bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Heart Disease using Naïve Bayes Technique of Data Mining
Authors:   Computer Science and Engineering ,Guru Nanak Dev University,gurdaspur, india., Arshdeepkaur  , kumar* Anil ,   Computer Science and Engineering ,Guru Nanak Dev University,amritsar, india.
Published: March 2020

Coronary illness is responsible for deaths in all age groups and is common among males and females. An excellent answer for this issue is to have the option to predict what a patient's health status will in future so the specialists can begin treatment much sooner which will yield better outcomes. Data mining plays most significant role in area of investigation by means of the objective to finding essential data from massive amount of information. Currently, data mining strategies and tools are utilized by researchers in the field of healthcare, especially for prediction of sickness. Data mining methodology affords improvement approach to interchange huge data into beneficial information for attaining selection. In utilising data mining patterns they desires considerably fewer amount of funding intended for the forecasting the ailment alongside better accurate and precision. Moreover, analysis of study paper depicts the estimation of coronary illness in clinical field by utilizing data mining. Various popular data mining algorithm on the dataset of 13 attributes is applied to forecast the coronary ailment at initial stage. The dataset is collected from UCI machine learning repository and analysed with various parameters like Accuracy, Recall, Precision, F-measure, ROC area and Kappa statistics. Experimental results show that the Naïve bayes algorithm is always becomes the best-performing data mining method which accomplishes an accuracy of 86.716% in coronary illness prediction.
Automatic Question Generation u sing Sequence to Sequence RNN Model
Authors:   Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India., Jayarajan* Alina K. , A. Ajumol P. ,   Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India., Sunny Ani ,   Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India.
Published: March 2020

Automatic Question Generation (AQG) has recently received growing focus in the processing of natural language (NLP). This attempts to create questions from a text paragraph, where certain sub-spans of the passage in question will answer the questions produced.. Traditional methods predominantly use rigid heuristic rules to turn a sentence into related questions. In this research, we suggest using the neural encoder-decoder model to produce substantive and complex questions from the sentences of natural language. We apply a attention-based sequence to sequence learning paradigm for the task and analyze the impact of encoding sentence vs. knowledge at paragraph level. Information retrieval and NLP are the core components of AQG. It incorporates the application of production rules; recurrent neural network (RNN) based encoder-decoder sequence to sequence (seq2seq) models, and other intelligent techniques. RNN is used because of its long short term memory power (LSTM).The proposed system focus on generating factual WH type questions.
Efficient and Secure Data Transaction with Storage Optimization in Information Centric Network
Authors:   Ph.D, Professor, Department of Computer Science and Engineering , Sona College of Technology, Salem., Sakthivel *Dr. S. , M.E S. Hemalatha ,   Department of Computer Science and Engineering, Sona College of Technology, Salem.
Published: March 2020

Network utilization has been widely utilized by means of greater wide variety of users and managing user request with its increasing demand for content material transport is an main task has been dealt with by using Information centric network (ICN) through network cache method. An efficient access manage mechanism is required to make use of community resource, content material dissemination and better delivery service. Cache primarily based records shipping is an environment friendly approach to handle improving users request however it reasons high computation overhead and surprising extend in statistics delivery. In our proposed work an environment friendly method to beautify the utilization of network, request dealing with and storage optimization has been bought via Secure and Efficient Resource Utilization Framework (SERUF) for ICN. Unauthorized consumer request has been validated and blocked in edge of the community itself and cache based totally statistics retrieval is applied with content de-duplication. To maintain our file in impervious way thru Enhanced Attribute based encryption (E-ABE) is used which lets in special file to save in server. Hence our strategy consists of storage utilization, secure information retrieval and handles user request in efficient way.
Structural and Optical Properties of Alcohol, Alcohol-Aqueous and Aqueous Mediums Mediated Zinc Oxide/Copper Oxide (Zno/Cuo) Nanocomposites Synthesized Via Co-Precipitation Process
Authors:   Assistant Professor, Department of Physics, Academy of Maritime Education and Training (AMET) – Deemed to be University, ECR, Chennai, Tamil Nadu, India., Anandan* Dr. K. , Sharma Mr. S. Vinoth ,   II M.Sc., Student and The New College, Chennai, Tamil Nadu, India., Hussain Mr. S.G. Mohammed ,   Assistant Professor, PG and Research Department of Physics, The New College, Chennai, Tamil Nadu, India., Rajendran Dr. V. ,   Head & Associate Professor, Department of Physics, Presidency College, Chennai, Tamil Nadu, India.
Published: March 2020

