-4d90550d17f4602e089-6c2 20220604050720862 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 11 30 2019 8 4 Research Scholar, Rajah Serfoji College, (Affiliated to Bharathidasan University), Tamil Nadu, India. C.Amali Pushpam* J.Gnana Jayanthi Assistant Professor, Dept.of Computer Science, Rajah Serfoji College, (Affiliated to Bharathidasan University), Tamil Nadu, India A very fast and efficient classification algorithm is imperative to any application. Nowadays all kinds of applications produce a huge volume of data. Handling these 5’V characteristics data is really very crucial. While processing data, data classification simplifies the mission. Though many classification algorithms are available, they are not up to the mark to meet the fast growing challenges of current digital world. To fill this gap, feature selection is integrated with classifiers, as Feature selection has proved its impact on performance of classifiers. SVM is one of the most frequently used classifier. In this paper, different feature selection methods have been analyzed by studying 21 articles. This survey makes public that SVM based feature selection works better and widely used. Also in feature selection, filter method is widely used. 11 30 2019 7252 7256 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5279.118419 https://www.ijrte.org/portfolio-item/D5279118419/ PG and Research Department of Computer Science, Rajah Serfoji Govt. Arts College (Autonomous), Thanjavur, Tamilnadu, India S. Subbulakshmi* Dr.D.J. Evanjaline Assistant Professor, PG and Research Department of Computer Science, Rajah Serfoji Govt. Arts College (Autonomous), Thanjavur, Tamilnadu, India. Credit cards are a significant component of everyday life. Whether purchasing gas and supermarket stores or reserving a hotel and lease a car for the next holiday. Credit cards are a pleasant and safe type of client payment. Advantages that differ from harm security on payments to the convenience of disputing suspect fees or suspicious activity make credit cards such an appealing form of transaction. It takes an hour for any time activities, online shopping, and paperless system. As the amount of credit card customers rises day by day, significant illegal activities eventually enhance. CT18 technique is the procedure for categorizing information directed at reformatting observations into CT18, whereby each observation belongs to the closest mean cluster. This is one of the simplest unsupervised learning algorithms that solve the well-known grouping problem 11 30 2019 7257 7260 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5280.118419 https://www.ijrte.org/portfolio-item/D5280118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College(Autonomous), Tiruchirapalli, Affiliated to Bharathidasan University, Tiruchirappalli, Tamilnadu, India. A Zakiuddin Ahmed* Dr.T.Abdul Razak Associate Professor, Dept. of Computer Science, Jamal Mohamed College(Autonomous), Tiruchirappalli, Affiliated to Bharathidasan University, Tiruchirappalli, Tamilnadu, India. Weather has a lot of blow in our daily life and also gained researchers concentration due to its enormous effect in the human life. To defend ourselves from weather, we need to predict the weather such as rainfall, humidity and temperature etc. Using classification algorithms, we can predict the weather by using the past datasets. In this research paper, WEKA tool is used to implement classification algorithms for weather forecasting. Machine Learning is an internal part of artificial intelligence, which is used to design algorithms based on the relationships between data and data trends. 11 30 2019 7261 7263 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5281.118419 https://www.ijrte.org/portfolio-item/D5281118419/ Assistant Professor, Jamal Institute of Management, Tiruchirappali, Tamilnadu, India. Dr. G. Sivanesan* Dr. A. Selvarani Associate Professor, Jamal Institute of Management, Tiruchirappali, Tamilnadu, India. V. Kanagaraj Research Scholar(PhD), Jamal Institute of Management, Tiruchirappali, Tamilnadu, India. A career fair is an event that provides employees and employers a simultaneous to meet one another, set up professional contacts, and chat potential job and/or placement openings. Many companies from a mixture of industries attend, and there are both general and specialized career fair events. There are many progressive reasons to take the time to prepare for and attend a career fair. Networking with employers is eminent while organizing a job fair. Career fairs are a free resource for you to realize which employers are hiring and interested in your skill set in a cost-effective, efficient manner. Jobs Fairs aim to give people the chance to explore employment opportunities in their local community. A virtual career fair is an online proceeding where employers and job seekers meet each other in a virtual environment, using chat rooms, teleconferencing, webcasts, webinars and/or email to exchange information about job opportunities. In today's digital world, it's only natural that the solution would also be a digital one. CV Capture apps are the recruiters' grievances solved. With this new technology, recruiters can digitally capture and store candidate resumes in a matter of seconds. Relatively new trends are the so-called online job fairs or virtual career fairs. The concept is the same as with traditional career fairs, but all interaction occurs on an online platform specifically designed for the purpose. 