bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient Implementation of Big Data Access Control Scheme with Privacy-Preserving Policy
Authors:   Department of Computer Applications, M S Ramaiah Institute of Technology, Bangalore, India., M. Dr. Niranjanamurthy , Jain Dr. Esha ,   School of Management, The NorthCap University (Formerly ITM University), Gurugram, India, Nigam Dr. Bhawna ,   Department of Information Technology, Institute of Engineering & Technology, Devi Ahilya University, Indore, India., M. Ms. Sushmitha ,   Department of Computer Applications, M S Ramaiah Institute of Technology, Bangalore, India.
Published: August 2019

In the time of big data, cloud computing, an immense measure of information can be created rapidly from different IT, non-IT related sources. Towards these big data, cloud computing, customary PC frameworks are not up to required skilled to store and process this information. Due to the adaptable and flexible figuring assets, distributed computing is a characteristic fit for putting away and preparing big data. With cloud computing, end-clients store their information into the cloud server and depend on the advanced cloud server to share their information to different clients. To share end-client's information to just approved clients, it is important to configuration access control systems as indicated by the prerequisites of end clients. When re-appropriating information into the cloud, end-clients free the physical control, virtual physical control of their information. In addition, cloud specialist co-ops are not completely trusted by end-clients, which make the entrance control additionally testing. on the off chance that the conventional access control systems (e.g., Access Control Lists) are connected, the cloud server turns into the judge to assess the entrance approach and settle on access choice. Subsequently, end-clients may stress that the cloud server may settle on wrong access choices purposefully or accidentally and uncover their information to some unapproved clients. To empower end-clients to control the entrance of their own information, a proficient and fine-grained huge information access control plot with protection saving strategy is proposed. In particular, the entire trait (as opposed to just its qualities) in the entrance strategies are scrambled. To help information decoding, encoding, a novel Attribute Bloom Filter is utilized [14][16] to assess whether a characteristic is in the entrance arrangement and find the accurate position in the entrance approach on the off chance that it is in the entrance strategy. Just the clients whose traits fulfill the entrance arrangement are qualified to unscramble the information.
Assessing the Effect of Financial Literacy on Investors Decisions Making
Authors:   Pursuing PhD at Amity Business School,Amity University Noida, India., Yadav Neha , Raman Dr. T.V. ,   Professor & Head of the Department, Accounting and finance in Amity Business School Amity University Noida, India.
Published: August 2019

Indian economy has made its growth at an accelerating pace over the last decade. The study aims to assess literacy level of investors. The association between demographic, socio-economic profile of investors and their financial literacy level has been studied. The study also finds that whether literacy of investors have any effect on decision making of investors. To see the impact of demographic factors on financial literacy level, regression is performed. The result of the study states that decision of investors is significantly affected by literacy and knowledge of investors regarding financial terms.
An Effecient Fake News Detection System Using Machine Learning
Authors:   Department of Computer Science & Engineering, Raghu Engineering College, Visakhapatnam,A.P,India, Lakshmanarao A. , Swathi Y. ,   Department of Computer Science & Engineering, BABA Institute of Technology&Sciences, Visakapatnam,A.P,India, Kiran Dr. T. Srinivasa Ravi ,   Department of Computer Science, P.B.Siddhartha College of Arts & Science Vijayawada, India
Published: August 2019

Social media plays a major role in several things in our life. Social media helps all of us to find some important news with low price. It also provides easy access in less time. But sometimes social media gives a chance for the fast-spreading of fake news. So there is a possibility that less quality news with false information is spread through the social media. This shows a negative impact on the number of people. Sometimes it may impact society also. So, detection of fake news has vast importance. Machine learning algorithms play a vital role in fake news detection; Especially NLP (Natural Language Processing) algorithms are very useful for detecting the fake news. In this paper, we employed machine learning classifiers SVM, K-Nearest Neighbors, Decision tree, Random forest. By using these classifiers we successfully build a model to detect fake news from the given dataset. Python language was used for experiments.
Machine Learning Based Supervised Feature Selection Algorithm for Data Mining
Authors:   Research Scholar, Bharathiar University, Coimbatore, Tamil Nadu, India., Sutha K. , Tamilselvi Dr.J. Jebamalar ,   Professor, Department of MCA, Jaya Engineering College, Chennai, Tamil Nadu, India.
Published: August 2019

Data Scientists focus on high dimensional data to predict and reveal some interesting patterns as well as most useful information to the modern world. Feature Selection is a preprocessing technique which improves the accuracy and efficiency of mining algorithms. There exist a numerous feature selection algorithms. Most of the algorithms failed to give better mining results as the scale increases. In this paper, feature selection for supervised algorithms in data mining are considered and given an overview of existing machine learning algorithm for supervised feature selection. This paper introduces an enhanced supervised feature selection algorithm which selects the best feature subset by eliminating irrelevant features using distance correlation and redundant features using symmetric uncertainty. The experimental results show that the proposed algorithm provides better classification accuracy and selects minimum number of features.
Pre-Competitive Anxiety Of Malaysian Premier League And University Football Players
Authors:   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Karim Zulakbal Abd , Mahadi Rania ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Hizan Hazuan ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Mustafa Mirza Azny ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Malik Zulezwan Ab ,   Faculty of Sports Science and Coaching, Sultan Idris Education University, Malaysia., Syed Ali Syed Kamaruzaman ,   Faculty of Education, University of Malaya, Malaysia.
Published: August 2019

