-4d90550d17f4602e08912e4 20220626235948953 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 Faculty of Ocean Engineering Technology & Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia. Nurul Adyani Ghazali* Norhazlina Suhaimi Faculty of Ocean Engineering Technology & Informatics, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia. Ahmad Zia Ul-Saufie Mohamad Japeri Faculty of Computer and Mathematical Science, Universiti Teknologi MARA, 13500, Permatang Pauh, Pulau Pinang, Malaysia. Air pollution has been an ongoing problem in Malaysia. One of the major air quality issue in Malaysia is high concentrations of ozone in urban area. Rapid increase in vehicles number and fossil fuel consumption in Malaysia cause the emission of ozone and their precursors especially nitrogen oxides increasing sharply. This research focus on daytime and nighttime ozone concentration at Kuala Terengganu, Malaysia. The aim of this study is to predict ozone concentration using feed forward back propagation neural network (FFBP-NN) with two hidden layers. Five performance indicators were used to evaluate the models performances which are normalized absolute error (NAE), root mean squared error (RMSE), index of agreement (IA), prediction accuracy (PA) and coefficient of determination (R2). Result show that FFBP-NN with 2 hidden layers model gives good performance for prediction of ozone concentration with high accuracy measures (IA=0.9551, PA=0.8453, R2=0.8402) and small error measures (NAE=0.1642, RMSE=4.4958) for daytime and nighttime (IA=0.9541, PA=0.8429, R2=0.8358, NAE=0.2160, RMSE=3.2485). The result from this study provides a reference for city council to improve the existing guidelines and to plan an effective mitigation measures to monitor the status of air quality towards a sustainable environment. 11 30 2019 9257 9260 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9406.118419 https://www.ijrte.org/portfolio-item/D9406118419/ Ph.D. Research Scholar, Department of Commerce, Delhi School of Economics, University of Delhi(Assistant Professor Vivekananda College University of Delhi Mukesh Kumar Meena* As We Know In The 21st Century All The Organizations Are Facing Competition. The Service Sector Is The Major Contributor Throughout The World Economy. In The Service Sector Employees Play An Important Role. Because Of The Quality Of Service Depends On The Employees Who Are Serving That Service. In That Support Objective Of Our Study Is To Trend In Earnings Of The Organization And Expenditure Incurred On Employees By The Organization. SBI Is The Leading Public Sector Bank, So We Have Collected Data From Annual Reports Of The SBI Bank From The Period Of 2009 To 2019. After Analyzing The Data We Found The Correlation Between Total Income Of SBI And Expenditure Incurred By SBI On Their Employees. On The Basis Of This Study, We Conclude That Employees Play An Important Role In The Organization. And Organizations Are Just Increasing Expenditure On Employees In The Same Trend Of The Organization's Income. The Organization Should Put Employees On The Balance Sheet As Assets. Organizations Are Still Showing Employees As Expenditure. In Coming Future, If The Organization Will Recognize Employees' Contributions That Will Lead To More Satisfaction In The Employees And This Boost In Satisfaction Will Improve The Performance Of Employees Due To That The Overall Performance Of The Organization Will Improve. 11 30 2019 9261 9265 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9407.118419 https://www.ijrte.org/portfolio-item/D9407118419/ Ph.D. Research Scholar, Department of Commerce, Delhi School of Economics, University of Delhi (Assistant Professor Vivekananda College University of Delhi Mukesh Kumar Meena* As we know in the 21st century all the organizations are facing competition. The service sector is the major contributor throughout the world economy. In the service sector employees play an important role. Because of the quality of service depends on the employees who are serving that service. In that support objective of our study is to trend in earnings of the organization and expenditure incurred on employees by the organization. INFOSYS is the leading public sector bank, so we have collected data from annual reports of the INFOSYS bank from the period of 2010 to 2018. After analyzing the data we found the correlation between total income of INFOSYS and expenditure incurred by INFOSYS on their employees. On the basis of this study, we conclude that employees play an important role in the organization. And organizations are just increasing expenditure on employees in the same trend of the organization's income. The organization should put employees on the balance sheet as assets. Organizations are still showing employees as expenditure. In coming future, if the organization will recognize employees' contributions that will lead to more satisfaction in the employees and this boost in satisfaction will improve the performance of employees due to that the overall performance of the organization will improve. 