11 30 2019 7264 7266 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5282.118419 https://www.ijrte.org/portfolio-item/D5282118419/ Research Scholar, Bharathidasan University, Engineering and Applications, School of Computer Science, Tiruchirappalli, Tamilnadu, India Ashok Kumar J* Dr. Gopinath Ganapathy Registrar, Bharathidasan University, Tiruchirappalli, Tamilnadu, India. Access control and Data confidentiality are key technology to ensure the security of system and to protect the privacy of the users. The modified Collaborative Trust Enhanced Security (CTES) model has an inbuilt access control mechanism for Kerberos protocol itself to enforce the access control policy directly into the Client system node. This paper explains the hybrid access control model with Role Based Access Control (RBAC) and Attribute Based Access Control (ABAC) for modified CTES framework through Kerberos protocol. Hence, it retains the concept of “role”, “group” and “attributes” for the user which are necessary to protect data privacy in the system. Data confidentiality for the stored data in Cloud is achieved by cryptographic techniques. Gnu Privacy Guard (GnuPG) based certificate is capable enough to verify the identity of the correspondent in information exchange as well as the information integrity. It is a strongest authentication technique where the user is asked to provide his/her digital ID for validation in the Server and enables Single sign-on services for Kerberos Authorization in modified CTES model. In this paper, it is proposed for a new Kerberos Authorization with Hybrid Access Control Model (KAHAC) for single-domain systems and multi-domain systems in Public Cloud based on roles, attributes, groups, access modes and the type of resources. 11 30 2019 7267 7271 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5283.118419 https://www.ijrte.org/portfolio-item/D5283118419/ JRF (Junior Research Fellow) in the Department of School of Computer Science and Engineering at Vellore Institute of Technology (VIT), Chennai, Tamilnadu, India. Ajins Joy* Dr.R. Saranya Assistant Professor, Department of Computer Science, Central University of Tamil Nadu, Thiruvarur, Tamilnadu, India. In recent trend, Speech recognition has become extensively used in customer service based organization. It has acquired great deal of research in pattern matching employed machine learning (learning speech by experience) and neural networks based speech endorsement domains. Speech recognition is the technology of capturing and perceiving human voice, interpreting it, producing text from it, managing digital devices and assisting visually impaired and older adults using unequivocal digital signal processing. In this paper we have presented a comprehensive study of different methodologies in android enabled speech recognition system that focused at analysis of the operability and reliability of voice note app. Subsequently we have suggested and experimented an android based speech recognizer app viz. Annotate which predominately focus on voice dictation in five different languages (English, Hindi, Tamil, Malayalam and Telugu) and extracting text from image using Automatic Speech Recognition (ASR) and Optical Character Recognition (OCR) algorithm. Finally, we identified opportunities for future enhancements in this realm. 11 30 2019 7272 7277 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5284.118419 https://www.ijrte.org/portfolio-item/D5284118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University), Tiruhcirappalli, Tamilnadu, India. A. Jainulabudeen* Dr. M.Mohamed Surputheen Associate Professor, Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University), Tiruchirappalli, Tamilnadu, India. Secure and energy efficient routing is one of the major requirements of the WSN models. This is due to the resource constrained environments and remotely deployed conditions. This work proposes an effective model that ensures security and energy efficiency during the routing process in a WSN. The proposed model modifies the Ant Colony Optimization algorithm to perform routing based on these multiple objectives. The proposed model uses trust as the major component to provide security, and the randomness associated with the metaheuristic nature of the model enables uniform usage of all sensor nodes. This also extends the network lifetime, making the proposed model highly efficient and deployable in real-time networks. Experiments and comparisons also indicate that the proposed model exhibits shorter time requirements and provides more optimized paths compared to models in literature. 11 30 2019 7278 7282 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5285.118419 https://www.ijrte.org/portfolio-item/D5285118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University), Tiruhcirappalli, Tamilnadu, India. M. Abdullah* Dr. M. Mohamed Surputheen Associate Professor, Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University), Tiruchirappalli, Tamilnadu, India. On-demand cloud services must be provided to customers at any time by ways of cloud service providers due to cloud demand. It is obligatory for cloud service providers to lessen large volumes of data, thereby it can reduce costs for maintaining large storage systems.Infrastructure level performance is an important problem which directly affects the overall working of cloud computing environment. The objective of our framework is enhancing the performance of cloud infrastructure. Proposed approach demonstrates high effective in cloud performance enhancement, as it displays enhancement in both the service providers as well as for cloud users. 11 30 2019 7283 7287 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5286.118419 https://www.ijrte.org/portfolio-item/D5286118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College, Trichy, Tamilnadu, India. V. Sobanadevi* G. Ravi Associate Professor and Head, Department of Computer Science, Jamal Mohamed College, Trichy, Tamilnadu, India. Fraud detection in credit card transactions is one of the major requirements of the current business scenario due to the huge amount of losses associated with the domain. This work presents a multi-level model that can provide highly effective fraud detection in credit card transactions. The model is based on the amount for which the transaction is committed. The proposed MLFD model identifies the nature of the transaction and depending on the significance level of the transaction, the appropriate learning model is selected. Experiments were performed with the standard benchmark data and comparisons were performed with existing model in literature. Results shows that the proposed model exhibits high performance compared to the existing model. 