bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Behavior of Intrusion Detection System (Ids) Based On Ensemble Base Classifier (EBC)
Authors:   Associate Professor, Department of Computer Science, ICOER, Wagholi, Pune, India., Phursule Dr. Rajesh
Published: September 2019

There is a tremendous growth in the area of information technology due to which, network defence is also facing major challenges. The conventional Intrusion Detection System (IDS) is not able to prevent the recent attacks and malwares. Hence, IDS which is an essential component of the network needs to be protected. Data mining introduce to the process of separate hidden, previously unknown and useful information from huge databases. Data Mining based Intrusion Detection System is combined with Multi-Agent System to improve the presentation of the IDS. We combine the classifiers which is the widespread approach, to increase the accuracy of a single classifier. For experimentation purpose, we use a benchmark intrusion detection dataset, which is KDDCup’99 and the accuracy of the classifiers were estimated using 10-fold cross validation method. In this work, we use the feature selection methods, namely Flexible mutual information based feature selection (FMIFS) and hybrid feature selection algorithm (HFS) to evaluate the importance of features. This work provides Support Vector Machine (SVM), Nave Bayes (NB) and Feed Forward Neural Network (FFNN) to classify attack and normal threads as well as to improve the accuracy we ensemble all classifier into single hybrid classifier using Bagging algorithm. The proposed hybrid approach achieves an accuracy rate of 95.11
Sentiment Analysis using Optimized Feature Sets in Different Twitter Dataset Domains
Authors:   PhD Research Student, MUIT, Lucknow., Raut Anup , Pandey Dr. Rahul K. ,   Research Guide, MUIT, Lucknow
Published: September 2019

in the last years, the relevance of sentiment analysis is broad and dominant. The capability to take out insights from social data is a tradition that is being extensively accepted by all over globe. Sentiment Analysis has turn out to be a hot-trend issue of technical and marketplace research in the area of Natural Language Processing (NLP) and Machine Learning. Sentiment analysis is enormously useful in social media supervising as it permits us to expand an impression of the wider open estimation behind definite topics. Investigation of social media streams is typically limited to just essential sentiment analysis and count based metrics. This is of the same kind to just scratching the outside and missing out on those elevated value insight that is ahead of you to be discovered. There’s a lot of effort to be done, but perfections are being prepared every day. It is a way to appraise on paper or verbal language to settle on if the expression is favorable, unfavorable, or unbiased, and to what level. Today’s algorithm-based sentiment analysis tools can touch vast amount of client response constantly and precisely. Balancing with text analytics, sentiment analysis exposes the customer’s estimation concerning topics ranging from your goods and services to your position, your advertisements, or even your challengers. These efforts scrutinize the crisis of studying texts, like posts and reviews, uploaded by user on Twitter. The Support Vector Machine (SVM), k-nearest neighbors algorithm (KNN) and proposed optimized feature sets model is offered to progression the tweet features and to recognize the out of sight sentiments from these tweets. These essential concepts when used in combinations become a very significant tool for analyzing millions of variety conversations with human echelon accurateness. The projected optimized feature sets model Sentiment Analysis exercise the assessment metrics of Precision, Recall, F-score, and Accuracy. Also, average measures weighted F1-scores are constructive for categorization of Positive, Negative and Neutral multi-class problems. The running time of the technique is evaluates by accomplishing diverse methods in the same investigational setup consisting a cluster of 8 nodes. Planned optimized feature sets model Sentiment Analysis reachs 82 % accuracy as compare with SVM 78.6 % and KNN 75 %. Further, while analyzing sentiments of tweets we have measured only tweets in English acknowledged by Twitter streaming API.
Use of RS and GIS for Land Use/Land Cover of Historical Badami Town, Bagalkot District, India
Authors:   Research scholar, Department of civil engineering Basaveshwar Engineering College, Bagalkot, INDIA., Kumar P. Manju , Soraganvi Dr. Veena S. ,   Professor, Department of Civil Engineering, Basaveshwar Engineering College, Bagalkot. INDIA., D C Dr. Lingadevaru ,   Team Lead, Karnataka State Remote Sensing Application Centre, Bangalore.
Published: September 2019

India is one of the biggest countries and is 7th largest nation in the world; also India is 2nd country in population next to China. The Towns are like trees, both of them grow under natural limits. One of the objectives of any master plan is to guide town development by studying the natural properties of the town border and to determine a suitable direction of town growth. It should include general information for understanding the effective factors on the town’s form. This report is mainly concentrated towards the historic Badami town development to prepare an accurate land use/land cover map on 1:21,000 scale appropriate allocation of land resources of the Badami A need for GIS driven analysis of factors such as urban planning, which in turn create various types of geo-referenced data, GIS was carried out to create, store, edit, visualise, analysis, and to present the data needed for carrying out the allocation of land for meeting various needs of the smart city.After the implementation of the Smart concepts desirable results have obtained and these outputs have the potential to fulfil the need of all the inhabitants without causing any pollution. The outputs of this project would help in sustainable planning to existing town.
Segmentation of Human Spermatozoa using Threshold-Based Image Segmentation
Authors:   School of Computing, SASTRA UNIVERSITY, Thanjavur, India., Prabaharan L. , Sivapathi A. ,   School of Computing, SASTRA UNIVERSITY, Thanjavur, India., Raghunathan Dr. A. ,   AGM (Retd.), Bharath Heavy Electricals Ltd., Trichy, India.
Published: September 2019

