bluuebunny/crossref_metadata_2025 huggingface dataset:
Fuzzy Logic Based Path Stability Forecasting Scheme for Improving Data Dissemination in MANETs
Authors:   Assistant Professor, Tagore Govt. Arts and Science College, Pondicherry, India., C. Calarany , R. Manoharan ,   Professor, Department of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, India.
Published: March 2020

Path stability of the mobile nodes in MANET plays a vital role in effective data dissemination as it depends on factors such as mobility, energy, signal strength. Several studies reveal that the prediction of path stability might provide solutions thereby routing performance can be increased. In most of the protocols route selection is based on metrics namely hop count, energy, etc. The metric namely mobility factor “MF” is used in some of the protocols. These protocols include nodes with less energy or nodes with high mobility which results in loss of path in a short period of time. Since it preserves the neighbor’s history, more control overhead and maintenance complexity exist. Hence, a new metric namely Active Interactive new Neighbor Rate (AINR) has been considered for optimum path selection. In scenarios of path loss, there is an immediate need for alternative paths for continuous data transfer. From literature it is evident that fuzzy logic is more significant in exploring different possible states under path stability determination. Hence a new prediction mechanism based on fuzzy logic has been proposed by considering the Residual Energy (RE), Hop count (Hop) and proposed metric Active Interactive new Neighbor Rate (AINR) as the factors for the prediction of the optimal path. This prediction mechanism is leveraged in MANET scenarios where alternate paths should be available on hand in situations such as battlefield and natural disaster. From the simulation, it has been proved that fuzzy logic prediction model provides better results in terms of various performance metrics such as Throughput, Packet delivery ratio, End-to-end delay, Energy consumption and routing overhead than the existing protocols.
Electrical Percent Loading Assessment for the Distribution Transformers Residential-Used of a Barangay
Authors:   Instructor, Electronics and Communications Engineering Department, Don Honorio Ventura State University (DHVSU), Philippines., Gomez Romalyn H. , Dizon John Leslie M. ,   Staff Engineer , Technical Services Department , Pampanga I Electric Cooperative (PELCO I), Philippines, Teodoro Christine Ann S. ,   College Instructor, Electrical Engineering Department, Technological Institute of the Philippines - Quezon City (TIP-QC), Philippines., Demegillo Joeme Carl ,   Production Manager , D'Truck Specialist Inc, Florencondia Noel T. ,   Dean, College of Engineering of Nueva Ecija University of Science and Technology (NEUST), Philippines.
Published: March 2020

Proper rating of transformer is important to maximize the useful life and efficiency of the equipment. A higher or lower rating of the transformer can provide either a higher system loss or disconnection of consumer to an electricity provider. In this study, assessment of residential transformer of a barangay was considered. The percent loading of each transformers was evaluated by the used of the standard set by National Electrification Administration (NEA). The software used in the study is Microsoft Excel 2016 for determining the percent loading of each residential transformers. After the percent loading was identified, clustering of transformers was made according to the loading conditions. Changes in rating were also performed to correct the percent loading of the transformer. From 2017 to 2019, 13 transformers or 48.14 % were underloaded while 6 or 22.22% were found to be overloaded. By changing the rating of the transformer in the barangay, the percent loading of the 6 overload transformers were corrected. For the 13 underloads, 12 of which were amended. Moreover, there is still an underload unit RT19 considering the change in rating the available lowest rating of the transformer was already reached. The researchers recommend using load centering to minimize the number of transformers. To compare the monthly kWhr consumption, the monitor of the daily basis kWHr ingestion using Automated Mapping/Facility Management/ Geographical Information System or AM/FM/GIS was endorsed to identify the peak load of each transformer.
Automatic Target Acquisition and Bull Tracker using GPS and GSM Technology
Authors:   Dept. of Electronics and Communication Engineering, Sri Krishna College of Technology, Coimbatore, India., Jayarajan P. , Ragul S. Shri Charan ,   Dept. of Electronics and Communication Engineering, Sri Krishna College of Technology, Coimbatore, India., Yogesh V. Sri ,   Dept. of Electronics and Communication Engineering, Sri Krishna College of Technology, Coimbatore, India., Ramvel D. ,   Dept. of Electronics and Communication Engineering, Sri Krishna College of Technology, Coimbatore, India.
Published: March 2020

An efficient bull tracking system is designed and implemented for tracking the movement of any bull from any location at any time. The designed device works using GPS and GSM technology for bull tracking. Arduino microcontroller is used to control the GPS and GSM module. The device is embedded on a bull whose position is to be determined and tracked in real time. The microcontroller is used to control the GPS module to get the coordinates at regular time intervals. The GSM module is used to transmit the updated coordinates of bull location to the client via SMS and mobile application. When the SMS is received, the app will automatically read the SMS and update the location of the bull to the user. This device will help the user to always keep an eye on their bull.
Traffic Management for Smart Cities using Traffic Density and Swarm Algorithm to Inform Diversion Route
Authors:   Research Scholar-Mother Theresa Women's University Faculty, Department of Computer Science, Kristu Jayanti College, Bangalore., Peter Mary N , Rani M. Pushpa ,   Professor & Head, Department of Computer Science, Mother Theresa Women‟s University, Kodaikkanal.
Published: March 2020