11 30 2019 7288 7292 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5287.118419 https://www.ijrte.org/portfolio-item/D5287118419/ Assistant Professor, PG and Research Department of Computer Science, Jamal Mohamed College (Autonomous), [Affiliated to Bharathidasan University], Tiruchirappalli, TN, India. K.N. Abdul Kader* Nihal Assistant Professor, PG and Research Department of Computer Science, Jamal Mohamed College (Autonomous), [Affiliated to Bharathidasan University], Tiruchirappalli, TN, India. Object detection in the video sequence is a significant problem to be resolved in image processing because it used different applications in video compression, video surveillance, robot technology, etc. Few research works have been designed in conventional works to discover moving objects using various machine learning techniques. However, dynamic changing background, object size variations and degradation of video frames during the object detection process remained an open issue. In order to overcome such limitations, Anisotropic Sophisticated Spatiotemporal Contours based Deep Neural Network Learning (ASSC-DNNL) practice is projected. ASSC-DNL Technique initially obtains a number of video file as input at the input layer. After acquiring the video, input layer forward it to hidden layers. Subsequently, ASSC-DNL Technique accomplishes the encoding process in the first hidden layer using Anisotropic Stacked Autoencoder (ASA). During the encoding process, ASSC-DNL practice maps each video frames pixels in input video via code. This practice results in compressed video with enhanced quality. Afterward, ASSC-DNL practice transforms compressed video into a numeral of frames in the second concealed layer. Followed by, ASSC-DNL practice carried out Teknomo–Fernandez Spatiotemporal Based Background Subtraction (TS-BS) process at the third hidden layer, in which it effectively segments the foreground images from dynamic changing background. Then, ASSC-DNL practice deep analyzes the foreground image of video frames and mines some features like shape, color, texture, intensity, and size. Finally, ASSC-DNL Technique exactly finds the moving objects in video frames according to identified features with minimal time at the output layer. Therefore, ASSC-DNL Technique obtains enhanced moving objects detection performance when compared to existing works. The simulation of ASSC-DNL practice is conducted via different metrics such as accuracy, time and false positive rate towards in detection. 11 30 2019 7293 7300 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5288.118419 https://www.ijrte.org/portfolio-item/D5288118419/ Assistant Professor, Department of Statistics, Periyar E.V.R. College (Autonomous), Bharathidasan University( Affiliation), Tiruchy, Tamilnadu, India. M. Balasubramaniam* Abel Thangaraja.G Assistant Professor and Head of the Computer Science, KayPeeYes College of Arts and Science, Kotagiri, Tamilnadu, India. Bharathidass. S Assistant Professor, Department of Statistics, Periyar E.V.R. College (Autonomous), Bharathidasan University( Affiliation), Tiruchy, Tamilnadu, India. Consider a retrial queue with VoIP calls and two kinds of heterogeneous services such as essential and optional services. The multiple vacation policy, retrial policy, customer’s impatience and the concept of catastrophe are adopted to derive the required solutions. The steady state system size distribution and probability generating function under different level have been obtained. Based on some assumptions, special and particular cases are discussed. 11 30 2019 7301 7305 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5289.118419 https://www.ijrte.org/portfolio-item/D5289118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College (Autonomous), [Affiliated to Bharathidasan University], Tiruchirappalli, Tamilnadu, India. B. Mohamed Faize Basha* Dr. M. Mohamed Surputheen Associate Professor, Department of Computer Science, Jamal Mohamed College (Autonomous), [Affiliated to Bharathidasan University], Tiruchirappalli, Tamilnadu, India The most serious and broad infections considered lung disease that sets up a principal general wellbeing risky and has a high demise level. In this worry, appropriate division of lung tumor from X-beam, CT output or, MRI is the moving stone to accomplishing totally electronic analysis framework for lung disease location. With the advancement of innovation and attainable quality of information, the regarded time of a radiologist can be secured by methods for PC apparatuses for tumor division. This paper, to improve the Lung cancer segmentation and classification a new model is introduce. To overawed the existing segmentation limitations in this proposed system for lung nodes detectionModified kernel-based Fuzzy c-means clustering (MKFCM) technique is used. The proposed method segmentation includes two modules, the fire-fly clustering module and the MKFCM clustering module. For feature Extraction feature of this paper a (Gray-Level Co-Occurrence Matrix), Local binary patterns (LBP) and Histogram of oriented gradients (HOG) based hybrid system is used. To select the best feature fire fly base Feature Selection (FS) technique is used. For proposed Lung cancer classification long short-term memory (LSTM) classifier is used. The proposed system is also named as FF-MKFCM-FF-FS-LSTM system. Finally the performances are evaluated. From that analysis the proposed module provide 96.55% of segmentation accuracy and the proposed classification provides 98.95% of classification accuracy. 