Volume-08 , Special Issue-01 , Feb - 2020 Go Back

Named Entity Recognition (NER) is a task of identifying named entities from text written in Natural Language. In this task, a string of text in the form of sentence or paragraph is accepted as input and relevant nouns like names of people, places, organizations etc. that are mentioned in that string are identified. This task belongs Information Extraction of the field of Natural Language Processing (NLP). Significant amount of work has been carried out on named entities recognition, but most of the researches have been done for resource-rich languages and domains. It is a challenging task for an informal text and code-mixed text which complicates the process with its unstructured and incomplete information. In this paper, we propose a method of extracting named entities from code-mixed data with different machine learning based algorithms using content and contextual features extracted from code-mixed data.

Named Entity, Machine Learning, Support Vector Machine, Decision Tree, K-Nearest Neighbour

[1] Kalika Bali, Jatin Sharma, Monojit Choudhury, and Yogarshi Vyas. 2014. “i am borrowing ya mix-ing?” an analysis of english-hindi code mixing in facebook. In Proceedings of the First Workshop on Computational Approaches to Code Switching, pages 116–126.
[2] Yogarshi Vyas, Spandana Gella, Jatin Sharma, Ka-lika Bali, and Monojit Choudhury. 2014. Pos tagging of english-hindi code-mixed social media con-tent. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 974–979.
[3] Arnav Sharma, Sakshi Gupta, Raveesh Motlani, Piyush Bansal, Manish Srivastava, Radhika Mamidi, and Dipti M Sharma. 2016. Shallow parsing pipeline for hindi-english code-mixed social media text. arXiv preprint arXiv:1604.03136.
[4] Sudha Morwal, Nusrat Jahan, and Deepti Chopra. 2012. Named entity recognition using hidden markov model (hmm). International Journal on Natural Language Computing (IJNLC), 1(4):15–23.
[5] Rupal Bhargava, Yashvardhan Sharma, and Shubham Sharma. 2016a. Sentiment analysis for mixed script indic sentences. In Advances in Computing, Com-munications and Informatics (ICACCI), 2016 Inter-national Conference on, pages 524–529. IEEE.
[6] Asif Ekbal and Sivaji Bandyopadhyay. 2008. Bengali named entity recognition using support vector machine. In Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages.
[7] Deepak Gupta, Shubham Tripathi, Asif Ekbal, and Pushpak Bhattacharyya. 2016. A hybrid approach for entity extraction in code-mixed social media data. MONEY, 25:66.
[8] Irshad Ahmad Bhat, Manish Shrivastava, and Riyaz Ahmad Bhat. 2016. Code mixed entity extraction in indian languages using neural networks. In FIRE (Working Notes), pages 296–297.
[9] Vinay Singh, Deepanshu Vijay, Syed S. Akhtar, Manish Shrivastava. Named Entity Recognition for Hindi-English Code-Mixed Social Media Text. In Proceedings of the Seventh Named Entities Workshop, pages 27–35, Melbourne, Australia, July 20, 2018, Association for Computational Linguistics
[10] Alan Ritter, Sam Clark, Mausam, Oren Etzioni; Named Entity Recognition in Tweets: An Experimental Study; in Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, July, Year:2011, Address:,Edinburgh, Scotland, UK.

Suparna Arya, Amit Majumder, Sulabh Majumder, Aparajita kundu, Nuzhat shamim, Ira Nath, "Supervised Machine Learning approach for Extracting Named Entities from Hindi-English Mixed Social Media Text", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.1-4, 2020.

Human beings have been developing and designing since the stone age. They have worked for the betterment of society ever since. However, it is always not possible for them to attend a situation at a given time in person. Hence, the solution we came up with is a gesture-controlled robotic arm where we are controlling the device from a distant location. The project comprises mainly of two parts, viz, the sending and receiving part. In the sending part, we are using an MPU6050 3-axis gyroscope plus a 3-axis accelerometer sensor compiled with an Arduino nano micro-controller and an IR transmitter based bend sensor is used. Similarly, for transferring information, we are using an RF module. In another part. The thing that is happening in the robotic arm moves up, down, left, or right along with gripping according to the hand movement made by the user. Following the direction of the movement, the gripping process is brought about. The applications of this project can be found in the fields of biomedical, defense, industrial, and many others. Like in the medical field, during times of surgery, the doctors can carry out the operation even in his absence at that particular location. Also, in the field of defense, our robotic arm can be of great importance, like diffusing a bomb without the intervention of humans. Thus, in this era of science and technology, where the world says nothing is impossible, few factors provide limitations to this. So, by using this project, we tried to give a hand to reduce the problems of society.