This study aimed to identify the level of state anxiety among football players of a Malaysian premier league and a university football players. This study involved 40 players aged between 18 to 32 years old. The questionnaire used in this study was Competitive State Anxiety Inventory-2 Reverse Survey (CSAI-2R) to measure the level of athlete's somatic anxiety, cognitive anxiety and self-confidence. The findings showed that the premier league players has a lower level of somatic and cognitive anxiety than the university players. Premier league players also were shown to have higher levels of self-confidence. Based on the findings, experience and achievement level are the contributing factors in determining the level of anxiety and increasing self-confidence. The more experience and skills the athlete has, the easier it is for athletes to control the level of anxiety.
An Integrated Technique for Face Sketch Recognition Using DCNN
Authors:   Department of Computer Science and Engineering Godutai Engineering College for Women, Kalaburgi, India., Patil Shivaleela. , DC Dr. Shubhangi. ,   Department of Computer Science and Engineering VTU Regional Centre, Kalaburgi, India.
Published: August 2019

Face Recognition (FR) is considered as one of the chief use in the investigation of criminals. In the majority of the cases, information about the criminal is not available. In such situations, sketch artist draw the sketch of the guess with the oral
Graph of an Intuitionistic Fuzzy Ideal of M⟙ Groups in Near Rings
Authors:   PhD- Research scholar, Department of Mathematics, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, Mala S K , Shanmugapriya M M ,   Professor, Head(i/c) , Department of Mathematics, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu
Published: August 2019

The objective of this paper is to establish a relationship between intuitionistic fuzzy (IF) theory, graph theory, intuitionistic fuzzy graph theory with the ideal algebraic structure of a near ring in MΓ group. The idea of graph of an intuitionistic fuzzy (IF) ideal, the regular graph of an intuitionistic fuzzy (IF) ideal and their isomorphism in MΓ group of near rings are discussed. Also, few properties of theirs are studied here as theorems
Design and Implementation of Real Time Data Acquisition System in All Programmable System on Chip
Authors:   (Senior Member IEEE), Dept. of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamilnadu, India, Suresh P. , Saravanakumar U. ,   (Senior Member IEEE), Dept of ECE, Muthayammal Engineering College, Namakkal, Tamilnadu, India, Karthikeyan V. ,   RF Application Engineera, Scientific Society Group, Tamilnadu, India, Krishna G.Vamsi ,   Dept. of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamilnadu, India, Sreekanth K. ,   Dept. of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamilnadu, India, Reddy G.Kumar ,   Dept. of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamilnadu, India
Published: August 2019

In the recent era, the world has faced drastic improvement in automation industries and there is an need of speedy multi-functional system with higher performance device. The demand for faster, smaller and energy efficient computing systems for miniaturized devices is tremendously increased day by day. Over the past decades, there is a drastic change in semiconductor industry due to its advantages and higher performance of integrated circuits even there is more complexity in design and more expensive. The semiconductor industry started to embrace new design and reuse policies are mutually discussed as system-on-chip (SoC) design. This technology allows to develop a system with higher performance only with required blocks for different applications. In this paper, it is proposed to implement SoC based data acquisition system to measure the atmospheric parameters with different sensors in real time.
Organizational Ergonomics: Human Engineering Leading To Employee Well-Being
Authors:   Ph.D Research Scholar, School of Management Studies, Vels Institute of Science and Technology & Advanced Studies. Pallavarm, Chennai, India., Gomathi K. , G Dr.Rajini. ,   Corresponding Author, Professor & Head-MBA (Integrated), School of Management Studies, Vels Institute of Science and Technology & Advanced Studies, Pallavaram, Chennai, India
Published: August 2019

Human engineering is the application of mental health and physiological principles to the structure of products, procedures, and schemes. The aim of human engineering is to decrease human mistake, improve productivity level, and increase safety and well-being with a particular focus on the association between the human and the thing of intrigue. Practicing good ergonomics leads to increased productivity, improved health and safety of workers, higher job satisfaction and retention of employees. Sampling technique is probability, multistage sampling , sampling units garment companies, The multiple regression analysis was used to study the relationship between the factors influencing ergonomics, resilience, subjective and objective well-being. This study was conducted in India’s Textile hub of Garment industry: Tiruppur District, Tamilnadu state. The data was collected from 453 garment industry employees through a structured questionnaire. The finding of this study organisational ergonomics, resilience, subjective well-being and objective well-being has strongly depends on physical workplace environment and machines. Task, but doesn’t have an effect of psychosocial factor. Subjective well-being strongly depends on Task, Organisational ergonomics, Resilience. Objective well-being is depends on organisational ergonomics. Proper workplace environment and good condition machinery creates better comfortable and safe workplace which leads to employee well-being. Human engineering factors (Physical workplace environment, Machines, Task, and Psychosocial Factor) facilitated by organisational ergonomics leads to a better employee well-being.
Subject Independent Automatic Facial Expression Recognition from Partially Occluded Still Images by Employing Appearance Based Feature Extraction Schemes
Authors:   Department of ECE, S D M Institute of Technology, Ujire, Karnataka, INDIA, Kumar H N Naveen , S Jagadeesha ,   Department of ECE, S D M Institute of Technology, Ujire, Karnataka, INDIA
Published: August 2019

