bluuebunny/crossref_metadata_2025 huggingface dataset:
Uma proposta interdisciplinar para o desenvolvimento de aplicativos de matemática financeira em um curso de graduação em Engenharia Elétrica
Authors: Elias Ana Paula de Andrade Janz , Motta Marcelo Souza , Hussein Fabiana Roberta Gonçalves e Silva
Published: August 2019

Resumo: Este artigo tem como objetivo apresentar uma proposta de trabalho interdisciplinar entre as disciplinas de Programação de Computadores e Matemática Financeira em um curso de graduação em Engenharia Elétrica. A ferramenta utilizada foi o software App Inventor. Inicialmente, no percurso metodológico, a Matemática Financeira foi trabalhada de forma “tradicional” para, posteriormente, apresentarmos a possibilidade de programar aplicativos financeiros para o cálculo de Juros simples e Compostos. Os estudantes responderam a dois questionários. Apresentaremos aqui como se deu a aceitação dos estudantes em relação a proposta de trabalho interdisciplinar, bem como a análise de suas respostas aos questionários propostos. Fica evidenciado que a integração das disciplinas teve grande influência no processo de construção do conhecimento de Matemática Financeira.Palavras chave: Interdisciplinaridade. Matemática Financeira. Programação. App Inventor. AN INTERDISCIPLINARY PROPOSAL FOR THE DEVELOPMENT OF FINANCIAL MATHEMATICS APPLICATIONS IN ELECTRICAL ENGINEERING UNDERGRADUATION COURSEAbstract: This article aims to present a proposal of interdisciplinary work between the disciplines of Computer Programming and Financial Mathematics in an Electrical Engineering undergraduate course. The digital tool used was App Inventor software. In the methodological course, initially, "Financial Mathematics" was worked in a "traditional" way to later present the possibility of programming financial applications for the calculation of simple and compound interest. The students answered two questionnaires. We present here how students were accepted in relation to the interdisciplinary work proposal, as well as the analysis of their answers to the questionnaires proposed. It is evidenced that the integration of the disciplines had great influence in the process of construction of the knowledge of Financial Mathematics.Keywords: Interdisciplinarity. Financial Mathematics. Programming. App Inventor.
Do start ao game over: analisando narrativas de aprendizagem de inglês com jogos eletrônicos
Authors: Santos Keila Mendes , Araújo Costa Cleide Jane De Sá
Published: August 2019

Resumo: Este estudo objetiva investigar o processo de aprendizagem de estudantes de língua inglesa (LI), que assumem terem aprendido o idioma por meio da prática de jogos eletrônicos, especificamente os chamados jogos MMORPG, e também destacar as estratégias adotadaspelos aprendizes ao longo do referido processo. Trata-se de uma pesquisa qualitativa que teve como participantes três estudantes de letras/inglês, gamers. Para coletar os dados foram utilizadas narrativas de aprendizagem nas quais os aprendizes relataram seu processo de construção do conhecimento em LI, partindo do contato com os jogos. A pesquisa teve por fundamento o seguinte questionamento: De que forma a prática de games do gênero MMORPG auxiliam no processo de aprendizagem da língua inglesa? Os resultados demonstraram que esses jogos podem ser percebidos como recursos significativos no desenvolvimento de habilidades distintas, ampliando, também, o conhecimento vocabular, além de proporcionar atitudes autônomas, considerando as estratégias de aprendizagem adotadas pelos gamers.Palavras chave: Língua inglesa. Jogos eletrônicos. Narrativas de aprendizagem.  FROM START TO GAME OVER: ANALYSING ENGLISH LEARNING NARRATIVES WITH ELECTRONIC GAMES. Abstract: This study aims to investigate the learning process of english language (EL) students, who assume that they have learned the language through the practice of electronic games, specifically the so-called MMORPG games, and also highlight the strategies adopted by learners throughout this process. This is a qualitative research that had as participants  three students of letters/english, gamers. To collect the data, learning narratives were used in which the learners reported their process of knowledge construction in EL, starting from the contact with the games. The research was based on the following question: How can MMORPG games help in the English language learning process? The results showed that these games can be perceived as significant resources in the development of different abilities, also improving vocabulary knowledge, besides providing autonomous attitudes, considering the learning strategies adopted by the gamers.Keywords: English language. Electronic games. Learning narratives.
A trajetória do movimento social pelo reconhecimento da cidadania LGBT
Authors: Gomes José Cleudo , Zenaide Maria de Nazaré Tavares
Published: August 2019