Gesture, robotic arm, RF transmitter, receiver, Arduino nano

[1] Amithash E. Prasad, Murtuza Tambawala, “Human ControlledRemote Robotic Arm”(HCRRA).
[2] Norberto Pires, Pedro Neto, J, and A. Paulo Moreira, “Accelerometer- Based Control of an Industrial Robotic Arm,” published at IEEE Xplore
[3] Satyajit Sinari, Sunil Karamchandani, Amrita Aurora, Dharmesh Ruparel, “The Gesture Replicating Robotic Arm” at International Symposium on Computational and Business Development
[4] Rudiger Dillmann, “Teaching and learning of robot tasks via observation of human performance,” in Elsevier, Robotics and Autonomous Systems, vol. 47, no. 2-3, pp. 109-116, 2004.
[5] A. Skoglund, J. Aleotti, and T. Duckett, “Position teaching of a robot arm by demonstration with a wearable input device,” in InternationalConference on Intelligent Manipulation and Grasping (IMG04), Genoa, Italy, July 1- 2, 2004.

Raktim Pratihar, Debmalya Sadhukhan, Roberto Bhowmick, Anuron Mullik, Bansari Deb Majumder, "Implementation of PID control Based Hybrid Model for Gesture Controlled Robotic Arm", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.5-9, 2020.

In the given project entitled NYSE Data Analysis using Big Data (Apache Pig), a database of New York Stock Exchange collected from the open source of New York Stock Exchange daily report where we will analyse the data and produce the required output. Here, the data is referred to the daily stocks of all the companies or industries which is enlisted in the NYSE daily report. We will use the Apache Pig which is used to analyse large data sets representing them as data flows. It is designed to provide an abstraction over MapReduce, reducing the complexities of writing a MapReduce program. Basically, the MapReduce uses java program to execute and to analyse the dataset and it has to use certain logics to provide the desired output. Apache Pig gives us a better platform to do the work more efficiently and quickly using certain logical lines. Apache Pig is one of the best platforms for the analyzation of Big Data.

analyse, NYSE, Big Data, MapReduce, Apache Pig

[1] http://www.thesojo.net/key-domains-with-opportunities-in-big-data/
[2] http://www.datamation.com/data-center/50-top-open-source-tools-for-big-data-1.htm
[3] Apache: Couchdb (Online; Oct 2015)
[4] MongoDB: Mongodb (Online; Oct 2015)
[5] Neo Technology, I.: Neo4j, the world’s leading graph database.
[6] Pig.apachi.org (online Oct 2015)
[7] https://www.ijraset.com/fileserve.php?FID=3679
[8] https://www.tutorialspoint.com/apache_pig/index.htm

Sayantan Halder, Dristi Dugar, Ira Nath, Pranati Rakshit, Dharmpal Singh, "A New Technique for New York Stock Exchange (NYSE) Data Analysis Using Apache Pig", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.10-15, 2020.

Accidents are more common now a days and prevention of accidents is really a great concern of people. So an accident prevention system is of great help and so our paper deals with a smart road safety and prevention system to avoid road accidents .Here sensors are used along with Arduino and for indication purposes IR sensors, buzzers and RGB LED light are used. Here we are using a counter to keep the count of vehicles passing through the road. To overcome the accidents due to curve and narrow roads this safety system is preventive. The main purpose of this paper is to make a safety road system to reduce the number of road accidents due to curvy and narrow roads. This indication system gives indication to the vehicles that other vehicles are coming from the other side so that they can take the safety measures before hand only.