Number of vehicles increasing day by day in the world which results in traffic, air pollution, delay in reaching designation. Traffic density is increased in the roads, especially in the signals. The traffic congestion has negatively affected the efficiency, aggressiveness, and financial development of a nation. Thus, congestion control of traffic has become a significant zone of research, and a substantial number of answers for this issue left different research endeavors in the said field in recent decades. The traffic volume changing after some time, and in this way, long traffic lines are produced at the street intersections. Consequently, the Intelligent Transport System answers these related issues. It has incredible possible and ability to make transportation systems safe and smart efficiently. ITS provides the accessing and driving services of effortlessly participating transportation systems in a smart city. Traffic congestion can be managed in a proper manner by using time estimation and other route diversion in a pre-informed way. For this, we have to calculate the values of traffic congestion density and find the neighboring route. Density algorithm and distance measure algorithm were used to find the traffic density, and the Swarm algorithm was used to find the nearby path.
Design and Development of Automatic Water Level and Quality Warning System of Latphrao Canal Community Bangkok, Thailand
Authors:   Department of Electronics and Computer Technology. Faculty of Industrial Technology Phranakhon Rajabhat University, Bangkok, Thailand., Saiapattalung Keeradit , Thongyoo Thongchai ,   Department of Electronics and Computer Technology. Faculty of Industrial Technology Phranakhon Rajabhat University, Bangkok, Thailand., Netayaraks Hattaya ,   Department of Environmental Science and Technology. Faculty of Science and Technology Phranakhon Rajabhat University, Bangkok, Thailand., Ruekkasaem Lakkana ,   Faculty of Industrial Technology, Phranakorn Rajabhat University, Bangkok, Thailand, Aungkulanon Pasura ,   Department of Materials Handling and Logistics Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand
Published: March 2020

The objectives of this research were to design and develop an automatic water level warning system for communities living along Khlong Lad Phrao (Lad Phrao Canal) in Bangkok. The development of the system was divided into the following four main parts: 1) a water level measurement system; 2) a precipitation measurement system; 3) a water quality testing system covering dissolved oxygen, pH, turbidity and electrical conductivity and 4) an internet alert system utilizing the LINE application and web-based application information display. The first three parts were to be solar-powered. The design and development effort showed that the system successfully measured water levels along with water quality with speed and precision. Moreover, the system was easy to measure results and was able to alert through the LINE application when water in Khlong Lad Phrao approached critical levels, thereby reducing damage from water levels. Precision testing of the developed water level and quality measurement systems found that precision was in the range of 99.74-99.77%.
An Electric Eye for Human Activity Recognition: A Hybrid Neural Network
Authors:   Assistant Professor , Department of Computer Science & Engineering at Coimbatore Institute of Technology, India., Prethi K. N. Apinaya , Sangeetha M. ,   Associate Professor, Coimbatore Institute of Technology, Coimbatore, India., Nithya S. ,   Assistant Professor, Department of Computer Science & Engineering at Coimbatore Institute of Technology, India., Priyadharshini G. ,   Assistant Professor, Department of Computer Science and Engineering at Coimbatore, India., Anithadevi N. ,   Assistant Professor, Department of Computer Science and Engineering Information Technology, Coimbatore Institute of Technology, Coimbatore, India.
Published: March 2020

A real time detection of human movements is a practical solution to monitor aged people or mentally challenged people with the permission of their family. Household person is needed to monitor the elder and differently abled people. Instead of monitoring their activities with the help of other people, smart phones are used as a remote to monitor their activities and simultaneously send the message to their family members. The accelerometer sensor placed in the mobile phones. It is used to identify the activities of the person who holds the mobile phones. The most commonly used classifier technique is Naive Bayes classifier which has a limitation of handle with the large set of data. To overcome this defect, the proposed system classifies the data using k-nearest neighbor (K-NN) technique and Neuroevolution. This system recognize some representative human movements such as walking, climbing upstairs, climbing downstairs, standing, sitting and running ,using a conventional mobile equipped with a single tri-axial accelerometer sensor.
Leaf Disease Detection using Deep Learning Algorithm
Authors:   Department of Computer Engineering, Dr. D. Y. Patil Institute of Technology, Savitribai Phule Pune University, Pune, India., Patil Kishori
Published: March 2020

