bluuebunny/crossref_metadata_2025 huggingface dataset:
Inferring of Political Leaning from Tweets, Retweets of Indian politics
Authors:   Computer Science and Engineering, VRSEC, Vijayawada, India., Kishore* Dr.G. Krishna , Dasari Suresh Babu ,   Computer Science and Engineering, VRSEC, Vijayawada, India., Kishan S. Ravi ,   Computer Science and Engineering, VRSEC, Vijayawada, India.
Published: October 2019

The current use of on-line social networks to unfold information and change opinions, by using most of the people, news media and political actors alike, has implement new outlet of research in computational political science. Here The trouble of compute and inferring the political leaning of Twitter customers. We formulate political leaning inference as a convex optimization problem that consists of ideas: Twitter users generally tend to tweet and retweet constantly, and Similar Twitter users have a tendency to be retweeted through similar sets of target audience. Then take a look at our inference technique to a massive dataset of Indian political personnel’s related individual tweets amassed over a time frame. On a fixed of regularly retweeted resources, our method achieves a few percentage of accuracy and excessive rank correlation compared with manually created labels. By analyzing the political leaning of some amount regularly retweeted property, and get regular clients who retweeted them, and the hash tags utilized by those sources, our quantitative have a examine sheds slight at the political demographics of the Twitter population, and the temporal dynamics of political polarization as activities spread..
An Efficient Policy User Web Page Correspondence Searching for Support Query Rewriting
Authors:   Pursuing M.Tech.(CSE), Narasaraopet Engineering College, Narasaraopeta, AP – 522601, India., Shaik* Shammi , Rao Dr. S. N. Tirumala ,   Professor, Computer science and engineering, Narasaraopeta Engineering College, Narasaraopet, AP -522601, India., Reddy Dr. Venkata ,   Associate Professor, Computer Science and Engineering, Narasaraopeta Engineering College, Narasaraopet, Andhra Pradesh 522601, India.
Published: October 2019

Nowadays, Social media positions remain a favorite combination as clients studying to distribute their occurrences, activities on the network. These websites receive large quantities of user-supplied elements during the vast difference natural world results of various varieties, reach. An effective advertisement marketing approach is designed by using the products that contain the information, additionally client inclinations and conclusions on information about products. By this kind of similarity between concepts of profile, a precise matching method is developed to match the profile of the Web services and user. In this work, the approach is developed to search the concept similarity in the second phase of the process of query rewriting is performed after extraction queries. Similarity measure techniques are very much useful in processing database queries such as top-k queries, reverse top-k queries, k-nearest neighbor queries and other different types of queries related to trading sales activities.
Organizational Health: the Role of Technology Disruption and Competency Adequacy in Jordanian Constrcution Sector
Authors:   Civil Engineering Department, Faculty of Engineering Technology, Al-Balqa Applied University, 11134 Amman, Jordan, Alzubi* Yazan , Malkawi Ahmad B. ,   Civil Engineering Department, Faculty of Engineering Technology, Al-Balqa Applied University, 11134 Amman, Jordan, Habib Maan ,   Civil Engineering Department Faculty of Engineering Technology, Al-Balqa Applied University, 11134 Amman, Jordan
Published: October 2019

This study aimed to analyzethe mediating impact of competence adequacy on organizational health and technology disruption. Leading construction firms in Jordan participated in this quantitative study and he results revealed significant positive effects of competence adequacy, on organisational health. These findingsprove to be an important contribution and implications to both practitioners and policy makers. Moreover, advantageous insights on how CA, TD can enhance the overall organizational health is also provided by this study. Findings and contributions of the study are as follows. Firstly, Jordanian construction firms will get more insight on the importance of institutionalizing competence building in their establishments by increasing awareness in managers. Additionally, anticipating environmental changes like technology disruption are also highlighted by the findings which guide organisations to achieve a sustainable edge over competitors at the marketplace and for future survival.
Outlier Detection in Wireless Sensor Networks Data by Entropy Based K-NN Predictor
Authors:   Department of Computer Science & Engineering,Integral University, Lucknow, U.P., India., Yadav* Manmohan Singh , Ahamad Shish ,   Department of Computer Science & Engineering Integral University, Lucknow,U.P., India
Published: October 2019

Anomaly (outlier) detection is plays very significant role in ESN based monitoring application using on large data used for biomedical and defence. Wireless Sensor network monitor environmental parameters (temperature, humidity, pressure, vibration etc). Group of sensor nodes forms a (WSN) and observations collected from these sensor produces low data quality and reliability due to the limited energy, memory, computation capability and bandwidth. The dynamic environment of network and roughness of the working condition are also responsible to generate inaccuracy in measurements. In this paper, an approach for outliers detection based entropy value of received sensor voltages is applied using KNN prediction model .The algorithm development and analysis involves a real time database generated on 14 sets of MICA2 wireless sensor kit with anomaly inserted by real time motion based intrusion in the lab by volunteers from Intel Berkeley lab. On each sensor data pair segmentation is applied by fixed window size in order get large outliers’ measurements training dataset. The analysis demonstrates the measurement accuracy in detection of number of outliers that its 86%. Moreover, the algorithm also provides an analysis in terms of impact of variation in distance types and number of nearest neighbours in the KNN prediction model. This work is helpful in the application in the situations where high amount of noise or distortions are present. The outlier part from distorted data can be figured out and recollected to enhance application accuracy.
A Movie Recommender System using Ontology Based Semantic Similarity Measure
Authors:   Department of Computer Engineering, SES's R. C. Patel Institute of Technology, Shirpur Dist. Dhule, India., Patil* Vandana Mohan , Patil Prof. Dr. J. B. ,   Department of Computer Engineering, SES's R. C. Patel Institute of Technology, Shirpur Dist. Dhule, India.
Published: October 2019