By using different solvents the zinc oxide/copper oxide (ZnO/CuO) nanocomposites were synthesized via co-precipitation process. A Physico-chemical property of zinc oxide/copper oxide nanocomposites was identified by powder X-ray diffraction (XRD) and Photoluminescence (PL) techniques. The obtained results were demonstrated that the alcoholic mediated zinc oxide/copper oxide nanocomposites are exhibit smaller crystalline size and enhanced optical properties than that of aqueous mediated nanocomposites materials. From the results, it was confirmed that the synthesized samples would be promising metal oxide composites materials for opto-electronic device applications.
IoT Edge Data Retrieval System for Big Data Analytics in Smart Retail S tores
Authors:   Research-Scholar, Bharath University, Chennai,TamilNadu, India., Karthikeyan* RR , Raghu Dr. B. ,   Principal, SVS Groups of Institution, Warangal, Telangana,India
Published: March 2020

An IoT Edge system is to collect the sensor, set point and other device data with the help of micro controller and send those to IoT Hub via Edge Hub. The Building Management System (BMS) playing major role to control, communicate between various devices such as sensors, actuators with user interfaces, consumers and other technical devices. Commercial buildings like retail stores have two important systems called HVAC (Heating, Ventilating, and Air Conditioning) and refrigeration control. The proposed IoT Edge system collects the various device data via BAS and send it to IoT Hub. IoT Hub is a secure and two-way communication service system between the IoT Edge and the cloud platform where we can process telemetry data generated from sensor devices. IoT Edge helps to a computing near datasource. IoT Edge agent monitor and control all the modules running on it. With high speed internet connection users can access information and computational resources from anywhere in the world. Cloud platform can supply a range of Virtual machines with shared resources with big power and storage using inexpensive disks, which are much necessary for enterprise applications with Big Data. Disks.
Software Defined Radio: USRP N210 with GNU Radio
Authors:   Associate Professor, Dept. of ECE, CMR Engineering College, Kandlakoya, Telangana, India, Reddy* B Siva Kumar , Chari K Subramanya ,   Assistant Professor, Dept. of ECE, CMR Engineering College, Kandlakoya, Telangana, India
Published: March 2020

Driven by the increasing interest from the research community, this paper presents the current role of software defined radio (SDR) in academic and commercial applications which is helpful for the researchers, professors as well as students working in the area of signal processing and wireless communication. The authors mainly focus on universal software radio peripheral (USRP) N210 which is employed as hardware and GNU Radio as software to implement SDR for various applications that help the researchers to test and analyze various proposed techniques for different systems. Furthermore, this paper presents the implementation of basic analog/digital modulation techniques, and recent research works carried out by using SDR. This paper also presents several limitations and current usage of SDR in commercial and academic applications.
Semi Automaized Sugarcane Planting Technology
Authors:   PhD degree, Power Quality,Anna University, Chennai, India, Senthilnathan* N. , Gomathy S. ,   Assistant Professor in the Department of Electrical and Electronics Engineering, Kongu Engineering College, Tamil Nadu, India., Rahul S.S. ,   Bachelor of Engineering degree in the stream of Electrical and Electronics Engineering in Kongu Engineering College, Erode, Tamil Nadu, Ramkumar M. ,   Bachelor of Engineering degree in the stream of Electrical and Electronics Engineering in Kongu Engineering College, Erode, Tamil Nadu, Ramkumar R. ,   Bachelor of Engineering degree in the stream of Electrical and Electronics Engineering in Kongu Engineering College, Erode, Tamil Nadu, Shankar P. ,   PhD degree, Power Quality,Anna University, Chennai, India, Shankar P. ,   Bachelor of Engineering degree in the stream of Electrical and Electronics Engineering in Kongu Engineering College, Erode, Tamil Nadu
Published: March 2020

The main epigram of this paper is to overcome the labour shortage and to reduce time and money. Mainly cultivation of sugarcane involves three process - cutting of sugarcane into reliably smaller pieces, ploughing the field for sowing the sugarcane and sowing them in the sand. This paper proposes a piece of equipment which can perform the above mentioned three works simultaneously. In this paper, we come up with the use of pneumatic pistons for cutting the sugarcane, which is also attached to the equipment/planter. The planter consists of a plough setup and addition plough control at the back to cover the cane with sand after it is sowed in the sand.
A Decentralized Service based E-commerce
Authors:   Computer Science,SRM institute of science and technology, Chennai, India., Mahajan* Abhishek , Pisipati Sourabh ,   Computer Science,SRM institute of science and technology, Chennai, India., Madhavan P. ,   Computer Science,SRM institute of science and technology, Chennai, India.
Published: March 2020

The decentralization of many processes has the potential to help many service-based industries to scale up the operations in magnitude and efficiency horizontally, as well as to reduce exponential overhead costs of operation set-up in a new location though e-commerce. This is achieved through the backbone of connecting different operational units through the internet, more specifically through the cloud. The technologies like cloud computing, block chain, native applications for mobiles, and web applications as well, enable a decentralized yet synchronized environment, which is sustainable with a larger ceiling of overburden on the sector. The e-commerce will use web application, android as well as iOS applications, cloud computing as well as security through block chain techniques. It also makes it easier to adjust according to the customer feedback using collaborative filtering as well as adjusting for errors in remote operational units. For the purpose of understanding, we will take the example of a decentralized, cross city e-commerce laundry service in this paper.
Non-Invasive Fruit Analyser_1.7
Authors:   Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, Vijayachitra* Dr.S. , E Hariprasanna. ,   Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, S Haripriya. ,   Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, S Kavin.V. ,   Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai, Ranjith.P Mohan ,   Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Perundurai
Published: March 2020

