-74813b3e17f460286df-7736 20220309042710650 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/ 05 30 2020 9 1 Assistant Professor, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India. Dr. N. Srinivasan Mr. Gurrala Nohar Reddy Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India. Mr. Thumu Kiran Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India. X-Ray security stuff screening frameworks are generally introduced in pretty much every station/air terminal to guarantee open vehicle security. In any case, the unwavering quality of manual recognition has been bothersome in genuine circumstances. For a stuff screener, recognizing the precluded things is typically so arduous and exhausting that missing some undermining things is unavoidable by and by. Particularly, in times of heavy traffic, travelers ordinarily take a great deal of time hanging tight for security checking in line. A solid programmed disallowed thing location framework is subsequently ideal for accelerating the screening procedure just as improving the precision of risk identification. X-Ray age is identified with the arrival vitality of the electrons when they arrive at the material, which is an element of the voltage of the material and the vitality of the electron bar. By estimating the X-Ray discharge and knowing the vitality of the electron pillar, the voltage of the material can be resolved. An information growth strategy for enhancing the X-Ray denied thing pictures utilizing GAN based methodology. In the first place, the forefronts containing precluded things are removed by a Region of Interest (ROI) division calculation from the gathered X-Ray security pictures. At long last, to confirm whether the created pictures have a place with its comparing class or not founded on the basic CNN model. 05 30 2020 2768 2772 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9834.059120 https://www.ijrte.org/portfolio-item/F9834038620/ CSE department, Koneru Lakshmiah Educational Foundation, Vaddeswaram, India. Rama Chandra Naradasu* Dharma Sri Harsha Tontepu CSE department, Koneru Lakshmiah Educational Foundation, Vaddeswaram, India Dr. Subramanyam Kodukula CSE department, Koneru Lakshmiah Educational Foundation, Vaddeswaram, India Estimating the stock value is a tough task, because it depends more on value of stock and there`s no exact variable which is able to guess exactly a value of a stock every other day. What so Ever, Efficient Market Hypothesis said a stock vaue is crucially dependent upon new information. Many sources of info is the choice of the person in the social media.The choice of public on factory outlet from a specific firms can determine the stability of that particular firm and thus affect the decision of the many members to buy the company's stock. When using opinion as an important data, an appropriate analysis of that opinion is necessary. One of the well know example of using opinion as an important data is anbrief note of sentiments.Analysis of sentiment is a way to determine emotion within the choice of public about some reason, in the given case some of thecorporations goods. There is some way of analyzes of the sentiment required to guess stock prices. Bollen concludes on his research that with 87.6 per cent accuracy, interestin social networking site such as Twitter can guess DJIA interest. This shows a clear relationship between the analysis of sentiments and the stock values. Our goal in this research is to use simple sentiment analysis to forecast Indonesian stock market. Naïve Bayes and the algorithm Random Forest are used to identify tweet to measure a company's opinion. Sentiment analysis are used to display the stock value for the product. The prediction model is built using linear regression approach. Our research shows that predictive models are using before stock prices and hybrid feature as predictor provide the accurate prediction with determination coefficient of 0.9989 and 0.9983. 05 30 2020 1443 1446 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9853.059120 https://www.ijrte.org/portfolio-item/F9853038620/ Associate Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India. Dr. M. Prakash* Aparna S Department of Computer Science and Engineering, SRM Institute of Science and Technology Kattangulathur, Tamil Nadu, India. Yash Srivastava Department of Computer Science and Engineering SRM Institute of Science and Technology, Kattangulathur, Tamil Nadu, India. Low light computer vision is an arduous task because of the low signal to noise ratio and less photon count. This means that the images captured in low light experience noise, which can result in blurring of the image. Although there are multiple techniques to overcome the noise and blur, their results are bounded in undue conditions as in there is a drop in the video imaging at night. This low light enhancement is a daring task as there are multiple factors like brightness, de-noising, de-blurring, contrast must be handled at the same time. Even the development of a CNN has proved to perform poorly on such data. This paper uses a technique to take care of this issue using GANs. Our technique gives a platform to enhance the image captured in low light and increase its resolution giving out an enhanced super resolute image. To support the low light image processing, we have used a dataset of low-light images. This method can give promising results on the dataset, and display a break for the future work. 05 30 2020 1544 1547 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9859.059120 https://www.ijrte.org/portfolio-item/F9859038620/ Assistant Professor, Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, India. Dr.K. Rajakumari* K. Dinesh Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, India. M. Deepan Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, India. V.A.Kiran karthi Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, India. C.G. Gavyarani Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, India. A model for Greenhouse farming Air Pollution Monitoring System for the concentrations of majorair pollutant gases has been developed. Air pollution in greenhouse farming is caused due to various elements in which the major constituent are fertilizers. This system uses IOT based Air Quality monitoring system and prediction framework. This device measures the concentration of harmfull gases like CO, LPG, Ammonia, Methane using gas sensors. The sensors will detect the environmental conditions of the farm and will send the data to Arduino. The device is connected to Cloud using Thing Speak via WiFi module. This system provides information about the air quality in the farm with the help of Android application which helps the farmers to maintain the air conditions in the farming land. The motivation of this project is to provide a cheaper monitoring systems which is beneficiary to all users 05 30 2020 1127 1130 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9869.059120 