-74813b3e17f460286df-6ac 20220604072854636 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 A Department of Computer Science and Engineering, Government College of Engineering, Tirunelveli, Tamil Nadu, India G. Tamilpavai* C. Vishnuppriya Department of Computer Science and Engineering, Government College of Engineering, Tirunelveli,, Tamil Nadu, India Amino acids are little bio-particles with different properties. The capacity to ascertain the physiochemical properties of proteins is pivotal in many research regions, for example, tranquilize plan, protein displaying and basic bioinformatics. The physiochemical properties of the protein decides its collaboration with different atoms and subsequently its capacity. Foreseeing the physiochemical properties of protein and translating its capacity is of extraordinary significance in the field of medication and life science. The point of this work is to create python based programming with graphical UI for anticipating the physiochemical and antigenic properties of protein. Thus the instrument was named as ASAP-Analysis of protein succession and antigenicity expectation. ASAP predicts the antigenicity of the protein succession from its amino corrosive arrangement, in light of Chou Fasman turns and antigenic file. ASAP computes different physiochemical properties that is required for invitro tests. ASAP utilizes standardization esteems that expansion the affectability of the apparatus. 11 30 2019 7426 7432 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5312.118419 https://www.ijrte.org/portfolio-item/D5312118419/ Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India Ms.S. Ramya* Dr.C.S.Kanimozhi Selvi Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Globally, people are spending a cumulative amount of time on their mobile device, laptop, tab, desktop, etc,. for messaging, sending emails, banking, interaction through social media, and all other activities. It is necessary to cut down the time spend on typing through these devices. It can be achieved when the device can provide the user more options for what the next word might be for the current typed word. It also increases the speed of typing. In this paper, we suggest and presented a comparative study on various models like Recurrent Neural Network, Stacked Recurrent Neural Network, Long Short Term Memory network (LSTM) and Bi-directional LSTM that gives solution for the above said problem. Our primary goal is to suggest the best model among the four models to predict the next word for the given current word in English Language. Our survey says that for predicting next word RNN provide accuracy 60% and loss 40%, Stacked RNN provide accuracy 62% and loss 38%, LSTM provide accuracy 64% and loss 36% and Bidirectional LSTM provide accuracy 72% and loss 28%. 11 30 2019 7433 7437 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5313.118419 https://www.ijrte.org/portfolio-item/D5313118419/ Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Dr.C.S. Kanimozhiselvi* Ms.K.S. Kalaivani Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Dr.S. Poonguzhali Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Mr.D. Jayaprakash Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Autism is a serious, incurable mental disorder that hampers one's ability to interact and communicate. This disorder may be present as early as 18 months of age and can diagnose from early childhood. In recent times, one in every 68 children diagnosed with Autism Spectrum Disorder (ASD). Early diagnosis, social acceptance of kids suffering from this disorder and clearing misconceptions about the same is extremely important for social welfare. As of now, intervention is not of good quality in India and needs an institution building and professionalization to create real impact. Hence, it is necessary to provide autism intervention and therapies in school as well as in home to students from the age group of 2 to 16. Hence, there is a necessity to develop a mobile app, which will help the parents and teachers to train the autistic children. This mobile app will act as a therapeutic app and can offer help to caregivers in performing therapy and increase the time a child is engaged to therapy at reasonable cost. 11 30 2019 7438 7442 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5314.118419 https://www.ijrte.org/portfolio-item/D5314118419/ Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Dr.C.S. Kanimozhiselvi* Mr.D. Jayaprakash Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Autism spectrum disorder is a pervasive developmental disorder that affects the behavioral and communication function of the children. It shows poor performance in communication, social and cognitive abilities, which are generally characterized by developmental delays and abnormal activities in their regular work. Early intervention can reduce the autism spectrum disorders. Machine learning techniques are used to detect autistic features in childhood. The prediction models are implemented as classification problem in which model is constructed by using real-time autism dataset. The proposed work is use Backpropagation and learning vector quantization with different distance measures like Euclidean Distance, Manhattan Distance, and City Block Distance to predict whether a child has autism spectrum disorder and also defines the grade of the autism. So that it can be supported for the clinical decision making. It enables automated clinical autism spectrum disorder diagnostic process using machine learning models. 