Fruit quality is an important parameter in the food processing industries. It is necessary to analyze internal and external characteristics of the fruit sample. Standardizing the quality of fruit in Agro industries is essential. There is a need of standardizing equipment of affordable price because it involves huge man power. In this project, quality of the fruit is analyzed based on the capacitor concept in which the fruit will act as a dielectric medium between two parallel plates. The obtained output voltage is proportional to the condition of the fruit sample. The color variation in the outer layer of the sample is also determined using the image processing techniques. To find the quality, it is also that considered volume and weight as important parameters. All these three data are combined together in order to give the desired results at an affordable price. This product will also reduce the labor cost and the losses possibly occurred due to the destructive analysis and so on.
Link Prediction in Complex Networks using Embedding Techniques and Similarity Measures
Authors:   Department of Computer Science and Engineering Delhi Technological University, New Delhi, India., Kumar* Sanjay , Gupta Vipul ,   Department of Computer Science and Engineering, Delhi Technological University, New Delhi, India., Singh Sudhanshu Shekhar ,   Department of Computer Science and Engineering, Delhi Technological University.
Published: March 2020

Networks have proved to be very helpful in modelling complex systems with interacting components. There are various problems across various domains where the systems can be modelled in the form of a network with links between interacting components. The Problem of Link Prediction deals with predicting missing links in a given network. The application of link prediction ranges across various disciplines including biological networks, transportation networks, social networks, telecommunication networks, etc. In this paper, we use node embedding methods to encode the nodes into low dimensional embeddings and predict links based on the edge embeddings computed by taking the hadamard product of the participating nodes. We further compare the accuracy of the models trained on different dimensions of embeddings. We also study how the introduction of additional features changes the accuracy when introduced to various dimensions of node embeddings. The additional features include overlapping measures such as Jaccard similarity, Adamic-Adar score and dot product between node embeddings as well as heuristic features i.e. Common Neighbors, Resource Allocation, preferential attachment and friend tns score.
Empirical Methodology and Innovative Algorithm for Mining High Utility Itemset on Temporal Data
Authors:   P.G Student, Department of Computer Science and I.T Amrita School of Arts and Sciences, Kochi, Amrita Vishwa Vidyapeetham, India, Raj Rachith , Krishnan* Ajay ,   P.G Student, Department of Computer Science and I.T Amrita School of Arts and Sciences, Kochi, Amrita Vishwa Vidyapeetham, India, Kumar C.V. Prasanna ,   Assistant Professor , Department of Computer Science and I.T, Amrita School of Arts and Sciences, Kochi
Published: March 2020

Ever since the humans found the significance of data we are using different methodologies to extricate data patterns in the most useful way to reach at various conclusions based on our needs. The proper utilization of data will leads to meaning full results. Here our focus is to expand the concept of "High utility itemset mining" and also introducing the concept of "timestamp" on it. Here we proposed an effective algorithm to find the best possible data patterns that generate maximum profit within the given "time period" and also proposed a new framework to calculate the "utility support”. Our analysis can be utilized to improve profitability in business and also make better decisions for improving sales in the organization.
Air Quality Prediction u sing A rtificial Intelligence
Authors:   Research Scholar, Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India., Nandhini* P. Shree , Amudha Dr. P. ,   Associate Professor, Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India., Sivakumari Dr. S. ,   Professor and Head, Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India
Published: March 2020

Due to the critical impacts of air pollution, prediction and monitoring of air quality in urban areas are essential tasks. However, because of the dynamic nature and high Spatio-temporal variability, the prediction of the air pollutant concentrations is a complex Spatio-temporal problem. The data is collected in specific area such as climate condition and vehicular pollutant occurring in the peak hours. the predication process is used to compare the algorithm artificial neural network and support vector machine process. This paper presents a survey on Air quality prediction using artificial intelligence
Congestion Control in Wireless Sensor Network using Artificial Intelligence Techniques
Authors:   Research scholar, Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India., Vanitha* G. , Amudha P. ,   Associate Professor Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India, Sivakumari S. ,   Professor and Head, Department of Computer Science and.Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India.
Published: March 2020