Continuous growth in information available on the Internet overwhelms the users during navigation. This information overload may result in users’ dissatisfaction which is undesirable. Users’ satisfaction is very important aspect in every domain. Recommender systems play a vital role in dealing with information overload problems. The recommender systems filter the huge information on the Internet to generate limited and personalized information to users. This helps in increasing users' satisfaction by retaining his/her interests during navigation. Pure Web usage data based recommender systems have been used from last few years. However, they lag in precise recommendations because of absence of domain knowledge. Further, the similarity measures play a vital role in recommendation process and hence affect the performance of the recommender systems. The performance of recommender systems can be enhanced through integration of domain knowledge with usage data. This paper presents an approach to movie recommender system that integrates domain knowledge with usage data. The ontology is used to represent domain knowledge. The proposed approach is based on a new ontology based semantic similarity measure. The experimental results prove that the recommendations’ quality andaccuracy of prediction can be enhanced through integration of ontological domain knowledge with Web usage data.
Morality Prediction Model in Cardiovascular Disease with Significant Feature Selection and Hybrid KNN Classification Technique
Authors:   Ph.D Research Scholar, PG and Research Department of Computer Science and Applications Vivekananda College of Arts and Sciences for Women (Autonomous), Elayampalayam, Tiruchengode-637205, Tamilnadu, India., Sowmiya* C. , Sumitra P. ,   Assistant Professor in PG and Research Department of Computer Science and Applications, Vivekanandha College of Arts and Sciences for Women, Elayampalayam, Tiruchengode(TK), Namakkal(DT), TamilNadu, India.
Published: October 2019

Nowadays morality rate is increasing globally due to heart disease. It is one of the leading health risk facing men today. So early detection of heart disease assist the patients to maintain a healthy life style. Several techniques are used in the medical field to detect or diagnose disease in view of patient family health history and some other aspects. However, developing a system to predict the heart diseases without any medical tests is still challenging. Machine learning (ML) approaches is suitable and effective in providing decision and prediction from enormous health care data. Several previous researches provide an overall view in ML methods for disease prediction but the accuracy of prediction is still needed to be improved. In this study, a novel framework is presented that intent at removing the unwanted features with Bacterial Colony Optimization algorithm and applies the Hybrid KNN algorithm with great accuracy in identifying the heart disease. This prediction model is developed with UCI Cleveland dataset with several known classification approaches. An enhanced model is presented with 99.83% accuracy in heart disease prediction. The presented study is compared with other classification approaches.
Fabrication and Experimental Analysis of Heat Transfer Characteristics of Acetone /Water by using Tube in Tube and Shell and Tube Heat Exchanger
Authors:   Department of Mechanical Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram, Andhra Pradesh, India, Emmanuel* B. , Kumar P. Ravindra ,   Department of Mechanical Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram, Andhra Pradesh, India, Prasanna M.P.V.L. ,   Department of Mechanical Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram, Andhra Pradesh, India
Published: October 2019

Cooling is essential to maintain the required efficiency and reliability in a wide range of products such as automobiles, high and medium cogeneration power plants, high power laser systems. Part of heat load amplification and the heat fluxes induced by more industrial products, cooling is one of the industry's main technical problems such as manufacturing, transport and in microelectronics. The main content of the paper is to study the LMTD (logarithmic mean temperature difference), Heat transfer Coefficient and Effectiveness (ε) of combined heat exchanger using acetone/water mixture as a function of a different mass flow rates. This paper deals with the experimental study on the three different heat exchangers like tube in tube, shell and tube and combined (tube in tube & shell and tube) heat exchanger with acetone/water mixture mostly to check the elevation of convective heat transfer coefficient, LMTD, effectiveness, overall heat transfer coefficient. This experimentation work give a summary of, the experimental study of the forced convective heat transfer and flow characteristics of a 25% acetone consisting of 75% water. Acetone/water mixture flow in to a parallel, counter direction in the tube in tube, shell and tube heat exchanger and combined heat exchanger under laminar flow conditions. A maximum increase in the coefficient of convective heat transfer of 58.4% and an effectiveness of 48.5% is recorded. However, combined heat exchanger provides better heat transfer characteristics than parallel and counter flow tubular and shell and tube heat exchanger due to the multi-pass flow of acetone/water. The overall heat transfer coefficients, Reynolds number, logarithmic mean temperature difference, the effectiveness of the acetone/water are also studied and the results are presented in tabular columns and figures.
Feature Correlation Measure Based Real Time Discrimination Prevention with Transactional Data Sets using Social Networks
Authors:   Research Scholar Jamal Mohamed College,Department of computer science,Trichy., Zubeir.* M. A Jamal Mohamed Yaseen , Shanavas A.R. Mohamed ,   Associate Professor, Department of computer science,Jamal Mohamed College,Trichy
Published: October 2019

