-74813b3e17f460286df-5f40 20220330081536903 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/ 03 30 2020 8 6 Assistant Professor, Department of civil engineering, SRM IST, Chennai-603203, Tamilnadu, India. S. Prakash Chandar* A.Ramnath Reddy PG Student, Department of Civil Engineering, SRM IST, Chennai 603203, Tamilnadu, India. R. Ramasubramani Assistant Professor, Department of civil Engineering, SRM IST, Chennai-603203, Tamilnadu, India. In the present generation the construction activity is rapidly increasing as a result the usage of cement is growing more and leads to environmental hazards. This study deals with the mechanical properties of partial replacement of cement by GGBS and Fly-Ash in M40 grade concrete. Cement were replaced as partially in the form of 5%,10%,15% and 20%. As per IS 456:2000 [1] the tests were conducted on 3,7 and 28th days after curing condition. This study proves that the possible replacement to cement by GGBS is 10% and fly ash 15% used in the concrete, which helps in minimizing the consumption of cement and environmental problems also. 03 30 2020 1385 1388 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7743.038620 https://www.ijrte.org/portfolio-item/F7743038620/ Department of Electrical Engineering, Sangam University, India. Kapil Parkh* Dr. Vinesh Agarwal Department of Electrical Engineering, Sangam University, India. In this paper investigation of the application of teaching learning based optimization (TLBO) technique for the design of a modified Phillips haffron model of SMIB installed with SSSC based controller is made. The design objectives are to reduce low frequency oscillation and improve power system stability. Simulation result are demonstrated with Eigen value analysis, where various types of disturbance is applied as mechanical torque input and reference voltage settling, variation in parameter & various loading condition. The results obtained are compared with some well-known optimization techniques, such as the genetic algorithm (GA), particle swarm optimization (PSO) and the gravitational search algorithm (GSA). A comparative study of results demonstrates that the results of the proposed controller were more precise and robust 03 30 2020 1389 1399 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7744.038620 https://www.ijrte.org/portfolio-item/F7744038620/ Master of Computer Science, Postgraduate Programs STMIK Nusa Mandiri, Jakarta, Indonesia. Amsal Pardamean* Dewy Yuliana Informatics Engineering Department, Faculty of Computer ScienceUniversitasSriwijaya, Palembang, Indonesia Sri Watmah Master of Computer Science, Postgraduate Programs STMIK Nusa Mandiri, Jakarta, Indonesia. Sisferi Hikmawan Master of Computer Science, Postgraduate Programs STMIK Nusa Mandiri, Jakarta, Indonesia. Sfenrianto Information Systems Management Department, BINUS GraduateProgram – Master of Information Systems Management,Bina Nusantara University, Jakarta, Indonesia Arabic is the most widely used language in the world, especially the Arab League Country. Of course, in those countries often use Arabic numeral in banks and business applications, postal zip code and data entry application. This research has focused on handwriting recognition of Arabic numeral that has unlimited variation in human handwriting such as style and shape. The proposed method on the deep learning technique is Convolutional Neural Network. LeNet-5 architect also used in training and recognizing the handwritten image of Arabic numeral as much as 70000 images derived from MADbase dataset. The experimental result on 10000 images of database used is by comparing the number of epoch in training process yields, and the average accuracy is 97.67%. 03 30 2020 1187 1190 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7745.038620 https://www.ijrte.org/portfolio-item/F7745038620/ Research Scholar, SCSIT DAVV, Indore, MP, India. Pradeep Rusiya* Dr. N. S. Chaudhari Professor, IIT, Indore, India. The advancement of computer technology facilitates in the field of medical science for the analysis of complex Diseases related to the neurology. These technologies named as BCI (brain computer interface). The BCI is open area of research for physically challenge people such as paralyzed and amputees. The current technology of computer interface interest in EEG (electroencephalographic) for the analysis of signals for the predication of nervous system. The current trends of brain computer interface focus on process signal of EEG for the sense of human body behaviors and movement of nervous system, motor imagery and various senses. The gathered signal by the EEG is very noisy and predication and recognition of the motor imagery is typical. The minimization of noise upgrades the predication procedure and examination of signal behaviors. For the analysis of behaviors system utilized soft computing processing approach, for example, neural system, optimization techniques. The component extraction and feature selection are also major issue in motor imagery analysis for critical and complex disorder of human brain system. 