https://www.ijrte.org/portfolio-item/F9869038620/ Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India. Vinothini A* Kruthiga L Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India. Monisha U Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India. Flood are one of the unfavorable natural disasters. A flood can result in a huge loss of human lives and properties. It can also affect agricultural lands and destroy cultivated crops and trees. The flood can occur as a result of surface-runoff formed from melting snow, long-drawn-out rains, and derisory drainage of rainwater or collapse of dams. Today people have destroyed the rivers and lakes and have turned the natural water storage pools to buildings and construction lands. Flash floods can develop quickly within a few hours when compared with a regular flood. Research in prediction of flood has improved to reduce the loss of human life, property damages, and various problems related to the flood. Machine learning methods are widely used in building an efficient prediction model for weather forecasting. This advancement of the prediction system provides cost-effective solutions and better performance. In this paper, a prediction model is constructed using rainfall data to predict the occurrence of floods due to rainfall. The model predicts whether “flood may happen or not” based on the rainfall range for particular locations. Indian district rainfall data is used to build the prediction model. The dataset is trained with various algorithms like Linear Regression, K- Nearest Neighbor, Support Vector Machine, and Multilayer Perceptron. Among this, MLP algorithm performed efficiently with the highest accuracy of 97.40%. The MLP flash flood prediction model can be useful for the climate scientist to predict the flood during a heavy downpour with the highest accuracy. 05 30 2020 425 429 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9880.059120 https://www.ijrte.org/portfolio-item/F9880038620/ Department of Information Technology, Rajiv Gandhi College of Engineering and Research,Nagpur,India. Manish M. Goswami* The auto sector stock price trend is based on many national and international uncertain factors. It is challenging to predict the impact of such a factor on the stock price trend as the impact of the same factor varies at different points of time. In this research work, we are predicting the auto sector stock price trend using patterns in the historical data using a machine learning method. 05 30 2020 1131 1134 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9882.059120 https://www.ijrte.org/portfolio-item/F9882038620/ Assistant professor - ECE, Dr.N.G.P. Institute of Technology, Coimbatore, India. Dr.C. Senthilkumar* Dr.K.Gayathri Devi Professor - ECE, Dr.N.G.P.Institute of Technology, Coimbatore, India. Dr.M. Dhivya Associate Professor - ECE, New Horizon College of Engineering, Bengaluru, India. Mr.R. Rajkumar Assistant professor - ECE, Dr.N.G.P.Institute of Technology, Coimbatore, India. Security is imperative to individuals' key opportunity. In the course of recent decades with the headway of correspondence innovation the utilization of web has developed amazingly to trade data with no separation bearer. The most recent drama covers the threats against our technology infrastructures. The most challenging issue in the military network is that secure retrieval of confidential data. Information installing is the way toward implanting data in an information source without changing its perceptual quality. Stenography is the method of thrashing a document, message, picture or video surrounded by another record, message, picture or video. In previous methods, usage of image and text as key produces low security and reversible data hiding as algorithm produces less compression ratio. In our paper we proposed a novel method for increasing the video security by using One Time Password (OTP) and voice key as password and improving compression rate by using Blind detection algorithm. The uses of blind detection algorithm includes greater computational accuracy, high flexibility and deliver faster execution by an estimated high PSNR value .In addition, this paper also includes compressing image, audio and video files and embedding into a single video. 05 30 2020 705 709 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9890.059120 https://www.ijrte.org/portfolio-item/F9890038620/ Dept. of ECE, Dibrugarh University Dibrugarh , India. G.R. Michael* Dr Aditya Bihar Kandali. Electrical Department, Jorhat Engineering college, Jorhat, India. over the recent years much advancement are made in terms of artificial intelligence, machine learning, human-machine interaction etc. Voice interaction with the machine or giving command to it to perform a specific task is increasingly popular. Many consumer electronics are integrated with SIRI, Alexa, cortana, Google assist etc. But machines have limitation that they cannot interact with a person like a human conversational partner. It cannot recognize Human Emotion and react to them. Emotion Recognition from speech is a cutting edge research topic in the Human machines Interaction field. There is a demand to design a more rugged man-machine communication system, as machines are indispensable to our lives. Many researchers are working currently on speech emotion recognition(SER) to improve the man machines interaction. To achieve this goal, a computer should be able to recognize emotional states and react to them in the same way as we humans do. The effectiveness of the speech emotion recognition(SER) system depends on quality of extracted features and the type of classifiers used . In this paper we tried to identify four basic emotions: anger, sadness, neutral, happiness from speech. Here we used audio file of short Manipuri speech taken from movies as training and testing dataset . This paper use CNN to identify four different emotions using MFCC (Mel Frequency Cepstral Coefficient )as features extraction technique from speech. 