11 30 2019 7443 7446 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5315.118419 https://www.ijrte.org/portfolio-item/D5315118419/ Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Dr.C.S. Kanimozhiselvi* Mr.M.Balaji Prasath Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. Miss.T. Sathiyawathi Computer Science and Engineering, Kongu Engineering College, Perunduari, Erode, Tamil Nadu, India. The human voice construction is a complex biological mechanism capable of Changing pitch and volume. Some Internal or External factors frequently damage the vocal cords and change quality of voice or do some alteration in the voice modulation. The effects are reflected in expression of speech and understanding of information said by the person. So it is important to examine problem at early stages of voice change and overcome from this problem. ML play a major role in identifying whether voice is pathological or normal in nature. Voice features are extracted by Implementing Mel-frequency Cepstral Coefficients (MFCC) method, and examined on the Convolutional Neural Network (CNN) to identify the category of voice 11 30 2019 7447 7450 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5316.118419 https://www.ijrte.org/portfolio-item/D5316118419/ Department of CSE, Kongu Engineering College,Erode, Tamilnadu, India B. Krishnakumar* Dr.K. Kousalya Department of CSE, Kongu Engineering College,Erode, Tamilnadu, India. Dr.R.S. Mohana Department of CSE, Kongu Engineering College,Erode, Tamilnadu, India. Dr.K. Dinesh Department of CSE, Kongu Engineering College, Erode, Tamilnadu, India. S. Santhiya PG Scholar, Department of CSE, Kongu Engineering College, Erode, Tamilnadu, India. Human beings are affected by several diseases nowadays. All those diseases are healable with minimal amount of treatment when they are identified at its early stage. Several patients were not serious enough in diagnosing the disease initially, which makes the disease incurable for the patient lifelong. Hence in recent days number of death rates are getting increased. Cancer is the most dangerous diseases. Among several types of cancers women are mostly affected by breast cancer. In most of the developing and under developing countries breast cancer is the most prominent reason for women mortality. It is also curable when it is identified at its starting stage. During the later stages the cancer cells will be disseminated all over body hence it is difficult to remove it completely. Hence it has to be identified at its initial stage in order to give best treatment for the patient at right time. In this paper , Convolution Neural Network (CNN) a deep learning model is proposed for the investigation of breast cancer images for finding whether the person is affected by cancer or not. In the proposed work , features from images are extracted using convolution layers and then it is passed to the fully connected layer where it classifying the images as either malignant or benign. Experiments using standard benchmark datasets for the proposed CNN Model and standard Visual Geometry Group Network (VGGNet) has been conducted to measure its performances. From the results ,it is clear that CNN outperformed with the accuracy of 86.32% when compared to VGGNet which provides only 50% accuracy for the identification of breast cancer. 11 30 2019 7451 7454 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5317.118419 https://www.ijrte.org/portfolio-item/D5317118419/ Research Scholar & Assistant Professor, Vellalar College for Women (Autonomous), Erode–638012, Tamilnadu, India. P. Anitha* Dr.P.R. Tamilselvi Assistant Professor, Govt Arts and Science College, Komarapalayam – 638183, Tamilnadu, India. Our aims are to find the accuracy of classification with the normalisation in different types and the features in the techniques of selection on Diabetic Mellitus and the Pima Indian Diabetic dataset. Data Mining is the process of extraction. It extracts the previous unknown, valid and important information from the large amount of the data bases and can make the crucial decisions using the information. The classification methods are K-Nearest Neighbour and J48 decision tree can be applied to the data set of original and as well as the dataset with the pre-processed dataset. All the process of pre-processing can be applied to Pima Indian Diabetic Dataset to analyse the classification performance in terms of accuracy rate. The performance metrics is used to identify the accuracy classification is Recall, F-measure, Sensitivity and specificity, Precision, and Accuracy. The simulation is done by R tool. 11 30 2019 7455 7458 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5318.118419 https://www.ijrte.org/portfolio-item/D5318118419/ AP/Computer Technology, Kongu Engineering College College, Perundurai, Tamilnadu, India. Dr.S. Karunakaran* Dr.A. Sivakumar AP/Mechanical, Kongu Engineering College College, Perundurai, Tamilnadu, India Dr.N.T. Renukadevi AP/Computer Technology, Kongu Engineering College College, Perundurai, Tamilnadu, India. Dr.K. Saraswathi AP/Computer Technology, Kongu Engineering College College, Perundurai, Tamilnadu, India. Digital Technologies are getting worldwide popular. People are bounded with emerging technologies to make their life faster and smarter. Business organizations over the world taking this as an opportunity to launch more digital products to cover people. Users not aware of the importance of their private data. But the others know how to make use of it in favor of them. People need to be conscious and tailored to life in the digital age. This paper reveals the technical loop holes in variety of current digital applications that are familiar among the people. The aim is to create awareness among the people on security practices to safeguard from digital attacks. 