03 30 2020 5235 5246 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7754.038620 https://www.ijrte.org/portfolio-item/F7754038620/ Senior lecturer, Subdepartment of Architectural Environment Design, Cherepovets State University (Cherepovets, Russian Federation). Dmitry Mikhailovich Astanin* A historical analysis of the formation of environmental trends in science, literature and philosophies is carried out in the context of the theory of multilevel development of environmental protection systems (religion, state, science, society, international law). Eastern scientific and philosophical thought of the Middle Ages and the ancient world had an advantage over the western part of the humanization of the natural component. The formation of the term "ecology" refers to the middle of the 19th century. It was connected with the end of the era of great geographical discoveries. However, ecology in the 19th century was purely practical in nature, aimed at preserving nature in order to classify reserves for future consumption. Humanitarian-philosophical understanding of the problems of ecology and aggressive-consumer society should be placed on Russian and Indian cultures in the person of L. N. Tolstoy and M. Gandhi, who suggested the synthesis of Russian, Western and Eastern thought as a means of preventing environmental disasters. The approbation problem of developing a universal international methodological apparatus is the disunity of scientific and philosophical thought: the history of mankind develops according to a cyclical model - the medieval west was not familiar with Arabic science, and today the west is also not familiar with the theory of the noosphere, which is currently not completed. 03 30 2020 2399 2402 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7756.038620 https://www.ijrte.org/portfolio-item/F7756038620/ Mcom Finance And System Amrita School Of Arts And Sciences, Kochi. Devi R* Diana Jolly Jose Mcom Finance And System Amrita Scjhool Of Arts And Sciences, Kochi. Preetha R Assistant Professor Amrita Scjhool Of Arts And Sciences, Kochi. In this era of glamour and style women adopt the new trends and brands by making film stars as their role models. They think that the only way to achieve that beauty is by applying the cosmetics being endorsed by celebrities. Nowadays media has created an impression that if a woman becomes fair it can pave way to acquire her dreams. Women tend to use the same brand even after the arrival of new products. The taste and preference for their brand does not make any change as they know that the brand assure them the same comfort and satisfaction. It is the marketing strategies used by companies that makes a brand unique and frontrunner even when there is a vast range of product available in the market .This study is being conducted to understand the most preferred brand among women’s in Ernakulam District and the companies marketing strategies that creates brand loyalty among them. 03 30 2020 1477 1480 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7758.038620 https://www.ijrte.org/portfolio-item/F7758038620/ Dept. of Computer Science and Engineering, Dr APJ Abdul Kalam Technical University, Lucknow, India. Suvarna Vashistha* R K Sharma Dept. Computer Science and Engineering, Dr APJ Abdul Kalam Technical University, Lucknow, India. Harmful gases leaking from the equipment that are installed in the industries cause huge loss of lives of the workers as well as people living nearby the industries. The main causes for the gas leakage are poorly maintained machines, leaky storage tanks. So, focusing on the concentration of harmful toxic gases, a virtual analysis has done using QualNet 6.1. Different numbers of nodes have dropped randomly in different terrain areas. Three protocols LRWPAN, LRWPAND, LRWPANDMC have been used to virtually analyze the gas leakage scenario. These sensors detect the gases when the leakage is near about or more than the limit. At each time some nodes will be in sleep mode and others will be in active mode, this mechanism will increase the lifetime of the battery, as changing battery frequently will not be possible especially in remote areas. The crucial profit of this paper is to show the network performance which is simulated with a sink node receiving packets for different time duration and at different frequencies. The idea is to find out the optimal and efficient network for fast information flow with 50, 100, 300 nodes. The terrain area of the network is 100×50 m2, 100×100 m2, 500×500 m2 with the communication range of 10 m. The routing protocols implemented are Low-Rate Personal Area Network (LRPAN), Low-Rate Personal Area Network with Drift (LRPAND) and Low-Rate Personal Area Network with Drift and Multi-Channel. This paper has evaluated and analyzed the influence of packet flow at the different frequencies of 2.425, 2.450, 2.475 and 2.480 GHz. It is analyzed that performance of each protocol has varied significantly for different number of nodes. The performance of the network is improved by the different frequencies instead of 2.4 GHZ frequency. The parameters average end to end delay (seconds), jitter (seconds), throughput (bits per second) and network lifetime (hours) for different protocols such as LRPAN, LRPAND and LRPANDMC for different numbers of nodes 50, 100 and 300 are evaluated and compared. The optimum results are obtained by the LRPANDMC in the simulation process. Evaluation and analysis of the influence of different protocols on different number of nodes for different parameters has been done to determine most effective protocol. This type of network can be used in oil and gas industries, petroleum industries at remote areas where there are high chances of gas leakage incidents. The aim is to provide information in real-time scenario virtually. 