The role of image processing in processing and analyzing the microscopic medical images is the most challenging and required task in the assisted method of fertilization for human society. The Human eye evaluation for the process of detecting the defective spermatozoa from the sample semen smear using the microscope yields subjective results, which may vary from person to person. The objective evaluation is based on an automated computer program segments the portion of interest from the image based on segmentation techniques. The effective segmentation in the medical image is to highlight the expected portions such as head, tail, and mid-piece for the further process of analyzing the defects in the sperm cell. Cluster-based image segmentation is one of the effective methods to segment the object from the background in the microscopic medical images [1]. Entropic thresholding techniques also had an impact on the segmentation of medical images [2]. We have implemented the various threshold based image segmentation and compared their results with the help of segmentation metrics and showed the effectiveness of thresholding techniques for microscopic medical images.
7T Based SRAM Topologies with Low Power and Higher SNM
Authors:   Department of Electronics & Communication Engineering, Government Engineering College, Ramangara, India, Research scholar VTU Belgaum., Kumar C S Hemanth , B S Kariyappa ,   Department of Electronics & Communication Engineering, RVCE,Bengaluru,India.
Published: September 2019

Now the era is of electronic gadgets like processors and portable devices, in which Memory plays a significant role through the usage of Static RAMs (SRAMs).Hence designing of Low power SRAM is immense for applications. But the design of SRAM is involved in higher power requirement. So there is still scope for adequate Low power Memory Array design. The Main Moto of this paper is involved in designing & Simulating Low Power 16x16 SRAM Arrays using 7T SRAM cells based on Conventional, Self Controllable Voltage (SVL) & Improved Self Controllable Voltage (I-SVL) methods. Also Comparative Power and SNM Analysis is carried between Conventional 7T, 7T-SVL and 7T-ISVL based Arrays. The Proposed Array using 7T Cell consumes 6.24mW which is 67.64% lesser than the Array design [2].Also I-SVL based 7T SNM is better than the SVL-7T and 7T based cell.The proposed work is carried using cadence virtuoso tool with standard library gpdk 180nm.Also Proposed Array based on I-SVL is efficient in terms of power. The proposed Cell SNM resulted in 68.57% higher in comparison with existing cell of 8T and 10T [3].
Advanced Secure Energy Aware Trade-off Model to Control Data Communication in Wireless Networks
Authors:   Assistant Professor, Research scholar, Department of computer science and engineering, ANU, KLEF, Guntur, AP, India., Nagendram S. , H Rao Dr. K. Ramchand ,   Professor, Department of computer science and engineering, ASN College Engineering and Technology, Tenali, Guntur, AP, India.
Published: September 2019

Secure data transmission in ad hoc related wireless networks is an aggressive concept in present node to node communication. Secure energy trade-off between different node communication is also major challenge in wireless ad hoc networks. To provide efficient communication with secure data aware between nodes in ad hoc wireless networks. So that in this paper proposes and introduces Advanced Secure Energy Aware Trade-off Model (ASEATM) for energy trade results in wireless ad hoc networks, also use Elliptic curve cryptography to describe/ provide source authentication with respect to efficient communication in wireless networks. Our experimental results show efficient secure communication in wireless ad hoc networks with comparison to existing approaches in real time scenario.
Design and Analysis of Metamaterial Unit CellUltra-Wide Band Triangular Antenna for C Band Applications
Authors:   Research Scholar,Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, Hyderabad-500007, Telangana, India., Reddy Thogaru Abhishek , Paidimarry Chandra Sekhar ,   Professor, Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, Hyderabad-500007, Telangana, India.
Published: September 2019

This works discuss about the design and development of a metamaterial triangular micro strip ultra-wideband antenna for C-Band communication. This study includes design and performance analysis of patch based antenna to serve C- band applications such as satellite communications. In first scenario, simple triangular antenna with normal ground plane has designed and analyzed. And In second scenario, to improve the antenna radiation, ground has altered and replaced with a unit cell structure. To further improve the antenna performance Split Ring Resonators are incorporated along with radiating patch. In these three different scenarios, antenna performance has been improved from first scenario to last scenario, while dimension of antenna got miniaturized, which is most desirable feature. The antenna gain of antenna in three scenarios is 4.96 db, 5.65 db and 6.15 db respectively. Antenna radiates over 6-7 GHz frequency band in first case, whereas in second scenario it radiates from 5.7 – 7.1 GHz and in third scenario antenna radiates at 5.6-7.4GHz band. This antenna can be placed in limited space.
Seismic Effect on Multi Storey Building with Different Positioning Of Floating Column
Authors:   PG Student M.Tech, IARE, Hyd, TS, India, Wasay Mohammed Abdul , Baraik Suraj ,   Assistant Professor, IARE, Hyd, TS, India
Published: September 2019

