bluuebunny/crossref_metadata_2025 huggingface dataset:
Mockup Strategy and Analysis of Data Accretion in NS2 for Wireless Sensor Networks
Authors:   Associate Professor, Department of Computer Science, College of Arts and Sciences, Wadi Al-Dawasir, Prince Sattam Bin Abdulaziz University, KSA, Alameen Dr Abdalla , Gupta Dr Ashu ,   Assistant Professor, Department of Computer Science, College of Arts and Sciences, Wadi Al-Dawasir, Prince Sattam Bin Abdulaziz University, KSA
Published: January 2020

Wireless Sensor Networks (WSNs) stay built after partial towards plentiful figures of dispersed interrelated sensor nodes. Standing and running a detailed and systematic test bed for enormous networks turn out to be affluent and time consuming. Predominantly in networking domain, it is classy to set up complete network deprived of simulation process since positioning with certain products may possibly be overpriced and more time consuming. In such Network Simulators save much of time and money. Recreation is used for data networking and it in that way aids investigators in resolving interrogations on time and likewise in insignificant cost. Energy effectiveness is a significant metric in source controlled Wireless Sensor Network (WSN). Data accretion is attained through repeatedly smearing the recommended structure at gathering domes. Multi-Interface Multi-Channel Routing Protocol is instigated here which makes use of metric demarcated by end to end delay, data and vitality ingestion. Further, the projected firmness and accretion are completed to additionally advance energy reserves and network epoch.
Secure and Selective Cloud Data Auditing using Deep Machine Learning
Authors:   Research scholar in Department of CSE , UCE,OU., Radharani S. , Narasimha Dr V.B. ,   Assistant professor, Department of CSE,UCE,O.U
Published: January 2020

The tradition of moving applications, data to be consumed by the applications and the data generated by the applications is increasing and the increase is due to the advantages of cloud computing. The advantages of cloud computing are catered to the application owners, application consumers and at the same time to the cloud datacentre owners or the cloud service providers also. Since IT tasks are vital for business progression, it for the most part incorporates repetitive or reinforcement segments and framework for power supply, data correspondences associations, natural controls and different security gadgets. An extensive data centre is a mechanical scale task utilizing as much power as a community. The primary advantage of pushing the applications on the cloud-based data centres are low infrastructure maintenance with significant cost reduction for the application owners and the high profitability for the data centre cloud service providers. During the application migration to the cloud data centres, the data and few components of the application become exposed to certain users. Also, the applications, which are hosted on the cloud data centres must comply with the certain standards for being accepted by various application consumers. In order to achieve the standard certifications, the applications and the data must be audited by various auditing companies. Few of the cases, the auditors are hired by the data centre owners and few of times, the auditors are engaged by application consumers. Nonetheless, in both situations, the auditors are third party and the risk of exposing business logics in the applications and the data always persists. Nevertheless, the auditor being a third-party user, the data exposure is a high risk. Also, in a data centre environment, it is highly difficult to ensure isolation of the data from different auditors, who may not be have the right to audit the data. Significant number of researches have attempted to provide a generic solution to this problem. However, the solutions are highly criticized by the research community for making generic assumptions during the permission verification process. Henceforth, this work produces a novel machine learning based algorithm to assign or grant audit access permissions to specific auditors in a random situation without other approvals based on the characteristics of the virtual machine, in which the application and the data is deployed, and the auditing user entity. The results of the proposed algorithm are highly satisfactory and demonstrates nearly 99% accuracy on data characteristics analysis, nearly 98% accuracy on user characteristics analysis and 100% accuracy on secure auditor selection process
Latent Feature Word Representations to Enhance Topic Models for Text Mining Algorithms
Authors:   Professor, Malla Reddy College of Engineering & Technology, Hyderabad, India., Mohammed Dr Thayyaba Khatoon , Gayatri M. ,   Associate Professor, Malla Reddy College of Engineering & Technology, Hyderabad, India., Sandeep M. ,   Associate Professor, Malla Reddy College of Engineering & Technology, Hyderabad, India., Reddy Dr.VSK ,   Principal &Professor, Malla Reddy College of Engineering & Technology, Hyderabad, India.
Published: January 2020