The effect of social network in anti-discrimination has been analyzed in detail.Various approaches towards anti-discrimination on transactional data have been identified, but does not produced expected performance level. To improve the performance, a feature correlation measure based approach has been presented in this article. The method reads the transactional data set and generates number of patterns based on the purchase details. For each pattern generated, the method estimate pattern impact measure towards the data set. Based on the value of PIM (Pattern Impact Measure), a subset of patterns is selected. With the selected pattern set, the method reads the social network user data and identifies the list of items being discussed. According to identified items, the method estimates the feature correlation measure (FCM) for each items identified. According to the value of FCM, a subset of items with higher value has been selected. The selected items are identified as more sensitive and being sanitized with the publishing data set. The sanitization is performed using probabilistic sanitization algorithm. The FCM algorithm has leverage the discrimination prevention and sanitization performance.
Linear Prediction of Nucleotides in a Genome Sequence
Authors:   Research Scholar, Dept. of Computer Science, MG-NIRSA, Affiliated to University of Mysore, Manasagangotri, Mysore, Karnataka, India., Pedakolmi* Venkateswarlu , Rajan E. G. ,   Director, MG-NIRSA; Director, PRC Global Technologies Inc., Ontario, Canada.
Published: October 2019

Nucleotides are organic molecules, which are monomer units that form polymers of nucleic acid ‘deoxyribonucleic acid (DNA)’ and ‘ribonucleic acid (RNA)’. The four nucleotides A, T, G and C get connected by phosphodiester bonds to form strands. Strand formation depends on innumerable factors related to inter and intra cellular parameters and functions. One cannot precisely say that a particular strand gets formed using such and such rules. The infinite possibilities of strand formation cannot be determined experimentally or in the framework of classical genetics. One can alternatively formulate a notion of the “Language of Genomes” wherein one can finitely specify infinite strands. This paper introduces a novel prediction algorithm, which generates possible strands based on available nucleotides statistics.
A Retrospection on Current Trends in Biogas Purification
Authors:   PhD Scholar, Sant Gadge Baba College of Engg & Technology, Bhambori, ME Heat Power Engineering, S Patil* Mr. Deepak , Barjibhe Dr. Rahul B. ,   Professor, Shri Sant Gadge Baba College of Engg & Technology, Bhambori, India., Chopade Mr. Vipin ,   Assistant Professor, AISSMS Institute of Information Technology Pune, India., Patil Mr. Sunil Subarao ,   Assitnat Professor, D Y Patil College of Engineering Akurdi Pune, India.
Published: October 2019

As the non-renewable resources are depleting at a lighting speed there will be crisis for requirement of energy in near future. The only alternative is to go for renewable resources. It has been proven that biogas and gasoline can be used with association to reduce the energy demand. As even though electric vehicles are booming in the market, it will take more than a decade to move towards electric world, especially in India. The reason behind that is, the raw material required to make batteries is not at all available with India, so the only option is to export, which imposes additional cost on the country's financial books. And also the tendency of common Indian pupils to shift from IC engine to electric vehicles will incur a high debt. So to reduce the dependency on electric vehicle and also to reduce cost, biogas in the form of compressed natural gas is the only way to come in near future. The motivation of this review work is to produce biogas from food wastes, to purify and store in cylinder used to run vehicles and to analyze the effect of performance and emission characteristics of an engine.
Impact on Strength of Concrete by Coconut Coir and Polypropylene Fibers
Authors:   Post graduation Student, Department of Civil Engineering, Institute of Aeronautical Engineering, Dundigal, Hyderabad , Telangana, India., Dhanasree*  , Rao N. Venkat ,   Associate Professor, Department of Civil Engineering, Institute of Aeronautical Engineering, Dundigal, Hyderabad , Telangana, India., Rao P. Ram mohan ,   Professor, Department of Civil Engineering, Institute of Aeronautical Engineering, Dundigal, Hyderabad , Telangana, India.
Published: October 2019

Plain concrete is tough in terms of compression and feeble in tension, which leads to development of cracks in structure. The internal micro cracks in concrete which are formed due to tensile stresses, can be minimized and prevented by the addition of fibers in concrete. This project aims at the enhancement of concrete properties with the intrusion of hybrid fibers, by controlling the effect of cracks. The dosages of fibers are 0%, 1%, 2%, 3%, 4% to the weight of cement. The hybrid fibers used in this work are the combination of synthetic fiber of polypropylene twines of 1 to 2 cm and natural fiber of coconut coir of length 2 to 3 cm. The specimen made up of hybrid fibers and conventional concrete are tested for engineering properties like compressive, split-tensile, flexure strength. A comparative study is done between hybrid concrete and conventional concrete.
High Throughput CORDIC Architecture Based 3D-DCT/IDCT Processor
Authors:   Department of Electronics & Telecommunication Engineering, Yeshwantrao Chavan College of Engineering ,RTM University, Nagpur, India., Masram* Bharati , Karule P.T. ,   Department of Electronic Engineering, Yeshwantrao Chavan College of Engineering, RTM University, Nagpur, India.
Published: October 2019