Modern multi storied buildings are being constructed with floating column at the ground floor to meet the requirements of parking or other aesthetic or utility value. Masonry buildings have proved to be most vulnerable when earthquakes strike in any part of the world. The damage caused by the earthquake cannot be eliminated but it could be mitigated by taking extra precaution. Floating columns can be constructed at any level or storey, at any point in the construction area. Seismic analysis is a major tool in earthquake engineering; this is used to understand the response of buildings due to seismic excitations in a simpler manner. Response Spectrum Analysis was used. Assumptions were made to study the seismic effect on different position of floating column for a six storied RC framed building.
Kinetic Modelling of Anthocyanin Extraction from Grape (Vitis vinifera) using Response Surface Methodology
Authors:   Ph.D Scholar, Department of Food Processing & Engineering , Karunya Institute of Technology & Sciences , Coimbatore, Tamil Nadu, India., Kannampilly Nikki John , Devadas CT. ,   Former Professor & Director, Department of Food Processing & Engineering, Karunya Institute of Technology & Sciences, Coimbatore, Tamil Nadu, India.
Published: September 2019

Anthocyanins are natural food colorants and functional compound, those substitute synthetic colours. One of the major source of Anthocyanin is Grapes, and by implementing suitable extraction process, it is possible to obtain high yield extract. In our study, we have optimized anthocyanin extraction from grape pomace (Vitis vinifera) by using response surface methodology. Owing to its simple, economical and efficient alternative to other extraction process, this method of extraction was found to be appropriate. Various parameter combinations were performed to determine the anthocyanin concentration such as extraction temperature, extraction time and pH and the process was optimized and validated. Various characterization of grapes and anthocyanin such as moisture, ash, total phenolic content, quantification of anthocyanin, HPLC and FTIR were also performed.
Mechanical Properties and the Effect of Sliding Distance on Aluminium Composites Material Prepared Using Multiwalled Carbon Nanotubes as Reinforcements
Authors:   Assistant Professor, Department of Mechanical Engineering, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka, India, M Rajesh , C.R Mahesha ,   Assistant Professor, Industrial Engineering and Management Department, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka, India
Published: September 2019

Interest in multiwalled carbon nanotubes (MWCNTs) as the reinforcements for aluminium composites has gained much importance in the production of latest light weight and high specific strength materials. Various investigations have been conducted to understand the effect of the carbon nanotubes inclusion in the aluminium metal matrix. The present work was intended to enumerate the enhancement in the mechanical properties of the prepared aluminium composite material. The study involves the electroless technique of deposition of the nickel on the surface of the multiwalled carbon nanotubes in 35.58% proportion. Followed by the fabrication of the aluminium composite materials using stir casting technique. The determination of the tensile strength, hardness evaluation and wear studies relating to sliding distance were conducted in detail. The preparation of the composites were done with 0wt%, 2wt%, 4wt% and 6wt% of nickel coated MWCNTs addition, the composites were produced via liquid metallurgy routing. The increase in the strength when the specimen was subjected to the tension test was found upto 23.65% and the brinell hardness number was increased upto 15.38% when compared with ascast aluminium. The effect of variation of the sliding distance and wear mechanism of the fabricated composites were studied by keeping the load and sliding velocity as a constant factor and it was observed that the wear rates increased with the sliding distance. Wear behaviour results for the developed composites have been reported.
A Weight based Scheme for Improving the Accuracy of Relationship in Social Network
Authors:   Research Scholar, Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India., A Rohini , T SudalaiMuthu ,   Associate Professor, Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India.
Published: September 2019