Proximity sensors, Arduino microcontroller, Counter, RGB LED

[1] Published in: 2017 International Conference on Intelligent Computing and Control Systems (ICICCS)INSPEC Accession Number: 17487357,DOI:10.1109/ICCONS.2017.8250761 Publisher: IEEE
[2] Published in: 2018 1st International Conference on Computer Applications & Information Security (ICCAIS)INSPEC Accession Number: 18043292,DOI: 10.1109/CAIS.2018.8441951Publisher: IEEE
[3] Published in: 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), INSPEC Accession Number: 17579777, DOI: 10.1109/R10-HTC.2017.8288908, Publisher: IEEE
[4] Published in: 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), Accession Number: 18617740, DOI: 10.1109/ICCUBEA.2018.8697663, Publisher: IEEE
[5] Published in: 2019 International Conference on Innovative Trends in Computer Engineering (ITCE), INSPEC Accession Number: 18473398, DOI: 10.1109/ITCE.2019.8646591, Publisher: IEEE
[6] Published in: 2017 3rd IEEE International Conference on Computer and Communications (ICCC) INSPEC Accession Number: 17651929, DOI: 10.1109/CompComm.2017.8322721, Publisher: IEEE
[7] Published in: 2017 International Conference on Computer Communication and Informatics (ICCCI), INSPEC Accession Number: 17392872, DOI: 10.1109/ICCCI.2017.8117791, Publisher: IEEE
[8] Published in: 2016 Online International Conference on Green Engineering and Technologies (IC-GET), INSPEC Accession Number: 16864673, DOI: 10.1109/GET.2016.7916857, Publisher: IEEE
[9] Published in: 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES) INSPEC, Accession Number: 16776775DOI: 10.1109 /ICAEES.2016. 7888006 Publisher: IEEE
[10] Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: 12 , Issue: 1 , March 2011 )Page(s): 15 - 24INSPEC Accession Number: 11834565DOI: 10.1109/ TITS.2010.2050060 Publisher: IEEE

Dwaipayan Saha, Indrani Mukherjee, Jesmin Roy, Sumanta Chatterjee, "Smart Safety and Accident Prevention System for Mountain Roads", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.16-18, 2020.

The method of hiding a message so that only the actual recipient receives it properly and securely is referred as encryption. Encryption can contribute a technique for hiding data from intruders. As huge amount of data is stored on computers or transmitted via computers are exposed to the attackers which is at a risk. With the quick evolution of digital information transmission in electronic way, data safety is essential in information storage and transmission. The confidentiality of data has a remarkable role in various fields like ethics, law and currently in Data Systems. With the progress of human intelligence, the art of cryptography has grown to be more complicated with the aim of make data more safe and secure. Different collections of Encryption systems are being utilized in the world of Data Systems by different institutes. A new algorithm has been proposed for the security purpose of the data to be hidden from any unauthorized access. The proposed algorithm takes a 4-digit user-defined key and also generates a key which will be used to decrypt the same. The new technique is able to handle any size data efficiently and effectively for cryptography. We have used two layers cryptography technique which is totally new as far of our knowledge. It can provide more security of data than existing works in linear time.

Cryptography, Security, Multi level Security

[1] Diaa, S., E, Hatem M. A. K., & Mohiy M. H. (2010, May) Evaluating the Performance of Symmetric Encryption Algorithms. International Journal of Network Security, Vol.10, No.3, (pp.213-219).
[2] Sudipta Singha Roy, Kazi Md. Rokibul Alam, Md. Asaf- Uddowla, Shaikh Akib Shahriyar, and Yasuhiko Morimoto (2017). “A novel encryption model for text messages using delayed chaotic neural network and DNA cryptography”.
[3] Stallings, W. (2006). Cryptography and network security: principles and practices. Pearson Education India.
[4] Deshpande, H. S., Karande, K. J., & Mulani, A. O. (2014, April). Efficient implementation of AES algorithm on FPGA. In Communications and Signal Processing (ICCSP), 2014 IEEE International Conference on (pp. 1895-1899).
[5] Sanket A. Ubhad, Prof. Nilesh Chaubey, Prof. Shyam P. Dubey (2015). “Advanced ASCII Based Cryptography Using Matrix Operation, Palindrome Range, Unique id”.
[6] Nadeem, H (2006). “A performance comparison of data encryption algorithms”, IEEE Information and Communication Technologies, (pp. 84-89).
[7] Samir A. El-Seoud and Hosam F. El-Sofany (2017). “Studying Security of Data in Cloud Computing through
[8] Rashmi Welekar and Deepti Chaudhary (2015). “Secure Authentication Using Visual Cryptography”.
[9] Padate, R., & Patel, A. (2014). Encryption and decryption of text using AES algorithm. International Journal of Emerging Technology and Advanced Engineering, 4(5), 54-9.
[10] Kretzschmar, U. (2009). AES128–AC Implementation for Encryption and Decryption. TI-White Paper.
[11] Abhishek Pandya & Bobby Jasuja. (April 2015). Crypto-Compression System: An Integrated Approach using Stream Cipher Cryptography and Entropy Encoding