11 30 2019 7306 7312 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5290.118419 https://www.ijrte.org/portfolio-item/D5290118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University), Tiruchirappalli, Tamilnadu, India. A.Basheer Ahamed* Dr. M. Mohamed Surputheen Associate Professor, Department of Computer Science, Jamal Mohamed College (Autonomous), (Affiliated to Bharathidasan University) , Tiruchirappalli, Tamilnadu, India. Predicting performance of students in sports is analyzed and studied. There are many techniques identified for the prediction of sports interest and they are not producing expected value. Towards performance development, a novel time variant multi perspective hierarchical clustering approach towards user interest prediction. The proposed time variant model reads the sports log and groups them according to the time domain. The entire log has been split into different of clusters as like time window. Then using window log, the method splits the logs according to different sports. For each time window, the method identifies the list of actions or sports played or tagged or chat with other users. Using the class of log, the method identifies the category of sports log and for each category of sports, the method compute the sports strike strength (SSS). Based on the value of SSS, the method identifies the user interest. Similarly, the interest of the student at each time window has been identified and used to generate the knowledge. The proposed method improves the performance of sports interest prediction on students with less false ratio. 11 30 2019 7313 7317 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5291.118419 https://www.ijrte.org/portfolio-item/D5291118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College (Autonomous) (Affiliated to Bharathidasan University), Tiruchirappalli, Tamilnadu, India. S. Peerbasha* Dr. M. Mohamed Surputheen Associate Professor, Department of Computer Science, Jamal Mohamed College (Autonomous) (Affiliated to Bharathidasan University), Tiruchirappalli, Tamilnadu, India The problem of bipolar disorder has been well studied and analyzed. To perform the detection of presence of BD, there are number of approaches available and the result of detection has been used in several ways. In order to improve the performance in BD detection and utilize the result in gauging the performance of students, a behavioral pattern base psychotic analysis model has been presented in this paper. The method maintains the behaviors, habits and interests of different students in different period of time. The student behaviors includes mood change, depression, sudden laughs, uninterested, short temper, lack of concentration, adamant, frustration, energy, sleep and so on. Such behaviors has been tracked for number of students for prolong period and stored in the behavior set. By reading the behavior set and with the identified samples of BD, the method generates set of behavioral patterns. The behavioral pattern has been generated for three different classes like lower, medium and high. For each class of behavioral pattern, the method generates set of fuzzy rules. Using the fuzzy rule, each student has been analyzed for their behavioral pattern in different time window. Based on the patterns, the method estimates BDCW (Bipolar Disorder Class Weight). Based on the weight measure, the presence of BD has been identified and classified under different class. Identified results have been used to generate academic pattern and helps to generate analysis result to improve the student performance. The proposed approach improve the performance of student development, monitoring and health development. 11 30 2019 7318 7322 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5292.118419 https://www.ijrte.org/portfolio-item/D5292118419/ Research Scholar, Department of Computer Science, Jamal Mohamed College (Autonomous) (Affiliated to Bharathidasan University), Tiruchirappalli, Tamilnadu, India. M.A.Jamal Mohamed Yaseen Zubeir* Dr. A.R. Mohamed Shanavas Associate Professor, Department of Computer Science, Jamal Mohamed College (Autonomous) (Affiliated to Bharathidasan University), Tiruchirappalli, Tamilnadu, India. The problem of discrimination in transactional data set has been well studied. Numerous techniques has been recommended by various researchers but suffer to achieve higher performance. To handle this issue, a real time feature convergence measure based discrimination prevention algorithm is presented in this paper. The method first eliminates the noisy records by preprocessing the transactional data set. Second, the transactional data set has been grouped into number of clusters according to the pattern relevancy measure (PRM). Using the clusters generated, the the feature convergence measure (FCM) is computed for each item towards each cluster. The value of FCM is used to select a subset of items as sensitive one. Based on identified sensitive items, the method performs sanitization using probabilistic mapping scheme. The FCM algorithm supports the performance development of sanitization and discrimination prevention. 11 30 2019 7323 7327 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5293.118419 https://www.ijrte.org/portfolio-item/D5293118419/ Department of Humanities, Veer Surendra Sai University of Technology, Burla, Orissa, India. Dr. Prasanta Kumar Padhi* Charles Wright is one of the experimental American novelists of the mid-sixties and is concerned with depicting the absurdity of life in a world that threatens to destroy man’s sovereign self. As a black humourist, he not only highlights the black man’s despair in the white dominated America, but also the general condition of man in a hostile universe. He has placed his characters in the most bizarre setting to bring out man’s utter helplessness in the world. He tries to show how man becomes an easy victim of both the cosmic and social forces in the present day world. But despite his treatment of the bleak universe of human beings, Wright’s vision of life is not dominated by cynicism and despair. In this paper an attempt has been made to show how by incorporating into his fiction the vision of black humour Wright presents a constructive vision of life by not choosing an alternative to the meaningless and purposeless life, but by complementing it with a spirit of laughter which should help man in confronting life with courage and fortitude. His treatment of black man as a paradigm of the precarious human condition divorces him from other black novelists of the protest tradition. Whereas the writers of the protest tradition are occupied with the specific nature of black man’s problems, Wright is concerned with the idea that the black man, by his special burden in history, becomes the ultimate metaphor of the general human condition. 