The usage of social media has become unavoidable in the last decade. The social media is highly dynamic in nature and grows rapidly. The community network offers a rich expedient of various data. The detection of communities is based on the frequency in the networks which is usually represented by graphs. The vertices (nodes) are representing the social actor and the edges (links) represent the relation between those actors. The community link detection is as hard as the graph increases up to millions of vertices and edges. The accuracy of link prediction for inferring missing (erased or broken) links is very complex due to the dynamic nature of links. The links are updated from time to time and the new links are established dynamically. As the links are appeared and disappeared dynamically, the accuracy of identifying the edges of the social network graph of the user is complex in nature. Many efforts have been put up in developing link prediction algorithms in the past, but still there is a lacuna in accuracy in predicting inferred / broken links. A weight based link prediction algorithm is proposed to improve the accuracy of the link prediction on inferred / broken links in the social media. In this method, a weight based link analysis is employed to quantify the relative value between two nodes in the community network. The correlation value for relationship is also determined over a period of time using the designed relationship matrix. The relationship value between the nodes is computed by a Euclidian distance approach. The relationship value of each node is determined by the relationship equation using weight values. The proposed approach is experimented in constrained environment for 2 users’ Facebook usages over a period of a year. The accuracy of relationship is used as performance metrics. The results shown that the accuracy is improved 2.35% more than random predictor method.
IoT Based Farming Recommendation System Using Soil Nutrient and Environmental Condition Detection
Authors:   Apex Institute of Technology, Chandigarh University, Mohali, India., Kumar Arun , Kumar Abhishek ,   Apex Institute of Technology, Chandigarh University, Mohali, India., De Akash ,   Apex Institute of Technology, Chandigarh University, Mohali, India., Shekhar Shashank ,   Apex Institute of Technology, Chandigarh University, Mohali, India., Singh Rohan Kumar ,   Apex Institute of Technology, Chandigarh University, Mohali, India.
Published: September 2019

Over one third of world workforce are employed in agriculture and the amount is steadily falling because of the financial losses of the farmers. One of the key reason behind this financial loss is the lack of technology in agriculture. Continuous cropping and overuse of fertilizers cause the decline in soil productivity and effect the environment as well. This paper demonstrates how the soil productivity can be optimized by implementing an IoT (Internet of Things) based model. Specifically, the paper describes the way to identify the amount of soil nutrients and environmental conditions, followed by the recommendations for cropping and site specific fertilization. Nitrogen, phosphorous and potassium are the key nutrients that are responsible for the plant growth. Soil moisture, pH level of soil and environmental conditions also effects the productivity of crops. In this present work, the system incorporated with various chemicals and sensors to report NPK level, pH level, soil moisture level, temperature and weather forecast. The proposed system takes the soil sample as the input and performs the chemical reactions, corresponding changes in the color of sample is sensed by color sensors and decoded by colorimetry technique. An android application has been built to show the test report and recommendations based on sensed data. The paper has proposed a scientific way to develop a robust, fully automated and low-cost smart farming solution to suit the socioeconomic conditions of small scale farmers in developing countries.
Informational Support of Cash Flow Management Processes in Public Administration
Authors:   Department of Economics and Marketing, Kharkiv Petro Vasylenko National Technical University of Agriculture, Kharkiv, Ukraine, Onegina Viktoriya
Published: September 2019

Management functions of the state in the field of regulation of financial flows is the basis of a modern market economy. The intricate and complex nature of the control object itself also forces us to continually look for ways to increase the effectiveness of both analysis and planning techniques. High-quality informational support predetermines the effectiveness of managerial decisions in the sphere of regulation of financial flows. The wide variability of information support is the key to the ability to apply effectively administrative impact. At the same time, accounting, control and analysis are interconnected management functions that provide information support for making management decisions at any level. The information analysis technique based on fuzzy decision trees is an innovative and well-proven way to provide government institutions with a reliable analytical tool.
Implementation of Technopreneurship Scientific Learning for Produce Electronic Product Prototypes in Engineering Education
Authors:   Faculty of Teaching and Education Science, Universitas Bung Hatta, Padang, Indonesia., Hidayat Hendra , Tamin Boy Yendra ,   Faculty of Law, Universitas Bung Hatta, Padang, Indonesia., Herawati Susi ,   Faculty of Teaching and Education Science, Universitas Bung Hatta, Padang, Indonesia., Hidayati Abna ,   Faculty of Education Science, Universitas Negeri Padang, Padang, Indonesia., Muji Anggarda Paramita ,   Faculty of Education Science, Universitas Negeri Padang, Padang, Indonesia.
Published: September 2019

This research aims to describe the implementation of the technopreneurship scientific learning for produce electronic product prototypes in engineering education. This research method uses a research and development approach. In this research development approach is carried out in 3 stages, namely: Phase I needs analysis and model design, Phase II develops with validity and practicality, and Phase III will implement the model. This research will only focus on phase III, namely the implementation of the model, which involves 40 students taking entrepreneurship subjects in engineering education at Bung Hatta University, Padang, Indonesia. As a result of the activities of technopreneurship scientific learning, students produce prototypes of electronic products that have commercial potential. One of the results of technopreneurship scientific learning is a prototype of an electronic product in the form of a water detector in the bath. The implementation of this tool was tested and analyzed with the Electronics Workbench software version 5.12. The measurement results from the implementation in the field show that electronic products have worked well and after the measurements are made, students make a business plan of the product, which is a water detector. A business plan that has been made has been through consumer needs analysis.
Internet Marketing in the Brand Technologies of the Tourism Industry
Authors:   Department of Economic and Environmental Problems of Seaside Regions, Institute of Market Problems and Economic & Ecological Research, National Academy of Sciences of Ukraine, Odessa, Ukraine, Andryeyeva Natalya , Davydenko Iryna ,   Department of Tourism, Hotel and Restaurant Business Odessa National Economic University, Odessa, Ukraine, Balyk Ulyana ,   Department of Marketing and Logistics, Lviv Polytechnic National University, Lviv, Ukraine, Kolisnyk Mykhailo ,   Management and Organizational Development Department, Ukraine Catholic University, Lviv,, Rulinska Olha ,   Department of Marketing, Odessa National Economic University, Odessa, Ukraine, Bulysheva Daria ,   Geodesy and Nature Management Department, Odesa State Agrarian University, Odessa, Ukraine
Published: September 2019