11 30 2019 7459 7462 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5319.118419 https://www.ijrte.org/portfolio-item/D5319118419/ Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India K. Nanthini* T. Kavitha Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India. Dr. D. Sivabalaselvamani Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India. M. Pyingkodi Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India. Gourav Kumar PG Student, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India. Unpredictable nature of epilepsy, patients only has more need of awareness about precautions and how to handle the occurrence. Epilepsy belongs to have a recurrent seizures tendency throughout the life. Seizure may happen due to number of reasons like tumor, head injury, pregnancy time, genetic etc. It can be curable with proper diagnosis, incurable but controllable with lifelong medication and remaining are uncontrollable that leads to death. Recording of alert symptoms like auras, prodromes and precipitant factors are helped to self-alert the patient, create positive impact on quality of life and increase the efficacy of treatments. The need of enhancing early seizure detection and developing wearable monitoring product with low cost is used to create fear free environment among the affected people. In this connection, my proposed work reviewed on existing and currently available IOT based seizure detection and alert systems feasibility. 11 30 2019 7463 7466 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5320.118419 https://www.ijrte.org/portfolio-item/D5320118419/ Assistant Professor(s), Department of Computer Applications, Kongu Engineering College, Perundurai, Tamilnadu, India. Mrs. K. Chitra Dr. A. Tamilarasi Professor and Head, Department of Computer Applications, Kongu Engineering College, Perundurai, Tamilnadu, India. Mrs. T. Kavitha Assistant Professor(s), Department of Computer Applications, Kongu Engineering College, Perundurai, Tamilnadu, India. Mrs. S. Hemalatha Assistant Professor(s), Department of Computer Applications, Kongu Engineering College, Perundurai, Tamilnadu, India. Sentiment Analysis is an interesting research area. It useful for analyze the user comments with the help of natural language processing. While consider a huge data and improper data, the sentiment classification with better accuracy is a very big challenge in sentiment analysis. The social media records relevant to Sentiment analysis is a difficult one to identify with a people’s situation, thoughts, and view in the direction of a certain event, which has a number of applications such as election guess and product assessment. This paper focuses on the basic idea of optimal binary search Tree Technique to find the optimal solution (aspect) from a sentence among the several aspects; specifically, we perform the classification process appropriate to various features, which is used to identify the best one aspect among the several aspect terms in a sentence. In the proposed system, We have introduced optimal binary search Tree aspect level sentiment analysis technique. Through this we are getting best and efficient aspect level solution compare to General Tree. The main novelty of the paper is analyzing how aspect sentiment extracted from each word in a sentence through Dictionary based approach with help of the syntactic Patterns. It provides a well understanding of the appropriate role of every words to obtain optimal Aspect in an efficiency way. 11 30 2019 7467 7471 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5321.118419 https://www.ijrte.org/portfolio-item/D5321118419/ Assistant Professor, Department of English, Kongu Engineering College, Perundurai. Tamilnadu, India. Ms.R.D. Gomathi* Dr.V. Radhakrishnan Principal, K.S.Rangasamy Arts and Science College, Thiruchengodu. The classroom environment plays a major part in learning. The atmosphere is more essential for a student. The Students have a different psychological stimulus when performing the activities inside the classroom. The classroom atmosphere helps the students in learning the foreign language.TBLT is being applied inside the language classroom. With the new method, the teachers try to correlate the contents and the task design of teaching closer to their profession, because student participants can find it out easy for communicating via different stages tocarryout the tasksin all aspects of capabilitiesin second language acquisition. This paper is focused from all perspectivesof Task Based Language Teaching particularly in terms of meaning and concept, certain issues of conventional language teaching andexplaining the real value of execution of Tasks in language classroom . 11 30 2019 7472 7474 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5322.118419 https://www.ijrte.org/portfolio-item/D5322118419/ Department of Information Technology, Kongu Engineering College, Erode, Tamilnadu, India. Dr.C. Poongodi* Dr.K. Lalitha Department of Information Technology, Kongu Engineering College, Erode, Tamilnadu, India. Mr.A. Jeevanantham Department of Information Technology, Kongu Engineering College, Erode,Tamilnadu, India. Mr.D.Vijay Anand Department of Information Technology, Kongu Engineering College, Erode, Tamilnadu, India. Delay-tolerant networks (DTNs) are basically opportunistic networks and uses store-carry-and-forward switching for message forwarding. Performance of DTNs can be improved by placing stationary nodes, called throwboxes which increases the contact opportunities among nodes. Throwbox is viewed as relaying node and the message delivery is enhanced by spreading as many messages as possible. Increasing the contact opportunities in throwbox based DTN model depends on the deployment of throwboxes in suitable places. The objective of this paper is to identify optimal deployment locations of the throwboxes with a pre-specified transmission range, and to maximize the coverage of all the throwboxes in order to increase average delivery and to reduce the average delay among all the nodes in the network. We