In this paper, 8x8x8 3D-DCT/IDCT processor based on CORDIC architecture for high data rate of image processing and video coding with reduced hardware has been presented. It uses two stages of CORDIC DCT processor i.e. one is 1D-DCT and another one is 2D-DCT processor based on fully pipelined unfolded CORDIC architecture with RAM buffer. The one-dimensional DCT is useful in processing of speech waveforms. For images and video signal processing, we need a 3D version of the DCT/IDCT data, especially in coding for compression and decompression, for its best performance. This processor performs both the DCT and IDCT simultaneously with the help of CORDIC algorithm of both 3D-DCT and IDCT which has boost the speed of the processor. Ease the use of less computation based unfolded CORDIC architecture in the processor reduces complexity and power consumption. With the working frequency approximately 414 MHz less power dissipation, low latency and high throughput can be obtained. The processor has been implemented on Xilinx ISE 14.7 and design is simulated in DE-2 board. This processor has not only reduces the complication but also increases the speed which lead to broad use in image and video processing.
Enterprise Architecture for Designing Human Resources Application Standard Reference
Authors:   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia,, Wati* Amalia Fajar , Ranggadara Indra ,   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia., Kurnianda Nia Rahma ,   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia., Irmawan Dhani ,   Faculty of Psychology, Mercu Buana University, Jakarta, Indonesia., Frizki Dheny ,   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia.
Published: October 2019

Human resources within the company is the most important thing because in managing a company requires competent, creative and innovative human resources. This research was made based on observations from several companies that discuss problems and complaints from employees about human resources in the company. The human resource standard reference application is created using the TOGAF Framework which can help in designing human resource standard references because within the TOGAF framework there are several stages in building a corporate Enterprise architecture. The human resource standard reference application is also supported by UML design method. With these two methods, the human resource standard reference application can become an application for monitoring all data and reports on human resources transparently without having to bother and come directly to the office and in managing information applications of the human resource standard reference using SMS support technology.
E-Health System Based on Statistical Equation Modeling
Authors:   Research Scholar ,Deptt of Computer Science &Engg IKGPTU KAPURTHALA, PUNJAB, Kaur* Amandeep , Gupta Anuj Kumar ,   Professor,Deptt of Computer Science &Engg, CGC, LANDRAN, PUNJAB
Published: October 2019

In this research work, a design has been proposed for the Health Monitoring system that works with statistical equation models. The key advantage of this method is that it can work with different number of health parameters to through light on the health status of a person. The selection of the variables that will form the health monitoring model was done on the basis of three (Pearson, Kendall,spearman) correlation metrics. The root cause analysis based on OLS regression method confirms the mathematical relationship between the health indicators variables. It was found that visceral fat, as health indicator and as a dependent variable can act as function of seven other variables for knowing the health condition of a person. The validation of the model is done on the basis of multiple statistical tests.
The Correlation between Customer Satisfaction and Service Quality in Jordanian Uber & Careem
Authors:   Department of Computer Science, Middle East University, Amman, Jordan., Murad Sharefa , Al-Kayem Aisha ,   Department of Software Engineering, Princes Sumaya University for Technology, Amman, Jordan., Manasrah Anood ,   Department of Software Engineering, Princes Sumaya University for Technology, Amman, Jordan., Halemah Nancy Abu ,   Department of Software Engineering, Princes Sumaya University for Technology, Amman, Jordan., Qusef* Abdallah ,   Department of Software Engineering, Princes Sumaya University for Technology, Amman, Jordan.
Published: October 2019

Customer satisfaction is a great concern for all companies in all sectors, to measure customer satisfaction it is necessary to measure the service quality to examine the relationship among them. In this paper, SERVQUAL model is used to measure service quality and the effect of these dimensions (tangibles, responsiveness, empathy, assurance, reliability) in customer satisfaction on intelligent transport applications (Uber & Careem) in Jordan by conducting an online questionnaire. The archived results show that Reliability has a high degree of importance on the impact of customer satisfaction and 89.2 % of the sample prefer to use Uber & Careem smart app rather than traditional taxis.
An Encrypted key Exchange Protocol to Secure Communication among Fog Nodes and the Cloud
Authors:   CSE department, GRIET, Hyderabad, India., Karuna* G. , Goutami Bijjam ,   CSE department, GRIET, Hyderabad, India., Rupa B. ,   CSE department, GRIET, Hyderabad, India.
Published: October 2019