Resumo: Este trabalho retoma um dos temas tratados em pesquisa de mestrado, que buscou analisar as ações implementadas pelo então Programa Brasil sem Homofobia do Governo Federal, a partir da sua transversalidade com as políticas públicas e das interfaces com o movimento de Lésbicas, Gays, Bissexuais, Travestis e Transexuais (LGBT) em nível local. Dessa maneira, o objetivo deste artigo é refletir a noção de cidadania, a partir da história do movimento social LGBT, recorrendo aos seguintes referenciais teóricos: Marshall (1976); Dagnino (1994); Benevides (1996); Cortina (2005); Gohn (1997). Trata-se, portanto, de uma pesquisa bibliográfica, na qual foi realizada uma revisão de literatura de cunho exploratório e com abordagem qualitativa, em que evidenciamos a trajetória do Movimento LGBT, em nível internacional, nacional e local, enfatizando o seu surgimento e a sua luta pelo reconhecimento da cidadania de LGBT, a partir de obras científicas e escritos da própria militância, tais como Green (2003); Facchini (2005); MacRae (2011); Reis (2012); Vieira, L. (2015). Como resultados, apontamos as conquistas do movimento LGBT no contexto democrático a partir das dimensões política, civil, econômica e social como parte da trajetória e reconhecimento da luta social e cidadania LGBT.Palavras-chave: Movimento Social. Cidadania. História do Movimento LGBT. THE TRAJECTORY OF SOCIAL MOVEMENT FOR THE RECOGNITION OF LGBT CITIZENSHIPAbstract: This paper summarizes one of the themes addressed in a master's research thesis, which sought to analyze the actions implemented by the Brazilian Program without Homophobia of the Federal Government, from its transversality with public policies and interfaces with the movement for Lesbian, Gay, Bisexual, Transgender and Transgender (LGBT) at A local level. In this way, the objective of this article is to reflect the notion of citizenship, starting from the history of the LGBT social movement, using the following theoretical references: Marshall (1976); Dagnino (1994); Benevides (1996); Cortina (2005); Gohn (1997). It is, therefore, a bibliographical research, in which an exploratory literature review was carried out based on a qualitative approach, where we highlight the trajectory of the LGBT Movement, contemplating international, national and local levels, emphasizing its emergence and its struggle for the recognition of the citizenship of LGBT, from scientific works and writings of their own militancy, such as Green (2003); Facchini (2005); MacRae (2011); Reis (2012); Vieira, L. (2015). As a result, we point out the achievements of the LGBT movement in the democratic context from the political, civil, economic and social dimensions as part of the trajectory and recognition of the social struggle and LGBT citizenship.Keywords: Social movement. Citizenship. History of the LGBT Movement.
Central Monitor Based On Personal Computer Using Single Wireless Receiver
Authors: Fanani Ahmad , Irianto Bambang Guruh , Pudji Andjar
Published: August 2019

Central monitor is a tool that monitors the patient's condition with several devices into one display on a personal computer (PC). Pulse Oxymetri serves to monitor the state of oxygen saturation in the patient's blood without going through blood gas analysis. This tool uses a wireless delivery system, HC-11 that can transmit data as far as 10 meters without obstruction. This tool uses a finger sensor, an analog signal conditioner and a microcontroller that is processed to produce a percentage value of SpO2 which is then sent through HC-11. The workings of this tool are very simple by entering the finger sensor on the finger and then it will be detected by the finger sensor that will be displayed on the PC. Digital data from the ADC Atmega is received by the personal computer (PC) via Bluetooth HC-011. Furthermore, the data is processed with the Delphi program and displayed on the monitor. Appears on the Delphi application. After measurement, get an error in the SpO2 parameter, the biggest error is 1.02% and get the smallest error 0.8%.
Advanced Deep Learning Framework for Stock Value Prediction
Authors:   PhD Scholar Biju Patanaik University of Technology, Rourkela, Odisha, India., Das Sumanjit , Mishra Sarojananda ,   Dept. of Computer Science and Engineering Indira Gandhi Institute of Technology, Saranga, Odisha, India
Published: August 2019

The main attractive feature to stock market is speedy growth of stock economic value in short yoke of time. The investor analyses the demonstration, estimated value and growth of organizations before investing money in market. The analysis may not be enough by using conventional process or some available methods suggested by different researches. In present days large number of stocks are available in market it is very difficult to study each stock by help of very few suggested foretelling methods. To know the anticipated stock value we need some advanced prediction technology for stock market. This paper introduce an advanced skillful method to plan and analyze the different organizers stock execution in market and prognosticate best suitable stock by predicting close price of stock. The projected arrangement is based on multilayer deep learning neural Network optimized by Adam optimizer. Recent 6 years (2010-2016) data of different organizations are applied to the model to demonstrate the skillfulness of the projected proficient method. From result it has been ascertained that the projected framework is best suited to all different data set of various sectors. The prediction error is very minimal as visible from outcome graph of framework.
An Efficient Technique to Remove Gaussian Noise and Improve the Quality of Magnetic Resonance Image
Authors:   Department of EEE, Malla Reddy Engineering College (A), Maisammagauda, Hyderabad, India., Rajeswaran N. , Lawrence T.Samraj ,   Department of CSE, Francis Xavier Engineering College (A), Tirunelveli, India., Ramkumar P. ,   Department of CSE, Malla Reddy Engineering College(A),Maisammaguda,Hyderabad,India., Thangadurai N. ,   School of Engineering and Technology,,Jain University, Bangalore,India
Published: August 2019