use Non-Dominated Sorting Genetic Algorithm–II for optimizing the deployment of throwboxes in DTN. The simulation results are analyzed for better strategy in deploying throwboxes and to improve the performance of throwbox-augmented DTNs. 11 30 2019 7475 7479 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5323.118419 https://www.ijrte.org/portfolio-item/D5323118419/ Department of Computer Applications, Kongu Engineering College, Erode, Tamilnadu, India. M. Pyingkodi* Dr. S. Shanthi Department of Computer Applications, Kongu Engineering College, Erode, Tamilnadu, India. Cancer gene selection plays a prominent work in the area of Bioinformatics. Gene selection methods aim to retain relevant genes and remove redundant genes. This proposed technique deals on gene selection techniques based on information theory. By investigating the information theory based on composition of feature relevancy, we consider that a excellent gene technique method could boost novel classification of the cancer gene data while reducing gene redundancy. Therefore, a modified gene selection technique called Composition of Feature Relevancy (CFR) is carried out. To assess CFR, the experiments are carrying out on five real-world cancer gene expression data sets and three best classifiers (KNN, Support Vector Machine and Random forest). The modified gene selection technique gives best outcome when competing to other recent technique in terms of accuracy and sensitivity in classification. 11 30 2019 7480 7484 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5324.118419 https://www.ijrte.org/portfolio-item/D5324118419/ Dept of CSE, Kongu Engineering College, Erode, Tamil Nadu, India Vani Rajasekar* J. Premalatha Dept of IT, Kongu Engineering College, Erode Tamil Nadu, India. K. Sathya Dept of CT/UG, Kongu Engineering College, Erode, India, Tamil Nadu, India. Block chain has drawn major attention recently in the area of cyber security. Till to date many detection techniques and protection mechanisms have been proposed to enhance the security. In this paper we have proposed an overview of distributed ledger framework, block chain to defense against the cyber attacks. We here present a comprehensive overview of block chain architecture and some major algorithms used in different block chains. The future trends of block chain technology in the applications such as IoT security, E-voting, Banking sector has also coined out in this paper. 11 30 2019 7485 7488 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5325.118419 https://www.ijrte.org/portfolio-item/D5325118419/ Assistant Professor (SLG) in the Department of Computer Applications, Kongu Engineering College, Tamil Nadu, India Dr. S. Shanthi* M. Pyingkodi Assistant Professor in the Department of Computer Applications, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India The global environment is presently facing a key issue of air pollution. The four air pollutants which are becoming a concerning intimidation to human health are respirble particulate matter, nitrogen oxide, particle matter, and sulfur dioxide. A vast amount of air quality data is collected in different monitoring stations throughout the world. The collected data can be analyzed to forecast the air quality index (AQI) of future. This paper proposes machine learning algorithms such as random forest, support vector machine, self adaptive resource allocation to predict the future AQI. Tamil Nadu Pollution Control Board (TNPCN) deployed air pollution monitoring station in five regions. Air pollutant of PM10, PM2.5, SO2 and NO2 are monitord and AQI is calculated.. The data collected from January 2019 to November 2019 by TNPCN and also AQI of previous five years were used This system attempts to predict the level of pollutant PM,SO2,NO2 in the air to detect the AQI. 11 30 2019 7489 7492 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5326.118419 https://www.ijrte.org/portfolio-item/D5326118419/ Assistant Professor (Sr.G), Department of English, Kongu Engineering College, Perundurai – 638060, Tamilnadu, India G. Chitra* A substantialincrease in the quantity of Students taking up Englishas the Second Language is so obvious in developing countries like India. The need for effective measures to augment and reinforce the learning of English with respect to such students has become paramount importance. A small group ofsuch students wasselected and their efficiency in the learning process of English in a specified time was carried out on different paraphernalia towardsof such an exercise. Two methods wereadopted in the evaluation of the learning process.. One group of students was taught both in English and in their respective mother tongue. The other group of students was taught only in English and at no point their mother tongue was involved in the exercise. The First group of students was taught to read in their respective mother tongue and gradually movedto English and the enhancement in the cognitive proficiency was evaluated with reference to the reading exercises.Students who have had both the efficiencies in their mother tongue andEnglish wereinvolved as assisting forces. The Second group of students was taught only in English. The various paraphernalia considered for the study remained the same irrespective of the student group. Standard procedures of Specially Designed Academic Instruction in English (SDAI) were adopted in following the augmentation process of learning and ability in acquiring English. All the basic and essential modalities were included in the study. Students were encouraged to involve themselves so voluntarily and wholeheartedly and their participation was encouraged. The group of students who used theirmother tongue was found to be in an advantageous position and use of mother tongue proved to be a significant factor in assisting themin the learning process. The group of students taught only in English didn’t exhibit better understanding or perception of English than their counterparts. The shortcomings experienced in language perception in every aspectof the different paraphernalia taken up in the study, in respect of the group of students taught only in English could not be considered as lack of skill in the acquisition of English and the difficulties to cope with the learning process seems to be temporal and keeping up with efficiency of the other group is only transitional The findings of both of these approaches for students acquiring English are highlighted in the present paper. 