11 30 2019 7328 7334 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5294.118419 https://www.ijrte.org/portfolio-item/D5294118419/ BTECH in Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India. Arjun Varma* Ashwath A BTECH in Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India. Ayush Verma BTECH in Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India. A. Bagubali Assistant Professor, Vellore Institute of Technology, Vellore, Tamilnadu, India. Kishore V Krishnan Associate Professor, Vellore Institute of Technology, Vellore, Tamilnadu, India. This project attempts to create an obstruction avoiding robot which can automatically sense the presence of an obstruction in its path and avoid them. It intelligently detects barrier present in its path through the ultrasonic sensors, with the help of the internal code from the Arduino UNO, decisions are made to avoid the barriers. This has been achieved by using an ultrasonic sensor and the development board Arduino UNO. The ultrasonic sensor is mounted on a servo motor at the front of the vehicle for a wider field of view. The ultrasonic sensor acquires data which is processed by the Arduino which then decides the direction of travel for the robot. The robot requires low voltage and minimal maintenance for continued operation. Arduino being an open-source software has gained popularity for the creation of basic prototypes due to its relative simplicity in both design and coding. It also boasts of a large online community of learners and engineers. 11 30 2019 7335 7339 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5295.118419 https://www.ijrte.org/portfolio-item/D5295118419/ Anirudh Ganesh Sriraam, VIT Vellore, Tamilnadu, India Manav Badamwala, Student, VIT Vellore, Tamilnadu , India Shaswat Kumar Singh* Sangeet Aggarwal VIT Vellore, Tamilnadu , India Manav Badamwala, Student, VIT Vellore, Tamilnadu , India Savitoj Singh Aulakh, VIT Vellore, Tamilnadu, India Manav Badamwala, Student, VIT Vellore, Tamilnadu , India Jamadagni Nagesh Adarsh VIT Vellore, Tamilnadu, India Manav Badamwala, Student, VIT Vellore, Tamilnadu , India Shaswat Kumar Singh VIT Vellore, Tamilnadu, India Manav Badamwala, Student, VIT Vellore, Tamilnadu , India An Airfoil has various parameters, controlling which, it is possible to design an application specific shape to serve a certain purpose. These parameters include, but are not limited to, Chord, Camber, Maximum Camber Position, Thickness, Maximum Thickness Position, Leading Edge Radius and Trailing Edge Radius. This research seeks to study the effect of change in such parameters in the design of a Custom Airfoil, for the application in the Front Wing of Formula Student Car. With most Formula Student Cars being traction limited, high-lift low aspect-ratio wings are desired for optimal increase in Lateral Acceleration under cornering circumstances. Owing to the relatively softly sprung nature of the car, it is also desirable to have a wing which is less sensitive to changes in ground proximity. Taking these factors into consideration, this paper delves into the design of a Custom Airfoil by varying four major parameters- Camber, Maximum Camber Position, Thickness, Maximum Thickness Position. The research then proceeds to manufacture the complex shape in the most economically efficient manner. 11 30 2019 7340 7350 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5296.118419 https://www.ijrte.org/portfolio-item/D5296118419/ Research Scholar, Department of Electronics and Communication Engineering, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka, India. K. Chidananda Murthy* Mahalinga. V. Mandi Professor, Department of Electronics and Communication Engineering, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka, India. R. Murali Professor, Department of Mathematics, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka, India. Pseudorandom binary sequences find various applications in different areas such as security, communication, steganography and cryptography. The properties like sensitivity to initial condition, ergodicity, mixing property and dynamic behavior are used in the designing of random number generators known as chaotic systems. In this study, an efficient chaotic binary sequence generator using logistic map is proposed, implemented and analyzed. The proposed binary sequence generator generates 50 chaotic sequences by varying initial condition with fixed system parameter. Subsequently, the generated sequences are transformed to binary sequences using thresholding method. The output of binary sequences is statistically tested with FIPS 140-2 test suite in order to identify the specific properties expected for truly random binary sequences. The experimental results prove that the generated binary sequences possess identical characteristics of true random numbers and can pass all tests of FIPS 140-2 test suite. 