Facial expression recognition is the process of identifying human emotion through expressions. The world around us is constantly changing and in this ever-changing scenario, development of a system which performs automatic detection and recognition of facial expressions in a given scene is of paramount importance, and at the same time highly challenging. It becomes even more challenging when the aforesaid scene is partially occluded, thus limiting the facial area which could be explored. As such, expression recognition from partially occluded images is still largely an unexplored area. The proposed work is an attempt towards subject independent automatic expression recognition from partially occluded images. Salient features of the proposed work involves careful approximation of contributions made by facial regions like eye, mouth, and nose towards recognition of each basic expression; determination of a particular region in face which contributes the most discriminative and abstract feature for recognition of a particular expression; identification of facial region wherein expression recognition is independent of any occlusion happening with respect to that particular region. The proposed work to begin with segments facial regions from a static facial image; discriminative and abstract features extracted from so segmented facial regions are experimented upon to better understand the contribution made by each region in recognition of a facial expression. Various appearance features such as HOG, LBP and OGBP have been incorporated in the experimentation, and results obtained thereby infer that mouth region convey lion’s share of the information about probabilistic determinant of an expression and its intensity when compared to remaining regions. The proposed system outperforms holistic approaches in connection with facial expression recognition.
Sentiment Analysis on Social Media Big Data With Multiple Tweet Words
Authors:   Department of Computer Science, Alagappa University. Tamil Nadu, India., Maheswari S. Uma , Dhenakaran Dr. S. S. ,   Department of Computer Science, Alagappa University. Tamil Nadu, India.
Published: August 2019

The main objective of this paper is Analyze the reviews of Social Media Big Data of E-Commerce product’s. And provides helpful result to online shopping customers about the product quality and also provides helpful decision making idea to the business about the customer’s mostly liking and buying products. This covers all features or opinion words, like capitalized words, sequence of repeated letters, emoji, slang words, exclamatory words, intensifiers, modifiers, conjunction words and negation words etc available in tweets. The existing work has considered only two or three features to perform Sentiment Analysis with the machine learning technique Natural Language Processing (NLP). In this proposed work familiar Machine Learning classification models namely Multinomial Naïve Bayes, Support Vector Machine, Decision Tree Classifier, and, Random Forest Classifier are used for sentiment classification. The sentiment classification is used as a decision support system for the customers and also for the business.
Methods of Assessing the Strength of Masonry to Ensure the Reliability of Reconstructed Structures
Authors:   Department of Building materials, Emperor Alexander I St.Petersburg State Transport University, Saint-Petersburg , Russia, Kazanskaya L.F. , Belentsov Yu.A. ,   Department of Building materials, Emperor Alexander I St.Petersburg State Transport University, Saint-Petersburg , Russia
Published: August 2019

The reliability of structures in the reconstruction of buildings depends on quality control methods that can be destructive and non-destructive. Directions for improving the accuracy of methods for assessing masonry as a complete construction system are proposed in the paper. The factors to be taken into account when assessing the bearing capacity of the operating buildings have been stated. Margin of errors of a number of parameters using different methods of strength assessment have been determined.
UMN Site Traffic Prediction using Technical Method
Authors:   Informatics Department, Universitas Multimedia Nusantara, Tangerang, Indonesia., Alexander Alvin , Hansun Seng ,   Informatics Department, Universitas Multimedia Nusantara, Tangerang, Indonesia.
Published: August 2019

The Marketing division of Universitas Multimedia Nusantara has a role in attracting prospective students to join and continue their next level of education. To help their task, the Marketing division needs an application that can predict the site traffic profile visits for the next following day. Therefore, a website-based application was created to assist the Marketing division. We used the Weighted Moving Average algorithm to calculate the number of subsequent visitors and its future prediction number. We also used the Weighted Mean Absolute Percentage Error after getting the prediction results to get the error rate of a prediction made. In the implementation process that has been done, the percentage error is 2.57%. The built application also had been evaluated by the UMN Marketing division employees by the means of questionnaires to find out how satisfied the application was.
Document Image Compression using DC-DWT
Authors:   Assistant professor, GCOEA, Amravati, India, Thakare Prof. S. S. , Kale Prof. Dr. S. N. ,   Assistant professor,SGBAU, Amravati, India
Published: August 2019