India is a nation of agriculture and over 70 per cent of our population relies on farming. A portion of our national revenue comes from agriculture. Agriculturalists are facing loss due to various crop diseases and it becomes tedious for cultivators to monitor the crop regularly when the cultivated area is huge. So the plant disease detection is important in agriculture field. Timely and accurate disease detection is important for the loss caused due to crop diseases which affects adversely on crop quality and yield. Early diagnosis and intervention can reduce the loss of plant due to disease and reduce the unnecessary drug usage. Earlier, automatic detection of plant disease was performed by image processing. For disease detection and classification, image processing tools and the machine learning mechanism are proposed. Crop disease will be detected through various stages of image processing such as image acquisition, pre-processing of image, image feature extraction, feature classification, disease prediction and fertilizer recommendation.detection of disease is important because it will may help farmers to provide proper solution to prevent these disease.
Multi-Documents Extractive Text Summarization using Node Centrality
Authors:   Research Scholar, Department of Computer Science, Jairams Arts and Science College Karur affiliated to Bharathidasan University Tiruchirappalli, Tamil Nadu, India., Kuriakose Anish Mathew , Umadevi V. ,   Director, Department of Computer Science, Jairams Arts and Science College Karur affiliated to Bharathidasan University Tiruchirappalli, Tamil Nadu, India.
Published: March 2020

The advancement of technologies produce vast amount of data over the internet. The massive amount of information flooded in the webpages become more difficult to extract the meaningful insights. Social media websites are playing major role in publishing news events on the similar topic with different contents. Extracting the hidden information from the multiple webpages are tedious job for researchers and industrialists. This paper mainly focuses on gathering information from multiple webpages and to produce summary from those contents under similar topic. Multi-document extractive summarization has been developed using the graph based text summarization method. Proposed method builds a graph between the multi-documents using the Katz centrality of nodes. The performance of proposed GeSUM (Graph based Extractive Summarization) is evaluated with the ROUGE metrics.
Short term Predication of Risk Management Integrating Artificial Neural Network ANN
Authors:   University of Derby, Derby, United Kingdom., Nayak Malaya , Abdullah Tariq ,   University of Derby, Derby, United Kingdom.
Published: March 2020

The IT industry has boomed in the past few years with an ever increasing number of risk management applications being developed. There are inherent risks in software development projects and failure to deliver software projects within deadline or failure to develop software according to specifications can be costly. The software risks may occur during the project process. The management process of software risks consists the risk refinement, risk identification, risk monitoring, risk maintenance, risk estimation and risk mitigation. Neural Network has ability to stimulate hidden pattern recognition skill. The primary study of this paper is to focus on various risk management models and how risk tools may help in mitigating software risks during the project development. With the application of Neural Network, We propose short term risk management model which can predict the risk involvement with the upcoming project risks, analyzing from the previous projects causing serious loss in the IT project in terms of values on certain risk factors. Neural Network model can also ability to evaluate the assessment of risks in software development and acts as an effective instrument in analysis and minimizing risks that enable continuous improvement in software processes and products.
Theoretical Research on the Flight of Onion Seeds under Discharge from the Seeding Unit
Authors:   Doctor of Technical of Sciences, Docent, Department of General Technical Disciplines, Namangan Engineering Construction Institute, Namangan, Uzbekistan., Turdaliev V. M. , Igrashev B. ,   Doctor of Philosophy in physical and Mathematical, Docent, Department of higher Mathematics, Namangan Engineering Construction Institute, Namangan, Uzbekistan.,, Makhkamov G. U. ,   Scientific Applicant, Department of General Technical Disciplines, Namangan Engineering Construction Institute, Namangan, Uzbekistan., Qosimov A. A. ,   Scientific Applicant, Department of General Technical Disciplines, Namangan Engineering Construction Institute.
Published: March 2020

One of the most important issues of sowing small-seeded crops (an example of onions) is considered. The method of sowing has a great influence on crop yields. The choice of planting method is due to the need for a more uniform distribution of plants over the field area in order to optimize the conditions for their development. Studying the movement of seeds during the sowing process is the most important task. Because, the object of sowing is the seeds. The article provides an analysis of previous work on the precision sowing of small seed crops. And also, the flight and the trajectory of the seeds from the ejection window to the bottom of the groove were studied theoretically. In research methods of higher mathematics were used, in which it was possible to obtain the necessary equation. Based on the numerical solution of the obtained equations, graphs are constructed that determine the path of onion seeds on the corresponding X and Y axes. It can be seen from the graphs that the flight path of the seeds changes according to the parabola law.
Prediction of Cell Phone Client’s Location utilizing Semantic Trajectory
Authors:   Department of Computer Applications, SRM Institute of Science and Technology, Chennai, India, Subramanian J. Venkata , Govindarajan S. ,   Professor, Department of EDP, SRM Institute of Science and Technology, Chennai, India,
Published: March 2020