Dealing with large number of textual documents needs proven models that leverage the efficiency in processing. Text mining needs such models to have meaningful approaches to extract latent features from document collection. Latent Dirichlet allocation (LDA) is one such probabilistic generative process model that helps in representing document collections in a systematic approach. In many text mining applications LDA is useful as it supports many models. One such model is known as Topic Model. However, topic models LDA needs to be improved in order to exploit latent feature vector representations of words trained on large corpora to improve word-topic mapping learnt on smaller corpus. With respect to document clustering and document classification, it is essential to have a novel topic models to improve performance. In this paper, an improved topic model is proposed and implemented using LDA which exploits the benefits of Word2Vec tool to have pre-trained word vectors so as to achieve the desired enhancement. A prototype application is built to demonstrate the proof of the concept with text mining operations like document clustering.
Metal Additive Manufacturing by Powder Blown Beam Deposition Process
Authors:   Research scholar, Department of Mechanical Engineering, Jawaharlal Nehru Technological University Hyderabad, Telangana, India & Department of Mechanical Engineering, CMR Institute of Technology, Hyderabad, India., Singh D. Dev , Arjula Suresh ,   Department of Mechanical Engineering, JNTUH College of Engineering Jagitial, Telangana, India., Reddy A. Raji ,   Department of Mechanical Engineering, CMR Technical Campus, Hyderabad, Telangana, India.
Published: January 2020

Additive Manufacturing (AM) is a tool less manufacturing process for building complex components layer by layer. Powder based AM techniques are used for producing porous and dense parts or products by Powder Bed Fusion (PBF) and powder blown Beam Deposition (BD) processes respectively suitable for different applications. The present review is mainly focused on the commercially available technology of powder blown Beam Deposition (BD) process for producing fully dense parts, and functionally graded materials used in automotive, aerospace, defense, and nuclear reactors. The properties of BD parts and comparison of the properties of BD parts with Selective Laser Melting (SLM), casting, and Acram's Electron Beam Melting (EBM) parts are presented. This paper provides an insight into the microstructural characteristics and mechanical properties of parts produced by BD process. A brief discussion is presented on challenging issues and applications of BD process. An attempt is made to present available and under development AM testing standards used to evaluate the properties of AM parts. This review also focused on porous parts produced by BD process for medical applications, and metal foil based BD process. Here, new developments in AM process like hybrid manufacturing and 4D printing are also discussed.
Fusion of Image Feature Descriptors for Person Re-identification
Authors:   Assistant Professor, Computer Science and Engineering Department, Christ (Deemed to be University), Kengeri Campus, K Sathish P , Balaji S. ,   Centre for Incubation, Innovation, Research and Consultancy, Jyothi Institute of Technology, Bengaluru India.
Published: January 2020

Person re-identification has gained a lot of research interest in recent years. Extracting and matching features play an important role in this scenario. Past studies of image feature detectors and descriptors are more generic in nature. Different types of detectors and descriptors are used for person re-identification over the last few years. Most of these descriptors are a combination of two or more variants of descriptors. This research paper will focus on the comparative analysis and evaluation of various features detectors and descriptors used for image matching with relevance to person re-identification. We also explore how the combination of local and global descriptors can improve the re-identification rate. VIPeR dataset is used for the evaluation of descriptors.
Drivable Road Corridor Detection using Flood Fill Road Detection Algorithm
Authors:   Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, University of Mumbai, India., Shetty Karthik , Kanani Pratik ,   Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, University of Mumbai, India.
Published: January 2020

Current image processing techniques for drivable road detection make use of lane markings. However, most roads lack lane markings which make such techniques obsolete. For such conditions, an image processing technique is required which identifies the boundaries of the road based on the color differences between the road and the surroundings. This paper proposes a flood fill road detection approach in which we first analyze a sample of the road and compute its RGB pixel distribution. The pixel range is used to detect the other road pixels in the image. Edge detection algorithms are then applied on the detected road to give road edge. It classifies the road on the basis of the visible differences between the road and its neighborhood. It allows for subtle color differences on the road surface, and unlike a color mask, due to the inherent growing nature of a flood fill algorithm, it does not detect neighborhood elements beyond the boundary having features similar to the road. This technique also manages to detect any obstructions on the road as opposed to other edge detection algorithms. We also propose methods to enable quick computation of otherwise expensive flood-fill algorithm. The method was tested on both marked and unmarked lanes and produced satisfying results for both images and videos.
Efficient Multipath Routing to Increase QoS by Link Estimation and Minimum Interference path in MANET'S
Authors:   Department of E&CE, Guru Nanak Dev Engineering College, Bidar, India., Karanje Pradeep , Eklarker Dr. Ravindra ,   Department of E&CE, Guru Nanak Dev Engineering College, Bidar, India.
Published: January 2020