Scanned Document Image compression is an important technology for digital image transmission and storage. This study proposes a unique image compression system based on discrete curvelet transform & discrete wavelet Transform (DC-DWT) with a varying pixels position. The discrete wavelet and the Curvelet transform technique, which because of their outcomes and characteristics, DWT and CT are the most suitable technology for the varied field of image processing. The position of a pixel in the document images and the high-impact components are handled using the curve let transform technique during the compression of the JPEG image. The Cuckoo search algorithm is used for image enhancement. Depending on two primary criteria checks, excellent outcomes were achieved; the compression ratio and the quality of recreated scan document.
A Deep Learning Neural Network for Detecting the Diabetic Retinopathy
Authors:   CSE department, RGMCET, Nandyal, India., Kumar Dr R. Raja , Kumar Dr G. Kishor ,   IT department, RGMCET, Nandyal, India., Koushik M.K. ,   IT department, RGMCET, Nandyal, India, Chennakesavulu M ,   IT department, RGMCET, Nandyal, India
Published: August 2019

Diabetic Retinopathy (DR) is the leading cause of disease to blindness of people globally. The retinal screening examinations of diabetic patients is needed to prevent the disease. There are many untreated and undiagnosed cases present in especially in India. DR requires smart technique to detect it. In this paper, we proposed a deep learning based architecture for detecting the DR. The experiments are done on the DR Dataset available in UCI machine Learning Repository. The results obtained from the experiments are satisfactory.
Cost Sensitivity Ranges in Rough Set Interval Transportation Problem
Authors:   Department of Mathematics, School of Advanced Sciences, VIT, Vellore., Pandian P. , Kavitha K. ,   Department of Mathematics, School of Advanced Sciences, VIT, Vellore.
Published: August 2019

A new technique namely, upper-lower bound technique is projected for solving the cost sensitivity analysis of fully rough integer transportation problem. Numerical sample is given to indicate the productivity of the projected technique.
Recent Updates on Electrochemical Detection of Perchlorate Ions
Authors:   Department of Electronics and Communication Engineering, GJUS&T, Hisar (Haryana), India, Rani Nisha , Singh Kuldeep ,   Department of Electronics and Communication Engineering, GJUS&T, Hisar (Haryana), India,, kanva Nitin ,   Department of Electronics and Communication Engineering, GJUS&T, Hisar (Haryana), India, singal Anuj ,   Department of Electronics and Communication Engineering, GJUS&T, Hisar (Haryana), India
Published: August 2019

Perchlorate is a highly toxic compound. It has both chemical and physical properties. Perchlorate is not easily degradable compound by both bio and non-bio degradation process because of its high stability, highly water soluble compound and low absorption. That’s why perchlorate reduction becomes a big challenge. In this research work we studied different type of electrochemical technique and effect of different electrodes on these techniques. In present days, many techniques were developed for the detection or reduction of perchlorate such as bio-degradation, optical, chemical, electrochemical and microbial technique. This article gives information about application of electrochemical technique for the detection or reduction of perchlorate. The electrochemical techniques have various types for the detection of ion. These techniques grouped on the behalf of various types of electrical signal such as potential or voltage, current and impedance which were produce in the presence of perchlorate into aqueous solution. Electrochemical technique such as impedance spectroscopy, this technique was performed on the electrochemical work station by applied a constant range of frequency. In cyclic voltammetry technique we were given a constant potential range and found results in the form of oxidation and reduction current. In the reduction of perchlorate history various researcher was found results using different electrochemical technique on different types of electrodes. The perchlorate salts and perchlorate have some useful application in the defense field, batteries, automobile airbags, rocket propellants and fuels. Perchlorate contamination is become a worldwide health problems. In many western states perchlorate was found in ground and surface water. It disturbs the thyroid gland to uptake iodine the human body. So its prevention technique was needed. However, the electrochemical techniques have more advantage such as low cost, user friendly, label free and real time monitoring over all other techniques. So we focus on electrochemical detection technique for the perchlorate.
Raspberrypi Based Assistive Communication System for Deaf, Dumb and Blind Person
Authors:   Computer Science and Engineering, PDACE, Kalaburgi, India., Nandyal Dr.Suvarna , Kausar Shireen ,   Computer Science and Engineering, PDACE, Kalaburgi, India.
Published: August 2019

Assisting to the people with visual, hearing, vocal impairment through the modern system is a challenging job. Nowadays researchers are focusing to address the issues of one of the impairment but not all at once. This work is mainly performed to find the unique solution/ technique to assist communication for the people with visual, hearing, vocal impairment. This system helps the impaired people to have the communication with each other and also with the normal person. The main part of the work is Raspberrypi on which all the activities are carried out. The work provide the assistance to visually impaired person by letting them to hear what is present in the text format. The stored text format is spoke out by the speaker. For the people with hearing impairment the audio signals are converted into text format by using speech to text conversion technique. This is done with the help of AMR voice app which makes them to understand what the person says can be displayed as the text message . And for people with vocal impairment, their words are conveyed by the help of speaker.
Adaptation using Machine Learning for Personalized eLearning Environment based on Students Preference
Authors:   holds M.C.A., M.Phil. B.Ed in Computer Science., Martin A. John , Maria Dr. M. ,   Dominic obtained his B.Sc, M.Sc, M.Phil and Ph.D in Computer Science.
Published: August 2019