Investigation on anticipating developments of cell phone consumers has pulled in a great deal of considerations lately. Considerable foreseeing procedures are created dependent on geographic zonal highlights of cell phone abuser’s directions. In this research, we put forward a new methodology for anticipating the subsequent place of a client's development dependent in cooperation of the territory and semantic highlights of clients' directions. Center thought of the expectation structure depends on new cluster centered forecast technique it assesses the subsequent place a cell phone client dependent on the continuous practices of comparable clients in analogous group controlled by dissecting clients' normal conduct in semantic directions. Through an exhaustive assessment by tests, our proposition is appeared to convey fantastic execution.
Diagnosis of Type-2 Diabetes using Classification and Mining Techniques
Authors:   ECE, SV Engineering College,Karakambadi,Tirupati,AP, Padmanabhan Sankar , M Manjunath K ,   ECE, SV Enguneering College, Karkambadi road, Tirupathi, AP., V Madhurima ,   ECE,SV Engineering college, Karkambadi road, Tirupathi, AP
Published: March 2020

Around two hundred and fifty million individuals, with a major part of them being ladies influenced by diabetes. This number may ascend to 380 million by another decade. The sickness has been named as the fifth deadliest illness in the world with not a single inevitable fix to be seen. With the ascent of data innovation and proceeding with an approach into the restorative and medicinal services part, the instances of diabetes and their side effects all around are archived. Information mining is a buzz word separating concealed data from an enormous arrangement of database. It assists scientists in building large database in the area of biomedical engineering. The Pima Indian diabetes database was used for investigation purpose. In this paper an attempt has been made to study the effect of various classification and mining Techniques like Decision Tree, Naïve Bayes, SVM, Regression etc on the diagnosis of Type-2 diabetes.
Hybridized Gradient Descent Spectral Graph and Local global Louvain Based Clustering of Temporal Relational Data
Authors:   Research Scholar, Department of Computer Science, Jairams Arts and Science College, (Affiliated to Bharathidasan University, Tiruchirappalli) Karur - 639003, Tamilnadu, India., Dhas L. Jaya Singh , Mukunthan B. ,   Research Supervisor & Assistant Professor, Department of Computer Science, Jairams Arts and Science College, (Affiliated to Bharathidasan University, Tiruchirappalli) Karur - 639003, Tamilnadu, India., Rakesh G. ,   Dean of Science, Department of Computer Science, Jairams Arts and Science College, (Affiliated to Bharathidasan University, Tiruchirappalli) Karur - 639003, Tamilnadu, India
Published: March 2020

Temporal data clustering examines the time series data to determine the basic structure and other characteristics of the data. Many methodologies simply process the temporal dimension of data but it still faces the many challenges for extracting useful patterns due to complex data types. In order to analyze the complex temporal data, Hybridized Gradient Descent Spectral Graph and Local-Global Louvain Clustering (HGDSG-LGLC) technique are designed. The number of temporal data is gathered from input dataset. Then the HGDSG-LGLC technique performs graph-based clustering to partitions the vertices i.e. data into different clusters depending on similarity matrix spectrum. The distance similarity is measured between the data and cluster mean. The Gradient Descent function find minimum distance between data and cluster mean. Followed by, the Local-Global Louvain method performs the merging and filtering of temporal data to connect the local and global edges of the graph with similar data. Then for each data, the change in modularity is calculated for filtering the unwanted data from its own cluster and merging it into the neighboring cluster. As a result, optimal ‘k’ numbers of clusters are obtained with higher accuracy with minimum error rate. Experimental analysis is performed with various parameters like clustering accuracy ( ), error rate ( ), computation time ( ) and space complexity ( ) with respect to number of temporal data. The proposed HGDSG-LGLC technique achieves higher and lesser , minimum as well as than conventional methods.
Design and Testing of Fuzzy Logic Based Controller for Active Suspension System of a Quarter Car Model
Authors:   Mechanical Engg. Dept., Research Scholar, Dr. D. Y. Patil Institute of Tech., & Asst. Prof., Pimpri Chinchwad College of Engg., Pune, India., Vivekanandan N. , Fulambarkar A. M. ,   Mechanical Engg. Dept., Prof. & Principal, Pimpri Chinchwad College of Engg., Pune, India.
Published: March 2020

In today’s scenario, due to increase in sales of Sports Utility Vehicles (SUV’s) more and more people are opting for off road drive. The main challenge is to improve the performance based on handling and comfort. Hence the conventional static spring and damper system are being modified to accommodate semi-active and active systems. In this paper to study the effectiveness of active suspension system, a quarter car model is developed and Fuzzy control strategy is proposed to reduce displacement of chassis. Hydraulic actuator is used to provide active control in the suspension system of the quarter car model. The fuzzy logic controller is interfaced with the hardware system by LabVIEW software. For connecting the hardware with LabVIEW software Arduino is used. The comparison of active and passive suspension system shows that the chassis displacement is decreased by 30% in case of active suspension system whereas the settling time decreases by 69%.
Classification of Brain Tumor using Convolutional Neural Networks
Authors:   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, India., Shetty Shravya , Shetty Jyothi ,   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, India.
Published: March 2020