Due to global digitalisation, Internet marketing has long become an integral part of any effective marketing campaign. According to a Zenith Media study, the growth of the global online advertising market in 2019 is only 10%, which is the lowest increase since 2001. Rest and travel is one of the most popular and discussed topics on social networks. We share new impressions, vivid photos, videos, stories, and 90% of them somehow affect the tourism industry. The global digitalization and widespread use of mobile gadgets has changed the very essence of online behavior. We spend most of our free time on the Internet, we are happy to talk about future plans and remember them after their implementation. Thanks to modern technologies and specialized platforms, advertising campaigns on the Internet are launched in a matter of minutes, receiving instant feedback in the form of comments, applications and even sales. Internet marketing has tremendous mechanisms for targeting, analyzing and processing big data. Therefore, the future of the brand, especially in the field of tourism, depends on the use of Internet marketing by enterprises.
Wear Behavior on Magnesium Reinforced with Nano Alumina Particulates
Authors:   Department of Mechanical Engineering, V R Siddhartha Engineering College, Vijayawada, Andhra Pradesh, India., Sridhar V , Ratnam Prof Ch ,   Department of Mechanical Engineering, Andhra University College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.
Published: September 2019

The present study explores the wear properties of Mg composites with different amounts of nano- alumina particles (up to 1.4 vol. percent). Tests are carried out on wear device with a constant load of 10N, at sliding speeds range between 1 to 10 m/s compared to EN31 steel disks. Magnesium metal matrix composites reinforced by 1.4 volume percent of alumina particles (nano – sized) possess mechanical properties equivalent or even superior to alike composites of high level micron reinforcement. The outcomes reveals that the introduction of nano powder in various proportions influences the increment of wear performance of magnesium alloy and shows better wear performance at both the speeds by adding 1.4 volume % nano Al2O3 to the pure Mg and other Mg- Al2O3 composites. Due to the presence of Al2O3 as reinforcement for lower and higher sliding speeds, the improvement if found in wear property. The enhancement in wear property of the nano- composites is due to the increased hardness and strength with the nano- alumina particles presence in matrix. Initially there is increase in porosity by the addition of nano alumina to magnesium and later decreased gradually by inceasing the nano alumina percentage. Magnesium nano alumina composites can be considered as an excellent material because of better wear components are of major importance, mainly used in the aerospace and automotive engineering applications.
A Method for Automatic Vietnamese Speech Segmentation
Authors:   Department of Computer Science, Faculty of Information Technology, Industrial College, in Thanh Hoa, Vietnam,, Tuan Anh Tran Phd. Student. , Nguyen Huu Dr. Mong ,   Department of Computer Science, Department of Information Technology, Military Technical Institute, in HaNoi, Vietnam, Trong Dr. Khanh Nguyen ,   Software Engineering, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam,
Published: September 2019

In speech synthesis and recognition, the segmentation is an important step. The result of further steps depend completely on this process. There are several effective segmentation method in the literature, but for Vietnamese speech, researchers usually base on their experience to set the length while using sliding window. It causes an inefficient segmentation; and they need to try with the other value (length of voice). In this paper, we propose a method supporting in segmentation for Vietnamese speech and automatically determine the suitable length of voices and silent pause. We firstly estimate, by experimenting, the min and average length of a voice and a silent pause for Vietnamese speech in three main type speaking (slow, normal and fast). Then, based on these values, we start to segment the voice and pause by sliding window with proposed algorithm. Experiment results show that the proposed method can be used to effectively segment the Vietnamese speech.
Closed Form Solution for Outage and Average Bit Error Rate of Asymmetric Relaying System
Authors:   Department of Electronics & Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, India, Singh Brijesh Kumar , Mukhopadhyay Mainak ,   Department of Electronics & Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, India
Published: September 2019