Information gathering is a lifelong process of human being and the learning takes place from womb to tomb. Learners acquire, recognize, map the gathered information to knowledge and use it in day to day life. Advancement in ICT and the utilization of ICT in teaching and learning process has contributed an exponential growth. An eLearning solution has almost reached maturity, where the teaching and learning community have the proper digital infrastructure, smart phones, tablet computers and the best software platform. An innovation in teaching and learning sector has become an integral part and is mandatory. Hence the challenge is to suggest quality and appropriate learning materials to the learners. The research aims to categorize the learner according to their learning ability and to find the learning path to facilitate the learner to have appropriate and quality learning objects with the help machine learning techniques. The focus of this work is to come up with a system architecture which predicts and adapts the learner style, find the learning path and to provide the suitable learning objects in eLearning environment based on their preferences. Personalization will assist learner to improve their learning performance.
Advanced Machine Learning Models to Handle Unifying Attacks in Images
Authors:   Department of Computer Science and Enginerring, S.R.K.R Engineering College, Bhimavaram, India., Krsihna K.P.Sai Rama , Sravani K. ,   Computer Science And Engineering, S.R.K.R Engineering College, Bhimavaram, India.
Published: August 2019

Critical advancement has been made with profound neural systems as of late. Sharing prepared models of profound neural systems has been a significant in the fast advancement of innovative work of these frameworks. In digital environment, there are different types of applications face security related attack sequences from third parties. Most of the machine learning related approaches was introduced to describe security in wind and vulnerable attack sequences. Digital Watermarking is one of the approach to handle adversary related security approach to handle attacks appeared in digital environment. But it has some limitations to describe efficient security behind the web related applications appeared in real time environment. So that in this paper, we propose and implement advanced machine learning approach i.e Neural Network based Click Prediction (NNBCP) to handle web related attack sequences in real time environment. It uses Integrated CAPTCHA procedure to provide machine learning based captcha generation for user login and registration to handle different types of attacks in digital systems.
Demystifying User Data Privacy in the World of IOT
Authors:   Ph.D. research scholar, Bharati Vidyapeeth Deemed University, College of Engineering, (Assistant Professor, Symbiosis Institute of Technology, Symbiosis International (Deemed University)), Pune, India., Patil Shruti , Joshi Dr.Shashank ,   Professor, Bharati Vidyapeeth Deemed University College of Engineering,Pune India
Published: August 2019

Internet of Things (IoT) would touch upon almost all aspects of everyday life, as a consequence of which, everything (i.e. living and non-living things) will have a counterpart virtual identities on the internet which would be readable, addressable and locatable. Although it would empower its users with 24×7 connectivity around the global world, unknowingly they would also provide it permission to peep into user’s personal world, which can generate a huge risk on the usability of IoT by users. Thus analyzing the framework of IOT from the perspective of user data protection is a very crucial self-test which is required for IoT implementation. Often the term security and privacy are used interchangeably, but in the IoT environment, both these concept would play a crucial but differentiating role. In this paper, we have scanned the IoT environment with the perspective of privacy requirements, possible threats and the mitigating solutions which are currently in use.
A Preliminary Exploration on Health Care Professionals (Doctors) Stress due to Competition, Advancement of Technology & Environment at Chennai
Authors:   Research Scholar, Dr.MGR Educational and Research Institute, Chennai, India., Asokan K , Brindha G ,   Professor and Head, Department of Management Studies, Dr.MGR Educational and Research Institute, Chennai, India., Valarmathi S ,   Research Officer (Statistics), The Tamil Nadu Dr. MGR Medical University, Chennai, India.
Published: August 2019

Due to the advancement of technological changes in the health care sector, health care professionals such as doctors, nurses, technicians, etc, are expected to work more intensely and successfully deliver more. The present study focuses on stress among young doctors due to rapid technological advent and intense industrialisation, especially in the metropolitan city Chennai. Data was collected from eighty seven young doctors through structured questionnaire. In the modern era, people who reside in the metropolitan city like Chennai are well educated, wealthy and aware of new innovative and sophisticated equipments, medicine, facilities, etc. and these are inevitable part of technological development. Hence the doctors have to update themselves in all field related technologies. They feel stressed physically and mentally when there is a lacuna in the competitive environment.
Implementation and Evaluation of Intelligence Incorporated Tutoring System
Authors:   her department is school of computer science University of Petroleum and Energy Studies, Bidholi , Dehradun,248007 India, Singh Ninni , Ahuja Neelu Jyothi ,   her department is school of computer science University of Petroleum and Energy Studies, Bidholi , Dehradun,248007 India
Published: August 2019