11 30 2019 7493 7495 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5327.118419 https://www.ijrte.org/portfolio-item/D5327118419/ MSc, M.Phil, , Research scholar, Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu 641029,India K.S. Gowri laksshmi Dr.R. Umagandhi MCA, M.Phil, PhD, Associate Professor and Head Department of Computer Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu 641029, India. Computed Tomography (CT) images are read by several lung nodule detection methods. The early step of contrast enhancement is mandatory because of low contrast in original image and further techniques of image processing are with unsatisfactory results. Hence this process are resulted an enhanced image of clearly discrete lung area from background. Image enhancement, feature extraction, and classification are three primary steps. In this work, Rule based Contrast Limited Adaptive Histogram Equalization (FRCLAHE) perform image enhancement step followed by feature extraction and Fuzzy Rule (FR) determines the contrast value. From rules upper contrast value are determined then image is enhancement from CLAHE. In the second, the feature extraction is conducted using the Fuzzy Continuous Wavelet Transform (FCWT) and Gray Level Feature Extraction (GLCM). After this step, the classification is completed using the Entropy Weighted Residual Convolution Neural Network (EWRCNN). Finally, the results are evaluated between the samples, compared to FP reduction with Faster R-CNN alone, the inclusion of rule‐based classification lead to an improvement in detection accuracy for the CAD system. These preliminary results demonstrate the feasibility of the proposed EWRCNN approach to lung nodule detection and FP reduction on CT images. 11 30 2019 7496 7502 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5328.118419 https://www.ijrte.org/portfolio-item/D5328118419/ Assistant Professor, Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore., Tamil Nadu, India S. Lakshmi Narayanan* Dr.K. Sankaranarayanan Dean, Department of Electronics and Communication Engineering, P.A. College of Engineering and Technology, Puliyampatti, Pollachi, Tamil Nadu, India. Dr.V. Vijayakumari Professor, Department of Electronics and Communications Engineering,Er.Perumal Manimekalai College of Engineering, Koneripalli, Hosur, Tamil Nadu, India.( Schemes of sharing a secret image are enhanced practically. The secret images are wrapped in cover imageon producing shadow images in this proposed scheme. In sequence,security is attained by means of methods of encryption and decryption while processing of sharing image. In the sharing step, cover image wrapped out the secret image by producing n images of shadow like cover image. This research dedicates a method of Improved Exploiting Modification Direction (IEMD) to conceal confidential data on preserving a high PSNR value. Pixel Segmentation Strategy EMD (PSSEMD) Method is used for wrapping confidential bit on all pixel cover image. the images as secret and cover are rebuilt by Shadow images. Lossless recovery of secret image is enriched by rebuilding the confidential image with lossless whereas by compressing the image before encryption and watermarking. Here Lossless image compression is done with the concern of sensitive information. Then chaotic encryption and decryption method is used for better security during image sharing process. Hence better embedding capacity and better quality in visual are attained in this proposed research results ensuring high security results in term of higher PSNR, lower MSE and higher correlation than the existing methods. 11 30 2019 7503 7510 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5329.118419 https://www.ijrte.org/portfolio-item/D5329118419/ Assistant Professor of Computer Science,Gobi Arts & Science College, Gobichettipalayam, Tamil Nadu, India. Mrs.G.A. Mylavathi* Dr.B. Srinivasan Associate Professor of Computer Science, Gobi Arts & Science College, Gobichettipalayam, Tamil Nadu, India. At an incredible speed, cyber security evolves in the ever-changing setting of attacks. Organisation processing of information inward and outward is huge in quantity and determining a threat amidst of information is challengeable. Late discovery of such instance is standstill challenge of the meticulous process. Thence, detection of intrusion and its prevention are rising challenge in Big data factors. the information inundation generally incorporate the Big data terms to dataset. The majorly focused issues are industrial oriented in big data challenge. Existing systems for big data cyber security problems are based on Online Support Vector Machines (OSVMs) framework. Bi-objective optimisation problem with primary objectives is designed as OSVMs configuration process for improving accuracy and less complexity of model. Here, a bi-objective optimization is implemented based on an Artificial Bee Colony (ABC). However, Online Support Vector Machines (OSVMs) has issue with computational complexity, and prematurity and local optimum is major problems in ABC algorithm. By overcoming this issue, developed research system designs an Ensemble Support Vector Machine (ESVM) framework for big data cyber security. Initially, the feature selection is done by using improved K-means clustering. Based on the selected features the intrusion detection and malware detection are performed using ESVM approach. In this proposed research work, a bi-objective optimization problem is designed as the ESVM configuration process for improving accuracy and less complexity of model and achieve its objectives. Cuckoo Search (CS) optimization algorithm is implemented for the bi-objective optimization. accuracy, precision, recall and f-measure are the parametric meters compared in proposed research attaining higher performance against existing approaches. 