SMART MOVES JOURNAL IJOSCIENCE <h2 data-fontsize="18" data-lineheight="27"><strong>SMART MOVES JOURNAL IJOSCIENCE</strong></h2> <p><strong>IJOSCIENCE (International Journal Online of Science<em>)</em> is a peer-reviewed journal that publishes monthly. IJOSCIENCE has been granted ISSN No 2455-0108 in the year 2015.</strong></p> <h3 class="fusion-page-title-bar fusion-page-title-bar-none fusion-page-title-bar-left">Publication Model</h3> <p> </p> <h4><strong>IJOSCIECE is an Open Access journal and we don’t receive any grant by any organization, hence we ask our authors to pay Article Processing Charge (APC). APC covers the expense of the administrative cost, the peer review process, publication processes, online publication, hosting the website, online security (virus attack), etc. An author will be asked to pay the publication fee along with the acceptance letter.</strong></h4> <p>Authors paying fees do not mean that the process would be curtailed short or they can get their publication fast. IJOSCIENCE does not compromise with its quality standards. We do not accept any fee unless a manuscript meets its set benchmarks or standards. This fee is only charged to meet the publication expense requirements. </p> <p>See the <a href="">Call for Paper</a> webpage for the Article Processing Fee information.</p> <p><strong>Ownership Statement</strong></p> <p>SMART MOVES JOURNAL IJOSCIENCE iis published by <a href="">SMART MOVES</a> publications, Bhopal, M.P., India. <strong>SMART MOVES</strong> (organisation name) is a registered organisation in the state of Madhya Pradesh, India. Smart Moves is a publishing house that was established in the year 2012. Mr Rajeev Tiwari (name of a person) is the proprietor/owner of Smart Moves. SMART MOVES is a for-profit publishing organisation.</p> <p><strong>About SMART MOVES</strong></p> <p>Please find the link to our publisher website <a href="">SMART MOVES</a></p> <p>Smart Moves is publishing research papers in order to enable online platforms to reach the international research fraternity. Smart Moves also publishes books in both formats, ebooks and print mode.</p> <p>We are publishing four open-access online journals Please find details below- </p> <p> 1-<a href=""></a></p> <p>2-<a href=""></a></p> <p>3-<a href=""></a></p> <p>4-<a href=""></a></p> SMART MOVES en-US SMART MOVES JOURNAL IJOSCIENCE 2582-4600 <p align="justify">IJOSCIENCE follows an Open Journal Access policy. Authors retain the copyright of the original work and grant the rights of publication to the publisher with the work simultaneously licensed under a <a href="">Creative Commons CC BY License </a>that allows others to distribute, remix, adapt, and build upon your work, even commercially, as long as they credit you for the original creation. Authors are permitted to post their work in institutional repositories, social media or other platforms. </p> <div id="deed-conditions" class="row"> <div id="deed-conditions" class="row"> <h3>Under the following terms:</h3> <ul class="license-properties col-md-offset-2 col-md-8" dir="ltr"> <li class="license by"> <p><strong>Attribution</strong> — You must give <a id="appropriate_credit_popup" class="helpLink" tabindex="0" title="" href="" data-original-title="">appropriate credit</a>, provide a link to the license, and <a id="indicate_changes_popup" class="helpLink" tabindex="0" title="" href="" data-original-title="">indicate if changes were made</a>. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.<span id="by-more-container"></span></p> </li> </ul> </div> <div class="row"> <ul id="deed-conditions-no-icons" class="col-md-offset-2 col-md-8"> <li class="license"><strong>No additional restrictions</strong> — You may not apply legal terms or <a id="technological_measures_popup" class="helpLink" tabindex="0" title="" href="" data-original-title="">technological measures</a> that legally restrict others from doing anything the license permits.</li> </ul> </div> </div> Thermal Analysis of IC Engine <p><strong>Calculating the heat transfer rate of the engine is very difficult due to the complex geometry design of the engine and the periodic flow of air and fuel during engine operation for full cycles. Various theories hypothesize that about 25% of the energy contained in the fuel is converted into useful work and the remaining 75% is released into the environment by the engine. The main objective of the present work is to improve the heat transfer rate of existing constructions of the engine cylinder block by modifying its construction and also with new materials. To this end, two CAD models were created using CATIA software, then a transient thermal analysis with ANSYS at ambient temperature for the summer season of 45<sup>o</sup>C for the real one and the proposed internal combustion engine design was performed one after the other. Other to optimize the geometric parameters and improve the heat transfer rate. From the results of the transient thermal analysis, it was found that the proposed engine cylinder block design has better performance and heat transfer rates than the actual engine cylinder block design.