Medical Resonance Imaging (MRI) is very useful in different medical applications for diagnosis the diseases in human body. But the main problem arising in MRI images is presence of various noises. These noises are affecting the originality of the MRI images and producing erroneous results. Here Brain MRI images are used for analysis of noise. Brain images are fractal in nature and especially those images are affected by various noises. In this paper we discussed about the Gaussian noise in brain MRI image. The effect of this noise is reduced by wavelet based thresholding techniques. They are namely Visu shrink, SURE shrink and Bayes shrink. These three methods are applied to the brain MRI images and obtained results are compared by PSNR(Peak signal to Noise ratio), MSE(Mean Square Error),Absolute error, Fractal dimension, IEF(Image Enhancement Factor),Normalized cross correlation and structural content.
An Empirical Analysis on Information Technology Adaptation in Nationalized and Private Sector Banks
Authors:   is an Adjunct faculty at Prestige Institute of Management Research ,Indore and Research Scholar at Medi-Caps University., Tuteja Mrs Simrat , Hyde Dr. Anukool Manish ,   Ph.D., M.P.A. & L.W., PGDPM, B.Sc. Professor and Head : HR and General Management, Somani Dr. Rashmi ,   Associative Professor and Research Guide at Medi-Caps University, Department of Management Studies Indore.
Published: August 2019

Information technology adaptation in banking system is essential for facing challenges with competitors, smooth running and to meet requirement of the target customers by providing them best and fast services expected by them. Hence the objective of present research is to compare the adaptation of information technology in Nationalized and Private sector banks. This paper assesses the use of Information Technology and its services in Nationalized and Private banks. The present study was conducted in Nationalized and Private sector banks of Indore (M.P) division. While selecting the bank branch, care was taken to check whether that bank is using Information Technology for providing services to customers. The study shows that there is no major difference in level of Information Technology Adaptation, but Nationalized banks does not provide proper technical assistance and training programs as compared to Private banks. Data was collected from 298 employees of Nationalized and Private Banks from Indore division. T-test was used for data analysis.
A Backward Single Source Shortest Path Algorithm For Directed Graph
Authors:   Ph.D Research Scholar, Research and Development Centre, Bharathiar University, Coimbatore, Tamilnadu, India., Priskilla D. Jasmine , Arulanandam Dr. K. ,   Head, Department of Computer Applications, GTM College, Gudiyattam, Tamilnadu, India.
Published: August 2019

A new directed backward variant of the Single Source Shortest Path algorithm was described in this paper. This algorithm accept that approaching adjacency list of the given graph vertex loads showed up in expanding request. The running time of forward, based strategy algorithm is the best aftereffect of O (n), which are the most ideal forward-backward SSSP consequences of Wilson et al. Moreover, the likelihood of the new algorithm additionally requires O (n) time.This is an equally improved version of exponentially and polynomial small probability derived by Wilson et al.
Bio Oil from Bio Waste (Mahua Oil Cake) Using Fast Pyrolysis Process
Authors:   Assistant Professor, Department of Mechanical Engineering, Annamalai University, Tamil Nadu India., Sukumar V. , Senthilkumar R. ,   Assistant Professor, Department of Mechanical Engineering, Annamalai University, Tamil Nadu India., Manieniyan V. ,   Assistant Professor, Department of Mechanical Engineering, Annamalai University, Tamil Nadu India.
Published: August 2019

Biomass is a renewable resource utilized to produce bio fuel from bio waste. In this experiment, fixed bed fast pyrolysis is carried out on a model of mahua oil cake (MOC dimension) to conclude predominantly the consequences of pyrolysis temperature, MOC dimension and nitrogen gas flow rate from the pyrolysis yields. The temperature, MOC dimension and nitrogen gas flow rate were varied between 500 to 600 oC, 2 mm to 6 mm and 0.2 to 0.4 liter per min (lpm). The utmost oil yield of 25.90 wt % was attained for a nitrogen gas flow rate of 0.3 lpm, particle size of 4 mm and pyrolysis temperature of 550oC. The pyrolysis oil had a calorific value of 28180 KJ/kg. The pyrolysis gas may well be utilized as a gaseous fuel. In addition, the bio-oil was illustrated by elemental, gas chromatography/mass spectrometry (GC-MS) analyzer.
Automatic Vowel Recognition from Assamese Spoken words
Authors:   Department of Information Technology, Gauhati University Guwahati, India., Sarma P , Mitra S ,   Department of Information Technology, Gauhati University Guwahati, India., Bhuyan M P ,   Department of Information Technology, Gauhati University Guwahati, India., Deka V ,   Department of Information Technology, Gauhati University Guwahati, India., Sarmah S ,   Department of Information Technology, Gauhati University Guwahati, India., Sarma S K ,   Department of Information Technology, Gauhati University Guwahati, India.
Published: August 2019