11 30 2019 7351 7355 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5297.118419 https://www.ijrte.org/portfolio-item/D5297118419/ Research Scholar, VISTAS, Vel’s University, Chennai, Tamil Nadu, India. C. Kalpana* Dr. B. Booba Professor, Dept. Of CSE VISTAS, Vel’s University, Chennai,TamilNadu, India. Data Analytics is a scientific as well as an engineering tool used to investigate the raw data to revamp the information to achieve knowledge. This is normally connected with obtaining knowledge from reliable information source and rapidity in information processing, and future prediction of the data analysis. Big Data analytics is strongly evolving with different features of volume, velocity and Vectors. Most of the organizations are now concentrating on analyzing information or raw data that are fascinated in deploying analytics to survive forthcoming issues and challenges. The prediction model or intelligent model is proposed in this research to apply machine learning algorithms in the data set. Then it is interpreted and to analyze the better forecast value of the study. The major objective of this research work is to find the optimum prediction from the medical data set using the machine learning techniques. 11 30 2019 7356 7360 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5298.118419 https://www.ijrte.org/portfolio-item/D5298118419/ Assistant professor, Department of CSE, Saveetha Engineering college, Chennai, Tamilnadu, India. Naveen Raju D* Hariharan S Professor, Deparment of CSE, Saveetha Engineering college, Chennai, Tamilnadu, India. Ramprasath M Associate Professor, Department of CSE, Madanapalle Institute of Technology Science, Chittoor district of Andhra Pradesh, India. Manickam M Associate Professor, Department of CSE, Saveetha Engineering college, Chennai, Tamilnadu, India. One of the most deadly dangerous disease is cancer which is among human beings. Skin cancer is of different types that is found recently among humans. Melanoma is one such type of skin cancer which causes majority of death rate. Biopsy method leads to conventional clinical diagnosis for detection of melanoma. The study in this paper presents different benchmarking techniques for melanoma prediction and evaluation. The main challenge is detection of malignant melanoma, which is found to have asymmetrical, irregular borders, notched edges and colour variations. The various stages of skin cancer prediction were analyzed in this paper. A detailed study on various techniques of medical image processing as applied to melanoma images for past years which need the more attention which is discussed here. The techniques and methods that exit are helpful in each of these process are evaluated and summarized. The paper aims at presenting an analysis on to identify on investigation efforts required to group and classify the sub categories available in the literature and to provide a summary of all the available methods for identification of melanoma cancer. 11 30 2019 7365 7369 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5300.118419 https://www.ijrte.org/portfolio-item/D5300118419/ Research Scholar, Dr. APJ Abdul Kalam Technical University, Lucknow, U.P., India Madhu Bala Sharma* Dr. Prateek Gupta Associate Professor, KIET School of Management, Ghaziabad, U.P., India. Purpose – The purpose of this paper is to explore the various implementation issues on the Ind AS converged with IFRS in India and measures to address the issues. Design/Methodology/approach – A detailed published literature reviewed in this context and found the scope of the research. A structured questionnaire on 5 points Likert-Scale has been used for the survey. Survey conducted on accounting professionals belongs to Delhi-NCR, India. Findings – The empirical research find the various areas of challenges faced by entities in converged IFRS implementation and suitable means for effective implementation of converged IFRS in India. Originality/value – One of the contributions to this study is to examine perceptions of Indian Accounting Professionals towards convergence and implementation of a single set of global accounting standards in India. As a result of globalization, many Indian companies initiated their business in other countries and some Multi-national companies also operated in India. Different countries having their own set of accounting standards that must be followed when incorporating financial statements hence, it creates a dual set of financial reports of entities. It is complex for the business houses and all the stakeholders to prepare, understand, Interpret and compare the end result of entities so it originates the need of uniform accounting standard which will be applied in all the countries hence International Accounting standard Board took the responsibility and after considering various signifying points issued IFRS for global benefit. Many developed and developing countries adopted IFRS. Indian accounting professionals also felt the need of adopting IFRS so the Institute of Chartered Accountants of India took initiative in this direction and issued a roadmap in this direction but due to some issues, it was not implemented properly. MCA announced a roadmap for Ind AS converged with the IFRS implantation in 2015. 11 30 2019 7370 7378 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5301.118419 https://www.ijrte.org/portfolio-item/D5301118419/ Department of Mathematics, St. Joseph’s College of Engineering, Chennai, Tamilnadu, India. F. Sweety* T. Kalyani Department of Mathematics, St. Joseph’s Institute of Technology, Chennai, Tamilnadu, , India. R. Stella Maragatham Department of Mathematics, Queen Mary’s College, Chennai, Tamilnadu, India. D.Gnanaraj Thomas Department of Science and Humanities (Mathematics Division) Saveetha School of Engineering, SIMATS, Chennai, Tamilnadu, India. In two dimensions, tiling the plane plays a vital role. Many picture generative models were attempted to tile the three dimensional space. A. Dharani et al. [6] introduced a new theoretical picture generative model to tile a three dimensional space using tetrahedral tile in two different ways namely Sequential Space Filling Grammar (SSFG) and Parallel Space Filling Grammar (PSFG). Local and recognizable tetrahedral picture languages are introduced in this paper and some of its properties are studied. 