In this paper, closed form solution of outage and bit error rate (BER) is evaluated for the purpose of performance analysis of the amplify and forward relaying scheme under the asymmetric fading environment. In this dual hop system, we have used Rayleigh fading along source S to relay R and Mixture Gamma fading along relay R to destination D. First, we have derived closed form solution of outage and then we have used this derived expression for getting closed form solution of bit error rate (BER) for different kinds of modulation. Since Mixture Gamma fading channel represents many fading channels as its special case, so proposed closed form solution of outage and bit error rate may be used for analysis of outage and bit error rate under various fading scenarios. Specifically, in this paper, for analysis of outage and bit error rate (BER), we have taken Nakagami-m fading as a particular case of Mixture Gamma fading and analyzed the performance of proposed system after observing effect of fading severity factor and signal to noise ratio (SNR) on outage probability and bit error rate (BER).
Visualization System for Water Levels and Environmental Conditions in the Flood Monitoring Information System
Authors:   Computer Engineering Department, Universitas Serambi Mekkah, Banda Aceh, Aceh, Indonesia., Satria Dedi , Yana Syaifuddin ,   Industrial Engineering Department, Universitas Serambi Mekkah, Banda Aceh, Aceh, Indonesia., Yusibani Elin ,   Electronic Engineering Department, Universitas Syiah Kuala, Banda Aceh, Aceh, Indonesia., Syahreza Saumi ,   Physics Department, Universitas Syiah Kuala, Banda Aceh, Aceh, Indonesia., Zulfan  ,   Computer Engineering Department, Universitas Serambi Mekkah, Banda Aceh, Aceh, Indonesia.
Published: September 2019

Flood disaster is a national disaster that takes a lot of victims and material for now. The government nationally implements short-term programs to anticipate disasters by supporting the various government and private institutions in developing disaster mitigation systems to reduce sustainable casualties. Based on this support, this research aims to develop a flood monitoring information system by implementing a real-time flood visualization system. System development is done by making two systems, namely hardware-based flood detection systems that are used as client systems and software-based flood monitoring information systems as servers. Flood detection systems are built using ultrasonic sensors, temperature sensors, rain sensors, Arduino microcontrollers, and Sim900A GSM modules. On the flood monitoring information system server using the Xampp component as a server application and Gammu as an SMS application. The communication system between the two systems uses the SMS Gateway communication system. The parameter values sent through the flood detection system will be visualized by the server in the form of animation and text. From the research, it was found that the flood detection system as a client has been able to send flood data, temperature, and rain conditions in real-time. And flood monitoring information systems have been able to capture data from client systems and store them in MySQL DBMS.
The Deep Learning and Apache Spark Enabled Architecture for Improving the Performance of Big Data Classification
Authors:   Research Scholar, Department of Computer Science and Engineering, KL Deemed to be University, Vijaywada, A.P., India., Brahmane Anilkumar V. , Krishna Dr. B. Chaitanya ,   Professor, Department of Computer Science and Engineering, KL Deemed to be University, Vijaywada, A.P., India.
Published: September 2019

At present the Big Data applications, for example, informal communication, therapeutic human services, horticulture, banking, financial exchange, instruction, Facebook and so forth are producing the information with extremely rapid. Volume and Velocity of the Big information assumes a significant job in the presentation of Big information applications. Execution of the Big information application can be influenced by different parameters. Expediently search, proficiency and precision are the a portion of the overwhelming parameters which influence the general execution of any Big information applications. Due the immediate and aberrant inclusion of the qualities of 7Vs of Big information, each Big Data administrations anticipate the elite. Elite is the greatest test in the present evolving situation. In this paper we propose the Big Data characterization way to deal with speedup the Big Data applications. This paper is the review paper, we allude different Big information advancements and the related work in the field of Big Data Classification. In the wake of learning and understanding the writing we discover the holes in existing work and techniques. Finally we propose the novel methodology of Big Data characterization. Our methodology relies on the Deep Learning and Apache Spark engineering. In the proposed work two stages are appeared; first stage is include choice and second stage is Big Data Classification. Apache Spark is the most reasonable and predominant innovation to execute this proposed work. Apache Spark is having two hubs; introductory hubs and last hubs. The element choice will be occur in introductory hubs and Big Data Classification will happen in definite hubs of Apache Spark.
Utilising P300 via Non-Invasive Brain Computer Interface to Control Wheelchair
Authors:   School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India., M Sivabalakrishnan. , S Jeeva ,   department of Computer Science and Engineering, Brilliant institution of Engineering and Technology, Hyderabad, telugana, India.
Published: September 2019

Physically challenged people have certain difficulties that prevents a public from living a natural life. The main advantage or need for design smart wheel chair is mobility. There are products catering to disabled person to satisfy also assist them to overcome the issues they face in move from one place to another, in various ways. The proposed system allows a person in need to move a wheelchair using his/her brainwave signals. That will be achieved by using a NeuroSky TGAM1 module and Arduino Mega 2560 over a Bluetooth communication establishment. The ultimate outcome is to comfort and cater to a larger population of the physically challenged with a simpler, cheaper yet effective alternative.
Project Activities in the Context of the Implementation of State Standards of the New Generation
Authors:   ", E. Y. Salyaeva ,   Institute of food technology and design",   - branch of the State budget educational institution of higher education ",   Nizhny Novgorod state University of engineering and Economics", Z.V. Smirnova ,   Minin Nizhny Novgorod State Pedagogical University, Nizhny Novgorod, Russian Federation,, O. I. Vaganova ,   Minin Nizhny Novgorod State Pedagogical University, Nizhny Novgorod, Russian Federation,, E.N. Galkina ,   "Institute of food technology and design" - branch of the State budget educational institution of higher education "Nizhny Novgorod state University of engineering and Economics", S.D. Syrotyuk ,   Federal State Budget Educational Institution of Higher Education «Togliatti State University», A.A. Stryapikhina ,   "Institute of food technology and design" - branch of the State budget educational institution of higher education "Nizhny Novgorod state University of engineering and Economics", N.V. Bystrova ,   Minin Nizhny Novgorod State Pedagogical University, Nizhny Novgorod, Russian Federation,
Published: September 2019