Vowel plays the most important role in any speech processing work. In this research work, recognition of Assamese vowel from spoken Assamese words is explored. Assamese is a language which is spoken by major people in Brahmaputra Valley of Assam, Assam is a state which is situated in the North-East part of India. This automatic vowel recognition system is implemented by using three efficient techniques Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Random Forest (RF) classifier. The database used in the experiments is specially designed for this purpose. A list of phonetically vowel rich Assamese words is prepared for the experiment. As an initial effort, twenty different (20) words uttered by fifty-five (55) speakers are taken. Utterances from both male and female speakers are collected. Each utterance was repeated two times by every speaker. A database of the total of 2200 samples is prepared. After experimenting on different samples it is seen that Random Forest (RF) is giving the best performance compared to the other two classifiers. The performance of the system is shown with testing dataset and comparison is done. Outcome of this research work will enhance the Machine Translation from Assamese to any other language.
A Heterogeneous and Optimized System for Trainers for Analysis and Rectification of Compilation Errors
Authors:   Assistant Professor, Department of Information Technology, College of Computer Sciences and Information Technology College, Majmaah University, Al- Majmaah 11952, Saudi Arabia,, Almutairi Badr , Almotairi Sultan ,   Assistant Professor, Department of Natural and Applied Sciences, Community College, Majmaah University, Al- Majmaah 11952, Saudi Arabia
Published: August 2019

In the computing world where information is being gathered and analyzed it’s important for programmers to convert raw data into meaningful information and this can only be achieved through programming. The art of programming is not easy as many programming languages are present in the current programming world. The first programming course for any new programmer is always difficult. New programmers always try to copy the code provided by their instructors and after compiling the program, gets the number of errors which they are not able to solve. In this paper, we present a solution which helps the instructors and the programmers to know about student’s capacity of coding. This system provides a top few errors with their solutions. The programmers and the evaluators can also use the system to optimize the program which the students and the other stakeholders are using. As this system alerts the programmers and the other stakeholder about the compilation errors which occur and thus providing instant help for rectifications of the code when needed.
Implementation of Low density Parity Check system using Probabilistic Gradient Descent Bit Flipping Decoder
Authors:   Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India., Varri Venkateswara Rao , Vignesh N. Arun ,   Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India., Panigrahy Asisa Kumar ,   Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad , India., Kumari C H Usha ,   Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India.
Published: August 2019

This paper represents the concept of hard decision decoder in which PGDBF is suitable decoder for the basic model of hard-choice decoder as long as low-density parity check code (LDPC) which is increase the error correction. This design introduced dynamic architecture which reduce the capability of random disarrangement of the PGDBF. The design is working on the Short Random Sequence (SRS) that is replica cover on the PGDBF decoding guidelines. In each iteration flipping number of bits these are focusing on improvement in performance and decoding delay. The best SRS is essential to manage the well-known decoding achievement of PGDBF, we introduced two kind of access with same hardware categories, but various LDPC codes are perform different behaviors. In this design we are modifying small hardware decoding unit for obtaining a good decoding explanation for present and further purpose.
Personality Traits and Risk Tolerance among Young Investors
Authors:   Associate Professor- Management, Prestige Institute of Management, Gwalior, India., Mathur Dr. Garima , Nathani Dr. Navita ,   HOD, Management Dept., Prestige Institute of Management, Gwalior, , India.
Published: August 2019

India is a developing nation with highest number of youths in world. The youth is growing in the era of internet, least fare Wi-Fi connections. They have ample of knowledge available at one click. For any decision they search multiple options which give them sense that they are opting for the best and will reduce the chances of setbacks. Although every individual vary in their risk taking capacity and the capacity to tolerate setbacks is mostly related to kind of personality characteristics an individual carry. Present study is an attempt to identify the kind of relationship between personality types in (BIG Five model) and risk tolerance among youth. There are five personality traits measured through BIG Five namely; Extraversion, Agreeableness, Conscientiousness, Neuroticism (Emotional Instability) and Openness to Experience. The study intended to ask whether these personality types play an important role in deciding tolerance behavior among young investors. The data was collected on a five point scale for all five personality traits. Each trait was evaluated through five statements on a scale developed by Mayfield, Perdue & Wooten (2008) modified by Wong, Chuah, Kui, Soo & Ang (2016). There were 25 statements in totality for measuring personality traits. The data was collected for risk tolerance, inclusive of eight items developed by Grable and Lytton (1999). There were 102 respondents from whom data was collected. The sampling respondents were in the age range of 22 to 27 years, who either have just started earning or having less than 5 years of total earning tenure. These investors are considered a bit selective but high in risk tolerance. We also intend to find out the kind of relationship between variables. Results indicated that Agreeableness, Neuroticism and Openness were strongly correlated to risk tolerance, but there was no significant relationship of extraversion and conscientiousness with risk tolerance. Furthermore, risk tolerance was checked on the basis of gender. The results indicated that there was no difference in risk tolerance of male and female investors unlikely suggested by Mishra, Lalumiere & William (2011) who stated that risk propensity varies from male to female.
Supervised Machine Learning for Training a Neural Network as 5:2 Compressor
Authors:   research scholar in KL Deemed to be University, Vijayawada,AndhraPradesh,India, Maddisetti Lavanya , Maddisetti Lavanya ,   Assistant Professor in Department of ECE, Vardhaman College of Engineering., Senapati Ranjan K. ,   with KL Deemed to be University. He is a professor in the Department of Electronics and Communications Engineering, JVR Ravindra ,   with the Center for Advanced Computing Research Laboratory (C-ACRL), Department of Electronics and Communications Engineering, Vardhaman College of Engineering, Shamshabad, Telangana
Published: August 2019

