 – 8958, Volume-8 Issue-3, pp. 405-409.
[6] Raghavendra S, Santosh K J, Raghavendra B. K. (2019). Performance Evaluation of Machine Learning Techniques in Diabetes Prediction, International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-8 Issue-3, pp.75-79.
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Citation
Himani Maheshwari, Pooja Goswami, Isha Rana, "A Comparative Study of Different Machine Learning Tools," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.184-190, 2019.
E-Certificate Authentication System Using Blockchain
Research Paper | Journal Paper
Vol.7 , Issue.4 , pp.191-195, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.191195
Abstract
The traditional system of using and maintaining paper certificates is now facing a threat of forging and modifying the data. This forging of data on the certificates has become a very easy task, which reduces the credibility of paper certificates. Thus, there is a need of an effective anti-forge mechanism to reduce the counterfeiting of certificates. An E-certificate generation and authentication system based on blockchain technology is so proposed. Blockchain provides incorruptible, unmodifiable and encrypted data features. Thus, by using blockchain, an E-certificate with features like anti-counterfeit, anti-forge and verifiability is generated. Students won’t be able to forge the contents of E-certificates at all. The system, because of blockchain technology, will help to solve the problem of fraud certification by enhancing the credibility of the certificates. The system will also save the paper and management costs. Electronically, the loss risks of the certificates will be reduced. In short, the system is all beneficial to us. The working of the system in brief is: A valid electronic file of the certificate i.e. an E-certificate is generated on student’s request. At the same time, that student’s record is stored in the blocks of blockchain by making use of hash values. Along with E-certificate, a related QR code or unique serial number is also provided to the student. And then, the demand unit (e.g. company to which student applied for a job) can check the authenticity of the electronic file using the QR code or unique serial number which is based on the data stored in the blockchain.
Key-Words / Index Term
E-Certificate,Blockchain,Cryptography,Anti-forge
References
[1] Lein Harn and Jian Ren, “Generalized Digital Certificate for User Authentication and Key Establishment for Secure Communication”, IEEE Transactions on Wireless Communications, Vol. 10, Issue 7, July 2011.
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[3] Nwachukwu-Nwoceafor K.C, Igbajar Abraham, “Designing an Automatic Web Based Certificate Verification System for Institutions”, Journal of Multidisciplinary Engineering Science and Technology (JMEST), Vol. 2, Issue 12, December 2015.
[4] Ravinder Reddy B, Pavan Kumar, “Access Control and Data Security in Online Document Verification System”, In the proceedings of 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), India, 2016.
[5] Sajan Ambadiyil, Haritha Sree G S, V.P.Mahadevan Pillai ,“Facial Periocular Region based Unique ID Generation and One to One Verification for Security Documents”, In the proceedings of 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), India, 2016.
[6] Hamdi A. Ahmed, Jong Wook Jang, “Higher Educational Certificate Authentication System Using QR Code Tag”, International Journal of Applied Engineering Research, Vol. 12, Issue 20, 2017.
[7] Ahmed Dalhatu Yusuf, Moussa Mahamat Boukar, Shahriar Shamiluulu, “Automated Batch Certificate Generation and Verification System”, In the proceedings of 2017 13th International Conference on Electronics, Computer and Computation (ICECCO), Nigeria, 2017.
[8] N.S.Tinu, “A Survey on Blockchain Technology- Taxonomy, Consensus Algorithms and Applications”, International Journal of Computer Sciences and Engineering(IJCSE), Vol. 6, Issue 5, May 2018.
[9] Jiin-Chiou Cheng, Narn-Yih Lee, Chein Chi, Yi-Hua Chen, “Blockchain and Smart Contract for Digital Certificate”, In the proceedings of IEEE International Conference on Applied System Innovation 2018(ICASI), Japan, 2018.
[10] Guang Chen, Bing Xu, Manli Lu and Nian-shing Chen, “Exploring blockchain technology and its potential application for education”, Springer Open- Smart Learning Environments Journal, 2018.
Citation
A.G. Said, R.P. Ashtaputre, B. Bisht, S.S. Bandal, P.N. Dhamale, "E-Certificate Authentication System Using Blockchain," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.191-195, 2019.
Contribution of Word length in Deletion Error analysis of Punjabi Typed Text
Survey Paper | Journal Paper
Vol.7 , Issue.4 , pp.196-198, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.196198
Abstract
Word Length( i.e. number of characters )plays an important role in non-word error distribution of typed text .It plays an important role in Natural Language Interfaces, spellchecker, OCR and language related technology development etc .Though considerable work has been done in the area for English and related languages, the Indian Language scenario is still far behind. This paper focuses on the contribution of word length in deletion error analysis of Punjabi in Non-word Error distribution of Punjabi Typed Text that can be further useful in automatic text error correction in Punjabi language, the world’s most widely spoken language, This paper also give a brief statistical report about the distribution of various type of errors (substitution, insertion, deletion, transposition etc.) in Punjabi language.