05 30 2020 2364 2366 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9896.059120 https://www.ijrte.org/portfolio-item/F9896038620/ Student, Electrical Engineering, Universiti Malaysia Pahang. Ismail* Kamarul Hawari Professor, Faculty of Electrical and Electronics Engineering University Malaysia Pahang. The multifocus image fusion is a kind of method in image processing to collecting the sharp information from multifocus image sequence. This method is purposed to simplify the reader understand the complex information of image sequence in an image only. There are many methods to generate fused image from several images so far. Many researchers have developed many new and sophisticated methods. They show complicated computation and algorithm. So, that it is difficult to understand by the new students or viewer. Furthermore, they get difficulties to create the new one. In order to handle this problem, the proposed method a concise algorithm which is able to generate an accurate fused image without using a complicated mathematical equation and tough algorithm. The proposed method is the normalized random map of gradient for generating multifocus image fusion. By generate random map of gradient, the algorithm is able to specify the coarse focus region accurately. The random map of gradient is a kind of information formed independently from independent matrix. This data has a significant role in predict the initial focus regions. The proposed algorithm successes to supersede difficulties of mathematical equations and algorithms. It successes to eliminate the mathematical and algorithm problems. Furthermore, the evaluation of proposed method based on the fused image quality. The Mutual Information and Structure Similarity Indexes become our key parameter assessment. The results show that the outputs have high indexes. It means it is acceptable. Then the implementation of multifocus image fusion will increase the quality of the applied fields such as remote sensing, robotics, medical diagnostics and so on. It is also possible implemented in other new fields. 05 30 2020 1063 1069 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9904.059120 https://www.ijrte.org/portfolio-item/F9904038620/ Research scholar M.I.T Aurangabad, India, Bansode Balbhim Narhari* Bakwad K.M. Principal Puranmal Lahoti Government, Polytechnic college, Latur, MSBTE, Mumbai, India Ajij Dildar Sayyad Associate Professor and Vice Principal,MIT Aurangabad, India Existing methods on retinal disease detection are mostly depends on lesion detection techniques or multiple instance learning framework. However extensive research efforts fail to address effective representations of the different lesions from fundus images. In this paper, a innovative techniques is offered built on pre-examined entirely convolutional neural network (CNN) over and done with transfer learning. The proposed method utilizes the effective learning from recent deep CNN models with use of SVM classifier at the end. Meanwhile, additional retinal image pre-processing technique is applied for the better classification results. The improved result has contributed to the area of computer aided diagnosis for retinal screening system. Extensive experiments have been conducted on Messidor and IDRiD database with desired obtained accuracy of 96.29 % and 94.82 %. The proposed method supports retinal disease screening effectively by deep learning methods. 05 30 2020 878 884 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9905.059120 https://www.ijrte.org/portfolio-item/F9905038620/ Department of Computer Science and Engineering, Seth Vishambhar Nath Institute of Engineering and Technology, Barabanki, India. Lalit Kumar* Neelendra Badal Department of Computer Science and Engineering, Kamla Nehru Institue of Technology, Sultanpur, India. In the real world scenario, people are using various electronics devices according to their use. These devices are connected to each other in direct and indirect manner. This connection provides communication and sharing of information and data to one and another. This overall communication system uses various technologies i.e. Internet of Things, Cloud Computing, Fog Computing and other. The communication in IoT is based on Layered Structure. This layered structure helps to transfer data in safe and secure manner. For safe and secure transmission of data over IoT, user uses encryption method, but on encryption algorithm can be easily recognized by attacker so here user uses a hybrid approach. This hybrid approach is based on AES and Transpositional Reverse Algorithm. Here Transpositional Reverse Algorithm helps the users to secure the AES encryption scheme and helps to create an efficient Hybrid scheme. 05 30 2020 2734 2737 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9907.059120 https://www.ijrte.org/portfolio-item/F9907038620/ Assistant Professor, Department of Mechanical Engineering, Gnanamani College of Technology, Namakkal, Tamilnadu, India. Mr. Sachin S Raj* Dr.T.K. Kannan Professor/Principal, Department of Mechanical Engineering, Gnanamani College of Technology, Namakkal, Tamilnadu, India. Mr.S. Krishnakumar Assistant Professor, Department of Mechanical Engineering, Gnanamani College of Technology, Namakkal, Tamilnadu, India. Mr.M. Sudhagar Assistant Professor, Department of Mechanical Engineering, The Kavery Engineering College, Salem, Tamilnadu, India. Mr.M. Vairavel Assistant professor, Department of Mechanical Engineering, Anna Poorna Engineering College,Salem, Tamilnadu, India. Recently, composite materials are among the most prospective substances. The improved characteristics were possessed by Metal matrix composites (MMCs) but which is low in comparison to plain composites. Due to low cost and density, nowadays composite materials most trendy one. Therefore, composite materials reinforced with fly ash particulate of bagasse fly ash will probably overcome the barrier of expense in the applications of small motor and automobile industry. In the current study, a technique of stir casting has been utilized to prepare reinforcement of AL6061 alloy with 5 wt% to 25 wt% of fly ash particulate matter of bagasse fly ash. In this study, the identification of phase and characterization of structures was performed with the help of analysis of diffraction in the X-ray on the fly ash particulate matter of bagasse. The analysis of microstructure was performed with the help of optical microscopy and Scanning electron microscopy. The test like pitting corrosion, compression and hardness have been performed on composite materials and light metal. The analysis of SEM demonstrates that in the matrix stage, there is a homogeneous distribution of fly ash particulates of bagasse and also excellent adhesion is existing among reinforcement and matrix. The hardness, pitting corrosion and compressive strength were improved, and the density of the composite materials was decreased when there is an improvement in the number of fly ash particulates of bagasse. The enhanced pitting corrosion of reinforcement of aluminum alloy with fly ash particulates of bagasse is related to the initiation of the nobler second stage of fly ash particulate matter. 05 30 2020 1203 1211 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9909.059120 https://www.ijrte.org/portfolio-item/F9909038620/ Asst. Professor in Department of Computer Science and Engineering, Maharaja Institute of Technology Mysore. Mr. Honnaraju B* Dr. Murali S Professor in Department of Computer Science and Engineering at Maharaja Institute of Technology Mysore. Vision based mobile robot navigation is one of the important because the robots can resolve lots of problems in which human life is dangerous, difficult and costly. A difficult problem is to make a vision-based robot navigate properly to the target by avoiding the obstacles. Path information is very essential for successful navigation of the robot. The main purpose of this paper is to present an approach for mobile robots to generate path and construct maps. This work is focused on providing the path information of an environment using a single 2-D camera. Whenever robot identifies the human in the corridor, it generates the information of the path information and constructs the map is achieved based on the human moment and the human position. On the robot the camera is mounted which acquires images in real time. Oath information is generated for mobile robot using acquired real time images and processing real time images. 