Machine Learning has achieved substantial development in numerous applications like image processing, pattern recognition, approximate computing etc. This paper interlinks supervised machine learning algorithm and VLSI architectures to train a neural network as exact and approximate 5:2 compressors. Probabilistic pruning type of approximation technique has been employed on the exact 5:2 compressor. This approximation technique on compressors reduces the power consumption with variation in the outputs without affecting the error limit. The simulation of 5:2 compressors and training of neural network using machine learning algorithm has been done using Spectre simulator of Cadence Design Systems at 45nm CMOS technology node and Keras library with TensorFlow background respectively.
Citrus Classification and Grading Using Machine Learning Algorithms
Authors:   Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, D Sugumar , V Harshavarthan ,   Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, S Kavisri ,   Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, M.S Aezhisai Vallavi ,   Department of Mech, Government College of Technology-Coimbatore, P.T Vanathi ,   Department of ECE, PSG College of Technology, Coimbatore
Published: August 2019

Sorting of fruit into different grade is essential to fetch high price in the market. The fruits are graded based on height, size, area and weight. Each and every fruit changes the skin’s color in their life span. Hence, it is appropriate to grade them by processing color images of them and then applying estimation or recognition techniques on those images. Citrus (plant) grows even in temperature lands and it does not penetrate its root too deep. It is a precious commodity and used for various day to day activities. In this paper, Machine vision technique is used to sort citrus based on variety and quality. Primarily, the image is captured by a camera, placed at a particular distance. Then captured citrus image is classified into different categories, based on their color, size and quality. During the processing, the attributes are determined based on their defects in the surface of the citrus. Finally, the quality and breed are determined based on the three-color planes of color image and gray scale image respectively.
Machinability Optimization of Abrasive Water Jet Cutting Process on AA6082 Aluminium Alloy
Authors:   Assistant Professor, Department of Mechanical Engineering, Easwari Engineering College, Ramapuram, Chennai, India., Joel C. , Jeyapoovan Dr.T. ,   Professor, Department of Mechanical Engineering, Hindustan Institute of Technology and Science, Chennai, India.
Published: August 2019

Aluminium alloys are extensively used nowadays in various manufacturing industries due to its special properties and high strength. In this study, AA6082 aluminium alloy is taken into consideration by studying the machinability properties using the abrasive water jet cutting process. RSM technique is used for conducting the experiments by varying the input factors such as stand-off distance, abrasive feed and nozzle transverse speed. The effect of hardness and surface roughness is investigated. The correlation between the input parameters and the corresponding output was tested by analysis of variance to check the 95% confidence level.
Prediction of Vertical Handover Using Multivariate Regression Model
Authors:   Electronics Engineering, Fr. Conceicao Rodrigues College of Engineering, Bandra-West Mumbai,, Goutam Siddharth , Unnikrishnan Dr. Srija ,   Principal, Fr. Conceicao Rodrigues College of Engineering, Bandra-West Mumbai, India., Prabavathy Sundary ,   Associate Professor Mathematics,Fr. Conceicao Rodrigues College of Engineering, Bandra-West Mumbai, India, Kudu Neel ,   B.E Computer Engineering,
Published: August 2019

Choosing the best performing network among the pool of available networks is a challenge faced by every mobile user. This paper majorly focuses on the development of a system that can ease the above task based on available parameters like Received Signal Strength, Bandwidth, Cost, Network Coverage, Jitter, Packet Loss, Latency etc. The system uses Multivariate Regression Model to help select the best network with the help of a mobile application. The algorithm assigns a Handover value to each available network among the pool of available networks and makes a comparative study to facilitate the decision of the best performing network. The system can also be used by service providers to optimise their network performance by studying the effect of change in the network parameters. Another possible application can be to check the Handover feasibility of future technology networks. The paper also tries to focus on the giving insights on the influence each network parameter mentioned above has on the final value of Handover by using statistical methods and ANOVA.
Development of Prediction Models for the Dengue Survivability Prediction: An Integration of Data Mining and Decision Support System
Authors:   College of Computing Studies, and Information and Communication Technology, Isabela State University Cabagan, Philippines., Guiyab Rosalinda B.
Published: August 2019

Dengue is a viral disease that has been feared by people globally. Due to its rapid prevalence and increasing threat, this study explored on the use of data mining techniques together with decision support system to develop prediction models of dengue survivability. This study was focused on three important points namely: identify significant predictor attributes to dengue survivability prediction, development of a rule-based and decision tree models for dengue survivability prediction, and the development of a dengue survivability platform for prediction purposes. The developed rule-based and decision tree models were compared according to accuracy and they underwent the 10-fold cross validation procedure and were integrated in the system to provide a platform to predict the survivability of a patient given the input medical data using a client-server configuration via the Internet. The result of the prediction for the dengue survivability may be used as an intervention by medical practitioners in the general management of dengue cases.
Multi Modal Hybrid Image Fusion using Discrete Wavelet and Contourlet Transform
Authors:   Dept. ECE, GMIT, Davanagere, India, B M Dr. Latha , B K Manjula ,   Dept. ECE, GMIT, Davanagere, India, Sumana CH Venkata ,   Dept. ECE, GMIT, Davanagere, India
Published: August 2019