11 30 2019 9911 9914 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9408.118419 https://www.ijrte.org/portfolio-item/D9408118419/ PhD, Department Computer Science & Engineering , Acharya Nagarjuna University, Guntur, Moka Uma Devi* Uppu Ravi Babu Professor in Department of Computer Science and Engineering in reputed Engineering College. Age Classification is used in so many applications like crime detection, face detection and so on. . The age leads to significant variation in human face. The variation depends on many factors like gender, exposure to sunlight, drinking, weight loss or weight gain. In our paper the performance of face aging is established based on v pattern and Inverted v pattern by using the transition count of third order neighborhood. In our proposed method the age of the person is divided into 5 categories 1.Childhood (0-12years) 2.Young Adults (13-25years) 3.Middle Age Adults (26-40years) 4.Senior Adults (40-60years) 5.Senior Citizens (more than 60 years).The quantative evaluation and analysis is performed in our proposed method when compared to other existing methods after applying on 4 different facial image databases. 11 30 2019 8792 8796 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9410.118419 https://www.ijrte.org/portfolio-item/D9410118419/ Department of Economics and Law, Saint-Petersburg University of State Fire Service of Emercom of Russia, Saint Petersburg, Russia. Lyudmila Zubova* Anna Yakovleva Department of Economics and Law, Saint-Petersburg University of State Fire Service of Emercom of Russia, Saint Petersburg, Russia Tamara Stepanova Department of Economics and Law, Saint-Petersburg University of State Fire Service of Emercom of Russia, Saint Petersburg, Russia. Olga Koneva Department of Accounting, Analysis and Audit, Siberian Federal University, Krasnoyarsk, Russia Alana Vanieva Department of Accounting and Taxation, North Ossetian state university after K.L. Khetagurov, Vladikavkaz, Russia. The article proposes a universal technique, which consists in applying an assessment of the level of risk tolerance of the contractor of the State Defense Order, taking into account the stage of the life cycle of rocket and space technology; the relationship between the levels of risk tolerance of the enterprises of the rocket and space industry from the stage of the life cycle of the production process is revealed. Consideration of this pattern will allow to take preventive measures in advance. The result obtained is universal both for management, for marketing, and for the military economy and the economy of business entities as a whole. Specifically, at the stages of development and the birth of the production process, the level of risk is high, and the risk tolerance of the RCT enterprise is low; at the stage of development of production, when tactical and technical requirements (TTT) are achieved, risk tolerance increases; at the maturity stage of the production process, risk tolerance reaches a maximum level. Then, the hypothesis of the study is that when implementing the State Defense Order, it is necessary to introduce a plan for the continuity of control of production processes, where the SWOT analysis and risk tolerance assessment should become tools for monitoring the implementation of R&D, which will act as a tool for assessing guarantees of fulfillment and leveling the risks of not fulfilling R&D. Taking into account the revealed relationship between the levels of risk tolerance of executing enterprises and the stage of the R&D life cycle will make it possible to take preventive measures in advance during the implementation of the State Defense Order. 11 30 2019 7894 7898 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9413.118419 https://www.ijrte.org/portfolio-item/D9413118419/ Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. V Uday Kumar* CMAK Zeelan Basha Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. M Vikas Chandra Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. D Sai Mahesh Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. K. Anish Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. In this we explore the effectiveness of language features to identify Twitter messages ' feelings. We assess the utility of existing lexical tools as well as capturing features of informal and innovative language knowledge used in micro blogging. We take a supervised approach to the problem, but to create training data, we use existing hash tags in the Twitter data. We Using three separate Twitter messaging companies in our experiments. We use the hash tagged data set (HASH) for development and training, which we compile from the Edinburgh Twitter corpus, and