Now-a-days, wireless sensor network has many issues and challenges like energy-efficient, congestion control, delay, scalability, reliability, robustness, etc. Communication between the wireless sensor nodes requires minimum response delay and congestion. It also requires disclosure to be energy efficient. Many congestion control protocols are using to control the congestion and improve the energy-efficient in that particular problem. Then the WSN protocol is classified as the protocol based, wired, wireless, frequency-based, and it will give the solution to that problem efficiently. Then the artificial intelligence techniques are used in a wireless sensor network to control the congestion in the systems. However, the primary fact is that the sensor node runs out of energy quickly, and traffic (congestion) has issues in many congestion control protocols. Here, congestion control is detects by hierarchical, distribution, energy-efficient in the way of algorithm in a WSN.This paper Present a Survey on Congestion Control in wireless sensor network using artificial intelligence Techniques.
Augmented Reality Brings the Fifth Dimensional Experience in Educational System An Intensive Breakdown
Authors:   Assistant Professor, Computing and Informatics Department, Mazoon College, Muscat., Basha* Dr. Saleem , Abbas Dr. Mohamed ,   Assistant Professor, Computing and Informatics Department, Mazoon College, Muscat., Masruri Dr. Khalfan Al ,   Dean, Mazoon College, Muscat., Saadi Dr. Said AL ,   Assistant Professor, English Language Department, Mazoon College, Muscat., Azri Dr. Rashid Al ,   Assistant Professor, English Language Department, Mazoon College, Muscat., Mr Adnan  ,   Lecturer, English Language Department, Mazoon College, Muscat., Yusufi Ms Gazala ,   Lecturer, Computing and Informatics Department, Mazoon College, Muscat
Published: March 2020

Learning is a never-ending process since the evolution of mankind. The learning process has brought mankind to breakdown the atom to the formation of space exploration from International Space Station (ISS). There are many supporting tools and techniques to support the teaching and learning process. In this line of tools and techniques, Augmented Reality (AR) has kept the footprint in the educational system after a struggle of 50 years of research. The research in AR has great anticipation in enhancing the educational system by redefining the articulations of the system. It is believed that AR can bring a different perspective on the educational system. This research article shall investigate the facts and reasons from the past that can be attributed to this phenomenon. This article begins with the introduction of the educational system from the traditional method to present practice, the facts & research findings and concludes with the references at the end.
Machine Learning Based Braille Transliteration of O dia Language
Authors:   Assistant Professor, Department of Electronics and Telecommunication, KIIT, India., Jha* Vinod , Parvathi Dr. K. ,   Administrator, Department of Electronics and Telecommunication, Andhra University, Visakhapatnam, India.
Published: March 2020

Braille transliteration of natural languages is required for providing a better opportunity of learning and creating opportunities of ceceity people. It allows a bigger diaspora of non-blind teachers to have written communication with blind people. The present paper proposes a method of Braille transliteration of Handwritten and printed Odia characters automatically into Braille. The current work proposes a method of Braille transliteration of Handwritten Odia text with industry applicable accuracy. The method first preprocesses the text and then segments it into characters and then uses an SVM classifier trained on HOG features of Odia handwritten characters to predict characters and maps the predicted printable character to its corresponding Braille with a very good accuracy. The method can further be used with text to speech engines to help the blind students use this technique with refreshable Braille having audio facility to listen the same.
Diabetes and its Complication Prediction using Multi-Task Learning
Authors:   Department of Computer Science and Engineering Department, SRM Institute of Science and Technology, Kattankulathur, Chennai, India., Dey* Shubharthi , Choudhury Bagish ,   Department of Computer Science and Engineering Department, SRM, Institute of Science and Technology, Kattankulathur, Chennai, India., Sharanya S. ,   Department of Computer Science and Engineering Department, SRM Institute of Science and Technology, Kattankulathur, Chennai, India
Published: March 2020

Diabetes is a long-term disease that ends up in multiple side-effects. It has now become a reticent exterminator in society because it doesn’t reveal any signs hitherto to the patients until it’s too late. It leads to many complications to other organs, such as kidney, cardiovascular, liver or blood pressure [1]. This work tends to apply a unique multitask learning [2] to synchronously map the relation between manifold complications wherever every task conforms to risks of modelling of complications [3]. It also uses feature selection to reduce the set of risk factors from high-dimensional datasets. Then using the concept of correlation, it finds the degree of relativity among various side-effects. The proposed method is able to identify the possible future health hazards identified with the diabetes patient. This will enable us to explain medical conditions and can improves healthcare applications which would help to improve disease prediction performance.
Tool Wear Rate on Inconel 718 u sing W Powder Mixed Electric Discharge Drilling
Authors:   Associate Professor, Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamilnadu, India., Jeevamalar* Dr. J. , Vimalraj R. ,   UG Student, Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamilnadu., Vigneshwaran M. ,   UG Student, Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamilnadu., Vignesh G. ,   UG Student, Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamilnadu.
Published: March 2020