Sourav Ghosh, Prithwijit Das, Ira Nath, Dharmpal Singh, Sudipta Sahana, "NTCETLS: A Novel Technique For Cryptography Ensuring Two Level Security", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.19-24, 2020.

This paper state the analysis of change of structure of a power system by implementing modern grid network and also focus of modern structure of advanced power system for fulfilment of demands Energy is the basic necessity for the economic development of our country, many functions necessary to present day living grind to halt when the supply of energy stops. The main challenge today is to upgrade the existing technologies and to promote development, demonstration, scaling up and commercialisation of new and emerging technologies for widespread adaptation. India is resourceful country so India will be able to achieve a smooth transition from fossil fuel economy to sustainable renewable –energy-based economy and brings “Energy for all” and “Energy for ever” era for equitable, environment friendly and sustainable development. With increasing efforts worldwide to de-carbonise energy supply, a wide variety of generating plant types is being connected to electrical distribution network. So, in this paper we will focus different sectors of distribution generation.

Smart Grid, Grid Architecture, Renewal Energy, Smart Metering

[1] A course in Power Systems-J.B. Gupta, Kataria Publications.
[2] Distributed Generation-N. Jenkins, J.B. Ekanayake and G. Strbac
[3] Commission of the European, Union Smart Grids Technology Platform. European Technology Platform for the Electricity Networks of the Future. Available from URL://www.smartgrids.eu/[Accessed February 2010]
[4] Principles of Power System – V.K. Meheta. S. Chand.
[5] Electrical Power Systems-D.Das New Age International Publishers
[6] Blune S.W .Electric Power System Basics for Nonelectrical Professional,IEEE,press;2007
[7] IEEE 1547.IEEE Standard for interconnecting Distributed Resources With Electrica Power Systems:2003
[8] Electricity Network Associations Engineering Recommendation G59/1.Recommendations for the connection of Embedded Generation Plant to the Public Electrical Suppliers Distribution Systems: [1991].
[9] Modern Power System Analysis-Nagrath Kothari,TMH

A. Sen, S. Pal, R. Paul, "The Smart Architecture of Smart Grid", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.25-31, 2020.

Indian railways are one of the most vast and complex railway networks in the world in which majority of the population is dependent. But such vast and complex system comes with a cost, the real time tracking which are implemented by railways using GPS tracking mechanism is far from accuracy. People get annoyed due to late arrival of passenger trains and wish to switch to other means of transport. There is a lot of wastage of time and money of the passengers due to this unscheduled timing of trains where passengers are unaware of time at which the train actually leaves the station. Although efforts like “Where Is My Train” by Sigmoid Labs have managed overcoming this situation to an extent but it’s operating principle is not enough for keeping exact track of such a huge network and we users are quite aware about its limitation and discrepancies regarding real time train’s location. In this manuscript, we are proposing a real time local train tracking using surveillance camera. OCR based Computer Vision model is developed in order to fetch status of trains from the snaps and accordingly relevant data is generated and updated in the main frame server. CCTV’s installed at stations ends are utilized for this purpose the feed from these cams are passed to our OCR Model & the data collected or analysed from those feed is further uploaded & updated in the database. Data refers to train name, number & time stamp. Users are provided with an app through which they can keep an exact track of passenger train’s arrival & departure on a real time basis.