Fog computing is considered as a significantly virtualized perspective that can enable preparing at the Internet of Things devices, living in the edge of the framework, to convey organizations and applications even more capably and feasibly. Since Fog preparing starts from and is a non-minor development of circulated registering, it gets various security and insurance troubles of dispersed processing, causing the expansive stresses in the examination gathering. To engage genuine and confidential exchanges among a social occasion of fog centre points, proposes a capable key exchange show in perspective on figure content approach characteristic based encryption to develop secure correspondences among the individuals. To achieve confidentiality, approval, capriciousness, and access control, to join CP-ABE and mechanized mark techniques. The proposed method explores the efficiency to show similar to security and execution.
Spread Spectrum Sensing Techniques for Transformer Frequency Response Data
Authors:   Associate Professor, Dept. of ECE, CMR Engineering College, Kandlakoya, Telangana, India, Reddy* B Siva Kumar , Goel Anuj Kumar ,   Professor, Dept. of ECE, CMR Engineering College, Kandlakoya, Telangana, India
Published: October 2019

With the advent of wireless communication, the problem of data security is of greatest interest. In this paper, spread spectrum techniques have been employed due to its advantages in providing data security. Further, the mechanical integrity of a transformer is investigated using an off-line diagnosis test called as Frequency Response Analysis (FRA). The FRA data of a transformer has been taken as the input signal which is being transmitted from the field where transformer is kept and received at the control room. Furthermore, Direct Sequence Spread Spectrum (DSSS) and Frequency Hopping Spread Spectrum (FHSS) are employed on FRA data and analyzed the signals by transmitting over Additive white Gaussian noise (AWGN) and Rayleigh faded Channels.
Sentiment Analysis for Customer Opinion on Hotel Using Machine Learning Techniques
Authors:   Dept. of Computer Science & IT, Dr.B.A.M. University, Aurangabad, India., Balande* Bharti B. , Deshmukh Sachin N. ,   Dept. of Computer Science & IT, Dr.B.A.M. University, Aurangabad, India.
Published: October 2019

Opinions from others play a significant part to take our own decision, The people’s opinions, attitudes and emotions are a computational study toward an entity is called as Sentiment Analysis (SA) or Opinion Mining (OM). In today's world, everything like business, organization and even individuals wants to know opinion from public or customers about their presentation, products and about their services which will give clear idea about their product, portfolio in the market and if these services is not up to the mark how their services they improve, so that their business will perform better. To give output as positive, negative or neutral and find the difference of a specified user text or data from the dataset is the main task of the sentiment or opinion analysis. The opinions, sentiments and subjectivity of text are computational treatment in text mining with Sentiment Analysis (SA). With the help of sentiment analysis this paper describe the machine learning classification techniques for hotel reviews for which dataset obtained from Trip advisor hotel reviews website. System got 99.07 % accuracy for MAXENT Classifier with Train size and Test size 80% and 20% respectively.
Automatic Facial Expressions and Identification of different face reactions using Convolutional Neural Network
Authors:   Assistant Professor, Department of ECE, Salem., R* Anand , P.K Kalkeseetharaman ,   Department of ECE, Sona College of Technology, Salem., Kumar S Naveen ,   Department of ECE, Sona College of Technology, Salem.
Published: October 2019

Automatic Face expression is the significant device in computer apparition and a predictable knowledge discovery application in automation, personal security and moveable devices. However, the state-of-the-art machine and deep learning (DL) methods has complete this technology game altering and even better human matching part in terms of accurateness. This paper focuses on put on one of the progressive deep learning tools in face expression to achieve higher accuracy. In this paper, we focusses on Automatic Facial Expressions and Identification of different face reactions using Convolution Neural Network. Here, we framed our own data and trained by convolution neural networks. Human behavior can be easily predicted using their facial expression, which helps marketing team, psychological team and other required team to understand the human facial expression more clearly.
Energy Efficient Hierarchical Clustering using HACOPSO in Wireless Sensor Networks
Authors:   Department of Computer Science & Engineering, S J B Institute of Technology, Bengaluru, India., G S* Pavithra , N V Dr. Babu ,   Department of Electrical & Electronics Engineering, S J B Institute of Technology, Bengaluru, India.
Published: October 2019

The Wireless Sensor Network (WSN) is a collection of a various number of sensor node involved in a tremendous region for communicating data packets from one place to another in a productive way. The most significant techniques in the WSN are clustering, power consumption, lifetime and productive transmission of information in a secured manner with interconnected mobile nodes in networks. The clustering is the process of grouping the nodes for sharing the data packets to one cluster member to another cluster member through cluster heads present in the networks, which saves energy. Hence, K-Means clustering algorithm is used along with the Hybrid Ant Colony and Particle Swarm Optimization (HACOPSO) to produce a hierarchy of each CHs and observe that the energy savings increase with the number of levels present in the hierarchy. Ad hoc On-Demand Distance Vector Routing (AODV) uses two different operations to find and maintain routes: the route discovery process operation and route maintenance. Therefore, “K-Means-HACOPSO” methodology precisely transmit data from source to destination by evaluating better through-put, packet delivery ratio, packet loss, end-to-end delay and energy consumption in a secured environment.
Failure Node Detection and Recovery in Wireless Sensor Networks
Authors:   Associate Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India., Thangaraj* S. John Justin , Khanna M. Rajesh ,   Associate Professor, Department of Information Technology, Vel Tech Multi Tech Dr.Rangarajan Dr. Sakunthala Engineering College., Balamanigandan R. ,   Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India.
Published: October 2019