Image fusion is used to enhance the quality of images by combining two images of same scene obtained from single or multiple modalities. In medical diagnosis different types of imaging modalities such as X-ray, Computed tomography (CT), Magnetic resonance imaging (MRI), Magnetic resonance angiography (MRA), PET scan etc., provide limited information where some information is common and some unique. This paper presents a hybrid combination of Discrete Wavelet and Contourlet. For the obtained fused images, it is proposed to compute performance metrics like Entropy, Peak signal to noise ratio and Mean square error and compare them with existing methods as to come out with best combination of transformations that yield highly informative fused image. Proposed method will be simulated using MATLAB tool.
Influence of Leadership on Creativity In Business Academics/ Higher Education
Authors:   Research Scholar, School of Management, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India., Brahma Sanghamitra
Published: August 2019

Business academics/ higher education and training must continuously strive to cope up with the evolving demands of the corporate world. Proactive approach towards adaptability to the environmental changes may be mastered through creative leadership and mentoring of the academic institutes. It has been found that few research studies have focused on the cases of influence of leadership on creativity in higher education. This study addresses the challenges faced in the sector of business academics/higher education and empirically explores how leadership influences creativity among the academics to enable more advanced and appropriate education and training in management or business education sector/ higher education, in the mid-tier institutes, in particular. A qualitative, case research approach has been used to understand the relationship between leadership style and academic creativity and its role in enhancing the effectiveness of business academics/ higher education. The findings of the study have established a positive influence of creative leadership on the effectiveness of business academics/ higher education. It has led to the identification of three critical aspects that are essential for inducing creativity in business academics/ higher education, i.e., appropriate leadership style, organization structure that balances between hierarchy and heterarchy to facilitate communication, and creative interaction leading to learning and growth.
Applying and Evaluating Supervised Learning Classification Techniques to Detect Attacks on Web Applications
Authors:   Department of Cybersecurity Systems and Networks, Center for Cybersecurity Systems and Network, Amritapuri, India., Manish Madduri Venkata Sai Soma , Megalingam Dr. Rajesh Kannan ,   Department of Electronics and Communication, Amrita Vishwa Vidyapeetham, Amritapuri, India.
Published: August 2019

Web applications are the source of information such as usernames, passwords, personally identifiable information, etc., they act as platforms of knowledge, resource sharing, digital transactions, digital ledgers, etc., and have been a target for attackers. In recent years reports say that there is a spike in the attacks on web applications, especially attacks like SQL injection and Cross Site Scripting have grown in drastic numbers due to discovery of new vulnerabilities. The attacks on web applications still persist due to the nature of attack payloads, as these payloads are highly heterogeneous and look very similar to regular text even web applications with many security features in place may fail to detect these malicious payload strings. To overcome this problem there are various methods described one such method is utilizing machine learning models to detect malicious strings by classifying the input strings given to the web applications. This paper describes the study of six binary classification methods Logistic regression, Naïve Bayes, SGD, ADABoost, Random Forrest, Decision trees using our own dataset and feature set.
Privacy Preserving Outsourced Calculations With Symmetric Fully Homomorphic Encryption
Authors:   Research and Development Centre, Bharathiar University, Coimbatore, Tamilnadu, India,, Umadevi C.N. , Gopalan N.P. ,   Department of Computer Applications, National Institute of Technology, Trichy, Tamilnadu,, India,
Published: August 2019

Cloud computing is a new paradigm which provides cloud storage service to manage, maintain and back up private data remotely. For privacy concerns the data is kept encrypted and made available to users on demand through cloud service provider over the internet. The legacy encryption techniques rely on sharing of keys, so service providers and end users of the cloud have exclusive rights on the data thus the secrecy may loss. Homomorphic Encryption is a significant encryption technique which allows users to perform limited arithmetic on the enciphered data without loss of privacy and security. This paper addresses a new simple and non-bootstrappable Fully Homomorphic Encryption Scheme based on matrices as symmetric keys with access control.
Advanced Energy Management System For Hybrid Vehicle
Authors:   Professor & PG Co-ordinator, Department of EEE, UKF College of Engineering and Technology, Kollam, India., Stephen S Ben John
Published: August 2019