05 30 2020 226 229 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9910.059120 https://www.ijrte.org/portfolio-item/F9910038620/ Asst. Professor, Bharati Vidyapeeth College of Engineering, Navi Mumbai. Prof. B. W. Balkhande* Deepak C. Dhadve Student, Computer Science and Engineering,Bharati Vidyapeeth College of Engineering, Navi Mumbai. Pranalee P. Shirsat Student, Computer Science and Engineering,Bharati Vidyapeeth College of Engineering, Navi Mumbai Mayuri S. Waghmare Student, Computer Science and Engineering,Bharati Vidyapeeth College of Engineering, Navi Mumbai The smart surveillance system defines a approach to identify and recognize human faces from the surveillance videos. It is very tedious to find particular person within a video. This system gives a quick and efficient method to find the presence of a person within a surveillance video. The smart surveillance system uses various machine learning algorithms like Face Recognition and Face Detection to achieve the required results. This system can be used in many security systems to check the presence of a person in any video of the particular area. 05 30 2020 1135 1138 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9922.059120 https://www.ijrte.org/portfolio-item/F9922038620/ School of Mechanical Engineering, KIIT DU, Bhubaneswar, Odisha, India Dr Sushanta Tripathy* Dr. Puspalata Mahapatra KIIT School of Commerce & Economocs, KIIT DU, Bhubaneswar, Odisha, India Arpan Mahapatra Research Schloar, SSU. Cuttack, Odisha, India Dr. Suryakanta Panda Reader, Baranga, College, Bhubaneswar, Odisha, India Financial Efficiency is one of the important barometer for measuring the performance of Companies irrespective of their sector including insurance to attain their sustainability in the long run. Through this study attempt has been made to evaluate the influence of overseas Investment on the financial efficiency of Indian Insurers ( Public) and to find out whether Foreign Participation has remarkable impact on it or not. The existing study is analytical and descriptive in nature and used both primary as well as secondary data from different sources like Govt. Body report, IRDA annual report , Different Journals and on line data base. The collected data were analyzed through inferential statistical techniques like correlation, Multiple regression , f-test and Analysis of Variance (ANOVA) with the help of SPSS (18.0 version). The study wind-up with remarks that there is a significant association among FDI and Financial aspect including all the sub parameters. This Study will helpful to the Policy maker, IRDA and Govt to take the remedial measures to attract more and more FDI in to the Indian Insurance Sector to make it more penetrated and deveeloped.. Hence, it is recommended that more FDI should be encouraged in Indian Insurance sector to place it a better position in the global ranking and to assure financial stability in India. 05 30 2020 1860 1864 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9924.059120 https://www.ijrte.org/portfolio-item/F9924038620/ Department of Mechanical Engineering, Koneru Lakshmiah Education Foundation, Guntur, India. Samanthapudi Meghana* Seeram Srinivasa Rao Department of Mechanical Engineering, Koneru Lakshmiah Education Foundation, Guntur, India. Lower limb orthosis can be used to replace the loss of functioning of lower limb that causes a lot of inconvenience in carrying out day to day activities. However, wheelchair may assist to some extent it might lead to medical issues. Replacing the wheelchair with rehabilitation devices helps in sorting this issue. Various rehabilitation techniques and devices that are developed are reviewed and their specifications and comparisons are mentioned in brief. A lower limb orthosis is designed using solidworks and the design imported into MATLAB using simmechanics is simulated using simscape multibody and the resulting torques for each joint namely hip, ankle and knee joints are obtained. 05 30 2020 107 113 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9928.059120 https://www.ijrte.org/portfolio-item/F9928038620/ Department of Computer Science and Engineering, GITAM School of Technology, GITAM Bangalore Campus, Bangalore, India Rajesh S M Sukruth Gowda M A Department of Computer Science and Engineer- ing,School of Engineering, Presidency University, Bangalore, India Shivaprasada K H Department of Computer Science and Engineering, GITAM School of Technology, GITAM Bangalore Campus, Bangalore, India Sandhya G Department of Computer Science and Engineering, KNS Institute of Technology, Bangalore, India The growth in technology with respect to Internet of Things is rapid in the current scenario. Every device, every aspect is becoming smart. Smart home is one such application where in which delay in the efficient delivery of critical packets is the challenge. The existing techniques are time consuming and will not be able to satisfy the changing requirement. In this paper an efficient scheduling technique is proposed for smart home communities by identifying the critical messages and assigning priority along with the deadline to such packets which helps in reducing the delaying and serving the critical packets at the required time. 05 30 2020 1212 1216 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9937.059120 https://www.ijrte.org/portfolio-item/F9937038620/ Assistant Professor, Finance Loyola Institute of Business Administration (LIBA) Loyola College Chennai Dr. D. Madhava Priya* Dr. Deepa Ittimani Tholath Associate Professor, Marketing Loyola Institute of Business Administration (LIBA) Loyola College, Chennai When GST was implemented in India in the year 2017, there was a sea of change in the way in which tax was collected. In the Distribution process where there was different levels of partners involved there was collection of taxes in different stages which was followed till the implementation of GST. In this case study in order to familiarize the students with the evolution of the GST system and the impact of it on the channel partners we are looking at the case of Mr.Kumar , he had started his distribution agency Pitambar Distributors in 1986 the tax structure for a distributor in India had - value added tax, octroi and service tax .In 2006 the first step towards the implementation of