Local Train tracking, Computer Vision, Haar-Cascade, Optical Character Recognition (OCR), Tesseract v4

[1] Al Rashed, M. A., Oumar, O. A., & Singh, D. (2013). A real time GSM/GPS based tracking system based on GSM mobile phone.
[2] Second International Conference on Future Generation Communication Technologies (FGCT 2013). doi:10.1109/fgct.2013.6767186
[3] Prajapati, S., Joshi, S. R., Maharjan, A., & Balami, B. (2018).
[4] Evaluating Performance of Nepali Script OCR using Tesseract and Artificial Neural Network.
[5] 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS). doi:10.1109/cccs.2018.8586808
[6] Kumar, G. H., & Ramesh, G. P. (2017). Intelligent gateway for real time train tracking and railway crossing including emergency path using D2D communication. 2017 International Conference on Information Communication and Embedded Systems (ICICES). doi:10.1109/icices.2017.8070779
[7] Optical Character Recognition by Open Source OCR
[8] Tool Tesseract: A Case Study International Journal of Computer Applications (0975 – 8887) Volume 55– No.10, October 2012
[9] Nurhayati, Risda, B. C., & Masruroh, S. U. (2014). (Optical Character Recognition using Tesseract)
[10] Optical character recognition feature implementation in cooking recipe application using tesseract Google project.
[11] 2014 International Conference on Cyber and IT Service Management (CITSM). doi:10.1109/citsm.2014.7042173
[12] Alexander, A., & Dharmana, M. M. (2017). Object detection algorithm for segregating similar coloured objects and database formation. 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT). doi:10.1109/iccpct.2017.8074332
[13] Ashwini, B., Yuvaraju, B. N., Pai, A. Y., & Aditya Baliga, B. (2017).
[14] Real Time Detection and Classification of Vehicles and Pedestrians Using Haar Cascade Classifier with Background Subtraction.
[15] 2017 2nd International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS). doi:10.1109/csitss.2017.8447818
[16] Li, Q., An, W., Zhou, A., & Ma, L. (2016). (Optical Character Recognition using Tesseract)
[17] Recognition of Offline Handwritten Chinese Characters Using the Tesseract Open Source OCR Engine.
[18] 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). doi:10.1109/ihmsc.2016.239
[19] Abdallah Dafallah, H. A. (2014).
[20] Design and implementation of an accurate real time GPS tracking system.
[21] The Third International Conference on e-Technologies and Networks for Development (ICeND2014). doi:10.1109/icend.2014.6991376
[22] Nelson, L. M., & Levine, J. (n.d.).
[23] Understanding limitations of open carrier phase frequency transfer on a transatlantic baseline.
[24] Proceedings of the 2001 IEEE International Frequncy Control Symposium and PDA Exhibition (Cat. No.01CH37218). doi:10.1109/freq.2001.956187
[25] Nikolic, M. V., Kosic, B. D., Milanovic, M. D., Antonic, N. M., Stojkovic, Z. M., & Kokic, I. Z. (2014). Railway axle counter prototype. 2014 22nd Telecommunications Forum Telfor (TELFOR). doi:10.1109/telfor.2014.7034503

S. Sarkar, S. Lahiri, A. Biswas, A. Das, S. Bhowmick, S. Sahana, D. Singh, I. Nath, "Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.32-36, 2020.

With the predictions of the world Health Organization (WHO) that number of deaths due to traffic accidents will be around 2 million in next 15 years. Researchers nowadays are paying more attention in preventing traffic accidents and lower the number of occurred fatalities. The purpose of this work is an attempt to prevent traffic accidents due to fatigue or sleepiness of the driver. In this work we developed a customized goggles, which is microcontroller based anti sleep alert system for the drivers. In this device the inbuilt infrared sensor detect the obstacle and transfer signal to Arduino then Arduino supply signal to buzzer. This device can be used by the physical paralysed person to communicate with others, can be used by the security personnel at night and can also be used by the patient in comma.