Many significant techniques have been developed for real time transmission to meet stringent QoS for various applications of wireless sensor network. However routing in MANET’s still a challenging issue to achieve QoS due to frequent topology changes and its dynamic nature. For majority MANET applications, on demand multi path data routing protocols have been modelled to transfer data in multiple routes to prove its effectiveness on link disjoints and high packet delivery ratio. However due to mobility and underlying medium, multiple routes are exposed to interference and low power unstable link quality which are essential to guarantee QoS in routing. In this paper we propose link quality estimation and minimum path interference based on Geographic adhoc on demand multi path distance vector (GAOMDV) an adaptation of AOMDV routing protocol. To ensure the reliability of MANET’s this adaptation is done by considering routing metrics. GAOMDV selects forwarding neighbour nodes based on link quality and minimum path interference across multiple paths and ensures high stable links between nodes. Extensive simulation is carried on discrete event simulation tool and performance of GAOMDV is analysed in terms of network QoS parameters.
Diabetes Diagnostic Model Based on Truth-value Restrictions Method Using Inference of Intuitionistic Conditional and Qualified Fuzzy Propositions
Authors:   Associate Professor, Department of Mathematics, Chaudhary Charan Singh University, Meerut, India, Sharma *M. K. , Dhiman Nitesh ,   Research Scholar, Department of Mathematics, Chaudhary Charan Singh University, Meerut,India.
Published: January 2020

Diabetes is a challenging problem nowadays. Not only in India, but it also spreads over worldwide, In the present research paper a novel scheme based on intuitionistic fuzzy propositions to explore the knowledge base rule system with uncertainty has been developed and for the extension of fuzzy propositions to the domain of factors causing diabetes. In this paper, we have constructed the conditional and qualified intuitionistic fuzzy proposition mathematically for the diabetes diagnostic model. We have also developed an algorithm for Truth-value restriction method using the conditional and qualified intuitionistic fuzzy proposition;with the help of developed algorithm for truth-value restriction method we will give a scheme to check this severity of the diabetes. Numerical computations have also been carried out to demonstrate our approach.
Optimization of Biodiesel Synthesis using Heterogeneous Catalyst (SiO2) from Karanja Oil by Taguchi Method
Authors:   Research Scholar, Department of Mechanical Engineering, DYPIT, Pune (MS), India,, Patil Satish A. , Arakerimath Dr. R. R. ,   Professor and HOD, Department of Mechanical Engineering, G H Raisoni College of Engineering and Management, Wagholi, Pune, India
Published: January 2020

Biodiesel is renewable and environmental friendly fuel which has the capable to gain comparable engine performance. In this experimental study, Karanja oil synthesized by using Transesterification process. Transesterification of Karanja oil to biodiesel using SiO2 as a heterogeneous catalyst is studied using five different parameters and levels each. Minitab is used to fix the orthogonal arrays and Taguchi method is used to analyze the interaction effect for the transesterification reaction. The five different parameters responsible for biodiesel yield are molar ratio of methanol to oil, catalyst concentration, reaction temperature, reaction time and stirring speed. Effect of these parameters has studied on small scale. The biodiesel yield obtained experimentally at optimum conditions are 20% methanol to oil molar ratio, 3% SiO2 catalyst addition, 65ºC reaction temperature, 180 min reaction time and 500 rpm stirring speed is 77%.
Automated Tilt Conveyor for Cylinder Head
Authors:   Department of Mechanical Engineering, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering college, Avadi -600 062, Tamil Nadu, India., V Sathiyamoorthy , S Balamurugan ,   Department of Mechanical Engineering, Mahendra College of Engineering, Salem, Tamil Nadu, India., A Sivakumar ,   Department of Mechanical Engineering, Varuvan Vadivelan Institute of Technology, Dharmapuri-636 703, Tamil Nadu, India., K Arumugam ,   Principal, Gojan School of Business and Technology, Redhills, Chennai -600 052, Chennai, Tamil Nadu, India., S Palani ,   Department of Mechanical Engineering, Vel Tech Multitech, Avadi, Chennai-600 062, India.
Published: January 2020