GST - Goods and Services Tax was taken which became a reality and came into being by July 2017.The Post GST Scenario changed the playing field for FMCG companies which automatically reflected on their channel members namely distributers like Pitamber Industries. In this context with the data available from Pitambar agencies in the past year Mr.Kumar has to now rethink his strategies and decide whether to continue in the same business or not. This case can be used to identify the impact of GST on The FMCG Sector, Chart the progress of GST till date, to familiarize students regarding distribution processes and the implication of GST on the same, to identify impact on sales of different category of FMCG products after the implementation of GST 05 30 2020 885 894 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9946.059120 https://www.ijrte.org/portfolio-item/F9946038620/ Head of the Department, Department of EEE, Vel Tech, Chennai, India *Dr. M. Karthikeyan* Dharma Vignesh P.G. Student, Department of EEE, Vel Tech, Chennai, India, Kishor A Student, Department of EEE, Vel Tech, Chennai, India Normally, We are using refrigerating system to store the foods, Medicines..etc to extend the lives of the products. But in the existing refrigerating system which causes cooling effect with the help of refrigerants like CFC’s,HCFC’s. They are the harmful components which causes environmental Degradation. In order to overcome this we are using peltier concepts for refrigeration and protecting the environment. In this project to introduce a portable refrigeration using peltier Element. In peltier element when given DC supply produces cooling effect on one closed surface and heating effect on another surface. The cooling effect on one surface is circulated using a fan. The heat from the hotter side is sink in the heat exchanger is removed using circulating coolant or using fan. A 230V AC supply is step down using a Transformer and Rectified using a Bridge rectifier and given as a Input to the Buck converter. The Buck Converter supplies variable DC supply to the Thermo Electric Generator. The main advantage of this system is eco friendly and simplified system with reliable control. 05 30 2020 1447 1450 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9949.059120 https://www.ijrte.org/portfolio-item/F9949038620/ Assistant Professor in department of computer science & Engineering, Bangalore Institute of Technology, Bangalore. Maya B S* Dr. Asha. T Assistant Professor in department of computer science & Engineering, Bangalore Institute of Technology, Bangalore. The increasing in the incidence of stroke with aging world population would quickly place an economic burden on society. In proposed method we use different machine learning classification algorithms like Decision Tree, Deep Neural Network Learning, Maximum Expectization , Random Forest and Gaussian Naïve Bayesian Classifier is used with associated number of attributes to estimate the occurrence of stroke disease. The present research, mainly PCA (Principal Component Analysis) algorithm is used to limit the performance and scaling used to be adopted to extract splendid context statistics from medical records. We used those reduced features to determine whether or not the patient has a stroke disorder. We compared proposed method Deep neural network learning classifier with other machine-learning methods with respect to accuracy, sensitivity and specificity that yields 86.42%, 74.89 and 88.49% respectively. Hence it can be with the aid of both patients and medical doctors to treat viable stroke. 05 30 2020 2011 2017 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9954.059120 https://www.ijrte.org/portfolio-item/F9954038620/ Department of Computer Science and Engineering,GITAM School of Technology, GITAM Bangalore Campus, Bangalore, India Gunti Spandan Tanveer Ahmed Department of Computer Science and Engineering,GITAM School of Technology, GITAM Bangalore Campus, Bangalore, India Sangmeshwar Department of Computer Science and Engineering,GITAM School of Technology, GITAM Bangalore Campus, Bangalore, India Rajesh S M Department of Computer Science and Engineering,GITAM School of Technology, GITAM Bangalore Campus, Bangalore, India Mental stress, depression and anxiety are the major problems in our community, as these are the source of many health issues like hypertension, heart attack or even sudden deaths and self-annihilation. To reduce stress, it is necessary to predict it in its early stages before turning into chronic and irreversible damages. Generally, all these problems can be detected by counselling, questioner or observing a person for a long time. But we will focus on changes that occur in human body when he/she is in stress, depression or anxiety. We will monitor the heart beat and detect emotional changes occurred in a person when he/she is in stress, depression or anxiety. On detecting we will send an intimation message to their family member so that they will help that person to come out of his/her situation. 05 30 2020 1261 1265 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9971.059120 https://www.ijrte.org/portfolio-item/F9971038620/ Department of Computer Science, Rabindranath Tagore University, Raisen, Madhya Pradesh, India Nidhi Joshi Rajendra Gupta Department of Computer Science, Rabindranath Tagore University, Raisen, Madhya Pradesh, India. The key aim of the data mining techniques is to help the user by reducing the effort for exploring the data, recovering the patterns, and implementing applications that help to find the knowledge specific contents, decision making, and predictions. This research work develops a recommendation system by using the merits of data mining algorithms. They are used for designing web-based e-learning recommendation systems. This model aims to understand the user behavior and contents requirements of the learner. This purpose is solved by obtaining the information from the data source and producing the suggestions of suitable content to the learner. The concept of web content mining and web usage mining has been combined together for performing the required work. This technique involves the genetic algorithm and k-means clustering algorithm for designing the presented model. In this work the k-means clustering algorithm has been used to track user behavior and the genetic algorithm has been used as a search algorithm to find the necessary resources in the database. Finally, the presented system is implemented and its performance is measured. The estimated results demonstrate that the presented model enhances the accuracy of recommendations and also speeds up the computations. A related performance calculation has also provided to justify this conclusion. The obtained results demonstrate that this technique is acceptable for new generation application designs. 