03 30 2020 2441 2445 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7767.038620 https://www.ijrte.org/portfolio-item/F7767038620/ Faculty of Computing and Information Technology, Computer Science Department, King Abdulaziz University, Jeddah, Saudi Arabia Samah Alajmani* Prof. Kamal Jambi Professor, Faculty of Computing and Information Technology, Computer Science Department, King Abdulaziz University, Jeddah, Saudi Arabia. Predicting the probability of hospital readmission is one of the most vital issues and is considered to be an important research area in the healthcare sector. For curing any of the diseases that might arise, there shall be some essential resources such as medical staff, expertise, beds and rooms. This secures getting excellent medical service. For example, heart failure (HF) or diabetes is a syndrome that could reduce the living quality of patients and has a serious influence on systems of healthcare. The previously mentioned diseases can result in high rate of readmission and hence high rate of costs as well. In this case, algorithms of machine learning are utilized to curb readmissions levels and improve the life quality of patients. Unluckily, a comparatively few numbers of researches in the literature endeavored to address this issue while a large proportion of researches were interested in predicting the probability of detecting diseases. Despite there is a plainly visible shortage on this topic, this paper seeks to spot most of the studies related to predict the probability of hospital readmission by the usage of machine learning techniques such as such as Logistic Regression (LR), Support Vector Machine (SVM), Artificial Neural Networks (ANNs), Linear Discriminant Analysis (LDA), Bayes algorithm, Random Forest (RF), Decision Trees (DTs), AdaBoost and Gradient Boosting (GB). Specifically, we explore the different techniques used in a medical area under the machine learning research field. In addition, we define four features that are used as criteria for an effective comparison among the employed techniques. These features include goal, data size, method, and performance. Furthermore, some recommendations are drawn from the comparison which is related to the selection of the best techniques in the medical field. Based on the outcomes of this research, it was found out that (bagging and DT) is the best technique to predict diabetes, whereas SVM is the best technique when it comes to prediction the breast cancer, and hospital readmission. 03 30 2020 3226 3232 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7770.038620 https://www.ijrte.org/portfolio-item/F7770038620/ PhD in Economics, Associate Professor, Head of Institute №5 “Engineering Economics and Humanities”, Moscow Aviation Institute (National Research University), Moscow, Russia. Sergey V. Novikov* Andrey A. Sazonov PhD in Economics, Associate Professor, Moscow Aviation Institute (National Research University), Moscow, Russia. The article is dedicated to the analysis of the digital transformation processes of the procedure of making aviation technics based on the usage of high technological platform MindSphere. The architecture and tools of the Siemens IIoT MindSphere open cloud operating system are reviewed. There are the capabilities of the MindSphere platform for the digital transformation of industrial enterprises. In theoretical part of this article, the authors consider perspective technologies of digitalization at domestic aviation enterprises, where the main factors are work in the sphere of introducing artificial intelligence and creating unique digital twins of aircrafts. The research is based on the comprehensive analysis and synthesis with the following forming of the final grade of the main results of realization of technological domestic enterprises’ transformation. In the course of the study, the task is to identify key areas and areas of technological transformation and the possibility of using promising information technologies (IT) systems. The article’s authors point out that for solution of tasks of predictive analytics, multivariate analysis, trend prediction, and pattern analysis based on artificial intelligence / machine learning methods aviation enterprises have to use technological abilities of the platform MindSphere. It is defined that the development a full-fledged virtual object model based on technologies included in the platform Mindsphere will allow solving a lot of problems during its development and also there comes up an opportunity to qualitatively analyze the various options for the developed product and optimize the time / expenses connected to its last development. During the conducted analysis, it was found out that technologies Siemens PLM (Product lifecycle) Software on the platform MindSphere allow making verified models aircraft, their units, components and systems, as well as conduct their virtual tests. For typical aviation systems and components of the solution suggest available libraries of customized models, due to which reliable calculations and rejection of part of field tests are possible. In the result of the conducted research authors come to the conclusion that with the help of the platform MindSphere enterprises, holdings, and even whole industries it will be able to close digital chains between the design, manufacture, and product operation. 03 30 2020 1433 1437 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7772.038620 https://www.ijrte.org/portfolio-item/F7772038620/ Research Scholar, Bhagwant University, Ajmer, Rajasthan Ashutosh Dixit Nidhi Tyagi Professor, MIET, Meerut Computerized Data from various sources, such as remote sensors, cutting-edge sequencing of bioinformatics and high-performance instruments, are increasing at extremely high speeds. To keep analyzing through results for programming, facilities and measurements, The Researches have to use new procedures and techniques. Google's team started MapReduce programming system which aims to manipulate huge data sets in disseminated frameworks; this design lets software engineers create applications that are extremely valuable to large data processing. The motive of this paper is to explore MapReduce research techniques and to increase current research efforts to improve the execution of MapReduce and its capabilities. 