This research article elaborates the explication of domain knowledge into a tutorable form and illustrates the prediction of tutoring strategy prior to beginning of the tutoring session. The proposed intelligent tutoring system is christened as SeisTutor. It impersonates human intelligence by adjudging best tutoring strategy for the learner. An empirical analysis has been performed on group of applicants having fundamental knowledge of the domain. Experimental analysis reveals that the learners who have undergone tutoring through ‘SeisTutor’ embedded with intelligence present an overall 44.5 % learning gain as against that of 24.8 % shown by learners who underwent tutoring through the ‘SeisTutor’, while it does not impersonate intelligence by choosing content and style for the learner.
Exploring Statistical Parameters of Machine Learning Techniques for Detection and Classification of Brain Tumor
Authors:   Computer Science & Engineering, Guru Gobind Singh Indraprastha University, New Delhi, India., Singh Manu , Shrimali Dr. Vibhakar ,   Electronics & Communication Engineering, GB Pant Govt. Engineering College, New Delhi, India.
Published: August 2019

A computerized system can improve the disease identifying abilities of doctor and also reduce the time needed for the identification and decision-making in healthcare. Gliomas are the brain tumors that can be labeled as Benign (non- cancerous) or Malignant (cancerous) tumor. Hence, the different stages of the tumor are extremely important for identification of appropriate medication. In this paper, a system has been proposed to detect brain tumor of different stages by MR images. The proposed system uses Fuzzy C-Mean (FCM) as a clustering technique for better outcome. The main focus in this paper is to refine the required features in two steps with the help of Discrete Wavelet Transform (DWT) and Independent Component Analysis (ICA) using three machine learning techniques i.e. Random Forest (RF), Artificial Neural Network (ANN) and Support Vector Machine (SVM). The final outcome of our experiment indicated that the proposed computerized system identifies the brain tumor using RF, ANN and SVM with 100%, 91.6% and 95.8%, accuracy respectively. We have also calculated Sensitivity, Specificity, Matthews’s Correlation Coefficient and AUC-ROC curve. Random forest shows the highest accuracy as compared to Support Vector Machine and Artificial Neural Networks.
A New Pentagon Search Algorithm for Fast Block-Matching Motion Estimation
Authors:   Department of Computer Science, BBA University (A Central University), Lucknow, India., Kumar Neetish , Raj Deepa ,   Department of Computer Science, BBA University (A Central University), Lucknow, India.
Published: August 2019

The impact of search pattern is a crucial part in the block-based motion estimation for finding the motion vector. An issue of distortion performance and search speed heavily depends upon the size and shape of search strategy applied. Performing the deep analysis for motion vector distribution on standard test videos, it is desirable to have such type of algorithm that meets the requirement of searching motion vector in less time. Hence, a new kind of Pentagon algorithm is proposed in this paper for fast block-matching motion estimation (BMME). It is an easy and efficient technique for finding motion vector. Experimental results expose the proposed Pentagon algorithm sparsely surpass the noted Diamond search (DS) algorithm. The new Pentagon search algorithm is examined with the previously proposed Diamond search algorithm in terms of performance measure; the proposed algorithm attains better performance with the less complexity. The experimental examination also depicts that the pentagon algorithm is better than the previously proposed Diamond search (DS) in terms of mean-square error performance and required the number of search points. The overall speed improvement rate (SIR) is about 31% with respect to the DS.
Secure and Access Control Data Monitoring in Vehicular Ad Hoc Network
Authors:   Completed B.tech In GVIT(JNTUK) Engineering College and Pursuing M.tech In SRKR(A) Engineering College, Bhimavaram, Appana Nagarjuna , Raju P Udaya ,   Assistant Professor at Computer Science and Engineering Department, SRKR(A) Engineering College, Bhimavaram, 534204, India
Published: August 2019

Present days innovation identifies with internet of Vehicles (IOV) has been expanded to break down traffic in the board frameworks. It is utilized to portray traffic examination and improve proficiency of the vehicle traffic. The stage can take care of the issue of capacity, investigation and multi terminal dispersion of mass information, give traffic data administrations to traffic the board offices and people in general, it is a helpful endeavor to apply propelled data innovation to the transportation business. Causing the broad worries in the exploration network. To empower credible and classified correspondences among a gathering of haze hubs, in this paper, we propose a productive key exchange protocol based on cipher text policy attribute-based encryption (CP-ABE) to set up secure interchanges among the members. To accomplish classification, verification, certainty, and access control, we consolidate CP-ABE and computerized signature strategies. We investigate the productivity of our convention regarding security and execution. We likewise execute our convention and contrast it and the endorsement based plan to delineate its practicality.
Pixel Based Sar Image Classification using Random Forest Algorithm
Authors:   Research and Training Unit for Navigational Electronics (NERTU), Dept of ECE and University College of Engineering, Osmania University, Hyderabad, Telangana, India., Balnarsaiah Battula , Prasad T.S. ,   National Remote Sensing Centre(NRSC), Indian Space Research Organization (ISRO), Hyderabad, Telangana, India., Laxminarayana P. ,   Research and Training Unit for Navigational Electronics(NERTU), Osmania University, Hyderabad, Telangana, India.
Published: August 2019