Electrical Discharge Drilling (EDD) is an unconventional manufacturing process with large industrial performances. Addition of powder particles in dielectric changes some process variables and machines hard and hard to cut materials with greater surface finish high tolerance and accuracy to accomplish a superior material removal rate with a reduced Tool Wear Rate (TWR). This research work explores the performance of TWR on Tungsten Powder Mixed Electrical Discharge Drilling (W-PMEDD) on Inconel 718 super alloy. The input machining parameters of Peak Current (Ip) Pulse on (Ton) and Pulse off time (Toff) and the output measure of TWR were examined by Response Surface Method (RSM). Analysis of Variance was used to evaluate the effect of the machining parameters and it is concluded that Ip, Ton and Toff are the most significant parameters while machining of W-PMEDD on Inconel 718.
Design and Implementation of an Isolated Interleaved Buck Boost Converter with Phase Shifted Control
Authors:   Assistant Professor (Sr.G) in the Department of Electrical and Electronics Engineering in SRM Institute of Science and Technology (SRMIST) , Kattankulathur, India, Senthilmurugan* S. , Ganesh Viswanathan ,   B. Tech EEE in SRM Institute of Science and Technology, Kattankulathur, India, Prabhu Akash ,   B. Tech EEE in SRM Institute of Science and Technology, Kattankulathur, India., V.M Ajay Krishna ,   B. Tech EEE in SRM Institute of Science and Technology, Kattankulathur, India, R. R Ajit Ram ,   B. Tech EEE, SRM Institute of Science and Technology, Kattankulathur, India
Published: March 2020

tThis tpaper tfocuses ton tdeveloping ta tnovel method tfor tthe tdesign tof tdiscrete tbuck tbooster tconverter with tsingle tphase tpower tconsumption. tIn tthis tmethod, tit uses tconverters tbased ton thigh tfrequency tfrequency bridge-less tinterlaced twidth trectifiers. tThe tmerit tof tthis method tis tthat tby tincorporating tinterleaved tboost converters tinto tcomplete tbridge tdiode trectifiers, tswitching and tconduction tlosses tcan tbe tsignificantly treduced. tHere, we tanalyze tthe twhole tbridge tin tdetail twith tthe tdiscrete buck-booster tconverter tvoltage tcoefficient. tVoltage coefficient tcorrection thelps tincrease tthe tvoltage tgain tin tthe circuit. tWe tuse tan toptimized tphase tshift tmodulation strategy ton ta tcomplete tbridge tdiscrete tbuck tboost converter tfor timproved tperformance tand tincrease toverall efficiency. tTransformers twith tlow tratios tand tlow tvoltage MOSFETs tand tdiodes tcan tbe timplemented tto timprove efficiency. tBased ton ta tvariety tof tinterlaced tbooster converters, tincluding ttraditional tbooster tconverters tand high tstep-up tbooster tconverters twith tvoltage tmultipliers. From tthe tpoint tof tview tof tconversion tefficiency, tthe discrete tbuck-boost t(IBB) tconverter tis ta tgood tapproach. Unfortunately, tthe tfly-back tconverter tis ta ttypical tIBB converter, tbut tthe tefficiency tis tstill tvery tlow tdue tto tthe high tvoltage tpressure ton tthe tcomponents tand trectangles. In this tpaper twe tgive tan tinput tDC tsupply tof t12V tand tan output tvoltage tof t140V. tThe toutput tprototype twas designed tto tvalidate tthe teffectiveness tof tthe tproposed tIBB converters tand tits tcontrol tstrategies.
Predicting the Success Rate before Liver Transplant using ANN
Authors:   Assistant Professor, Department of Computer Science, DAV College for Boys, Hathi Gate, Amritsar, Punjab, India., Gupta Aditi
Published: March 2020

The counterfeit learning models, for example, the artificial neural system, radial basis function and art map have demonstrated a promising application in the medicinal industry. The present work is a comparative examination of the previously mentioned. The consequences of our examination have demonstrated that among Artificial neural system, radial basis function and art map the numeric qualities acquired from ANN were relatively better. Further, the investigation of the exactness among the three chose calculations was found 98.9708%, 97.2556%, and 58.1475% separately. As per writing overview performed, it is clear that most examinations right now got lesser consideration, particularly in India. In view of our discoveries it appears that the ANN could be the best mode to predict the joint stabilities during liver transplantation.
Analysis of User Acceptance Factors of the QR Code as a Pay ment System in Mobile Banking u sing the Utaut Method: Simobiplus Mobile Banking
Authors:   Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University Jakarta, Indonesia, S.kom* Prasetyo Jati Nugroho , S.kom Astari Retnowardhani ,   M.Kom, Phd Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University Jakarta, Indonesia, Fajar Dr. Ahmad Nurul ,   S.T., M.T Information Systems Management Department, BINUS Graduate Program – Master of Information Systems Management, Bina Nusantara University Jakarta, Indonesia
Published: March 2020