The battery and ultra-capacitor hybrid storage system (HESS) is a system which can be adopted in the EV. By utilizing Ultra-capacitors, the batteries can be protected from high peak currents, which can be especially harming to the batteries. Consequently it is conceivable to expand the battery life. Battery and ultra-capacitor are connected through a bidirectional non-isolated multi input converter which has numerous points of interest. Fuzzy logic based energy management strategy is an efficient method to manage energy through HESS and furthermore regulating the SoC of ultra-capacitor while smoothing the battery power profile.
Influence of Parameters Reinforced Concrete Floor to Stiffness of Beam – Columns Connector in Composite Structures
Authors:   Hanoi Architectural University, 100000 Ha noi, Vietnam, Nguyen Hong Son , Tran Van Quan ,   University of Transport Technology, 100000 Hanoi, Vietnam, Nguyen Quang Hung ,   Thuyloi University, Hanoi, Vietnam.
Published: August 2019

In this paper, the author introduces the beam – column connections, steel – concrete composite beams and floor element in the frame structures, and shows how to determine the stiffness connections of the typical beam - column according to European standards. Survey parameters affecting, including: slab thickness; section area and module elasticity of reinforcing bars; distance anchor, in order to clarify the influence of the parameters on the stiffness of the connections beam - column in composite steel – concrete structures.
Automatic Speaker Identification by Voice Based on Vector Quantization Method
Authors:   Scientific and Innovation Center of Information and Communication Technologies at TUIT named after Al-Kharezmi, Tashkent, Uzbekistan,, Narzillo Mamatov , Abdurashid Samijonov ,   Bauman Moscow State Technical University, Russia Federation, Parakhat Nurimov ,   Scientific and Innovation Center of Information and Communication Technologies at TUIT named after Al-Kharezmi, Tashkent, Uzbekistan, Nilufar Niyozmatova ,   Scientific and Innovation Center of Information and Communication Technologies at TUIT named after Al-Kharezmi, Tashkent, Uzbekistan
Published: August 2019

In this paper, the systems of speaker identification of a text-dependent and independent nature were considered. Feature extraction was performed using chalk-frequency cepstral coefficients (MFCC). The vector quantization method for the automatic identification of a person by voice has been investigated. Using the extracted features, the code book from each speaker was built by clustering the feature vectors. Speakers were modeled using vector quantization (VQ). Using the extracted features, the code book from each speaker was built by clustering the feature vectors. Codebooks of all announcers were collected in the database. From the results, it can be said that vector quantization using cepstral features produces good results for creating a voice recognition system.
Object-Based and Rule-Based Classification of Synthetic Aperture Radar Images
Authors:   Department of Computer Science and Engineering, National Institute of Technical Teachers Training and Research, Chandigarh, India., Rastogi Aishwarya , Doegar Amit ,   Department of Computer Science and Engineering, National Institute of Technical Teachers Training and Research, Chandigarh, India.
Published: August 2019

Since thousands of years, the land is the basic and very important requirement for humans to survive and grow. The surface area of the earth provided by nature contains many different geographical locations divided into oceans, mountains, rivers, barren land, fertile land, ice caps and many more. The huge land masses and water bodies need to be observed and analyzed for optimum utilization of resources. Remote sensing is the best possible way to observe the earth's surface from a distance through different satellites and sensors. But most of the satellite images are not clear up to the extent to classify different terrain features accurately. Hence classification of image is needed to observe different terrain features in original images. In this study, the aim is to propose a branch of natural computation for SAR image classification into different terrain features with better information retrieval and accuracy measures as compared to traditional methods for satellite image classification. The object-based analysis has been used to extract spectral reflectance of five texture measures namely urban, rocky, vegetation, water and barren to generate training set. Minimum distance to mean classifier has been used with one of the Nature Inspired computation technique i.e. bacterial foraging optimization algorithm for the satellite image classification, to extract the more accurate information about land area of Alwar district, Rajasthan, India. In the proposed study a high-quality thematic map has been generated with the 7-band multi-spectral, medium-resolution satellite images. This approach provides the greater speed and accuracy in its computation with 97.43% overall accuracy (OA) and 0.96 Kappa co-efficient.
Distributed Architecture for Secure, Attack-Resilient Crypto Currency Transactions for the Classified Temporal and Text Data
Authors:   CSE, Vignan’s Institute of Information Technology,, Narasimham Challa
Published: August 2019

In the digital world, the crypto currency has to do with the use of tokens based on the distributed ledger technology in a secure manner. Crypto currency can be a resource on a block chain network or can be seen as a tool to perform the transactions ensuring the privacy and security. Data may be available in temporal or text format. This paper describes about the distributed architecture for secure and attack-resilient bit coin-based crypto currency transactions for classified temporal and text data. The temporal data may be voice, sound or graphical information basing on the time series. If the data available is temporal this work describes about how it can be classified into a processed form. In this context, this paper describes the process of converting temporal data into text data. Further, the paper describes about the process of ensuring the security. This paper describes about the methodologies of cryptography-based hashing, attack-resilient nonce generation and verifiable encryption techniques for the construction of resilient transactions against stealthy data-integrity attack.
Network Data Classification through Artificial Neural Networks and GenClust++ Algorithm
Authors:   LASTIMI Laboratory, Superior School of Technologies of Sale, Mohammadia School of engineering, Mohamed V University city of Rabat, Morocco, lafram Ichrak , El idrissi Siham ,   LASTIMI Laboratory, Superior School of Technologies of Sale, Mohammadia School of engineering, Mohamed V University city of Rabat, Morocco., Marrhich Aicha ,   LASTIMI Laboratory, Superior School of Technologies of Sale, Mohammadia School of engineering, Mohamed V University city of Rabat, Morocco., Berbiche Naoual ,   LASTIMI Laboratory, Superior School of Technologies of Sale, Mohammadia School of engineering, Mohamed V University city of Rabat, Morocco., EL Alami Jamila ,   LASTIMI Laboratory, Superior School of Technologies of Sale, Mohammadia School of engineering, Mohamed V University city of Rabat, Morocco.
Published: August 2019