Synthetic Aperture Radar (SAR) images (Microwave data) were classified using Multi-Layer Feed Forward, Cascade Forward Neural Networks and Random Forest (RF) algorithms. For the Random Forest, a general model for classification of Remotely Sensed Radar dual-polarization data based on RF is implemented and classified of SAR image (microwave data) classifications. The RF model exploits spatial context between neighbouring pixels in an image, and temporal class dependencies between different images of the same region, in the case of multi-temporal data. Based on the well-founded experimental on basis of random forest techniques for classification tasks and the encouraging experimental results in RF algorithm , the authors conclude that the proposed RF algorithm is useful for classification of SAR (Sentinel 1A) imagery and evaluate its accuracy and kappa coefficient.
Cascaded Rf-Fso-Vlc System using Df Relays
Authors:   Department of Electronics and Communication Engineering, Indian Institute of Information Technology Guwahati, Assam, India., Deka Rima , Anees Sanya ,   Department of Electronics and Communication Engineering, Indian Institute of Information Technology Guwahati, Assam, India.
Published: August 2019

This paper presents performance analysis of cascaded radio frequency-free space optical communication-visible light communication (RF-FSO-VLC) system. The proposed model comprises of the RF link as the core network, a terrestrial optical link for providing last mile connectivity with the indoor cell users communicating through VLC environment. The RF link undergoes Nakagami-m distributed fading, while the terrestrial optical link is modeled by Double Generalized Gamma (DGG) distributed turbulence and Rayleigh-distributed misalignment losses. VLC links are characterized by the randomness in users’ position. Using statistical properties of system signal-to-noise ratio (SNR), outage and error performance of the proposed system is evaluated depending on whether the relays and the destination decode either perfectly or erroneously. The numerical results show that the system performance varies depending on field-of view (FOV) of the detector and user’s position. This is because as FOV increases along with the height of the LED, the outage probability of the system increases. Error probability depends on the type of detection techniques, where a heterodyne detection system performs better than a direct detection system. Moreover, through results it is inferred that severe fading and misalignment losses result in poor error performance of the considered system errors on the performance of the considered cooperative system.
Design of Planar and Conformal Microstrip Patch Antenna for Avionics Applications
Authors:   Electronics& communication Engineering,, GITAM University, Visakhapatnam, INDIA, Sankar Ch V Ravi , Jayasree Dr. P V Y ,   Electronics& communication Engineering,, GITAM University, Visakhapatnam, INDIA.
Published: August 2019

Microstrip patch antennas have an important role on Communication applications on satellites, aircrafts, missiles and other vehicles comparing to other types of antenna because of their conformability nature. In this paper several EM simulations performed on planar and conformal antenna for avionic applications. The design of the proposed planar antenna configuration is analyzed by using IE3D simulation software, it is MOM (Method of Moments) based and conformal antenna is analyzed by using HFSS simulator which is finite element method.In addition we are achieving circular polarization.
Deca Band Inset Fed Cross Slot Loaded Patch Antenna for LTE Applications
Authors:   Department of Electronics and Communication, J.K. Institute of Applied Physics and Technology, University of Allahabad, Prayagraj,U.P, India., Nitin Navendu , Ansari Jamshed Aslam ,   Professor and Head of the Department of Electronics and Communication, University of Allahabad., Agrawal Neelesh ,   Department of Electronics and Communication, J.K. Institute of Applied Physics and Technology, University of Allahabad, Prayagraj, U.P, India., Tiwari Devesh ,   Department of Electronics and Communication, University of Allahabad, Prayagraj, India, Saroj Abhishek Kumar ,   Department of Electronics and Communication, J.K. Institute of Applied Physics and Technology, University of Allahabad, Prayagraj, UP, India.
Published: August 2019

The cross slot loaded patch antenna with inset feed is designed and fabricated on FR4 substrate to get deca band. This proposed antenna consists of a cross slot on a rectangular patch with inset feeding, on a dielectric substrate. The simulated results of proposed antenna have ten resonating frequencies (2.30, 3.90, 5.30, 6.10, 8.70, 10.0, 12.9, 14.10,16.20, 19.0 GHz) while measured results of proposed antenna have eleven resonating frequencies (2.3089, 4.1079, 5.3073, 6.2069, 8.8056, 10.1050, 11.8041, 12.5038,14.3028, 16.1019, 19.1004 GHz). The frequency bands are useful for S band, C band, X band, Ku band, K band and for LTE applications. Frequency bands like 2.30, 5.30, 8.70 can be useful for LTE applications while other frequency bands can be used for different applications such as WIFI, WiMAX, satellite communication, radar communication etc. The simulation for desired antenna is performed with the help of software HFSS.
Influence Of Profesional Teacher Competence, Self Concept, Interest Learning, And Early To Learning Outcomes Mathemathics
Authors:   Post Graduate Education Science, Padang State of University., Nafis Hasnan , Rusdinal  ,   Education Science, Padang State of University. Profesor, Lecture & Researcher at Padang State of University., Ananda Azwar ,   Education Science, Padang State of University. Profesor, Lecture & Researcher at Padang State of University., Khairani  ,   Post Graduate Education Science, Padang State of University., Satria Haris ,   Post Graduate Environmental Science, Padang State of University. Active as Brand Activator, Lecturer & Researcher of Andalas University
Published: August 2019