Key-Words / Index Term
Addak, Gurmukhi, Non-word, Bindi
References
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[9] Wagner, Robert A. & Fischer, Michael J, `The string-to-string correction problem`, Journal of the A.C.M., vol.21, no.1, pp168-173, January 1974.
[10] Meenu Bhagat, ”Contribution of ‘Addak’and ‘Bindi’ in Non word Error Pattern analysis of Punjabi Typed Text”, “International Journal of Computer Sciences and engineering” vol. 5 issue 9.
Citation
Meenu Bhagat, "Contribution of Word length in Deletion Error analysis of Punjabi Typed Text," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.196-198, 2019.
Convolution Neural Network Based Automatic License Plate Recognition System
Research Paper | Journal Paper
Vol.7 , Issue.4 , pp.199-205, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.199205
Abstract
For the past few years, the automatic license plate recognition system has gained more importance in the development of smart cities for vehicle management, investigation of stolen vehicles, and traffic monitoring and control. In this paper, we propose an efficient Automatic License Plate Recognition system (ALPR) for the Indian license plate. ALPR first localizes the license plate by using an adaptive sliding window technique with the help of a convolution neural network classifier. Then, the characters are segmented from the license plate by using the morphological operations. Segmented characters are converted into text upon using Transfer learning techniques on Mobilenet. ALPR was tested and has outperformed traditional license plate recognition system. Also, the performance of ALPR was satisfactory in variation in illumination condition, text style, uncanny and skewness of the license plate. The ALPR system can be integrated with the Speed Calculation System so that the authority can notify the traffic offender.
Key-Words / Index Term
Automatic License Plate Recognition system(ALPR), convolution neural network classifier(CNNC), Optical character recognition(OCR), adaptive sliding window technique(ASW), MobileNet
References
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[4] Lin, C.-H., Lin, Y.-S., & Liu, W.-C. (2018). An Efficient License Plate Recognition System Using Convolution Neural Networks. IEEE Conferenceon Applied System Innovation 2018 (pp. 224-227). IEEE.
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Citation
Aman Raj, Devanshu Dubey, Abhishek Mishra, Nikhil Chopda, Nishant M. Borkar, Vipul S. Lande, "Convolution Neural Network Based Automatic License Plate Recognition System," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.199-205, 2019.
Utility Association Rule Mining – A Comprehensive Study
Research Paper | Journal Paper
Vol.7 , Issue.4 , pp.206-210, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.206210
Abstract
Utility mining is gaining attention towards researchers, as it discovers semantic significance among the items in a database. Utility association rule mining is one of utility mining techniques that retrieves highly profitable and highly associated products in a database. Many researchers started to replace traditional association rule mining with utility association rule mining, since utility association rules can reflect both association and semantic significance among the products retrieved from the database. Utility based association rule mining can be applied on various domains like Bio-informatics, Recommender systems, Medical database, Web mining, Image mining. This research work aims to provide in depth study on utility based association rule mining. The work also illustrates the need for utility association rules, by providing drawbacks of traditional association rules. The work also lists existing utility association rules algorithms.
Key-Words / Index Term
Utility mining is gaining attention towards researchers, as it discovers semantic significance among the items in a database. Utility association rule mining is one of utility mining techniques that retrieves highly profitable and highly associated products in a database. Many researchers started to replace traditional association rule mining with
References
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Citation
C. Sivamathi , S. Vijayarani, "Utility Association Rule Mining – A Comprehensive Study," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.206-210, 2019.
A Novel Medical Image Watermarking using IWT
Research Paper | Journal Paper
Vol.7 , Issue.4 , pp.211-219, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.211219
Abstract
Transmission of restorative pictures among remote spots is a general practice in telemedicine. Medical images might be changed deliberately or coincidentally as the transmission of these may happen through unbound systems, for example, web. Prior to settling on any demonstrative choices, the medicinal specialist needs to check the integrity of Region of Interest (ROI) in the received medical images so as to maintain a strategic distance from wrong determination. Watermarking can be utilized for checking the integrity of medicinal images. We propose a novel watermarking strategy dependent on IWT. This proposition checks the integrity of ROI, distinguishes alters inside ROI, gives robustness to the information hidden inside RONI and recoups unique ROI if ROI is altered. Test results demonstrate that the proposed technique gives robustness to the watermark information inserted inside RONI and precisely identifies altered regions inside ROI and recuperates the original ROI.