</strong></p> Sourabh Kumar Mr. Rajesh Soni Copyright (c) 2021 Sourabh Kumar, Mr. Rajesh Soni 2021-07-16 2021-07-16 7 7 9 16 10.24113/ijoscience.v7i7.396 A Novel and Efficient INC Based MPPT for PV System <p><strong>This paper discuss the Incremental Conduction based MPPT for tracking the solar power. Due to increment of power demand here to find the new type of generation system. The concept of Renewable Energy Source (RES) is now become a most popular for generation of power. There are basically three types of RES is used for generation process, Wind, PV, fuel cell. Solar system is one of the best RES technique for generation of electrical power but it have some drawback. It is only used in the daytime and has low efficiency. For improving the efficiency of the system here maximum power tracking is needed. Here Incremental Conduction based MPPT for tracking the solar power is used. The whole model is simulated in MATLAB /SIMULINK for checking the performance of the system and is applicable to different type of domestic loads. The THD of the system is calculated. </strong></p> Santosh Kumar A. K. Wadhwani Bharat Mishra Copyright (c) 2021 Santosh Kumar, A. K. Wadhwani, Bharat Mishra 2021-06-28 2021-06-28 7 7 34 42 10.24113/ijoscience.v7i6.395 Study on Multi-Objective Bio-Inspired Algorithms for Feature Selection <p><strong>With the era of big data, the problems of data size and data optimization have become more diversified and complicated, thus the optimization method has become the focus of people's attention. Algorithm is used to solve practical problems in various fields. In this paper, we studied different techniques of feature selection for big data using optimization algorithm.</strong></p> Rachna Kulhare Dr. S. Veenadhari Neha Sharma Copyright (c) 2021 Rachna Kulhare Dr. S. Veenadhari , Neha Sharma 2021-07-01 2021-07-01 7 7 5 8 10.24113/ijoscience.v7i7.394 Analytical Study of Task Offloading Techniques using Deep Learning <p>The Internet of Things (IoT) systems create a large amount of sensing information. The consistency of this information is an essential problem for ensuring the quality of IoT services. The IoT data, however, generally suffers due to a variety of factors such as collisions, unstable network communication, noise, manual system closure, incomplete values and equipment failure. Due to excessive latency, bandwidth limitations, and high communication costs, transferring all IoT data to the cloud to solve the missing data problem may have a detrimental impact on network performance and service quality. As a result, the issue of missing information should be addressed as soon as feasible by offloading duties like data prediction or estimations closer to the source. As a result, the issue of incomplete information must be addressed as soon as feasible by offloading duties such as predictions or assessment to the network’s edge devices. In this work, we show how deep learning may be used to offload tasks in IoT applications.</p> Mr Almelu Dr. S. Veenadhari Kamini Maheshwar Copyright (c) 2021 Almelu, Dr. S. Veenadhari, Kamini Maheshwar 2021-07-01 2021-07-01 7 7 1 4 10.24113/ijoscience.v7i7.393 Application of Deep Learning For Sentiment Analysis <p>Deep learning is a type of artificial intelligence that employs neural networks, a multi-layered structure of algorithms. Deep learning is an accumulation of artificial intelligence statistics based on artificial neural networks for the teaching of functional hierarchies. In sentiment analysis, deep learning is also applied. This paper begins with an overview of deep learning before moving on to a detailed examination of its present uses in sentiment analysis.</p> Neha Sharma Dr. S Veenadhari Rachna Kulhare Copyright (c) 2021 Neha Sharma, Dr. S Veenadhari, Rachna Kulhare 2021-06-28 2021-06-28 7 7 30 33 10.24113/ijoscience.v7i6.392 Energy Efficient Heterogeneous WNS Clustering Using Machine Learning <p>Heterogeneous wireless sensor network (HWSN) fulfills the requirements of researchers in the design of real-life application to resolve the issues of unattended problem. Wireless sensor networks are used in diverse areas such as battlefields, security, hospitals, universities, etc. It has been used in our everyday lives. Its development is rising day by day. Wireless sensor network includes hundreds to thousands of sensor nodes which aid in gathering various information like temperature, sound, location, etc. Recharging or modifying sensor nodes which might have limited battery power is usually difficult. Therefore, energy conservation is a crucial concern in sustaining the network. Clustering the networks is definitely one of the most common solutions for rendering WSNs energy. In this paper, &nbsp; review and compare different energy-efficient clustering protocols for WSNs</p> Kamini Maheshwar Dr. S. Veenadhari Mr Almelu Copyright (c) 2021 Kamini Maheshwar, Dr. S. Veenadhari , Almelu 2021-06-24 2021-06-24 7 7 24 29 10.24113/ijoscience.v7i6.391 Load Switching Analysis using Converter with Optimization Algorithm in Hybrid Renewable Energy System <p><strong>Recently, an increasing number of organizations have begun to view renewable energy and industries as opportunities rather than regulations in the context of their production, distribution, and services. In this paper, main objective of designing a grid integrated solar-wind hybrid energy system for driving loads for improving its reliability and efficiency. And the inverter control designing with an AI-based optimization algorithm to attain improved active power at the terminal of loading by reducing the losses. And Improvement in the reactive power output from the system by the inverter control by a designed hybrid system that can compensate the reactive power requirement when required. The active power output from the system has enhanced to 77860 W in the system having converter regulated from the proposed controller that is MF_DEH from 77230 as a result of improved performance and reduced losses. The system was first compared with the PI-directed inverter control and the THD% in current, as well as voltage waveform, was found to be reduced to 0.11% in voltage and 0.41% in current from 0.86% and 1.93% respectively.