11 30 2019 7379 7383 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5302.118419 https://www.ijrte.org/portfolio-item/D5302118419/ Assistant Professor P.G and Research Department of ComputerScience,Government Arts College, Coimbatore, Tamil Nadu, India. Buvaneswari. V.B* Dr. S. Shanthi Department of Computer Applications, Kongu Engineering College, Erode, India. M. Pyingkodi Department of Computer Applications, Kongu Engineering College, Erode, India. MapReduce is a programming model used for parallel computing of big data in public cloud. Big Data have characteristics like variety, velocity and volume. The research work carries out MapReduce using Matlab which is a powerful image processing and numeric computation tool. The research considers unstructured image data in public cloud Dropbox as big data and applies MapReduce algorithm to map and reduce all the images stored in it. The research work aims to retrieve the images in public cloud with maximum Red, Green, Blue color and the colors that intersect between them. The same code is modified to find all Red, Green and Blue that supports more parallelism and aids in improving the speed of MapReduce by eliminating the dependency between iterations. The speed of parallel MapReduce shows considerable improvement only with increased file size and coding style. Parallel MapReduce computation is carried out with default workers, three and four workers of the local cluster with scale up architecture. This model is developed using Matlab and can be implemented in Hadoop as well. 11 30 2019 7384 7390 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5303.118419 https://www.ijrte.org/portfolio-item/D5303118419/ Computer Science and Engineering Wing, Annamalai University, Annamalai Nagar,Tamil Nadu, India. Mrs. N. Subalakshmi* Dr. M. Jeyakarthic Assistant Director (Academic), Tamil Virtual University, Chennai, Tamil Nadu, India. Deep Neural Network (DNN) classifier is a DL model for categorizing the exactness of systematic scaling orders in the groupings as an Administration (IaaS) layer of cloud computing. The hypothesis in the study is that calculation precision of scaling orders can be improved by demonstrating a reasonable time-arrangement expectation calculation dependent on the presentation plan after some time. In the examination, outstanding burden was considered as the exhibition metric, and DNN were utilized as time-arrangement expectation procedures. The aftereffects of the trial demonstrate that expectation exactness of DNN relies upon there mining task at hand plan of the framework under learning. Precisely, the outcomes demonstrate that DNN has better forecast exactness in the situations with occasional and expanding remaining task at hand plans, while DNN in predicting unexpected load design. In addition, particle swarm optimization (PSO) algorithm is applied for the optimal selection of hidden layer count to resolve the classical DNN model which has the issue of trapping into local minima and the need of manual selection of hidden layer nodes. Accurately, this study proposed a DNN-PSO design for a self-versatile expectation suite utilizing an autonomic framework technique. This suite can indicate the maximum appropriate forecast technique based on the performance design, which leads to more exact forecast outcomes 11 30 2019 7391 7395 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5304.118419 https://www.ijrte.org/portfolio-item/D5304118419/ Assistant Professor,Department of Computer Science and EngineeringSri Krishna College of Engineering and Technology,Coimbatore.,TamilNadu,India. Majidha Fathima K M* Whenever a user browses the internet, the content he sends or receives takes the form a Protocol Data Unit as packets according to the OSI (Open Systems Interconnection) layers. These packets travel from the source to the destination through the path chosen by the routing protocols as OSPF (Open Shortest Path First) and BGP (Border Gateway Protocol). OSPF is used for interior routing within an AS (Autonomous System) and BGP is used for exterior routing between two external AS. Some customers are dual-homed where they have connections to two AS with one as the primary and the other one as secondary. Such diversed enormous traffic generated by the end users and the Internet Service Providers (ISP) have to be efficiently managed and monitored for the purpose of billing, security, QoS (Quality of Service) and SLA(Service Level Agreement) parameters. Hence the existing routing algorithms need to provide intelligent routing. The Simple Network Management Protocol (SNMP) generates the corresponding packets called SNMP traps. These specific packets are exchanged between the server and the appropriate interfaces of the routers when they are being polled. This polling technique generates a utilization graph which indicates the incoming and outgoing traffic at the core layer, distribution layer and access layer. The last mile traffic also has to be examined for checking the the bandwidth utilization. The traditional SNMP also has to incorporate the machine learning technique. This paper focuses on implementing intelligent network management in an Internet of Things environment. 11 30 2019 7174 7179 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5305.118419 https://www.ijrte.org/portfolio-item/D5305118419/ Department of Computer Technology - UG, Kongu Engineering College, Perunduai, Tamil Nadu, India. P.Gokila Bindha* R.R. Rajalaxmi Department of Computer Science and Engineering, Kongu Engineering College, Perunduai, Tamil Nadu, India. S. Poorani Department of Computer Technology - UG, Kongu Engineering College, Perunduai, Tamil Nadu, India. PCOS is an endocrine disorder which occurs due to hormone imbalance. PCOS may leads to infertility, diabetes mellitus and cardiovascular diseases. It may be identified by physical appearance, ultrasound scanning and clinical trials. The PCOS ovary can be identified as the follicles which are arranged peripherally and measuring 2-9mm of size. The dataset used in this paper consists of 119 samples with 17 features which represents the physical appearance