11 30 2019 7511 7518 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5330.118419 https://www.ijrte.org/portfolio-item/D5330118419/ Muthayammal College of Engineering, Rasipuram (Tamil Nadu), India. K. Santhosh Kumar* D. Maheswari Muthayammal College of Engineering, Rasipuram (Tamil Nadu), India. During the process of template matching with regard to finger vein identification, the probe used will get permitted only when the count of its vein points overlapping with the registered client is higher compared to the predetermined threshold. But, the admittance might be incorrect due to the neglect of the structure of the vein pattern. In the earlier works, the extraction of the vein structure (tri-branch) is done out of the vein pattern, and then combined with the entire vein pattern using a user-oriented threshold dependent filter setup. It renders a greater value of false acceptances, due to the User-oriented Threshold obtained from filter. In the step of branch tracking, the closest points are falsely detected, and therefore few tracking algorithms are needed. In order to resolve this, user-specific Threshold is generated on the basis of the correlation filter based selection combined with genetic algorithm. In the step of branch tracking, the closest points between the samples are decided by using the improved fuzzy clustering algorithm. It is observed that the local branches of the vein close to the segregation point of the vein pattern differ hugely from the fake pictures. The results of experiment carried out on two publicly available databases show the efficiency obtained of the novel design for boosting the performance achieved with respect to vein pattern based finger vein identification. 11 30 2019 7519 7525 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5331.118419 https://www.ijrte.org/portfolio-item/D5331118419/ Department of Mathematics, Nandha Arts and Science College,Erode, Tamil Nadu, India L. Anitha* S. Selvi Department of Mathematics, Bannari Amman Institute of Technology,Sathyamangalam, Tamil Nadu, India The gravity fieldand magnetic field impact with the inclusion of couple stress s r onshear waves in a transversely isotropic elastic solid medium is studied. Thedispersion equations for the particular problem have been obtained. Severalparticular cases are also examined. The numerical calculations are carriedout for specific rigidity parameter A, density parameter C, anisotropic factor N , initial stress parameter P , gravity parameter G, magnetic fieldparameter H , couple stress parameter  as well as wave number κ and theoutcomes are visually represented by graph. 11 30 2019 7526 7530 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5332.118419 https://www.ijrte.org/portfolio-item/D5332118419/ Research Scholar, Sri Ramakrishna College of Arts and Science for Women, Coimbatore, Tamil Nadu, India Usha. M* Dr .L. Sankar Associate Professor, Department of Computer Science, Sri Ramakrishna College of Arts and Science for Women, Coimbatore, Tamil Nadu India Dysarthria speech is the speech disorder which would be caused due to weakness of human muscles. The human with dysarthria disorder cannot speak normally whose speech will be very slow and congestive words which might be more difficult to understand. Thus it is required to create the environment where the speech of dysarthria disorder people can be recognized. This is done in our previous research work by introducing the method namely Hidden Markov Model based Speech Recognition (HMMSR). However this research work didn’t focus on accurate prediction and the echo noises presence in the speech signals. This would lead to inaccuracy in speech recognition. This is resolved by introducing the efficient dysarthria speech recognition framework namely Noise and Echo aware Dysarthria Speech Recognition Method (NE-DSRM). In this research work, Hybrid Least Mean Square-Adaptive Neuro Fuzzy Inference System (LMS-ANFIS) has been used for preprocessing. This method will remove both echo and noises present in the speech signals to ensure the accurate prediction outcome. And then speech recognition is performed by comparing the dysarthria speech with the phonological speech based on which relevancy would be identified. The accuracy of speech recognition can be improved by introducing the SVM based learning methodology which can classify the dysarthria speech based on which more relevant matching can be done. The objective of the system is, after being trained, to identify and classify limited-vocabulary sets of speaker-dependent. The overall assessment of the research work is done in the matlab simulation environment from which it is proved that the proposed method NE-DSRM tends to have better performance than the existing research works. 