In medical science, brain tumor is the most common and aggressive disease and is known to be risk factors that have been confirmed by research. A brain tumor is the anomalous development of cell inside the brain. One conventional strategy to separate brain tumors is by reviewing the MRI pictures of the patient's mind. In this paper, we have designed a Convolutional Neural Network (CNN) to perceive whether the image contains tumor or not. We have designed 5 different CNN and examined each design on the basis of convolution layers, max-pooling, and flattening layers and activation functions. In each design we have made some changes on layers i.e. using different pooling layers in design 2 and 4, using different activation functions in design 2 and 3, and adding more Fully Connected layers in design 5. We examine their results and compare it with other designs. After comparing their results we find a best design out of 5 based on their accuracy. Utilizing our Convolutional neural network, we could accomplish a training accuracy and validation accuracy of design 3 at 100 epochs is 99.99% and 92.34%, best case scenario.
Round Robin Load Balancer for the Three Node Swarm Cluster for Hosting a Service on the Cloud
Authors:   Dept of computer science and engineering, SRM IST, India., Shukla Aaradhya , Chauhan Ayush Singh ,   Dept of computer science and engineering, SRM IST, India, Kalaivani J. ,   Dept of Computer Science, SRM IST, India.
Published: March 2020

In this project we will be creating an application which uses socket programming for communication and all of the data/metadata are saved in mongo DB. We will be taking this application and hosting it on a 3 node swarm cluster. This cluster will be using Docker swarm technology to create a private network through which each of the nodes can talk to each other along a specified RPC port. So, based on this concept we will be making a Docker container which will handle the execution of multiple processes which lead to working of different projects concurrently. Docker is a PC program that performs working framework level virtualization otherwise called containerization.
PSO to Solve the Problem of Integrated Economic & Emissions Dispatch
Authors:   Assoc. Professor, Department of Electrical Engineering, Annamalai University, Chidambaram, Tamil Nadu, Sridhar ND.
Published: March 2020

An important role in the electricity industry has alwa ys been efficient & optimum economical function of electricity p owersystems. This field of concern has taken a new turn in recent years, as environmental issues are being gradually discussed by t he public. Through optimizing distribution of load between power plant, the adverse ecological effects of outlet of gaseous contaminants will be reed. It contributes however to a significant increase in the functional cost of the system. Everything must therefore be equilibrium. There are three techniques investigated for solving the Combination of Economic and Emission Dispatch (CEED) solution that is one traditional method-Lambda Iteration System & Particle Swarm Optimization (PSO). The prize factor method which will change the many-objective CEED solution into one single minimal solution. The survey of total operating costs, total emissions, and system losses on 6-generation units test systems. This is carried out. Results show that Particle Swarm Optimization (PSO) method is superior to the other Lambda Iteration technique for reducing operating costs in solving the problem of Combined Current Economic &Emission Dispatch (CEED). Therefore, PSO technique is highly suited and recommended for use online.
Principal Component Analysis Online Statistical Analysis Tool
Authors:   Professor, Department of Mathematics and Statistics, CCS Haryana Agricultural University, Hisar., Sheoran O. P. , Kumar Vinay ,   Assistant Scientist, 3Department of Mathematics and Statistics, CCS Haryana Agricultural University, Hisar., Poonia Hemant ,   Assistant Professor, 3Department of Mathematics and Statistics, CCS Haryana Agricultural University, Hisar., Malik Komal ,   Assistant Professor, Economics, Govt. College, Nalwa Hisar,
Published: March 2020

An online module to deal with PCA has been developed in ASP scripting language based on Server-Client Architecture. The module produces descriptive statistics via subprogram Descriptive Stats, computes eigenvalues and eigenvector using MxEigen Jacobisub-program, order eigenvector through MxEigsrtsub-program and finally produces eigenvalues, eigenvectors, output loadings and components scores through Output Eigenval, Output Loadings, Output Scoressub-programs. A user friendly interface has been developed for entering or pasting the data, entering various parameters such as number of variables, number of observations and selection of covariance/correlation matrix. A complete procedure for how to perform principal component has also been provided in help file.
Statistical Research and Efficiency in the Process of Direct-Flow Gin
Authors:   Doctoral Student. Namangan Institute of Engineering and Technology, Namangan, Uzbekistan., Majidov A. T. , Safarov N. M. ,   Department of Technical Science, Dots. Namangan Institute of Engineering and Technology.
Published: March 2020

The present time more attention is allocated with the purpose about an opportunity manufacture qualitative products to improve technologies. In clause, the improvement of engineering and technology for allocation fibrous raw material is investigated. The scientific significance of the research results lies in obtaining dynamic and mathematical models of motion, numerically solving the problems of determining the laws of motion and parameter dependencies, the modes of motion of the recommended working bodies (saw cylinder, working chamber, grate, raw roller accelerator, chain gear for saw cylinder drive, bearing support) saw gin. The practical significance of the research results is to improve the saw gin, which allows obtaining high-quality cotton fiber with high productivity due to the intensification of the ginning process, an increase in the working life, as well as a decrease in the required drive power. The technology and design of a heated gin working chamber for ginning raw cotton of high humidity has been developed.
Reducing Fraudulent News Proliferation using Classification Techniques
Authors:   Department of Computer Science and Engineering, V.R.Siddhartha Engineering College,Andhra Pradesh, Vijayawada, India., Pratap A Raghuvira , D Prasad J V ,   Department of Computer Science and Engineering, V.R.Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India., Babu Sallagundla ,   Department of Computer Science and Engineering, V.R.Siddhartha Engineering College,Andhra Pradesh, Vijayawada, India., Kumar V V N V Phani ,   Department of Computer Science and Engineering, V.R.Siddhartha Engineering College,Andhra Pradesh, Vijayawada, India
Published: March 2020