Information systems are becoming more and more complex and closely linked due to the exponential use of internet applications. These systems are encountering an enormous amount of traffic, this traffic can be a normal one destined for natural use or it may be a malicious one intended to violate the security of the system. Therefore, a defense method needs to be in place. One of the commonly used tools for network security is the Intrusion Detection System (IDS). An IDS, while ensuring real - time connectivity, tries to identify fraudulent activity using predetermined signatures or pre-established network behavior while monitoring incoming traffic. Intrusion detection systems based on signature or behavior cannot detect new attacks and fall when small deviations occur. Also, current anomaly detection approaches suffer often from high false alarms. As a solution to these problems, machine learning techniques are a new and promising tool for the identification of attacks. In this paper, the authors present a hybrid approach, combining artificial neural networks and a hybrid clustering algorithm based on k-means and genetic algorithm called GenClust++. The final framework leads to a fast, highly scalable and precise packets classification system. We tested our work on the newly published dataset CICIDS 2017. The overall process was fast, showing high accuracy classification results.
A Fuzzy Lattice System to Trust Management in Mobile Grid
Authors:   Department of Computer Science & Engineering Shivaji University Kolhapur, India, Otari Grantej Vinod , Ghorpade Dr. Vijay Ram ,   Department of Computer Science & Engineering Bharati Vidyapeeth's College of Engineering Kolhapur, India, Dhanani Dr. Sachin Harakhchand ,   Department of Mathematics K.I.T.’s College of Engineering, Kolhapur, India
Published: August 2019

Mobile Grid is a crossbreed technology formed by amalgamation of the two prominent technologies namely mobile technology and grid technology that enable sharing and collaboration of mobile resources cooperatively, transparently, efficiently, reliably and securely. Mobile Grid considers the mobility issues and overcomes the constraints and deficiencies in both the technologies. However, this heterogeneous, dynamic and open mobile grid network is more prone to malicious and selfish nodes inside and outside the network. Hence, a vigorous security mechanism is needed that considers different security threats and pro-vide different levels of security services. Here, we propose one such preventive security service based on Trust Management. The proposed trust management service uses a novel fuzzy lattice approach for trust estimation of the nodes in the network. A node with high trust value is allowed to participate in the network. A malicious node having low trust value is prevented from performing the task. A fuzzy lattice approach can compute incrementally the same intervals in the training data independent of the order of presentation within a short period. Experimental analysis of the fuzzy lattice approach shows that the proposed approach outperforms most of the existing approaches based on fuzzy logic.
Development and Experimental Characterization of Fibre Metal Laminates to Predict the Fatigue Life
Authors:   Research Scholar, St.Peter’s Institute of Higher Education and Research, Chennai. & Assoc. Professor, Vel Tech Rangarajan Dr. Sangunthala R&D Institute of Science & Technology, Chennai., G Boopathy , K.R Vijayakumar ,   Professor, Mechanical Engineering, Dr.MGR Educational and Research Institute, Chennai., M Chinnapandian ,   Professor, Aeronautical Engineering, St. Peter’s College of Engineering & Technology, Chennai., K Gurusami ,   Professor, St. Peter’s Institute of Higher Education and Research, Chennai.
Published: August 2019

During the last two decades, the concept of Fibre Metal Laminates (FMLs) has been evolved to find solution to the requirement of improving mechanical properties and reducing structural weight of elemental components of aircraft structures. In this work FML is prepared using Al 2024 by placing alternately with glass/carbon/aramid Fibres. From experimental results of FML shows greater advantage in mechanical properties then aluminium monolithic layer and this composite fibre laminates individual. The FMLs tested in this work were made of 3 layers of 2024 T3 aluminium alloy 0.28 mm thickness and fibre mats. The 5-3/2 laminates of size 300x300 mm with 3 mm thick were prepared using Vacuum Assisted Resin Transfer Moulding (VARTM) in cold compaction and test specimen were cut by using abrasive water jet machining as per ASTM Standards. The adhesion between fibre and metal layer will play a major role in strength of FML. By keeping this in consideration FMLs were prepared without blow holes and capable of withstanding delamination while preparing specimens through water jet and during various tests employed. The fracture surfaces of destructed specimens are studied with help Scanning Electron Microscope (SEM) image. Similarly, the numerical simulation of all the tests were done using Ansys APDL 10.0 Software. It is observed that aramid FML have substantially stronger in longitudinal directions. Hence, more priority given in this paper to investigate tensile strength and fatigue life of aramid FML.