This research is motivated by the problem of low learning result of mathematics of Pariaman high school students. Based on the observation and documentation, several factors that cause the low quality of professional teachers in teaching, student self-concept of the basics, low learning interest, and the initial ability of students who have not been awakened properly. The purpose of this study is to analyze the direct and indirect influence of each exogenous variable on endogen and analyze the effect simultaneously between variables.Thetype of this research is Path Analysis research, the research population is all students of SMA Pariaman amounting 4,160 people. The sample was taken using stratified proportional random sampling technique so that the number of samples taken was 100 people. Instruments used to retrieve data are questionnaires and documentation. Data were analyzed using SPSS version 16 analysis.
Performance Analysis of Cooperative Spectrum Sensing In Different Case Scenarios
Authors:   Department of Technology, Shivaji University, Kolhapur., Shirolkar Mr. Amardeep A. , Sankpal Dr. S. V. ,   D. Y. Patil College of Engineering and Technology, Kolhapur
Published: August 2019

Cooperative relay based spectrum sensing techniques are primarily available techniques in the field of research in cognitive radio networks. Even such techniques are available there is need to consider fundamental effects on spectrum sensing with various combination of scenarios that lead to false alarm detection. In this paper we have compared the three cases of cooperative spectrum sensing to analyze the effects and to form the direction of further research expectations in the field of cooperative spectrum sensing.
Performance Improvement of a Fin-Tube Heat Exchanger Using Rectangular Winglet as Vortex Generator
Authors:   Department of Mechanical Engineering, YMCA University of Science and Technology, Faridabad, India., Gupta Sachin , Gupta Arvind ,   Department of Mechanical Engineering, YMCA University of Science and Technology, Faridabad, India., Gupta Munish ,   Department of Mechanical Engineering, Guru Jambheshwar University of Science and Technology, Faridabad, India
Published: August 2019

Heat transfer performance of fin-tube heat exchanger can be augmented by using longitudinal vortex generators. Numerical simulations have been performed in the present work for investigating the effect of punching a rectangular winglet having hole from fin surface, on the heat transfer and flow resistance characteristics in a fin-tube heat exchanger. The concept of punching out a rectangular winglet having hole from the fin-plate surface is being proposed here and studied in two configurations namely, common flow down and common flow up. Comparisons on the basis of heat transfer and flow resistance characteristics have been drawn for all the configurations under consideration using Colburn’s factor (j), friction factor (f) and performance evaluation criterion (PEC) also known as area goodness factor (j/f). Investigations have been performed considering Reynolds number in the range of 1500 to 9000 and angle of attack as 45°. The result clearly indicates that punched out rectangular winglet with hole having common flow down configuration at upstream location as exhibiting the best thermal performance, followed by common flow up at upstream location and, common flow down at downstream location.
An Integrated Model of IoT and Cloud for Detecting Green House Gas Emissions
Authors:   Department of Information Technology, School Sathyabama Institute of Science and Technology, Chennai, India., Raj Jeberson Retna , Sasipraba  ,   School of Computing, Sathyabama Institute of Science and Technology, Chennai, India
Published: August 2019

Chennai is one of the oldest metropolitan city in India which consists of 15 zones and more than 200 wards. Chennai has the population of more than 8 million people and more than 20 tons of garbage collected and dumped into the two of the dumpyards Kodunkaiyur and Perungudy. These two dumpyards are catering the needs of the garbage and landfills collected from these zones, in which they are used to burn and disposed. The burning of waste is resulted into emission of higher amount of CO2. The decayed waste is one of the source for generating Methane and other greenhouse gases. This is dangerous for human lives and affects the environment. There is no such system has available to detect the CO2 and CH4 level automatically at these dumpyards. If a system automatically detects the level of CO2 and CH4 and make it available in a public domain, it will be helpful to the city administration to take the precautionary steps. Therefore, the need of the hour is to design a cloud enabled IoT based system to monitor the level of CO2 and CH4 and upload these data in the cloud for further processing. The sensor is installed in 20 of different places of these two dumpyard for monitoring the level of CO2 and CH4. The data is collected and uploaded in the cloud. The open source cloud platform Openstack is used to store all the recorded data into the cloud. The webpage www.chennaighgemissions.in is designed and the sensed data is available for public use. The system is successfully implemented and tested, and the test result is promising.