In an increasingly modern era of globalization, people and technology are now starting to coexist, technology is always associated with various fields and activities of human activities with the aim of helping the work process to achieve maximum results, one area of business that feels its development is the Banking sector. Previously, services were traditionally provided through branch offices, but now banking services have begun to be done digitally using the Mobile Banking service so that transactions can be done anytime, anywhere. The banking industry is now competing to provide better transaction services, one of which is by providing QR Code transaction services on mobile banking, QR Code Transactions are payment methods that are run using QR Codes that are read using a Scanner through the Mobile banking application. Sinarmas Bank is one of the banks that provides QR Code transaction services for its customers. However, since the QR Code service was launched to customers, transactions have not grown significantly and have not been in line with the company's business goals. The methodology that will be used in this study is the modified UTAUT method, with this method it is expected to know what factors influence the acceptance of the QR Code payment system, research data obtained from the questionnaire, then the data will be processed with the PLS SMART application. From the results of data processing it is known that Performance Expectancy (PE), Expectancy expectation (EF), Perceived Trust (PT), Social influence (SI), moderation 1 (EF-EX) significantly influence Behavior Intention (BI) and Behavior Intention (BI) ) and Facilitating Conditions (FC) affect Use Behavior (UB). From the results of the data processing, Sinarmas Bank can further develop focused on variables that significantly influence the acceptance of QR Code services so that the services provided are better.
Automatic Generation Control of Two Area Thermal Power System using Single Objective PSO and DE Optimization Techniques
Authors:   Department, ECE, Debre Berhan University, Debre Berhan, Ethiopia, Aklilu* Dr. Solomon Feleke
Published: March 2020

Now a days AGC has a great roll in controlling the mismatch between generation and load in interconnected power system, to attain AGC more optimal, tuning the controller using optimization techniques is needed. In this paper PSO and DE optimization techniques are employed for dynamic frequency control analysis. For dynamic analysis, the PID gain parameters obtained through single objective optimization using PSO and DE techniques, the controls are implemented by considering 1% of change in load disturbance in area 1 only and computed with sum of absolute value of ith area control error at time t as objective function and simulation result is obtained by interfacing Matlab (.m file) with Simulink block model under study . Comparison analysis is performed between PSO-PID, without controller and DE-PID. According to the investigations, better dynamic response performance is achieved through DE-PID method than the PSO-PID technique for the measured parameters of time response transient analysis such as maximum overshoot, rise time, maximum undershoot and settling time in AGC of two area system.
Utilization and Application of Weighted Keyword in Retrieval
Authors:   Department of M.Lib Burdwan University, West Bengal, Ghosh* Sandip
Published: March 2020

Keyword improvements must be addressed to address the core issue of ‘Keyword-Based Search System’ i.e. “High Recall and Low Precision”, which will in turn lead to systematic modification of KWIC indexing system. And this improvement can only be done by imposing a weight that is possible through the ‘Grammatical-Hierarchical Logic’ method. So, in this paper it is trying to establish a modified KWIC named ‘Key-Word Weighted-In-Intra Contextual-Content’ on the one hand, and on the other hand trying to draft a mechanism of an advanced ‘Search Engine’ outline with the modified indexing method named ‘KWWIICC’, by which most relevant and precise document will be provided as per the users requirement.
Brain Tumor Segmentation u sing K Means Clustering and Detection u sing Convolutional Neural Network
Authors:   Assistant Professor, Dept. of CSE, SRM Institute of Science and Technology, Chennai, India., M.* Prakash U. , Pandey Satyam ,   Dept. of CSE, SRM Institute of Science and Technology, Chennai, India., Kumari Khushbu ,   Dept. of CSE, SRM Institute of Science and Technology, Chennai, India., Sathishkumar P. ,   Assistant Professor, Dept. of CSE, SRM Institute of Science and Technology, Chennai, India.
Published: March 2020

This paper presents brain tumor detection and segmentation using image processing techniques. Convolutional neural networks can be applied for medical research in brain tumor analysis. The tumor in the MRI scans is segmented using the K-means clustering algorithm which is applied of every scan and the feed it to the convolutional neural network for training and testing. In our CNN we propose to use ReLU and Sigmoid activation functions to determine our end result. The training is done only using the CPU power and no GPU is used. The research is done in two phases, image processing and applying neural network.
Video Steganography using Sobel Edge Detection Technique
Authors:   Student, SRTM University, Nanded. Maharashtra, India, Deshmukh Dipika , Gajanan* Dr. Kurundkar ,   Assistant Professor, Department of Computer Science, Shri Guru Buddhiswami Mahavidyalaya, Dist. Parbhani, Maharashtra, India.
Published: March 2020