05 30 2020 1186 1195 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9991.059120 https://www.ijrte.org/portfolio-item/F9991038620/ Energy Centre, Maulana Azad National Institute of Technology, Bhopal 462003, M.P., India. Mukesh Kumar Rathore* Meena Agrawal Energy Centre, Maulana Azad National Institute of Technology, Bhopal The worldwide electrical energy consumption is growing day by day and also increasing the demand of power generation. So in addition into the electrical power system network for power production units a large number of renewable energy units is being combined. A wind energy generation system is the economical of all safe renewable energy sources and the environmentally clean in worldwide. The acceptance of variable speed generation systems the recent evolution of variable frequency drive and power semiconductors technology has been aided. Pitch angle control techniques is best factor to improve the efficiency as well as protection of the wind turbine blade. Therefore, presented in the work a comprehensive model of permanent magnet machines in wind turbine system. Modelling and simulation permanent magnet machines with wind turbine system of PI and PID controller based pitch angle control figuring performance is done by using MATLAB software. The significant result of these controller performance is being compared and also shown with validate approach with the existing survey. 05 30 2020 318 322 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F9995.059120 https://www.ijrte.org/portfolio-item/F9995038620/ Computer Science and Engineering, DKTE Society’s Textile and Engineering Institute, Ichalkaranji, India. Dr. S. K. Shirgave* Mr. P. M. Gavali Computer Science and Engineering, DKTE Society’s Textile and Engineering Institute, Ichalkaranji, India. Nowadays users express their opinions on different websites like e-commerce and special review websites. Analyzing customers' opinions and their responses is important for decision making. So the researchers worked on analyzing these reviews automatically using a classical machine learning approach like Support Vector Machine (SVM) and various modern deep neural networks. For these networks, words are represented by using vectors called word embeddings. The required word embeddings are taken from pre-trained Word2Vec or learned from a corpus of the given main task. But, each method has its demerits. In the case of pre-trained word embeddings, embeddings are learned from large general corpus so these embeddings are not task specific. While in the case of learning words from the corpus of the main task, it does not reflect the true semantics. To deal with these problems, we have proposed an embedding developer model. This model develops task specific word embedding which also reflects true semantics. Task specific word embeddings are generated from the given corpus using the embedding layer in Keras. It builds the embeddings by considering relationships between words in the window. While true semantics are taken from Word2Vec embeddings. The proposed model combines these two embeddings to generate true semantics and task specific word embeddings. Result analysis shows that the proposed system works better on many benchmark datasets. 05 30 2020 1689 1693 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2606.059120 https://www.ijrte.org/portfolio-item/A2606059120/ Pawar , Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India. Prof. Pruthviraj. P. Karthik Ganashekaran Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India. Prashant Popat Dhanawade Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India. Simranjit Khera Computer Engineering Bharati Vidyapeeth College Of Engineering Navi Mumbai, India. Automation of work has become an important part of industrial manufacturing process in the recent years. Tasks that usually take large amount of labor and time can now be easily completed by using robots which can be programmed to do the said task. Tasks such as assembly and object sorting which require tasks to be repeated can be carried out by robots. The system proposed here can be used for sorting objects in the industrial manufacturing process. The system focuses on sorting objects based on their size or color or both. The system is designed using IR sensors, a TCS3200 color sensor and Arduino UNO board for controlling the different parts. The proposed system gives better accuracy and performance as compared to the methods currently used. 05 30 2020 1770 1773 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2607.059120 https://www.ijrte.org/portfolio-item/A2607059120/ Department of CSE, School of Studies in Engineering and Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur, India Dugimpudi Abhishek Reddy Deepak Yadav Department of CSE, School of Studies in Engineering and Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur, India Nishi Yadav* Department of CSE, School of Studies in Engineering and Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur, India Devendra Kumar Singh Department of CSE, School of Studies in Engineering and Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur, India In the field of medicine, iris segmentation has become a great field of interest from the past few years. Iris segmentation is also largely used in iris recognition systems [3] which are extensively used in security control [1][2]. Here iris segmentation is done using semantic segmentation which is based on the U-Net architecture. The typical U-net architecture contains two paths- contracting path containing convolutional and pooling layers and the expanding path consists of transposed convolutional operations. The UBIRIS dataset is trained on the traditional U-Net model with some modifications according to the size of the images present in the UBIRIS dataset. The results obtained were very close to the ground truths and accuracy obtained is also appreciable. 05 30 2020 2024 2028 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2614.059120 https://www.ijrte.org/portfolio-item/A2614059120/ M.Tech student, Department of Electronics and Communication Engineering at SDM College of Engineering and Technology, Dharwad, Karnataka, India. Mamatha L Japate Dr.S.S. Navalgund Assistant Professor, Department of Electronics and Communication Engineering at SDM College of Engineering and Technology, Dharwad, Karnataka, India.. The 20th century is known as the Information age. Development of technology led to the storing and communication of information in the digital form. Digital technology provides easy access to the information through internet and other forms of technology. Transmission of information is also become easy using digital technology. The information stored or communicated may be vulnerable to attacks from the adversaries. All the organizations and individuals are facing the threat of the insecurity of the information of data over the internet. Development of communication media and insecure media emphasizes the requirement to secure the data. The method of securing the information so that it is not stolen by the hackers is known as encryption. The development of multimedia technology has increased the images as the carriers of information. The conventional encryption algorithms are not well suited for the image encryption. Image encryption has developed in the past recent years as an important field. In the image encryption, the substitution and transposition techniques are performed on the pixel values of the image based on the key. One of the mechanisms for image encryption is based on chaos theory. Chaos sequence is used as a key for encryption because of its properties. This method of encryption is more secure and robust. 