03 30 2020 3233 3239 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7773.038620 https://www.ijrte.org/portfolio-item/F7773038620/ Research Scholar, KIIT School of Humanities, KIIT University, Bhubaneswar, Odisha, India. Mrs. Ronismita Mishra* Dr.Swapnamoyee Palit Assistant Professor of Economics, KIIT School of Humanities, KIIT University, Bhubaneswar, Odisha, India Employment generation is treated as an important stimulus for enhancing growth in the developing countries. It is quite easy to believe that FDI inflows can provide the solution for many economic issues in the economy, but in case of employment creation this effect is quite convoluted in India. The central objective of this paper is to find out the relationship between FDI inflows and employment generation in India during the period 1991 to 2018. This research paper uses secondary data from different published sources to analyse the influence of FDI on employment generation in India using the relevant descriptive analysis.FDI has both backward and forward linkages in employment creation in India. FDI shows a three times increase in growth rate in the second decade than in the first decade, i.e., during 2002 to 2012 in the service sector in India. Banking and insurance sector is the first in attracting major FDI proposals followed by the telecommunication sector, which is in second position in attracting FDI in India. In the service sector FDI generates highest job opportunities than any other sector in India. The result of this study shows that employment generation in India during the last two decades is quite detectable, but FDI inflows may not be regarded as a major factor for this growth rate. Thus the government of India should take some policy measures to captivate employment generation in India basically in organised sector. 03 30 2020 1481 1489 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7777.038620 https://www.ijrte.org/portfolio-item/F7777038620/ MIS , University of Buraimi, Al buraimi, 968, Sultanate of Oman, Boumedyen Shannaq* Richmond Adebiaye Dept. of Informatics & Engineering Systems, University of South Carolina Upstate, Spartanburg, USA. The research paper developed a new software metric methodology for evaluating the analyzability indicator for software products. The proposed research methodology provided an objective and quantitative assessment in accordance with the requirements, limitations, purpose and specific features of software products. Forty-one (41) java programs were analyzed to extract and evaluate the software metrics described in ‘Halstead metrics. The mathematical classification model was developed to replace the expert output in the evaluating process as related to the software metric indicators. The output of the algorithm was applied to identify the metrics with the greatest analyzability influence. The result indicated that 13 measured metrics with 98% of “analyzability” are relevant to seven (7) software code metrics with the remaining six (6) metrics making up only ~ 5% of “analyzability”. The analyzed ROC-curves were similarly computed to test the performance of the proposed methodology compared to the expert’s metric evaluation. The ROC-curves indicator for the proposed methodology showed resultant scores of ROC = 7.4 as compared to 7.3 from the experts’ evaluation. However, both methods were correlated effectively after analytical computations with a resultant performance which showed that the proposed method outperforms the expert’s evaluation. 03 30 2020 2403 2408 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7780.038620 https://www.ijrte.org/portfolio-item/F7780038620/ Institute of Economics and Business, Ulyanovsk State University, Ulyanovsk, Russia. I. S. Pinkovetskaia* I. N. Nikitina Institute of Management, Samara State University of Economics, Samara, Russia T. V. Gromova Institute of Management, Samara State University of Economics, Samara, Russia One of the directions of the Strategy for the Development of the Information Society in the Russian Federation for 2017-2030 is elaboration of technology for processing data on the activities of economic entities, as a tool for analyzing economic activity and making decisions based on the most complete amounts of information. The number of small and medium enterprises in certain industries and regions of Russia amounts to tens and hundreds of thousands. The assessment of their performance indicators requires improving methods for the formation and analysis of relevant databases, as well as the development of computer economic and mathematical models. Taking into account the large number of enterprises included in the relevant aggregates, the authors propose a new original approach to the description of their performance indicators. The study aims to develop a methodology for a system analysis of performance indicators of small and medium enterprises using set theory. These indicators are formed on the basis of a combination of different variants of their sets. The authors also consider the interrelations between the indicators characterizing the sets of small and medium enterprises belonging to different size categories, industries and territories. The results of the study can be used to develop technology for processing data on the activities of business entities, as a tool for analyzing economic activity and making decisions. They make it possible to establish patterns and trends in the development of various aggregates of SMEs, substantiate proposals and recommendations for improving their functioning on the basis of the characteristics specific to particular aggregates, and provide a differentiated approach to solving problems of state regulation of entrepreneurship. 