Eyesensor, microcontroller, Arduino

[1]. The research and design of a kind of anti-sleeping student alarm clock with exercise and English learning functions,2014 IEEE 5th International Conference on Software Engineering and Service Science INSPEC AccessionNumber:14698862,DOI:10.1109/ICSESS.2014.6933662Publisher: IEEE,Conference
[2]. Development of a brand new system using RFID combining with wireless sensor network(WSNs) for real- time doze alarm, 2009 3rd International Conference on Anti- counterfeiting, Security, and Identification in CommunicationINSPECAccession,Number:10906202,DOI: 10.1109/ICASID.2009.5276929Publisher: IEEE
[3].A Microcontroller Based Car-Safety System: Implementing Drowsiness Detection And VehicleVehicle Distance Detection In Parallel. INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 4, ISSUE 12, DECEMBER 2015
[4]. Kenneth J. Ayala, “8051 Micro-controller Architecture, Program & Application],2nd Edition.
[5]. Drowsy Driver Sleeping Device and Driver Alert System, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064
[6]. Steven B. Ryan, Krystal L. Detweiler, Kyle H. Holland, Michael A. Hord and Vlastislav Bracha, “A long-range, wide field-of-view infrared eye blink detector

Adnan Ahmad, Anjali Sharma, Astha Singh, Sumanta Chatterjee, Apurba Paul, "Microcontroller Based Anti Sleep Alarm System", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.37-40, 2020.

In this paper we have proposed an energy efficient load balancing algorithm for cloud computing. This proposed algorithm categorized the virtual machines and the queued jobs in HIGH, MEDIUM and LOW clusters considering different criteria, jobs would be assigned accordingly to competent virtual machines. The proposed algorithm is considering battery power also for categorize its cluster, which promotes it as energy efficient algorithm.

Cloud Computing, Cluster, Energy Efficient Algorithm, Load Balancing, Virtual Machine

[1] The NIST Definition of Cloud Computing, Peter Mell Timothy Grance, NIST Special Publication 800-145
[2] Enhanced Equally Distributed Load Balancing Algorithm For Cloud Computing, Shreyas Mulay, Sanjay Jain, IJRET: International Journal of Research in Engineering and Technology ISSN: 2319- 1163.
[3] Chen, H., Wang, F., Helian, N., & Akanmu, G. (2013, February). User-priority guided Min-Min scheduling algorithm for load balancing in cloud computing. In Parallel computing technologies (PARCOMPTECH), 2013 national conference on (pp. 1-8). IEEE
[4] Y. Fang, F. Wang, and J. Ge, “A Task Scheduling Algorithm Based on Load Balancing in Cloud Computing”, Web InformationSystems and Mining, Lecture Notes in Computer Science, Vol. 6318, 2010, pages 271-277.
[5] Chen, H., Liu, Q., & Ai, Q. (2016, August). A New Heuristic Scheduling Strategy LBMM in Cloud Computing. In Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2016 8th International Conference on (Vol. 1, pp. 314-317). IEEE
[6] Anitha H M, P. Jayarekha , "Security Challenges of Virtualization in Cloud Environment", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.1, pp.37-43, 2001
[7] Kimpan, W., & Kruekaew, B. (2016, August). Heuristic Task Scheduling with Artificial Bee Colony Algorithm for Virtual Machines. In Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems, 2016 Joint 8th International Conference on (pp. 281- 286). IEEE.
[8] Agarwal, M., Srivastava, D.: A Genetic Algorithm inspired task scheduling in Cloud Computing. In : International Conference on Computing, Communication and Automation (ICCCA2016) (2016)
[9] B. Mondal,., K. Dasgupta, P. Dutta, P.: Load Balancig inCloud Computing using Stochastic Hill Climbing-A softComputing Appproach. ELEVIER (2012)
[10] Vanithaa, M., Marikkannu, P.: Effective resource utilization in cloud environment through a dynamic well Organised load balancing algorithm for virtual machines. Computers and Electrical Engineering (2017)
[11] Wang, T., Liu, Z., Chen, Y., Xu, Y., & Dai, X. (2014, August). Load balancing task scheduling based on genetic algorithm in cloud computing. In Dependable, Autonomic and Secure Computing (DASC), 2014 IEEE 12th International Conference on (pp. 146-152). IEEE.
[12] Ariharan, V., Manakattu, S.: Neighbour Aware Random Sampling (NARS) algorithm for load balancing in Cloud computing. 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT) (2015).
[13] Patel, Ronak & Patel, Swachil & Patel, Dhaval & DesaiTushar. (2016). Improved GA using population reduction for load balancing in cloud computing.2372-2374. 10.1109/ICACCI.2016.7732410.
[14] A.B. Majumder, S. Sil, S. Das, A. Mondal, "Priority Based Least Waiting Time Load Balancing Algorithm Applied in Cloud Computing", International Journal of Computer Sciences and Engineering, Vol.6, Issue.3, pp.384-388, 2018.
[15] Annwesha Banerjee Majumder Dipak Kumar Shaw and Sourav Majumder “ A Load Balancing Algorithm for Selection of Competent Server in Cloud Environment Based on Capacity, Load and Energy” ” Indian Journal of Computer Science and Engineering (IJCSE) Vol. 8 No. 4 Aug-Sep 2017