Federal state educational standards of higher education contain requirements that indicate the priority direction of the formation of the competencies of modern graduates. Competence-based educational paradigm necessitates the search and implementation of ways to promote the formation of a qualified specialist. The implementation of project activities in higher education is revealed as the leading direction of activity, ensuring the achievement of a high level of formation of competencies of students of higher educational institutions. The purpose of the article is to consider the project activities of students of higher education in the conditions of implementation of state standards of the new generation. The authors present the characteristics of the project activity, its typology, set the possibilities, the criteria for evaluating the implementation of project activities. As an example, presents a large-scale project of higher school of organization of independent work of students, which includes relevant conditions, educational landscape, allowing students to participate in various projects, thereby forming respective competences laid down in the standard. The project activity of students in the framework of this project develops at a higher level.
Efficient Energy Conservation using ARM Algorithm in Wireless Sensor Networks
Authors:   Associate professor, Kongu Engineering College, Erode, Abirami Dr.T. , Anandamurugan Dr. S. ,   Associate Professor Kongu Engineering College, Erode, H Muthukrishnan. ,   Assistant Professor, Kongu Engineering College, Erode, S Vinothkumar. ,   Assistant Professor, Kongu Engineering College, Erode
Published: September 2019

The Wireless Sensor Network (WSN) is that technology that provides ideal solutions that are cost-effective and used for a varied range of the applications that are used from environment to military operations, from healthcare to agriculture and so on. In the agricultural environment and its monitoring, the WSN will play a critical role owing to the cost effective and the comfortable WSN deployment. India is that country in which there are sufficient resources available naturally and these are based on the agriculture that contributes to the socioeconomic status and the economy. The very powerful tool which generates the vast as well as the diverse data that includes all the agricultural datasets is called Association Rule Mining (ARM). A very interesting topic in data mining in recent times is the association rules and their ranking. The work will deal with the network of agricultural sensors that measures the moisture of soil, the humidity, temperature and the ARM that is based on its ranking.
Hybrid Group Search Optimizer for Plant Leaf Classification
Authors:   Research Scholar, Department of CSE, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, India,, Ravishankkar A.M. , santhosh Dr.R. ,   Dean, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, India, Amudhavalli Dr.P. ,   Dean, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, India
Published: September 2019

The analysis of Big Data is a data mining discipline in which large quantity of unstructured data is analysed which can be challenging to store and also to retrieve efficiently. The classification of plants is based on the identification of leaf that has a very broad application in both agriculture and medicine. In this work, a method which is computerized is used to recognize a plant leaf based on images is proposed. The proposed method extracts features from the image and these are used for classifying the plant leaf. The process of deciding on the subset for all relevant features to be used in the construction of a system is known as feature selection. The Group Search Optimizer (GSO) is a nature-inspired algorithm that possesses all the qualities used effectively to solve feature selection tasks. In this work, there is a GSO-based algorithm of feature selection along with fuzzy logic and the classifier of a Neural Network (NN) is proposed. The results of the experiment prove the proposed method (GSO-NN) was able to achieve a better level of performance compared to the other methods.
An Experimental Examination of ‘5S’ Technique for Continuous Improvement of the Manufacturing Process
Authors:   Manipal University Jaipur, Jaipur, India, Goswami Dhara , Gupta Ravi Kant ,   Manipal University Jaipur, Jaipur, India, Choudhary Bharmal ,   Manipal University Jaipur, Jaipur, India
Published: September 2019

Lean manufacturing is the way of continuous improvement, provide support and execution of lean production system. This technique focused on improving quality of products, minimum cost, customer satisfaction and eliminating waste in industry. This research helps out to find out the various strategies of lean manufacturing. The main objective of this research paper is to study and analysis of improvements in waste reduction a well as improving productivity using 5S technique for an automobile ancillary unit for its production shop floor producing components from where the entire data is abstracted by applying 5S evolution methodology. Furthermore, the features and classification of 5S technique is discussed.
A Proficient Algorithm For Mining Frequent Item Sets
Authors:   Department of CSE, SASTRA Deemed to be UniversityKumbakonam, Tamilnadu, India,, Vanitha M , Narasimhan D ,   Department of Mathematics, SASTRA Deemed to be University, Kumbakonam, Tamilnadu, India,
Published: September 2019