03 30 2020 1400 1405 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7781.038620 https://www.ijrte.org/portfolio-item/F7781038620/ School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India. Siddharth Swarup Rautaray* Manjusha Pandey School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India. Mahendra Kumar Gourisaria School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India. Ritesh Sharma School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India. Sujay Das School of Electronics Engineering, KIIT Deemed to be University, Bhubaneswar, India. Agriculture is the spinal cord of the human society because it is an essential need of every organism that exists in this planet. Paddy cultivation is very significant so far as humans are concerned, especially in the Asian subcontinent. Since human beings are considered as one of the most intelligent species, it is necessary for us to protect the importance and productivity of agriculture. Since the entry of the IT industry, there has been some improvement in the productivity in the agriculture. It has done a lot of work in the healthcare of the agriculture. Deep learning is a buzzword in the IT sector. This buzzword has helped a lot to improve the productivity of in the agriculture field. In the recent past, due to excessive use of human made chemicals and pesticides, the diseases in plants have increased in a higher rate. These diseases in agricultural plants cannot be ignored as it can be dangerous in later stages. Also due to lack of technical knowledge, sometimes it becomes difficult to detect these diseases. So, this paper presents a model for detecting the disease present in the paddy plant. The model uses transfer learning approach which is a paradigm of solving deep learning problems in an efficient manner. This model also finds the probability of the occurrence of disease which can be helpful to take some vital decisions related to plant’s health. 03 30 2020 1490 1495 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7782.038620 https://www.ijrte.org/portfolio-item/F7782038620/ Student, Department of Mathematics, Amrita School of Arts and Science, Amrita Viswa Vidyapeetham, Amritapuri, Kollam, India Lakshmi G Jyothi Manoj Associate Professor, Department of Statistics, Kristu Jayanti College (Autonomus), Bengaluru, India Prediction of stock market performance is a challenging problem. There are numerous methods which are tried by various researchers in this regard. The memoryless property of Markov process seems to be more relevant when stock market prices are analysed for futuristic prediction. It is a stochastic process where the future probabilities are determined by the immediate present and not past values. This is suitable for the random nature of stock market fluctuations. The present study adopts this property to compare the performance of five prominent stocks in Oil and Gas Sector in India. The analysis is carried out based on past three years data of 5 prominent stocks in Oil and gas sector. The findings suggest that Bharat Petroleum,Reliance and Hindustan Petroleum are having high probability of increase in its value while Indian Oil corporation (IOC) and Oil India exhibits a higher chance of being stable with no significant increase or decrease. 03 30 2020 1516 1519 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7784.038620 https://www.ijrte.org/portfolio-item/F7784038620/ School of Applied Sciences, Centurion University of Technology and Mangement, Odisha, India. Pradip Kumar Prusty* Yashaswi Nayak School of Applied Sciences, Centurion University of Technology and Mangement, Odisha, India. Annapurna Sahoo Institute of Life Sciences, Odisha, India. Gagan Kumar Panigrahi* School of Applied Sciences, Centurion University of Technology and Mangement, Odisha, India. Sustainable development in agriculture is the need of the hour. Extensive use of agrochemicals in the agricultural sector for practices like weed control, pest control, enhancing soil fertility, etc. results in a broad range of uninvited effects not only to the agricultural ecosystem but also to the human health owing to the nondegradable nature of these chemicals. This situation is alarming and of serious concern. It’s high time to curb our dependency on agrochemicals and instead search for other alternatives, most importantly keeping an eye on their environmental impact. In this prospect, eco-friendly strategies should be adopted to ensure safe and healthy agricultural products for the society. Aquaculture being one of the fastest growing food fabrication sectors, thus we majorly focused on community-based aquaculture on the regions of eastern belt of India. The present study is a diagnostic approach that demonstrates how sustainability challenges can be overcome by utilization of local resources. 03 30 2020 1892 1895 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.F7790.038620 https://www.ijrte.org/portfolio-item/F7790038620/