Annwesha Banerjee, Sourav Majumder, Shubham Pal, Alap Putatunda, "An Energy Efficient Cluster based Load Balancing Algorithm Applied in Cloud Computing", International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.41-43, 2020.

In biometrics research face detection and recognition is a very popular topic and it has distinct advantages because of its non-contact process. This type of technology extensively draws attention due to its huge application and market value. like video surveillance system for detecting suspicious object. Face based recognition system is more popular over other biometrics because of its uniqueness. Face recognition is very difficult task because human face is a dynamic object and has variability in its appearance. So, here accuracy and speed of recognition is Min issue. The purpose of the paper is correctly recognized a person from an image face or a video. To correctly identify a person we have used three techniques: Linear discriminant analysis (LDA), Logistic Regression (LR) and support vector Machine (SVM) techniques with Principle Components Analysis (PCA) which extract the features and reduce dimensionality. The LDA and LR technique produce more accurate result compare to other methods. This paper achieved 93% successful recognition rate for recognizing different face database.

Face detection, Face Recognition, PCA, SVM, LDA, and LR

[1] R. Brunelli and T. Poggio, “Face recognition: Feature versus templates”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 15 , Issue.10 , pp. 1042 – 1052
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[3] Han Bing, “Research of Face Detection Based on AdaBoost and ASM”, The Open Cybernetics & Systemics Journal, 2014, 8, pp.183-190.
[4] Mrs. Madhuram. M, B. Prithvi Kumar, “Face Detection and Recognition Using OpenCV”, International Research Journal of Engineering and Technology (IRJET), | ISO 9001:2008, e-ISSN: 2395-0056, Volume: 05, Issue: 10.
[5] G. Gibert, D. D`Alessandro and F. Lance, "Face detection method based on photoplethysmography", IEEE International Conference on Advanced Video and Signal Based Surveillance, 2013, p. 449-453
[6] R. Niese, “Facial expression recognition based on geometric and optical flow features in colour image sequences”, Vol. 6, Iss. 2, pp. 79–89, doi: 10.1049/iet-cvi.2011.0064.
[7] X. Yi, W. Ying and P. Jun, "An improved adaboost face detection algorithm based on the weighting parameters of weak classifier"; In: Proceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, 2013, pp. 347-350.
[8] Mrs. Madhuram. M, “Face Detection and Recognition Using OpenCV”, International Research Journal of Engineering and Technology (IRJET), e-ISSN: 2395-0056, p-ISSN: 2395-0072, Volume: 05, Issue: 10.
[9] Face Recognition using Principle Component Analysis Kyungnam Kim Department of Computer Science University of Maryland, College Park MD 20742, USA
[10] Caifeng Shan,” Smile Detection by Boosting Pixel Differences”, IEEE Transactions On Image Processing, VOL.21, NO. 1, JANUARY 2012, Page(s): 431 – 436, DOI: 10.1109/TIP.2011.2161587.
[11] K. Rajakumari, “An Evaluation of Face Recognition By using Principal Component Analysis with Support Vector Machine”, International Journal of Recent Technology and Engineering (IJRTE), ISSN: 2277-3878, Volume-7 Issue-6S3 April, 2019
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