11 30 2019 7531 7536 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5333.118419 https://www.ijrte.org/portfolio-item/D5333118419/ Assistant Professor, Department of ECE, Vignan Institute of Technology and Science, Deshmukhi, Telangana, India. T. Rajeshwari* P.A.Harsha Vardhini Professor, Department of ECE, Vignan Institute of Technology and Science, Deshmukhi, Telangana, India. Agriculture plays a vital role in economic growth of every nation. In our nation major population - directly or indirectly depends on this sector. Technology growth introduced many automatic and intelligent systems that lead to smart agriculture. This paper presents high yield crop cultivation technique that monitors and also helps for the detection of germination of the disease and also to control the water supply to the plant. Various sensors are interfaced to the cultivation system for detecting the environmental conditions i.e., humidity, moisture, temperature across the farm. Wireless module is needed to transmit sensed data from Arduino to central unit (website) where data is stored, and analyzed. Arduino checks the present sensed data with disease condition (environmental) and soil condition, if the condition matches the sensed data, information is sent to the farmer and appropriate prevention methods will be implemented according to the condition of crop. 11 30 2019 7537 7540 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5334.118419 https://www.ijrte.org/portfolio-item/D5334118419/ Research Scholar, Management and Science University, Malaysia, South Eastern University of Sri Lanka, Srilanka. M. A. C. Salfiya Ummah* Prof. Dr. Chong Siong Choy Finanace, Accreditation Agency (FAA), Malaysia Prof. Dr. Ali Khatibi Management and Science University, Malaysia Social capital (SC) is vital in the form of networks since it acts as an agent for change of information and resources that can enhance the success or continued existence of women owned business entities. This study aims to examine the impact of SC on business performance (BP) of Muslim women entrepreneurs (MWEs) in small and Medium Enterprises (SMEs) in the Eastern Province of Sri Lanka (EPSL). SC was measured with the dimensions of familial affiliation such as parents and or husband if married or support from any other family members, someone who acts as a role model, economic status during childhood and non-familial affiliations such as business associated or trade associations. Structured questionnaire was used as the data collection technique with the sampling frame of 260 respondents using simple random sampling technique. Structural Equation Modeling (SEM) with AMOS as the data analysis technique while employing SPSS 23.0. The analysis of the structural model showed that, non-familial affiliation had a significant and positive relationship with business performance of Muslim women entrepreneurs where as familial affiliation did not significantly influence on business performance of Muslim women entrepreneurs in Sri Lanka. In most of the conservative Islamic families, women are not often allowed go out of their homes and mix with their counter parts independently. This situation can be observed in Sri Lanka Muslim families specially, in the Eastern Province where majority come from rural areas. However, those who can break this situation and were able to make affiliation with the business associates and other related bodies could enhance their business performance. Muslim women entrepreneurs, trade chambers and decision making authorities may use this finding of the study as a template to gain insight in to the factors influencing social capital on business performance of Sri Lankan MWEs. 11 30 2019 7541 7548 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5335.118419 https://www.ijrte.org/portfolio-item/D5335118419/ Department of Applied Mathematics, Pillai College of Engineering, New Panvel, Navi Mumbai, Maharashtra, India. S. Kuberl* Dr. Anshu Murarka Department of Applied Mathematics, Pillai College of Engineering, New Panvel, Navi Mumbai, Maharashtra, India. Adjunct Octagonal Array Token Petri Net Structures (AOATPN) are recently started out octagonal photograph delivering structures which out prolonged the Octagonal Array Token Petri internet systems. on this paper we view as AOATPN format over a control feature named inhibitor curves and separate it amongst a few critical octagonal photograph making and perceiving designs regarding the making energy. 11 30 2019 7549 7554 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5336.118419 https://www.ijrte.org/portfolio-item/D5336118419/ “Koneru Lakshmaiah Education Foundation, vaddeswaram”, Guntur, A . P, India. T. Srinivasa Rao* B. Srinivasa Kumar “Koneru Lakshmaiah Education Foundation, vaddeswaram”, Guntur, AP, India. S. Hanumantha Rao “Vignan’s Foundation for Science, Technology and Research, Guntur, AP, India. T. Nageswara Rao “Koneru Lakshmaiah Education Foundation, vaddeswaram”, Guntur, A P, India. ‘Γ’- ring concept was introduced by Nobusawa which is the generalization of a ring. In this paper we studied the concept of L – Fuzzy Ordered ‘Γ’- Semi ring along with non-membership and membership functions whose values are taken from a complete lattice and some properties. AMS Mathematics Subject Classification: 03B52 11 30 2019 7555 7557 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5337.118419 https://www.ijrte.org/portfolio-item/D5337118419/ Computer Science & Engineering, Nalla Narasimha Reddy Education Society’s Group of Institutions, Hyderabad, Telangana, India Dr.K. Rameshwaraiah* Dr.K.Srinivasa Babu Computer Science & Engineering, Nalla Narasimha Reddy Education Society’s Group of Institutions, Hyderabad, Telangana, India Mr.S.Sridhar Reddy Computer Science & Engineering, Nalla Narasimha Reddy Education Society’s Group of Institutions, Hyderabad, Telangana, India. In a few documents, cloud support safe information distribution plans be exhibited whereby clients be able to impart their information to other people/among a gathering through the cloud. This article proposes a proficient records distribution plan to allow savvy gadgets toward securely share records with others at the edge about cloud-helped Internet of Things (IoT). We additionally plan a safe looking through suggest to look through required records within possess/shared information on capability. 