The expansion of dishonorable information in normal get entry to social access media retailers like internet based media channels, news web journals, and online papers have made it hard to identify dependable news sources, subsequently growing the need for technique tools able to deliver insights into the reliability of online content substances.. This paper comes up with the applications of Natural language process techniques for detective work the dishonest news, that is, dishonorable news stories that return from the non-reputable sources. Solely by building a model supported mistreatment word tallies or a Term Frequency-Inverse Document Frequency matrix, will solely get you to date. Is it potential for you to make a model which will differentiate between “Real “news and “Fake” news? Thus our planned work is going to be on grouping a knowledge set of each pretend and real news and uses a Naïve mathematician classifier so as to make a model to classify an editorial into pretend or really supported its words and phrases.
Silicon Nitride as a Reinforcement for Aluminium Metal Matrix Composites to Enhance Microstructural, Mechanical and Tribological Behavior
Authors:   Department of Mechanical Engineering, M.A.N.I.T, Bhopal, India., Arya Ranjeet Kumar , Telang Amit ,   Department of Mechanical Engineering, M.A.N.I.T, Bhopal, India.
Published: March 2020

In recent years, aluminium and its hybrid composites receiving more attention due to its excellent property combinations like improved mechanical properties, better wear and high corrosion resistance, ease to process and probably reduced production cost etc.. Composite is made of two phases one is matrix and another one is reinforcement. The performance of composite highly depends on some key factors that decide overall performance and they are properties of constituent phases, reinforcement size, reinforcement distribution in the matrix and their interfacial interaction. Particle reinforced metal matrix composites (particulate metal matrix composites- PMMCs) are becoming more popular due to their low cost, easy to process and compatible to conventional processing techniques. Also they give isotropic properties. The most commonly used reinforcements are carbides, oxides and nitrides. A lot of research has taken place including carbide and oxide as a reinforcement particles for aluminum matrix composites (AMCs) and hybrid aluminium matrix composites (HAMCs) while there is a bit research lag in use of nitride as a reinforcement for development of AMCs and HAMCs. Recent competitive market demands the material having better combination of properties, cost effectiveness and eco-friendly nature. Present article focused on to study the microstructural features, physical properties, mechanical and tribological behavior of aluminium matrix composites when reinforced with silicon nitride particles (Si3N4). Potential area of applications has also been suggested on the basis of literature data. In this review a comprehensive study has done for current scientific development carried out in Al based Si3N4 composites as well as its future scope has also been discussed.
Dynamics of Speed Control of Dc Motor using Combine Armature and Field Control with Pi Controller
Authors:   Electrical Engineering Dept, University of Nigeria, Nsukka Enugu State Nigeria., Ejiofor Oti Stephen , C. Agada Stephen ,   Electrical/Electronic Engineering Dept, Michael Okpara University of Agriculture, Umudike Abia State, Nigeria., Chinedu Obe ,   Electrical Engineering Dept, University of Nigeria, Nsukka Enugu State Nigeria., Ahmed Salihu ,   Electrical Engineering Dept, University of Nigeria, Nsukka Enugu State Nigeria, C. Ogbuefi Uche ,   Electrical Engineering Dept, University of Nigeria, Nsukka Enugu State Nigeria.
Published: March 2020

This work examines the intrigues associated with the speed control of DC motor by nonlinear joint control of the voltage of the armature cum the field current in conjunction with the proportional integral controller. In the case of controlling the armature, the field current component is kept constant while the armature in contained with variable voltage. However, in the case of controlling the field, the voltage of the armature is kept constant while the field contends with a variable voltage. Both the field and the control of armature were used to acquire a DC motor speed control enhancement which offers a stability of the system. The proportional integral (PI) is for the purpose of extension for identification of better alternative. As consideration is given to the electrical, electromagnetic and the motional or mechanical arrangements, a model is developed for the separately excited DC motor (SEDM) which is mathematically analyzed. The originating models of the DC motor speed control schemes are simulated with the help of MATLAB/Simulink. The results obtained herein would be very useful for the control and process engineering oufits.
Hybrid Intelligent Technique SFLA-PSO for Control and Intellectual Process of Power System with Huge Penetration of Non Conventional Energy Sources
Authors:   Department of Power Systems Engineering, Stream National Institute of Engineering, Mysuru, Karnataka, India., S. Divya , Shivakumar S. B. ,   Ph.D., Department of Power Systems Engineering, Stream National Institute of Engineering, Mysuru, Karnataka, India., Ananthapadmanabha T. ,   HOD, Department of Electrical and Electronics, RYMEC, Bellary, Karnataka, India.
Published: March 2020