05 30 2020 1694 1699 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2615.059120 https://www.ijrte.org/portfolio-item/A2615059120/ School of Electronics Engineering, Vellore Institute of Technology, Vellore, India B.Sai Tejeswar Reddy Valarmathi. J School of Electronics Engineering, Vellore Institute of Technology, Vellore, India Classification of target from a mixture of multiple target information is quite challenging. In This paper we have used supervised Machine learning algorithm namely Linear Regression to classify the received data which is a mixture of target-return with the noise and clutter. Target state is estimated from the classified data using Kalman filter. Linear Kalman filter with constant velocity model is used in this paper. Minimum Mean Square Error (MMSE) analysis is used to measure the performance of the estimated track at various Signal to Noise Ratio (SNR) levels. The results state that the error is high for Low SNR, for High SNR the error is Low. 05 30 2020 1700 1704 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2616.059120 https://www.ijrte.org/portfolio-item/A2616059120/ Advanced Manufacturing Center, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 D. Tunggal, Melaka, Malaysia. R. Izamshah* M. Z. Kasman Royal Malaysian Maritime Police, 98700 Limbang, Sarawak, Malaysia M.S. Kasim Advanced Manufacturing Center, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 D. Tunggal, Melaka, Malaysia. M.S.A Aziz Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 D. Tunggal, Melaka, Malaysia. M. Rafiq Advanced Manufacturing Center, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 D. Tunggal, Melaka, Malaysia. Natural Rubber/Ethylene Propylene Diene Monomer (NR/EPDM) elastomeric has gaining popularity in the automotive industry owing to the fact in term of sustainability. With extensive studies and an increasing number of applications for future advancement, the need for an accurate and reliable guide in processing this type of elastomer has increased enormously. The present work deals with the study of compression moulding parameters (i.e. temperature, pressure, heating time and pressure time) and its effects against NR/EPDM elastomeric mechanical properties (i.e. ultimate tensile strength (UTS), cross-link density and eccentricity error) aim on establishing optimized processing parameters setup. The optimizations are achieved through the Response Surface Methodology (RSM) and mathematical model for each response is developed to access the relationship between the parameters. Adequacy of models is analysed statistically using analysis of variance (ANOVA) in the determination of significant input variables and possible interactions. Lastly, multi objectives optimization is performed through numerical optimization and predicted results are validated. Strong agreement between experimental and the selected solution are found in between 93% and 96%, thus validating the solution as an optimal run condition. The findings suggest that temperature and heating time is the main factor affecting ultimate tensile strength, whereas for cross-link density there is only one significant parameter which is temperature. UTS and cross-link density decrease with the increases of the temperature and heating time due to the degradation (temperature too high for NR/EPDM working temperature). Therefore, it is recommended to start the process below the NR/EPDM degradation point to avoid the scissoring rubber take place and subsequently improving the mechanical properties 05 30 2020 1705 1710 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2619.059120 https://www.ijrte.org/portfolio-item/A2619059120/ Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India. Hari Vamsi Yadavalli Diabetes-Retinopathy (DR) condition detection based on machine learning and image processing techniques makes use of the diabetic portion from the set of input images. Textural feature analysis is adopted for feature extraction. CNN is used to classify the extracted features. The execution of the proposed technique is carried out in MATLAB, and the analysis is based on the accuracy, sensitivity, specificity. In the light of analytic outcomes, it can be said that the introduced method performs better than the existing technique in terms of all the mentioned parameters. 05 30 2020 2436 2440 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2621.059120 https://www.ijrte.org/portfolio-item/A2621059120/ Professor, Department of Electronics and Communication Engineering, Vardhaman College of Engineering, Hyderabad, India. Dr. Ch. Subrahmanyam Aditi G Nayak Department of Electronics and Communication Engineering, Vardhaman College Of Engineering, Hyderabad, India AVSR Chandra Mouli Department of Electronics and Communication Engineering, Vardhaman College Of Engineering, Hyderabad, India Rayala Varshini Department of Electronics and Communication Engineering, Vardhaman College Of Engineering, Hyderabad, India The language of the traveler might not always be known to the tourist guides, or the information available about the place might not be right, and moreover the charges of the guides might be too high. In the end, the travel experience and the place does not satisfy the tourists. In this paper, the development of a portable device is described, so that the tourists can experience a hassle-free tour. The implementation and demonstration of a complete system is discussed, which provides accurate information to the tourists along with visual guidance and assists them during their tour. This system makes use of two concepts, namely RFID technology and context aware information. This system can be used in several different locations like museum, zoo, historic monuments, tourist spots, government offices to provide the user with directions and information relevant to their location. The system can also be used as a monitoring device at research centers and hospitals. 