Key-Words / Index Term
Watermarking, ROI (Region of Interest), RONI (Region of Non Interest), IWT (Integer Wavelet Transform)
References
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[5]. Rayachoti Eswaraiah and Edara Sreenivasa Reddy:, "Robust medical image watermarking technique for accurate detection of tampers inside region of interest and recovering original region of interest", IET Image Process., pp. 1–11, 2015.
[6]. R. Eswaraiah and E. Sreenivasa Reddy:, "Medical Image Watermarking Technique for Accurate Tamper Detection in ROI and Exact Recovery of ROI`, Hindawi Publishing Corporation, International Journal of Telemedicine and Applications, Volume 2014.
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Citation
G. Pavana Sahithi, Ch. Divya, B. Ratna Priya, D. Anusha, R. Eswaraiah, "A Novel Medical Image Watermarking using IWT," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.211-219, 2019.
Blending Biometric To Generate Symmetric Key for Cryptosystem
Survey Paper | Journal Paper
Vol.7 , Issue.4 , pp.220-224, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.220224
Abstract
Most of the human finds it hard to remember long cryptographic keys and it is highly impossible to remember the lengthy keys used in the cryptosystem nowadays. To overcome this memory related problem, the research community all around the world has been exploring approaches to utilize biometric features of the user to generate the secret key to be utilized in the encryption and decryption process and completely evade the difficulty of remembering the secret keys. This paper focuses on incorporation of the client`s biometric features to generate the secret key, in order to build the key arbitrary to intruder who is lacking of essential information about the client`s biometrics. The features present in the fingerprints are extracted in the form of 16X16 bit matrix and then the binary rows and columns in the extracted feature matrix are processed to produce a foolproof secret key. To strengthen the security measures and to nullify the intruders aim to crack the secret key, this paper blends two fingerprints of the user (sender and the receiver) and produces the secret symmetric key. Since two fingerprints are considered and the key extracted from each fingerprints are fused together in the formation of the secret key, the overall security of the system is improved considerably.
Key-Words / Index Term
biometric, security, symmetric, encryption, public key, cryptographic, fingerprints
References
[1] Nageshkumar.M, Mahesh.PK and M.N. ShanmukhaSwamy, “An Efficient Secure Multimodal Biometric Fusion Using Palmprint and Face Image”, IJCSI International Journal of Computer Science Issues, Vol. 2, 2009.
[2] Yan Yan and Yu-Jin Zhang, “Multimodal Biometrics Fusion Using Correlation Filter Bank", in proceedings of 19th International Conference on Pattern Recognition, pp. 1-4, Tampa, FL, 2008.
[3] T. Zhang, X. Li, D. Tao, and J. Yang, “Multi-modal biometrics using geometry preserving projections”, Pattern Recognition, vol. 41, no. 3, pp. 805-813, 2008.
[4] Muhammad Khurram Khan and Jiashu Zhang, "Multimodal face and fingerprint biometrics authentication on space-limited tokens", Neurocomputing, vol. 71, pp. 3026-3031, August 2008.
[5] Yi Wang ,Jiankun Hu and Fengling Han, "Enhanced gradient-based algorithm for the estimation of fingerprint orientation fields", Applied Mathematics and Computation, vol. 185, pp.823–833, 2007.
Citation
J.Lenin, B. Sundaravadivazhagan, M. Sulthan Ibrahim, "Blending Biometric To Generate Symmetric Key for Cryptosystem," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.220-224, 2019.
Real Time and Low Cost Smart Home Automation System Using Internet of Things Environment
Research Paper | Journal Paper
Vol.7 , Issue.4 , pp.225-229, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.225229
Abstract
This paper represents the real time Home Automation System measuring cost efficiency using IoT environment. The logic behind this paper is to control the home appliances like any electronic gadgets through Google Assistant which links with the IFTTT server. If the condition satisfies, then the action will be taken to the Adafruit MQTT server to get communication with the home appliances. We have also presented the way to replace the manual system and to save the electricity and human energy in this paper.
Key-Words / Index Term
Internet of Things (IoT), Home Automation, ESP8266 ESP-12E NodeMCU WiFi module, Google assistant
References
[1] M. Mohsin, S. Nandanwar, M. Shingate, “Home Automation and Security System Using Android ADK”, International Journal of Electronics Communication and Computer Technology, Vol. 3, Issue 2, March 2013.