Due to the pressure of decreasing the carbon emission and inadequate sources of fossil fuels being a major reason, Renewable Energy is being incorporated rapidly throughout the globe. Smart grids have a substantial prospective towards tapping the non-conventional energy sources in their grid-connected mode or stand-alone mode [2]. Such limited systems across the sectarian domains of distributed generation systems despite the fact of tapping non-conventional energy sources, stay expected to be the advanced networks which may assist in transmuting the power and energy segment through not only delivering energy to distant and isolated communities, but also through better safekeeping and dependability of electrical energy resource in the urban zones [2][3]. Predominantly, due to a very large or bulk dispersion of non-conventional energy, the system units are expected to practice substantial encounters in sheltered and steady state process, very prominently on advanced stages of inconstant and spasmodic non-conventional sources (solar and wind). This paper is aimed to investigate the influence of the distributed generation like Wind and PV on the power system due to the large diffusion of non-conventional sources.
Performance Analysis of Diesel Engine using Copper Oxide Nano Additive
Authors:   School of Mechanical Engineering, St.Joseph‟s Institute of Technology, OMR, Chennai, P Sabarish Kumar , Sunderraj Arthur Jebastine ,   School of Mechanical Engineering, St.Joseph‟s Institute of Technology, OMR, Chennai, Geethan K. Arun Vasantha ,   School of Mechanical Engineering, St.Joseph‟s Institute of Technology, OMR, Chennai, Praveen Harish ,   School of Mechanical Engineering, St.Joseph‟s Institute of Technology, OMR, Chennai, Gilbert  ,   School of Mechanical Engineering, St.Joseph‟s Institute of Technology, OMR, Chennai
Published: March 2020

This experimental study focuses on investigation of performance and utterance attributes of a normal diesel engine with biodiesel prepared from pongamia. This study aims to reduce the emission of nitrogen oxide by adding an oxidation inhibitor Tert-Butylhydroquinone (TBHQ). The analysis for each sample is to be carried out in compression ignition engine (standard diesel engine). The engine is tested with standard diesel, pongamia methyl ester biodiesel without any additives. Then the analysis is to be carried by adding nano additive copper oxide for about 50 ppm in the above mentioned fuels. From this the best combination is found out and test is again carried out by adding the oxidation inhibitor.
Performance Analysis of Solar Photovoltaic Module using Buck Boost Converter and Zeta Converter
Authors:   Department of EEE, Mar Baselios college of Engineering and Technology, Trivandrum 695015, India,, P Sandhya.
Published: March 2020

This paper compares the performance of buck-boost and zeta converter fed solar photovoltaic module. The study is carried out by considering a solar pv module, dc-dc converter, MPPT controller and a resistive load. The voltage gain, output voltage ripple and output current ripple of the two converters were compared. Maximum Power Point tracking is implemented and and ensures the extraction of maximum power from the solar panel. Here MPPT is achieved by using perturbation and observation method. Zeta converter topology provides a non inverted output voltage with increased voltage gain. Output has lesser voltage and current ripple compared to buck-boost converter. Photovoltaic module with Buck-Boost and Zeta converter are simulated using MATAB Simulink software and the result are shown.
Reactive Power Cost Optimization Acquiring the Combined Properties of Static and Aggregate Dynamic Load as Composite Load Model
Authors:   Electrical & Electronics Engineering Department, KIET Group of Institutions, Delhi-NCR, Ghaziabad, India., Saxena Nitin Kumar , Kumar Ashwani ,   Electrical Engineering Department, National Institute of Technology, Kurukshetra, India, Gebreyohans Gebrehiwot ,   Electrical and Computer Engineering Department, Wolaita Sodo University, Sodo, Ethiopia.
Published: March 2020

In electrical systems especially isolated wind and diesel based hybrid systems, voltage control has been achieved in several works from adequate supply of reactive power using STATCOM/SVC as dynamic compensators. However, in most of the existing works, studies are performed only with static loads which do not have any influence of previous system conditions. In such available studies, the two major concerns were (i) cost based studies, and (ii) control techniques of dynamic compensation. The electrical systems are always influenced by the unrealistic load modelling in such systems which is almost untouched in available works and therefore motivate the authors to work on it. Realistic loads are of composite nature that composes the blend of characteristics that acquire static as well as dynamic nature of the load. In present work, the authors are interested to investigate the lower cost of reactive power with composite load for best proportion of dynamic and static compensations. The study is done in MATLAB software with 10% step increment in reactive power demand and input wind power to analyse compensation effect for extreme voltage deviation of pu at load end as recommended by several energy policies and standard IEC 60038.
Brain MR Image Enhancement using Average Intensity Replacement Based on GWOHE Algorithm
Authors:   Department of ECE, Bangalore Institute of Technology, Bangalore, India., N. Vidyasaraswathi H. , C. Hanumantharaju M. ,   Department of ECE, BMS Institute of Technology and Management, Bangalore, India.
Published: March 2020