and psychological characteristics such as stress, exercising methods, eating habits, etc. The classification algorithms can be applied on these data to predict the present of PCOS. The aim of the paper is to compare the accuracy of the classification model and find the algorithm which best suites for the dataset in predicting the occurrence of PCOS 11 30 2019 7396 7399 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5306.118419 https://www.ijrte.org/portfolio-item/D5306118419/ Department of Computer Science and Engineering, Kongu Engineering College, Perunduai, Tamil Nadu, India. Dr.R.R. Rajalaxmi* Dr.E. Gothai Department of Computer Science and Engineering, Kongu Engineering College, Perunduai Tamil Nadu, India. Dr.R. Thamilselvan Department of Computer Science and Engineering, Kongu Engineering College, Perunduai Tamil Nadu, India. Ms.P.Gokila Bindha Department of Computer Science and Engineering, Kongu Engineering College, Perunduai Tamil Nadu, India Dr.P. Natesan Department of Computer Science and Engineering, Kongu Engineering College, Perunduai , Tamil Nadu, India. The bioinformatics research must deal with the analysis of the large volume of data. Disease classification deals with the identification of relevant genes in almost all gene expression analyses, where researchers attempt to select a minimum number of genes with exceptional performance. The gene selection process mainly selects significant genes related to the disease. This work aims to accomplish relevant genes from large volume of candidate genes that help to identify cancers. In the proposed work, Binary Firefly Algorithm (BFA) helps to identify related genes using the Naive Bayes classifier. Based on the experimental results, Naïve Bayes guided Binary Firefly Algorithm (NBBFA) provided high accuracy with fewer genes 11 30 2019 7405 7409 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5308.118419 https://www.ijrte.org/portfolio-item/D5308118419/ Department of CSE, Kongu Engineering College, Perundurai, Erode, Tamil Nadu India. Malathy. S* Dr.C.N. Vanitha Department of CSE, Kongu Engineering College, Perundurai, Erode, Tamil Nadu India. The main objective of this paper is to give details about the security problems related to IoT and ways to overcome it. Almost everyone are accessing to internet daily. Most crucial data are shared over internet among various persons. Things which are connected to internet are known to be Internet of Things. Even though Indians are facing the huge attack, they are the leading internet users around the world. The main type of attacks are Phishing, smart phone attacks etc. This the main reason for the raise of internet security which is termed as cyber security. Setting strong passwords, preventing illegal access using two factor authentications are most common ways for preventing the things from internet. 11 30 2019 7410 7413 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5309.118419 https://www.ijrte.org/portfolio-item/D5309118419/ Assistant Professor, Department of ECE, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India. Chitra M* Priyanka S Student, Department of ECE, Kongu Engineering College, Perundurai, Erode. Tamil Nadu, India. K.N. Vardhan Student, Department of ECE, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India. Ramya S Student, Department of ECE, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India. FIR filter is the basic filter used in many DSP applications because of its linear phase , stability , low cost and simple structure . Designing a high- speed and hardware efficient FIR filter is a very difficult task as the complexity increases with the filter order .In most Application the higher order filters are required but the memory usage of filter increases exponentially with the order of the filter using multipliers occupy a large chip area and need more access time. So the design and implementation of highly efficient look up table (LUT) based circuit for the implementation using DA Algorithm increases the speed. Multiplier sharing and sub-expression elimination methods are proposed to optimize the Structural adders. These methods split the structural adders into smaller adder blocks to reduce the delay. In order to reduce the complexity of structural adders round-off can be performed at the cost of sacrificing precision of the filter. 11 30 2019 7414 7417 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5310.118419 https://www.ijrte.org/portfolio-item/D5310118419/ Associate Professor, Department of Management Studies, Ramaiah Institute of Technology, Bangalore, Karnataka-560054, India Dr. T. Mohanasundaram* Dr.P. Karthikeyan Assistant Professor (Sr. Grade) Department of Management Studies Kongu Engineering College,Erode, TamilNadu – 638060, India. P. Deepika MBA Student, Department of Management Studies, Kongu Engineering College, Erode, TamilNadu – 638060, India. Health care industry is one of the prominent one across the world irrespective of economic, social and cultural background. India, too have bigger and vibrant market for the health care services. Given the challenges, the sector is seeing an enormous growth not just because of health problems but mainly due to growing health awareness and preventive measures taken by the people. For any country, health of its people is an important aspect and for providing healthy life-style, government undertakes many programmes and offers social welfare measures. Health index of a country becomes vital indicator in measuring the nation’s overall development. In this study, we attempt to explore the progress and issues pertain to health care sector with special attention for health insurance policies and the governments’ role in that. The paper covers wide-range of health aspects with regards to measuring the prevailing scenario in health care sector and health insurance in particular. 11 30 2019 7418 7425 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5311.118419 https://www.ijrte.org/portfolio-item/D5311118419/