Video Steganography is a procedure of hiding the message into video in such a way that no one can detect its presence. In proposed research work used two algorithms namely random scan and edge detection for hiding the data into video. Five edge operators are used for edge detection of selected frames namely Sobel, Canny, Prewitt, Log, Robert.
Heart Disease Prediction using Machine Learning Techniques
Authors:   M Tech (Data Science) Department of CSE, GITAM University, Hdyerabad, India., Yaswanth* Raparthi , Riyazuddin Dr. Y. Md. ,   Assistant Professor, Department of CSE, GITAM University, Hdyerabad, India.
Published: March 2020

Recent advancement of technology allows the automation of things to be done using machine learning techniques. These machine learning techniques can also be used for detecting or predicting the heart disease in the early phase. The health care industry produces a huge amount of data which is in unstructured manner that cannot be understood by a machine. Due to development of modern technology, health care industries also managing the data in a structured manner which can be understood by machine learning technology. In this environment if we use machine learning algorithms for prediction of heart disease, then there is a chance to detect the heart disease status in the early phase and to alert patient to get a better treatment to cure that disease. This paper implements seven supervised learning algorithms which are KNN, Decision Tree, Naive Bayes, Logistic Regression, Random Forest, Support Vector Machine and Neural Networks for heart disease prediction. This paper generates algorithm performance metrics like Accuracy, Precision, Recall, F-score and ROC values for how the system was predicting accurately. In this paper among those seven algorithms, Neural Networks gave best accuracy as 92.30% and this system provides experimental results for how the model is accurate for heart disease prediction.
Rotary Inverted Pendulum Control using Fuzzy Logic Controller
Authors:   Department of Electrical and Electronics Engineering, National Engineering College, Tamil Nadu, India., Neelakandan T. , subash S. Samivel ,   Department of Electrical and Electronics Engineering, National Engineering College, Tamil Nadu, India., Shanthakumar S. ,   Department of Electrical and Electronics Engineering, National Engineering College, Tamil Nadu, India., Sudalaimani P. ,   Department of Electrical and Electronics Engineering, National Engineering College, Tamil Nadu, India., Muniraj* R. ,   Ph.D., Department of Electrical and Electronics Engineering, Anna University, Chennai, India.
Published: March 2020

In Modern world the technology is developing faster. The system uses different control theories and various technologies are updated faster. Now here control analysis of various pendulums especially cart pendulum, rotary (Futura) inverted pendulum in various techniques like fuzzy controller Using some soft computing techniques like fuzzy logic controller because now the machine learning will be going to overrule all the fields. The analysis of various sources and simulated it in MATLAB.
An Ingenious M ethodology for the Collation of Existing Algorithms for the Prognosis o f Student Performance
Authors:   PG Student Assistant Professor Department of Computer Science and IT, Amrita School of Arts And Sciences,Kochi Amrita Vishwa Vidyapeetham, India, B V* Arya , P B Amritha ,   PG Student Assistant Professor Department of Computer Science and IT, Amrita School of Arts And Sciences,Kochi Amrita Vishwa Vidyapeetham, India., Kumar C V Prasanna ,   PG Student Assistant Professor Department of Computer Science and IT, Amrita School of Arts And Sciences,Kochi Amrita Vishwa Vidyapeetham, India.
Published: March 2020

In this proposed research work we use a profound Data mining technique which is an automated procedure of discovering interesting patterns by means of comprehensible predictive models from large data sets by grouping them. Predicting a student's academic performance is very crucial especially for universities. Educational Data Mining (EDM) is an approach for extricating useful data that could possibly affect a firm. Nowadays student’s performance is swayed by a lot of aspects. These aspects might involve the academic performance of a student. This subject evaluates numerous factors probably suspected to alter a student’s empirical performance in scholastic, and discover a subjective design which classifies and forecast the student’s learning outcomes. The intention of this research is to conduct a case study on factors swayed by the student’s academic achievements and to dictate greater impact factors. In this paper we focus on the academic achievement evaluation on the basis of correct instances and incorrect instances by means of Naive Bayes and Random Forest algorithms. This paper intends to make a metaphorical assessment of Naive Bayes and random Forest classifier on student data and dictate the best algorithm.
Evolutionary Method o f Detecting Intrusions u sing Different Population Dynamics
Authors:   Department of Computer Science and Engineering, St Joseph Engineering College, Mangaluru, India., Guruprasad* Sunitha , G. L. Rio D’Souza ,   Department of Computer Science and Engineering, St Joseph Engineering College, Mangaluru, India.
Published: March 2020