the emoticon data set (EMOT) from the I Sieve Corporation (ISIEVE) for evaluation. Twitter contains huge amount of data . This data may be of different types such as structured data or unstructured data. So by using this data and Appling pre processing techniques we can be able to read the comments from the users. And also the comments will be classified into three categories. They are positive negative and also the neutral comments.Today they use the processing of natural language, information, and text interpretation to derive and classify text feeling into pos itive, negative, and neutral categories. We can also examine the utility of language features to identify Twitter mess ages ' feelings. In addition, state-of - the-art approaches take into consideration only the tweet to be classified when classifying the feeling; they ignore its context (i.e. related tweets).Since tweets are usually short and more ambiguous, however, it is sometimes not enough to consider only the current tweet for classification of sentiments.Informal and innovative microblogging language. We take a sup ervised approach to the problem, but to create training data, we use existing hashtags in the Twitter data.This paper also contrasts sentiment analysis approaches in evaluating political views using Naïve Bayes supervised machine learning algorithm which performs in better analysis compared to other techniques Paper 11 30 2019 8797 8801 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9414.118419 https://www.ijrte.org/portfolio-item/D9414118419/ Computer Application, Dr. APJ Abdul Kalam University, Indore, India Sandeep Singh Rajpoot* Dr. Dhanraj Verma Computer Application, Dr. APJ Abdul Kalam University, Indore, India, Internet of things (IoT) is a quick-moving gathering of web associated sensors implanted in a wide-extending assortment of physical articles. While things can be any physical item (energize or lifeless) on the planet, to which you could associate or implant a sensor. Sensors can take countless potential estimations. Sensors produce gigantic measures of new, organized, unstructured, ongoing information, and structures enormous information. IoT information is exceptionally huge and confused, which can give genuine-time setting and supposition data about genuine articles or nature. Among the different challenges that the present IoT is facing, the three prime areas of concern are, need of efficient framework to receive IoT data, a need of a new scalable parallel indexing technique for efficiently storing IoT data and securing IoT generated data at all the stages i.e. from the edge devices to the cloud. A new efficient framework is introduced, which can retrieve meaningful information from these IoT devices and efficiently index it. For processing such enormous real time data generated from IoT devices, new techniques are introducing which are scalable and secure. The research proposes a general IoT network architecture. It describes the interconnectivity among the different things such as sensors, receivers and cloud. The proposed architecture efficiently receives real time data from all the sensors. The prime focus is on the elimination of the existing issues in IoT. Along with this, the provision has to make for standard future proofing against these new proposed schemes. 11 30 2019 9266 9270 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9417.118419 https://www.ijrte.org/portfolio-item/D9417118419/ Department of Information Technology, Kyiv National University of Construction and Architecture, Kyiv, Ukraine. Tetyana Honcharenko Yurii Andrashko Department of system analysis and optimization theory, State University «Uzhhorod National University», Uzhhorod, Ukraine. Olena Fedusenko Department of Intelligent Technologies, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine. Iryna Domanetska Department of Intelligent Technologies, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine. Nataliia Olkhova Department of Theory and Teaching Methodology of Primary Education, Lesya Ukrainka Eastern European National University, Lutsk, Ukraine. The study presents innovative method of generalizing spatial information into a single multidimensional data model technology based on multidimensional information objects (MIO). This advanced method is intended to describe various types of spatial information of general planning objects at a construction site and their generalization into a single multidimensional model of general plan data. The method was further developed on the basis of newly introduced operations on multidimensional information objects. The operations of simple and generalized change and spatial generalization make it possible to integrate heterogeneous spatial information into single information space at all organizational levels of management while maintaining its integrity. The paper considers mathematical