11 30 2019 7558 7561 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5338.118419 https://www.ijrte.org/portfolio-item/D5338118419/ Department of Software Engineering, College of Computing and Informatics, Haramaya University, Ethiopia B. Rajasekhar* Dr.Gavendra Singh Department of Software Engineering, College of Computing and Informatics, Haramaya University, Ethiopia Afendi Abdi Mohammed Department of Software Engineering, College of Computing and Informatics, Haramaya University, Ethiopia It is very essential to use smart agriculture in present days. This will solve various issues occur in agriculture. With Internet of Things (IoT), wireless sensors and fog computing an integrated system providing the smart agriculture is running in present villages. Various issues are identified on this smart agriculture. Parameters such as irrigation scheduling and inefficient utilization of water resources are two of several ubiquitous parameters restricting production in many agricultural regions. To solve these issues, energy consumption of the sensors plays major role to send and receive the data on various parameters. In this paper, an integrated energy efficient sensors by using thermal imaging to maintain the constant data flow from sensors to fog and cloud server. 11 30 2019 7562 7564 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5339.118419 https://www.ijrte.org/portfolio-item/D5339118419/ Ph.D.Scholar, Amity University, Noida, UP, India Sibotosh Dash* Dr. Rushina Singhi Guide of the Scholar, Assistant Professor, Amity University Noida, UP, India. The introduction of hybrid paddy seeds into rice farming system of Odisha has attracted almost all paddy growers. Because of high production potentiality and more profit the tribal farmers have been cultivating hybrid paddy and area is increasing over the years. Both farmers and distributors are experiencing constraints. There is considerable gap in adoption of recommended practices of hybrid paddy seeds leading less profit which requires Govt support in terms of incentives and technical support. The problems of seed distributors are lack of storage facility, quick germination while in store and timely supply of seeds to the growers. These problems need well thought programming of hybrid paddy cultivation in the state particularly in tribal zone as the tribes cannot afford to bear loss. 11 30 2019 7565 7572 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5340.118419 https://www.ijrte.org/portfolio-item/D5340118419/ Ph.D. Scholar, AMITY University, Noida, UP, India. N.K. Behera* G.K. Malik Guide of the Scholar, Assistant Professor, AMITY University, Noida, UP, India. Pulses are the integral part of farming system of Odisha. The production and productivity of pulses has not been increased for a long period. To supplement protein requirements of the rural population there is need to increase production level through adoption of recommended technologies. Besides to improve overall farming system the contribution of pulses in terms of enriching soil fertility, conservation of moisture and controlling of weeds are to be kept in mind. The present transfer of pulse technology system is quite weak which needs strengthening. The rate of adoption of pulse technologies stands with a gap of more than 50% along with problems of non availability of quality seeds and other inputs in time. To look at the future of pulse production in the state the steps like cluster approach, establishing of seed production centres,, variety wise seed plan, strengthening of Extension support, making input available in time at affordable cost, research linkage, year wise Production Program and Development of marketing chain for pulse are suggested based on the findings of the study. 11 30 2019 7573 7578 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5341.118419 https://www.ijrte.org/portfolio-item/D5341118419/ Poornima Institute of Engineering and Technology, Sitapura, Jaipur, Rajasthan, India. Pran Nath Dadhich* Deepak Sharma Swami Keshwanand Institute of Technology, Ramnagaria, Jagatpura, Jaipur, Rajasthan, India Explosive increase in urban population especially in major cities and towns has brought the strain on sustainable development of the city. Jaipur is one of the rapidly growing cities of India, facing several problems. One of the major issues is to find new area as well as restricted areas for further urban development. Therefore effective and efficient planning becomes mandatory for sustainable development of Jaipur. This research aimed to ascertain the built up growth of Jaipur city and its satellite towns; as well as connectivity of satellite town with all the basic amenities and facilities. In this paper satellite images are used to map built up growth and proximity analysis using GIS deployed for assessing connectivity to Jaipur city. Built up are showed enormous increase for Jaipur city and its satellite towns in last four decades. However proximity analysis provided details of distance to basic amenities and facilities from all towns. Although all towns are very well connected with road network but distances from facilities and basic amenities are almost lie in the range of 30-40 km, which indicated requirement of efficient transportation to avail facilities. Results can be used as preliminary guidelines for local governments and planners regarding development and management to achieve sustainable city. 11 30 2019 7579 7583 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D5342.118419 https://www.ijrte.org/portfolio-item/D5342118419/