[2] D. Naresh, B. Chakradhar, S. Krishnaveni, “Bluetooth Based Home Automation and Security System Using ARM9”, International Journal of Engineering Trends and Technology, Vol. 4, Issue 9, September 2013.
[3] D. Rohith, G. Mounica, K. Vinod, “Design and Implementation of an Embedded Web Controller for Automation”, International Journal of Emerging Technology and Advanced Engineering, Vol. 4, Issue 9, September 2014.
[4] M. Khatu, N. Kaimal, P. Jadhav, S. A. Rizvi, “Implementation of Internet of Things for Home Automation”, International Journal of Emerging Engineering Research And Technology, Vol. 3, Issue 2, February 2015.
[5] V. Sagar K N, Kusuma S M, “Home Automation Using Internet of things”, International Research journal of Engineering and Technology, Vol. 2, Issue 3, June 2015.
[6] K. Ghosh, K. Kalbhor, D. Tejpal, S. Haral, “Wireless Home Automation Technology Using Internet Of Things”, Internation Journal of Technical Research and Applications, Vol. 3, Issue 6 November, 2015.
[7] P. Bedekar, S. Nargundi, “A Review on Home Automation using Augmented Reality”, International Journal of Science and Research, Vol. 5, Issue 4, April 2016.
[8] S. Z. Z. Win, Z. M. Min, H. M. Tun, “Smart Security System For Home Appliances Control Based On Internet Of Things”, International Journal of Scientific & Technology Research, Vol. 5, Issue 6, June 2016.
[9] R. Ekatpure, D. Ingale, “Android based Interactive Home Automation System through Internet of Things”, International Journal of Sciennce and research, Vol. 5, Issue 7, July 2016.
[10] P. Rathod, S. Khizaruddin, R. Kotian, S. Lal, “Raspberry Pi Based Home Automation Using Wi-Fi, IOT and Android for Live Monitoring”, International Journal of Computer Science Trends and Technology, Vol. 5, Issue 2, March 2017.
[11] D. Purohit and M. Ghosh, “Challenges and Types of Home Automation Systems”, International Journal of Computer Science and Mobile Computing, Vol. 6, Issue 4, April 2017.
[12] Kishore. P, T. Veeramanikandasamy, K. Sambath, S. Veerakumar, “Internet of Things based Low-Cost Real-Time Home Automation and Smart Security System”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 6, Issue 4, April 2017.
[13] X. Mi, Y. Zhang, F. Qian, X. Wang, “An empirical Characterization of IFTTT:Ecosystem, Usage, and Performance”, Proceedings IMC ’17, ACM New York, NY, USA,November 1-3, 2017.
[14] T. Kim, J. Lim, H. Son, B. Shin, D. Lee, and S. J. Hyun, “A Multi-Dimensional Smart Community Discovery Scheme for IOT-Enriched Smart Homes”, ACM Transactions on Internet Technology, Vol. 18, Issue 1, December 2017.
[15] G. A. Ar. de Oliveira, R. W. de Bettio, A. P. Freire, “Accessibility of the smart home for users with visual disabilities: an evaluation of open source mobile applications for home automation”, Proceedings of IHC ’16, ACM New York, NY, USA, October 04-07, 2016.
[16] M. N. Kadima, F. Jafari, “A Customized Design of Smart Home using Internet-of-Things”, Proceedings of ICIME 2017, ACM New York, NY, USA, October 09-11,2017.
[17] E. Fytrakis, I. Georgoulas, J. Part, Y. Zhu, “Speech-Based Home Automation System”, Proceedings of British HCI ’15, ACM New York, NY, USA, July 13-17, 2015.
Citation
Deepjyoti Choudhury, "Real Time and Low Cost Smart Home Automation System Using Internet of Things Environment," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.225-229, 2019.
Modelling and Simulation of a two area system using a Phasor Measurement Unit
Research Paper | Journal Paper
Vol.7 , Issue.4 , pp.230-237, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.230237
Abstract
The character played by phasor measurement units (PMU) in power grid monitoring systems today showcases the significance and usefulness of this device. There is a major challenge regarding the design and implementation of PMUs today as the commercial PMU vendors strongly look after their hardware and software designs keeping it away from researchers. Wide Area Monitoring is becoming an emerging challenge for power system engineers and researchers due to complexity in the power system network. So, PMU is one such device that can challenge such issues in the power system. The proposed paper presents the design and implementation of a two area system in MATLAB/Simulink. The two area system is synchronized together and then the two PMUs are introduced in it to measure the respective parameters. The PMUs that are used in the analysis follows the IEEE C37.118-2011 standard. The functionality of the PMU was tested by performing experiments which measured magnitudes of voltage, current, phase angle and frequency of a balanced three phase signal from PMU. After this analysis, we have introduced a fault in the system to observe the post-measurements of PMU. The conducted experiments confirmed that the PMU protected the power system and also synchronized and estimated voltage magnitude, phase angle and frequency approximately.