descriptions and graphic representations of information models of various types of spatial objects of general planning based on multidimensional information objects 11 30 2019 8426 8432 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9419.118419 https://www.ijrte.org/portfolio-item/D9419118419/ Assistant Professor in the Department of Accountancy, Gauhati Commerce College. Alimpiya Bordoloi* Multi level marketing (MLM) is a new concept though it is deep rooted in the age old civilization. In India it is still in nascent stage, however has become popular among the masses. Since its entry in India in the mid 90s, it has attracted more than 5 million people. Through this study, the researcher tries to highlight the factors which persuade a person to join MLM business. With the growing trend of unemployment and lack of job avenues, the paper also focuses on the effect of MLM business on employment generation. 11 30 2019 8802 8805 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9423.118419 https://www.ijrte.org/portfolio-item/D9423118419/ Assistant Professor with the Information Technology Department, Faculty of Science and Technology, Suan Sunandha Rajabhat University, Thailand Sumitra Nuanmeesriis* Alumni are one of the most significant assets for the success of universities. After graduation, they enter a new society, have work and family responsibilities which change over time according to their age and economic status. It becomes more difficult to communicate between friends and university. This situation is challenging to collect up-to-date information about alumni from a university database as well as sharing it with all alumni. This article demonstrates the alumni relationship management (ARM) using speech recognition for the mobile application on smartphones. It has been designed and developed for Thai speech recognition to facilitate alumni especially the elderly who may have vision problems or typing by applied the ionic framework to support both iOS and Android. The contents were evaluated by five experts to identify each feature of the developed mobile application. Afterward, the application was evaluated by one hundred twenty alumni. The learning post-test results scored higher than the pre-test results. The effectiveness evaluation results in terms of the accessibility barriers at the high-level while being used has high consensus. 11 30 2019 9915 9923 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9424.118419 https://www.ijrte.org/portfolio-item/D9424118419/ Faculty of Accountancy, Universiti Teknologi MARA Cawangan Terengganu, 23000 Dungun, Terengganu, Malaysia. Noor Liza Adnan* Rokiah Muda Faculty of Accountancy, Universiti Teknologi MARA Cawangan Terengganu, 23000 Dungun, Terengganu, Malaysia. Wan Karomiah Wan Abdullah Faculty of Computer Science and Mathematics, Universiti Teknologi MARA Cawangan Terengganu, 23000 Dungun, Terengganu, Malaysia. Nur Raihana Mohd Sallem Faculty of Accountancy, Universiti Teknologi MARA Cawangan Terengganu, 23000 Dungun, Terengganu, Malaysia. This paper aims to understand the assessment preference of Gen Z, a student cohort currently being served in higher learning institutions. It tends to investigate the formative assessment activities preferred by Gen Z, followed by the range of marks for each activity. It also tries to discover their preference for the proportion of mark for formative assessment as compared to final examination. Data was collected from 420 diploma students and 22 lecturers taking (and teaching) management accounting subject in a public university in Malaysia. The values of mode and the frequency were used to achieve the above objectives. In addition, the interview session with students and lecturers was also conducted to gather additional related information. The results revealed that both students and lecturers favor traditional assessment over alternative assessment. In terms of alternative assessments, unlike lecturers, students ranked activities that require higher order thinking last. Both students and lecturers also allocate the highest marks to test and quiz, while other activities are only allocated with the lower range of marks. Majority agreed with the 40:60 ratio with the higher weightage goes to the final examination. This finding somehow contradicts previous finding which suggest that Gen Z prefer coursework rather than examination. The findings of the study might help academicians in designing appropriate assessment activities in order to maximize students learning especially in the field of management accounting. However, this study was conducted on the diploma students who might have different view and perception regarding assessment as compared to bachelor’s degree students. 11 30 2019 8806 8816 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D9427.118419 https://www.ijrte.org/portfolio-item/D9427118419/