A Wireless Sensor Network may often consist of hundreds of distributed sensors. Our goal is to formulate wireless sensor networks (WSNs) fault identification problem in terms of pattern classification and to introduce a newly developed algorithm, neighbor node hidden conditional algorithm (NHCA) to determine the unknown path through which packets are transmitted from source to destination. We propose a concept of fault recovery in WSN using clustering. This includes the protocols of Dynamic Delegation based Efficient Broadcast and Neighborhood Hidden Conditional Random Field Algorithm. The history of transmission is classified according to the pattern, sorted and ranked along with the cluster information. The data privacy is maintained with in the cluster during the packet transmission apart from the destination which may present outside the cluster. The leader of the cluster is restricted only to view the transmission path in order to maintain the confidentiality of the data transmitted. Our simulation results strongly enforce fault recovery in quick time and also maintain the confidentiality of data.
Prediction of Seismic zone in India using Neural Network Algorithms
Authors:   PG & Research Department of Computer Science, Rajah Serfoji Government College, Thanjavur, India., Sangeetha* K. , Mohankumar K. ,   Head, PG & Research Department of Computer Science, Rajah Serfoji Government College, Thanjavur, India.
Published: October 2019

In this world, earthquake is a major catastrophe which creates huge amount of loss in living non living things. The prediction of an earthquake is an important task in seismology. Neural network performs a key task in the prediction of earthquake. The neural network architecture are created with different input layer and hidden layers with deep learning optimization algorithms. The input layer was developed with the parameters of historical earthquake data of India taken from India Meteorological Department (IMD). The earthquake event such as date, latitude, longitude, depth, magnitude are mathematically converted into seismic indicators depend on Gutenberg-Richter’s inverse law, are the input layers of this neural network model. The developed network model was trained with set of data items using neural network algorithms such as Backpropagation and sequential learning. The Backpropagation is used to find the magnitude prediction and sequential learning is used to find the prediction model for the cartographic risky areas. The loss and accuracy of the model are analyzed with the help of software tool, Disaster Management System which is developed for this work using Python. The deep neural network optimizers such as Stochastic Gradient Descent (SGD), Adaptive Gradient algorithm (AdaGrad) and Root Mean Square propagation (RMSprop) are used to optimize the prediction model. The optimizer produced earthquake prediction model with high ability and more accuracy. Also give the cartography which shows the seismic zone in India face earthquake in future.
Effect of Mortar Strength On The Behaviour of Ferrocement Panel Under Low Velocity Impact
Authors:   Master’s degree program in structural engineering in MIT World Peace University, Pune-India, Patel* Yash N. , Gaidhankar Prof. Darshan G. ,   is currently associate professor in school of civil engineering, MIT World Peace University, Pune-India, Kulkarni Prof.Dr.Mrudula S. ,   is currently professor in school of civil engineering, MIT World Peace University, Pune-India.
Published: October 2019

The concept of industrialization of the construction technology has emerged as well accepted and preferred option in the field of building construction now days in order to reduce in – situ construction up to maximum extent. Ferrocement is the one of the relatively new cementitious composite considered as a construction material. The main aim of this study is to investigate the behavior of Ferrocement panel under low velocity impact. Size of panel is 250 x 250 mm and thickness is varying from 20mm to 40mm. Corrugated fibers were added in panels. Volume of corrugated fibers was considered as 1.5% of total volume of panel. Weld mesh and woven mesh were used in ferrocement panels. Numbers of layers of mesh were 2 and 3. Height of drop is 1m. M30 and M40 Grade of mortar were used. Equivalent stress, Normal stress and Deformation were the main parameters for this research work. From the results it can be concluded that weld mesh with corrugated fibers is good at the impact resistance.
Research on Enhancing RPL for Improved Performance in IOT Networks
Authors:   Senior Lecturer, Government Polytechnic Kohima, Nagaland., Chang* Hangkum Sao , Dutta Dr. Maitreyee ,   Professor and Head, Information Management and Coordination, NITTTR, Chandigarh
Published: October 2019

RPL (IPv6 Routing Protocol for Low-Power and Lossy Net- works) was developed by IETF (Internet Engineering Task Force) as the protocol for LLNs (low power and lossy networks) that comprise of resource constrained components such as those used in Internet of Things applications. Since then the research community and the industry have come up with many enhancements of RPL aimed at achieving a diverse range of objectives that include better performance under heavy traffic loads, higher throughput, lower packet loss, energy conservation, longer network lifetime, mobility of nodes and enhanced security. This paper presents a review of the various methods proposed to achieve these objectives. A comparative review and a taxonomy of these methods are presented in this paper. We aim to provide valuable insights into RPL and present the foundation for future works.
“No Energy” How’s Life (A General Reaction)
Authors:   Associate Prof. Dept. of ECE, Dr. C.V.Raman University, Bilaspur, Chhattisgarh, India., Mitra* Saurabh , Mitra Dr. Jayati Chatterjee ,   Associate Prof. Dept. of Chemistry, Dr. C.V.Raman University, Bilaspur, Chhattisgarh, India., Kashyap Rashmi ,   Assistant Prof. Dept of ECE, Dr. C.V.Raman University, Bilaspur, Chhattisgarh, India., Awasthi Akanksha ,   Assistant Prof. Dept. of ECE, Dr. C.V.Raman University, Bilaspur, Chhattisgarh, India.
Published: October 2019