</strong></p> Shilpa Bharti Abhishek Dubey Copyright (c) 2021 Shilpa Bharti, Abhishek Dubey 2021-06-24 2021-06-24 7 7 14 23 10.24113/ijoscience.v7i6.390 CFD Analysis on Francis Turbine to Analyse Erosion Wear Due to Sediment Flow <p><strong>In present work Computational fluid dynamics analysis based erosion wear prediction is performed for Francis turbine components, especially the runner. For the geometrical parameters, Francis turbine model with steady state condition and viscous flow turbulence SST model using ANSYS Fluent. The erosion effect on all the three component such as spiral casing, runner &amp; draft tube has been studied for different concentration of sand particles from 1% - 6%. For each of those concentration the effect of variation in size has been studied for different sizes 10 ?m - 80 ?m. Further the effect of total erosion was also analyzed for different particle size. Erosion damage is found close to the upper and lower portions of the leading edge of the stay vane. some erosion spots at guide vane on the blade pressure side where suction side has minimum erosion. Maximum erosion damage observed on runner especially at the middle of the blade. The draft tube situated closer to runner having highest velocity due to high absolute velocity of water coming out from the runner does not produce any serious erosion effect. Results shows that erosion rate is maximum on runner at particle size 80 ?m for all sand concentration 1% to 6%&nbsp; and minimum at 30 ?m. Thus, 30 ?m is the optimum size of sand particles for the erosion. </strong></p> Uttam Singh Yadav Shravan Vishwakarma Jitendra Mishra Copyright (c) 2021 Uttam Singh Yadav, Shravan Vishwakarma, Jitendra Mishra 2021-06-22 2021-06-22 7 7 1 13 10.24113/ijoscience.v7i6.389 A Review on Energy Efficient Clustering Algorithms for IOT Application <p>A large range of applications in different areas are available in wireless sensor networks (WSNs). The Internet of Things (IoT), which allows connections between various objects or devices through the internet, was one of the most recent emerging applications. However, as opposed to mobile ad-hoc networks, WSNs have a greater concern for battery capacity, which affects the network’s durability. Therefore, numerous studies have focused on reducing the WSN’s energy use. One of the many approaches to minimizing the energy of the WSNs is to design a hierarchical clustering algorithm. In this paper, an algorithm for IoT applications is presented that is based on energy-efficient clustering and the cluster head election process</p> Roshnee Adlak Pooja Meena Copyright (c) 2021 Roshnee Adlak, Pooja Meena 2021-04-28 2021-04-28 7 7 43 48 10.24113/ijoscience.v7i4.388 An Analytical Review on Application of Deep Learning in Medical Big Data Analysis <p><strong>The data of medical health has also incremented dramatically and methods of interpreting medical-driven huge big data have originated as the requirement with time, assisting in the reorganization of medical health condition intelligently the with the use of technologies of computer widely. Due to the heterogeneous, noisy, and unstructured nature of medical big data, it is still a difficult task to analyze medical big data. The conventional methods of machine learning can’t find out the major information involved in the medical big data efficiently, while deep learning designs a hierarchical model. It consists of effective features of extraction, potential feature expression, and typical model construction. This paper is dedicated to surveying different approaches for medical big data processing using a deep learning approach and extracting finding for future research scope</strong></p> Subham Kumar Dr. Farha Haneef Copyright (c) 2021 Subham Kumar, Dr. Farha Haneef 2021-04-28 2021-04-28 7 7 38 41 10.24113/ijoscience.v7i4.387 Application of Machine Learning in Fingerprint Image Enhancement and Recognition: A Review <p><strong>Biometric characteristics helps to recognize an individual among others. Each individual has a unique biometric feature. So, an automated system is designed to recognize an individual. In today’s growing AI development, biometric recognition is applied in many security systems. One of oldest and widely used authentic biometric methodology is fingerprint recognition. Many fingerprint recognition algorithms are designed and developed in order to reduce error rate and to improve accuracy. In this paper, a comprehensive review is presented on various techniques used for fingerprint recognition system along with their performance and their limitations. The purpose of this paper is to review various recent work on the fingerprint recognition system, to explain step by step the steps for recognizing fingerprints, and to provide summaries of the fingerprint databases with functionality</strong></p> Kshitij Singh Dr. Gireesh Kumar Dixit Copyright (c) 2021 Kshitij Singh, Dr. Gireesh Kumar Dixit 2021-04-23 2021-04-23 7 7 33 37 10.24113/ijoscience.v7i4.386