Chaos theory plays a vital role in any evolutionary based algorithms for avoiding the local optima and to improve the convergence speed. Various researchers have used different methods to increase the detection rate and to speed up the convergence. Some researchers have used evolutionary algorithms for the same purpose and has proved that the application of those algorithms provide good results. Most of the researchers have used population sizes which remains constant throughout the evolution. It has been seen that small population size may result in premature convergence and large population size requires more computation time to find a solution. In this paper, a novel application of different population dynamics to the genetic programming (GP) algorithm has been applied to manage the population size. The main focus was to improve the accuracy of the normal GP algorithm by varying the population sizes at each generation. The experiments were conducted on the standard GP algorithm using static and dynamic population sizes. Different population dynamics has been used to check the effectiveness of the proposed algorithm. The results obtained has shown that dynamic population size gives better results compared to static population size and also solves the problem of local optima.
Similarity Check to Detect Text Data Plagiarism
Authors:   Assistant Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Educational Foundation, Guntur, (Andhra Pradesh), India., Bhavani* Dasari Durga , Komati Bhuvana ,   Student, Department of Computer Science and Engineering Bachelor of Technology, Koneru Lakshmiah Educational Foundation, Andhra Pradesh, India., Kattamuri Vyshnavi ,   Student, Department of Computer Science and Engineering Bachelor of Technology, Koneru Lakshmiah Educational Foundation, Andhra Pradesh, India., Sravani Jakkula ,   Student, Department of Computer Science and Engineering Bachelor of Technology, Koneru Lakshmiah Educational Foundation, Andhra Pradesh, India.
Published: March 2020

Picking the affirmed progression of the others works can be considered as shaped bowing which impacts all quarters of works from the get-togethers. Expanding accessibility and[12] straightforwardness of information is engaging the people to have legitimately clear zone to data, which is irritating the issues of consistency. With the rising basic for delineating the data as defiled or non-appropriated reliant on the volume of words that are to be taken[4] from the sources, it is fundamental that it will flop stupendously. Subordinate upon the region there are conditions where the closeness scores are either considered as copied or the non-tainted. While in certain area, any little copy is correspondingly to be treated as copyright encroachment, in unequivocal spaces there is degree for suggesting or underscoring the information sources. In a plan, it might be granted that there isn't regularly any liberal definition for even printed scholastic robbery which is reliably kind of a zone subordinate and the ones that are tangling the issue in principal way.[1],[3] The setting of the dispute considered above prompts focusing in this doctoral theory, towards. checking the substance information academic thievery utilizing reasonable assessment and cosine likeness in reports. making contemporary plan of answer for astute robbery obvious affirmation squashing the objectives investigated in before outline.
An Effective Model for Detection of Dysfunctionality in Heart Based on Iridology using Deep Neural Networks
Authors:   Associate Professor, Department of Information Technology M. V. G. R. College of Engineering, India., Palavalasa* Sreenivasa Rao , Bheemavarapu Pradeep Kumar ,   Student, Department of Information Technology M. V. G. R. College of Engineering, India., Jain Siri Sahasra ,   Student, Department of Information Technology M. V. G. R. College of Engineering, India, Piriya Sai Sree ,   Student, Department of Information Technology M. V. G. R. College of Engineering, India., Tadiparthi Pavan Kumar ,   Associate Professor, Department of Information Technology M. V. G. R. College of Engineering, India.
Published: March 2020

In today’s world heart disease is the primary reason for deaths. WHO has anticipated that 12 million people die every year because of heart diseases. Every organ of the body is represented in the iris in a well-defined manner. The Iris is a micro-structure of the entire body. The abnormality of the heart can be detected using Iridology science. In this article, we examine the heart dysfunctionality through a chain of steps which are localization of iris, segmentation of iris, ROI extraction, histogram equalization of ROI and classification using deep convolutional neural network. The results are assessed based on various standards such as precision, recall, f-score & accuracy.
An Efficient Perspective of Neuro Fuzzy on Fog Net work for Latency Driven View Point
Authors:   Assistant professor of Information technology in SRM IST, Chennai, Tamil Nadu, India., Bama* B Sathya , Nishant  ,   Department of Information Technology, SRM IST, Chennai, Tamil Nadu,India, Kumari Rishu ,   Department of Information Technology,SRM IST,Chennai,Tamil Nadu,India., Diwan Shreyash Dhar ,   Department of Information Technology,SRM IST,Chennai,Tamil Nadu,India.
Published: March 2020

In the present milieu, changes in guidelines and the opening of intensity markets have showed as enormous measure of intensity move across transmission lines with visit changes in stacking conditions dependent on advertise cost. Since ordinary separation transfers may consider power swing as a shortcoming, stumbling in view of such breaking down would prompt genuine ramifications for power framework strength. A recurrence area approach for advanced handing-off of transmission line flaws relieving the unfriendly impacts of intensity swing on customary separation handing-off is introduced. A wavelet-neuro-fluffy consolidated methodology for deficiency area is likewise exhibited. It is not the same as customary calculations that depend on deterministic calculations on a well-characterized model for transmission line security. The wavelet change catches the dynamic qualities of flaw signals utilizing wavelet multi goals examination coefficients. The fluffy surmising framework and the versatile neuro fluffy derivation frameworkare both used to extricate significant highlights from wavelet MRA coefficients and in this manner to arrive at resolutions with respect to blame location.The results contained here approve the prevalence of the methodology over the for deficiency area.