Vitality is the capacity to do work Vitality comes in various structures: • Heat (warm) • Light (brilliant) • Motion (dynamic) • Electrical • Chemical • Nuclear vitality • Gravitational Individuals use vitality for everything from making a bounce shot to sending space explorers into space. There are two kinds of vitality: • Stored (potential) vitality • Working (dynamic) vitality For instance, the sustenance an individual eats contains synthetic vitality, and an individual's body stores this vitality until the individual in question uses it as dynamic vitality amid work or play. Vitality sources can be arranged as sustainable or nonrenewable At the point when individuals use power in their homes, the electrical power was most likely produced by consuming coal, by an atomic response, or by a hydroelectric plant on a stream, to give some examples sources. In this manner, coal, atomic, and hydro are called vitality sources. At the point when individuals top off a gas tank, the source may be oil refined from unrefined petroleum or ethanol made by developing and preparing corn. Vitality sources are partitioned into two gatherings: • Renewable (a vitality source that can be effectively recharged) • Nonrenewable (a vitality source that can't be effectively recharged) Sustainable and nonrenewable vitality sources can be utilized as essential vitality sources to create valuable vitality, for example, warmth or used to deliver auxiliary vitality sources, for example, power.
Computed Tomography Medical Image Compression using Conjugate Gradient
Authors:   Dept.of ECE ,GITAM(deemed to be university),Visakhapatnam,Andhra Pradesh,India, Rani* S.Saradha , Rao G.Sasibhushana ,   Dept.of ECE, AU College of Engineering(A),AU,Visakhapatnam, Andhra Pradesh, India., Rao B.Prabhakara ,   Dept.of ECE,JNT University, Kakinada, Andhra Pradesh,India.
Published: October 2019

Image compression which is a subset of data compression plays a crucial task in medical field. The medical images like CT, MRI, PET scan and X-Ray imagery which is a huge data, should be compressed to facilitate storage capacity without losing its details to diagnose the patient correctly. Now a days artificial neural network is being widely researched in the field of image processing. This paper examines the performance of a feed forward artificial neural network with learning algorithm as conjugate gradient. Various update parameters are considered in conjugate gradient methodology. This work performs a comparison between Conjugate gradient technique and Gradient Descent algorithm. MSE and PSNR are used as quality metrics. The investigation is carried on CT scan of lower abdomen medical image.
Antecedents of Organic Food Consumption among the Indian Customers
Authors:   Director , Datta Meghe Institute of Management Studies, Nagpur, Chib* Dr. Shiney , Dewal Dr.Kanchan ,   Assistant Professor, Datta Meghe Institute of Management Studies, Nagpur, Artani Kanchan ,   Assistant Professor, G H Raisoni chool of Management, Madhav Nagari, Nagpur., Turkar Sneha ,   Associate Executive, HCL Technologies, Nagpur.
Published: October 2019

Organic food products refers to food raised, grown and stored and/or processed without the use of synthetically produced chemicals or fertilizers, herbicides, pesticides, fungicides, growth hormones and regulators or generic modification. Generally people are aware about the benefits of these products. But still the products have not achieved the market share in India, as expected. This people is an effort to identify the factors, which influences the purchase of organic food products. For this the researchers have developed a questionnaire and administered on the respondents. Both online and off line data collection was done, to cover the major areas, so that data can be collected from distinct places. The paper explored the awareness level about organic food products, influence of demographic variables on organic food consumption and factors affecting organic food purchase intention.
Problem Analysis of RPL Overhead in 6LOWPAN using 5w1h Model
Authors:   Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia, Yusoff* Nin Hayati Mohd , Zakaria Nurul Azma ,   Center for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia., Harum Norharyati ,   Center for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia.
Published: October 2019