Frequent Item set Mining (FIM) discover recurrent item sets that are extremely associated in a transactional database. It can be used in big data applications like gene extraction, social network analysis, IOT devices sensor data analysis, etc. As the data size keeps on growing, an efficient procedure is necessary to process the enormous volume of data. Apriori is one of the topmost algorithm and its entry enhanced the research in mining. The algorithm requires multiple scans of the database and produce more candidate items, which increase the computation time and storage along with the transactions size. An efficient technique is required to boost the performance of the algorithm in terms of storage and computational complexity. To reduce the complexity we proposed a reduction factor to Apriori and it can be adopted before candidate generation. Experimental results revealed that our proposed technique greatly reduce the total execution time as well as storage requirements.
Computer Vision Based Detection And Classification of Tomato Leaf Diseases
Authors:   Department of ECE, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamil Nadu, India., Devi T. Gayathri , Srinivasan A. ,   Department of ECE, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamil Nadu, India., Sudha S. ,   Department of ECE, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamil Nadu, India.
Published: September 2019

Indian Economy mainly determined by the agriculture. Tomato is one of the highest used food crops in India. Due to which detection of disease on tomato plant becomes essential. The manual detection of plant diseases are very complex and high cost. Hence, image processing based detection of plant diseases gives the solution. Disease detection involves the steps like image capturing , various processing steps and classification. Most of the diseases of tomato plant detected at initial stages as they affect leaves first. By detecting the diseases at initial stage on leaves will surely avoid impending loss. The classifier, the classification is performed to classify the healthy and disease affected tomato leaves. Finally, the performance of K-nearest neighbor (KNN) and multi class Support Vector machine (SVM) are compared. The proposed system assured an excellent performance to farmers and researchers in admissible way.
Cycle With Parallel Chords Are Odd Even Graceful
Authors:   Department of Mathematics, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamilnadu, India, Venkatesh S. , Rajadurai P. ,   Department of Mathematics, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamilnadu, India, Parameswari K. ,   Department of Mathematics, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamilnadu, India, Atchayadevi A. ,   Department of Mathematics, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamilnadu, India, Sangeetha K. ,   Department of Mathematics, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbakonam, Tamilnadu, India
Published: September 2019

If C_n is a cycle of length n, then the graph cycle with parallel chords is obtained from C_n by adding an “edge “is the graph obtained by attaching a pendant edge at each vertex of the cycle” C_(n.) In this paper we prove that the graphs n-for n≡0,3(mod 4). the graph P_(a,b) obtained by identifying the end points of a internally disjoint paths each of length b, are odd even graceful for odd values of a and b.
Pascal Triple Entire Sequence Space of Fibonacci Binomial Matrix on Rough Statistical Convergence And Its Rate
Authors:   Department of Mathematics SASTRA Deemed University, Thanjavur, Tamilnadu, India., Narayanan Veena , Raghavendran Srikanth ,   TATA Realty-SASTRA Srinivasa Ramanujan Research chair professor for Number Theory, SASTRA Deemed University, Thanjavur, Tamilnadu, India., Subramanian N. ,   Department of Mathematics, SASTRA Deemed University, Thanjavur, Tamilnadu, India.
Published: September 2019

This paper initially discusses the definition of new rough statistical convergence with Pascal Fibonacci binomial matrix. Some general properties of rough statistical convergence are inspected. Further, approximation theory worked as a rate of the rough statistical convergence has been presented.
Smart Movement using Eyeball Pupil Position
Authors:   Assistant Professor, Department of Electronics and Instrumentation, Sri Sairam Engineering College, Chennai, Tamilnadu, India., R Premkumar , Srinivasan Shravan ,   UG Students, Department of Electronics and Instrumentation, Sri Sairam Engineering College, Chennai, Tamilnadu, India., I Mithran. ,   UG Students, Department of Electronics and Instrumentation, Sri Sairam Engineering College, Chennai, Tamilnadu, India., S R Aniruddhan ,   UG Students, Department of Electronics and Instrumentation, Sri Sairam Engineering College, Chennai, Tamilnadu, India., Raj. R Mani ,   UG Students, Department of Electronics and Instrumentation, Sri Sairam Engineering College, Chennai, Tamilnadu, India.
Published: September 2019

There are different kind of reasons for which people offer an material of locomotion such as a cursor. The number of students people and others, who need to artificially go with the cursor. Hence implementing a controlled system with which it enables them to change the place without the help of any other hardware. The proposal of eye controls is of actual use of people who suffered a lot with the problem faced daily with natural input and mostly used by the handicapped and disabled. Camera used here is capturing the image and action of eye pupil movement. First detect the pupil centre position . Then the different angle variation on pupil position gives different instruction set for cursor. The signal pass through the PC to automatically cursor move itself. The movement of the cursor capture and control with the direction and enable the cursor to move the different directions such as forward, left, right and stop.