05 30 2020 1774 1777 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2631.059120 https://www.ijrte.org/portfolio-item/A2631059120/ M.phil Research Scholar, Department of Economics, Sikkim University, Sikkim-737102, India. Utpaljit Deori* Dr. Rangalal Mohapatra Assistant Professor, Department of Economics, Sikkim University, Sikkim-737102, India. The present study attempts to measure the factors of rural out-migration and to assess the impact of rural out-migration on agriculture mainly on labour availability, crop yield and farm income on agriculture in origin areas of migration mainly of the Scheduled Tribes (ST) and Non-ST communities in Dibrugarh district, Assam due to the fact that there is continuous decline in agricultural cultivators, increase in the slum population and increase in the unemployment rate. A total of 150 samples were collected from the farm households with migrants for more than one year. The rural out-migration from the study areas were mainly dominated by male and mostly by married male migrants of the age-group of 25-34 years old with a monthly income in the range of ₹ 10,000-15,000 in the destination. The push factors such as unemployment, crop failure, lack of unemployment opportunities and pull factors such as better wage, continuous income etc play an important role in the rural out-migration. However, the ST community opines that soil erosion and poor housing condition is a major factor of rural out-migration as they reside near the river Buridehing and flood damages the houses and erodes the soil of the homeland areas of the houses that are just living beside the river and as result of which their homeland area decreases year after year. The ST people migrate to far off places whereas the Non-ST people migrate within the states of the study area. Remittances and the net sown area are the major factors of the impact on agriculture. The impact of rural out-migration is felt in negatively on the labour supply and positively on increase in the land area, increase in food crop production and vegetable production and increase in the flow of income of the household. The Non-ST community find tea plantation is an additional source of income for sustainable living. Migration can be checked if more focus is given on the creation of small and cottage industries along with the optimum utilization of the agricultural resources. Lastly, area-specific programme should be launched to absorb the local skill and unskilled people. 05 30 2020 1972 1980 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2777.059120 https://www.ijrte.org/portfolio-item/A2777059120/ PG II- year Student, Department of Civil Engineering, PSNA College of Engineering & Technology, Dindigul, India. Geethanjali K* Sivakumar M Professor, Department of Civil Engineering, PSNA College of Engineering & Technology, Dindigul, India. Subburaj V Assistant Professor, Department of Civil Engineering, PSNA College of Engineering & Technology, Dindigul, India. Mahendran S Professor, Department of Civil Engineering, PSNA College of Engineering & Technology, Dindigul, India. This paper aims to develop and evaluate the performance of concrete made with recycled concrete aggregates (RCA) and dune sand (DS) in addition with steel fibers (SF). This work is mainly intended to find the effective ways to reutilize the recycled concrete aggregates as coarse aggregate and due to sand demand dune sand were used as a fine aggregate. Different mechanical and durability properties of recycled concrete aggregates (RCA) and dune sand (DS) concrete mixtures were evaluated. To ensure the properties of cement, fine aggregate, coarse aggregate, recycled concrete aggregate and dune sand preliminary test were determined. Mix design is formulated based on its properties and requirements. Experimentation has been done by using M25 grade concrete. Ordinary Portland cement is used. Fine aggregate and coarse aggregate were partially replaced by recycled concrete aggregates and dune sand at different proportions (25%, 50%, 75%) in addition with 0.25% of steel fibers. Various strengths such as tensile strength, compressive strength, flexure strength and modulus of elasticity are determined. In particular for cube different tests such as non-destructive test (NDT), sorptivity, permeability and acid test has been done. It has been observed that the M2 mix (50% of recycled concrete aggregates and dune sand) has produced better results comparatively. 05 30 2020 2188 2193 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2829.059120 https://www.ijrte.org/portfolio-item/A2829059120/ PG-II year student, Department of Civil Engineering, PSNA College of Engineering and Technology, Dindigul, India. Manju Priyadharshini R* Sivakumar M* Professor, Department of Civil Engineering, PSNA College of Engineering and Technology, Dindigul, India. Mahendran S Professor, Department of Civil Engineering, PSNA College of Engineering and Technology, Dindigul, India. Mohan M* Assistant Professor, Department of Civil Engineering, PSNA College of Engineering and Technology, Dindigul, India. This study investigates about the behaviour of high performance concrete produced with multi component composite cements. Here, the cement is partially replaced with certain mineral admixtures. The mineral admixture used in the study are fly ash, rice husk ash, silica fume and ground granulated blast furnace slag in various percentages up to 50%. The mix proportion for fly ash and rice husk ash are kept constant thought the study as 25% and 7.5% respectively. The Mechanical properties such as (Compressive strength, split tensile strength, flexural strength and modulus of elasticity), Durability tests (Acid test, Sorptivity), permeability test and Non Destructive test are performed on M40 grade concrete cube material property, cylinder and prism. The outcomes were analyzed with the controlled mix. The results shown that the M3 mix ( 50% cement, 25% fly ash, 7.5% RHA,7.5 % silica fume and 10 % GGBS) obtained optimum strength, durability and other properties when analyzed with the other mixes. 05 30 2020 2405 2411 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2830.059120 https://www.ijrte.org/portfolio-item/A2830059120/ Student, Department of Structural Engineering, Integral University, Lucknow, India. Rishabh Srivastava Rajiv Banerjee Associate Professor, Department of Structural Engineering, Integral University, Lucknow, India. The paper elaborates the study of effects of location of shear wall in an irregular shaped building. The main concerned issue is the generation of torsion in a building which is irregular in plan. The paper points out the causes, effects and solution of the torsional forces in an irregular shaped building. The study is done on an ‘L’ shaped building which G+10 storied and is located in Seismic Zone IV exhibiting medium soil conditions and a damping of 5%. The modelling and analysis will be performed by using CSI ETABS ver.16. Dynamic Analysis is conducted in order to study the topic. The paper will finally point out the reasons for choosing a particular test model which exhibits lowest torsion and storey displacement. 05 30 2020 2475 2479 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A2836.059120 https://www.ijrte.org/portfolio-item/A2836059120/