Smart Home (SH) is one of the Internet of Thing (IoT) ecosystem that is experiencing rapid growth, especially in communication and application technologies. However, most applications of SH are embedded devices that are categorized as low power, less memory usage, and limited cost. Therefore, the IPv6 Low Power Area Network (6LoWPAN) is introduced by Internet Engineering Task Force (IETF) in order to fulfill the connectivity requirement of embedded devices. However, the 6LoWPAN standard is restricted to 250 kbps and the frame length is limited to 127 bytes, whereas the packet size over IPv6 is 1280 bytes. Because of this glaring discrepancy, routing becomes the main issues in 6LoWPAN network capability. There is a number of existing routing protocols for 6LoWPAN, and among them RPL is effective in terms of latency and throughput, but the overhead is considerably high when implemented in a large-scale network. Therefore, this study focusses on analysing the causes of RPL overhead in the 6LoWPAN network. For that, this document analysis employed the 5W1H (What, Where, When, Why, Who and How) model in investigating and describing the causes of RPL overhead in 6LoWPAN. The results of this model show four (4) critical parameters needed to be addressed in solving the RPL overhead problem: i) network topology change, ii) limitation of 6LoWPAN, iii) Node failure in the large network and iv) additional transmission information. Furthermore, the future goal of this study is to come up with a novel 6LoWPAN routing protocol algorithm that would be used as high-level technical recommendations for IoT SH ecosystem communication.
Learning Traditional Thai House through Gamification Based with 3D Virtual Application
Authors:   Computer Science Program, Faculty of Science and Technology, Suan Sunandha Rajabhat University. Thailand., Kularbphettong* Kunyanuth , Ajimakul Nopichai ,   Project Manager of Knack Corporation Company., Ampant Udomlux ,   Information System Program, College of Innovative Technology and Engineering, Dhurakij Pundit University. Thailand.
Published: October 2019

Traditional Thai house, called “Ruean Thai”, is a local wisdom in Thai architecture which is unique style in Thailand and it is very important and valuable knowledge to be passed from generation to generation. However, with the massive changes of latest technology, children or young people pay less attention to Thai wisdom and culture. Therefore, this research aims to preserve the Thai wisdom and cultural learning in Thai house by using gamification techniques and Thai house models in three dimensions to solve the above problems. This Thai house game application is a game based learning program to assemble Thai house models in three dimensions for entertainment and learning about the components of Thai houses of each region. In our project, students interact with a Thai house game application based gamification technique and able to learn and take challenges through gaming to expand and test their knowledge. The result shown that using Thai house game application enhances a more comprehensive understanding and engage student to raise their time learning and enjoyment during the experimental process.
Assessment of Flood Hazard and its Effects in Dolokhat village of Lakhimpur District, Assam
Authors:   Research Scholar, Department of Geography, Gauhati University, Guwahati-14, Assam, Khan* Azruddin , Bhuyan Manash Jyoti ,   Research Scholar, Department of Geography, Gauhati University, Guwahati-14, Assam., Borah Debashree ,   Research Scholar, Department of Geography, Gauhati University, Guwahati-14, Assam.
Published: October 2019

Land of rivers, India annually faces the perennial problems of flood and siltation basically along the flood plain region since millennia. Situated on a tectonically active zone and transversed by the Brahmaputra and Barak river system, Assam has been recognized as the worst sufferer. Increasing magnitude and devastation of the hazard is much owed due to the great earthquake of 1950 along with both natural and human-induced factors and activities. The regions located at upper Brahmaputra valley are frequently inundated and eroded wiping away vast areas of cropland, properties, and human lives. As such, the Lakhimpur district of Assam faces similar havoc each year with massive destruction leaving many people helpless and homeless. The people living in the rural areas of the district had to struggle hard to sustain their lives and livelihoods and thus, adopted their indigenous or traditional ways and means of coping with the floods. This paper, therefore, attempts to study the causes and impacts of floods caused by the river Singri, a sub-tributary of the Brahmaputra river on the inhabitants of Dolokhat village located in Lakhimpur district. This study also takes into account the differential shifting patterns of the river for a period of 12 years from 2005 to 2017, wherein highest erosion was observed during 2017 eroding 22.60 hectares of land displacing people and livestock. The study was undertaken using both primary and secondary sources of information. Data and information collected have been processed and analyzed using Google Earth Pro, ArcGIS 10.9.2, Microsoft Word and Microsoft Excel. Such information will enable the planners, policy-makers, geomorphologists, etc. in targeted solutions and strategies to initiate measures and mitigate such problems so that the adverse effects of floods could be reduced to a certain extent.
A Hybrid Genetic Algorithm Based Rainfall Prediction Model Using Deep Neural Network
Authors:   CSE, Sri Venkateswara college of Engineering, Tirupati, India., Satish* P. , Srinivasulu S. ,   CSE, Sri Venkateswara college of Engineering, Tirupati, India., Swathi Dr.R. ,   CSE, Sri Venkateshwara College of Engineering, Tirupati, India..
Published: October 2019

This paper is intended to design and develop an efficient prediction algorithm in the context of forecasting in the precipitation as well as the intensity of the rainfall in a local region over a relative short period of time. Despite of several existing addressing the problem of forecasting rainfall, still it is remind as an open challenge in the context of dynamic data acquisition and aggression. Prediction of rain is main application of science and technology to predict the state of the atmosphere. The main objective of the study is to develop a Genetic Algorithm based approach that utilize dimensionality reduction technique and Multi-layer Perceptron for efficient and dynamic analysis of real time data. Furthermore a deep neural networks based framework is proposed to predict rainfall of a certain region. A Hybrid genetic algorithm presents a novel solution to predicting the rainfall in certain area or different regions by using Deep Neural Network.