Key-Words / Index Term
Phasor Measurement Unit, Two Area System, Synchrophasor, Power System Stability, Wide Area Monitoring Protection And Control(WAMPAC)
References
[1] Asad Waqar, Zeeshan Khurshid, Jehanzeb Ahmad, Muhammad Aamir, Muneeb Yaqoob, Imtiaz Alam , “Modeling and Simulation of Phasor Measurement Unit (PMU) for Early Fault Detection in Interconnected Two-Area Network”, IEEE System Journal,2018.
[2] Shabana Urooj & Vani Sood, “Phasor Measurement Unit (PMU) Based Wide Area Protection System” 2nd International Conference on Computing for Sustainable Global Development (INDIACom), 2015.
[3] Debomita Ghosh ,Chandan Kumar ,T. Ghose D.K. Mohanta, “Performance Simulation of Phasor Measurement Unit for Wide Area Measurement System” International Conference on Control, Instrumentation, Energy & Communication, Calcutta, India,2014.
[4] Waheed Ur Rahman, Muhammad Ali, Amjad Ullah, Hafeez Ur Rahman, Majid Iqbal, Haseeb Ahmad, Adnan Zeb, Zeeshan Ali, M. Ahsan Shahzad, “Advancement in Wide Area Monitoring Protection and Control Using PMU’s Model in MATLAB/SIMULINK”, Smart Grid and Renewable Energy, pp.294-307, 2012.
[5] Phadke, A.G. & J.S. Trop, and M.G. Adamiak, “Synchronized phasor Measurements and their applications” Vol. 1, Springer, 2017.
[6] Anuprasad P, Stany E George, “Power System Observability and Fault Detection Using Phasor Measurement Units (PMU)”, International Journal of Science and Research (IJSR), Volume.5 Issue 9, pp.2319-7064,2016.
[7] K.V.S. Baba, S.R. Narasimhan, N.L. Jain; Amandeep Singh, Rahul Shukla, Ankit Gupta “Synchrophasor Based Real Time Monitoring of Grid Events in Indian Power System”, IEEE Conference, 2016.
[8] Markos Asprou, Saikat Chakrabarti &Elias Kyriakide,”A Two-Stage State Estimator for Dynamic Monitoring of Power Systems”, IEEE System Journal, 2014.
[9] Pathirikkat Gopakumar1, Maddikara Jaya Bharata Reddy1, Dusmanta Kumar Mohanta, “Adaptive fault identification and classification methodology for smart power grids using synchronous phasor angle measurements”, IET Generation Transmission Distribution, Vol. 9, Iss. 2, pp. 133–145, 2015.
[10] Pathirikkat Gopakumar, Maddikara Jaya Bharata Reddy & Dusmanta Kumar Mohanta, “Fault Detection and Localization Methodology for Self-healing in Smart Power Grids Incorporating Phasor Measurement Unit”, Taylor & Francis, Electric Power Components and Systems, Vol. 43 pp. 695–710, 2015.
[11] T. BHARATH KUMAR & M. UMA VANI, “Load Frequency Control In Two Area Power System Using ANFIS”, International Journal of Electrical and Electronics Engineering Research (IJEEER), Vol. 4, Issue 1, pp. 85-92, 2014.
[12] Pavel Chusovitin & Andrey Pazderin, “Small-signal stability monitoring using PMU”, IEEE Conference, 2014.
[13] Somudeep Bhattacharjee, Rupan Das, Gagari Deb, Brahma Nand Thakur “Techno-Economic Analysis of a Grid-Connected Hybrid System in Portugal Island” International Journal of Computer Sciences and Engineering Vol.-7, Issue-1, Jan 2019.
[14] S. Bhattacharjee, S. Chakraborty, B. B. Jena, S. Deb, and R. Das, “An Optimization Study of both On-Grid and Off-Grid Solar-Wind-Biomass Hybrid Power Plant in Nakalawaka, Fiji”. International Journal for Research in Applied Science and Engineering Technology, Vol.6, Issue4, pp.3822-3834, 2018
Citation
Sunpaul Debbarma, Priyanka Debbarma, Sangita Das Biswas, "Modelling and Simulation of a two area system using a Phasor Measurement Unit," International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.230-237, 2019.