The most important task in MR Image Enhancement is to obtain a high resolution optimized visual image using advanced image processing techniques. Most of the life photographs and various images such as aerial, medical and satellite are associated with noise and low grade intensity. To improve the quality for better visual appearance, noise has to be suppressed and contrast has to be enhanced. Traditional contrast improvement techniques do best for various images. But for MRI of brain images, there are chances of misrecognization of WMH (White Matter Hyperintensities) as Cerebrospinal fluid (CSF) in traditional enhancement techniques. To overcome this ambiguity and enhance WMH regions of MRI brain images, a novel algorithm has been proposed in this paper. This algorithm is called as Mean Intensity replacement based on Grey Wolf Optimization Histogram Equalization (GWOHE). This technique is applied on FLAIR images and comparison is tabulated along with existing technique for parameters such as PSNR, AMBE.
Influence of Various Temperatures on the Drying Time of 132 KV Transformer Insulations in Vapour Phase Drying Process
Authors:   Department of Mechanical Engineering, PES College of Engineering, Aurangabad, India., Siddiqui Mohd. Tareq , Pattiwar Jayant T. ,   Department of Engineering & Technology, Dr. BAM University, Aurangabad, India., Paranjape Avinash P. ,   Department of Electrical Engineering, Govt. Engineeirng College, Aurangabad, India., Keche Ashok J ,   Department of Mechanical Engineering, MIT College, Aurangabad, India.
Published: March 2020

Transformers are required to handle very high levels of voltage and hence proper insulation is very important in transformers. As of now, the most preferred form of insulation in transformers is cellulose based. The state of cellulose insulation materials like paper & pressboards determines the life end of a transformer. Paper with 1.5% moisture content ages 10 times faster than with only 0.3% moisture. For obvious reasons, it is very important that the moisture is removed from transformer insulation. Vacuum drying has been conventionally used in industries for insulation drying but, as of today the latest technology available is the vapour phase drying process. This paper evaluates the influence of temperatures at various locations on the drying time of the 132kv transformer insulations in vapour phase drying process.
Necessities, Properties, & Merits of using Geopolymer Concrete
Authors:   M.S. in Construction & Facilities Management, Name of the affiliated College or University/Industry, City, Country., Venugopal Manish
Published: March 2020

As urbanization across the globe is on the rise. Construction has become one of the largest industries across the world. Concrete being one of the most abundantly used material across the construction industry possess cement as the core ingredient in its mixture. Studies have indicated cement manufacturing alone accounts for about 8% of the carbon dioxide (CO2 ) emissions across the world. With a forecast of 85% increase in the volume of construction by 2030, there is a need to protect the environment from being affected further by the emissions from the construction industry. As such there is an immediate need to resort to alternative materials to achieve environment friendly construction. One such material that has been in use for more than a decade is geopolymer concrete. This paper analysis the available literature for the necessity of geopolymer concrete to be used in the construction industry. In addition, it also explores the properties, and merits of using them towards a sustainable environment.
Detection of Abnormal Tumor Regions in Ultrasonic Thyroid Images using SVM Classification Method
Authors:   Assistant Professor, Department of ECE, PKIET, Karaikal, India., Shankarlal B. , Sathya P. D. ,   Assistant Professor, Department of ECE, Annamalai University, Chidambaram, India.
Published: March 2020

Detection of tumor or abnormal regions in thyroid gland is difficult task in human. The following methods are presently used for detecting the abnormal regions in thyroid gland as blood test, sample testing from thyroid gland and image processing method. This paper develops a methodology to detect the tumor regions in thyroid images using image registration and image enhancement technique. The Support Vector Machine (SVM) classifier is operated in two modes as training pattern generation and testing mode. The generation of training pattern from both normal and abnormal ultrasonic thyroid images. This proposed method for thyroid tumor region detection obtains 96.54% of sensitivity, 97.57% of specificity and 98.56% of average tumor segmentation accuracy.
Strategies of Green Supply Chain Practices in Construction Industry
Authors:   Associate Professor, National Institute f Construction Management and Research, India., Muralidhar P.
Published: March 2020

Greening the supply chain practices is essential to all the sectors. Currently the management looking after the construction activities is also highly focusing on this. It is also coined as sustainable supply chain management. The sustainability is an important factor in construction industry rather than any other industries. The present research paper aimed at identifying and creating awareness of green supply chain management in materials and practices implied in Indian construction Industry. Many of the construction companies are not following sustainable practices in their day-to-day activities. There is a lot of scope to implement the sustainable practices, further helps in reducing the carbon emissions in the supply chain and helps to provide the recycling of the materials and thus reduces the wastage. This improves the construction industry economy and environment. The current research aimed at analyzing the strategies related to green supply chain management practices for construction Industry.