Cylinder head is one of the main components of an Automobile Engine. In machine shop there are three bays having a machines in which the cylinder head is machined. Makino machine is one of them where the operations like roughing, semi finish; drilling and tapping are carried out. The component has to be loaded by use of a manipulator in a vertical position into the machine such that its rocker face should be facing the operator. So, the component coming from the previous operation through a conveyor with combustion face on top should be tilted to 90 degree such that its rocker face will be facing the operator in a horizontal position. This tilting process has been carried out manually which results in damage of valve guide and valve seat of a cylinder head. This leads to reduction in quality and productivity and also it results in increased operator fatigue since the cylinder head weighs heavy. There is also a chance that when tilting the component manually the component may fall down and hurts operator which results in increased value of effort and ergonomic index. To overcome this problem our research work a modification is made in the conveyor of the makino machine with a low cost automatic arrangement provided for cylinder head tilting purpose.
Information on Tachinid Fauna (Diptera, Tachinidae) Of the Phasiinae Subfamily in the Far East of Russia
Authors:   Far Eastern Federal University, Vladivostok, Russia., O. Markova T. , V. Repsh N. ,   Far Eastern Federal University, Vladivostok, Russia., N. Belov A. ,   Far Eastern Federal University, Vladivostok, Russia., G. Koltun G. ,   FSBEI HE Primorskaya State Academy of Agriculture, Ussuriysk, Russia., V. Terebova S. ,   FSBEI HE Primorskaya State Academy of Agriculture, Ussuriysk, Russia.
Published: January 2020

For the first time, a comparative analysis of the tachinid fauna of the Phasiinae subfamily of the Russian Far East with the fauna of neighboring regions has been presented. The Phasiinae fauna of the Primorsky Krai (Far East of Russia) is characterized as peculiar but closest to the fauna of the southern part of Khabarovsk Krai, Amur Oblast and Eastern Siberia. The following groups of regions have been identified: Southern, Western and Eastern Siberia; Amur Oblast and Primorsky Krai, which share many common Holarctic and Transpalaearctic species.Special mention should be made of the fauna of the Khabarovsk Krai, Sakhalin Oblast, which are characterized by poor species composition and Japan (having a subtropical appearance).
The Role of Aquatic Training Program Among Special Need Children on Vestibular Processing of Sensory Stimulation
Authors:   PhD Scholar, ASPESS, Amity University Uttar Pradesh, Noida, India., Dey Anulekha , Sharma Malika ,   Assistant Professor, ASPESS, Amity University Uttar Pradesh, Noida, India.
Published: January 2020

This study is pursued to find the role of Aquatic Training Program for children with special needs. Sensory profile questionnaire was used to assess the before and after performance of each students of each groups for Vestibular Processing, of 25Children average of age nine years, randomly selected from Asha AWWA school at Delhi, India. Participants were divided into two groups Experimental (13) and Control groups (12). Result of Two Way ANOVA reflects positive accelerated change only in experimental group, showing moderate to considerable benefits with 27 session aquatic training program. In addition, individualized improvement was also studied, which resulted into minor to major enhancement of vestibular processing among all the experimental group participants. Hence a prolonged Structured Aquatic Training Program (intervention) is off paramount to get the best results. These findings also enhance the preceding research work based on aquatic intervention as vestibular senses develop first and controls other senses since the baby is in womb, so it is important to develop this sense so other sense can process better to acquire a better life.
Energy Consummation in cognitive radio network using Different Methods
Authors:   Research Scholar, Shri. JJT University, Churella, Jhunjhunu (Rajasthan) Churella, Jhunjhunu (Rajasthan) Engineering and Research, Pune, Maharashtra, Gunjal Shubhangi , Sharama Yogesh Kumar ,   HOD, Research coordinator, Shri. JJT University, Churella, Jhunjhunu (Rajasthan) Churella, Jhunjhunu (Rajasthan) Engineering and Research, Pune, Maharashtra, Todmal Satish Ramchandra ,   Academic Dean, JSPM’s Imperial College of, Churella, Jhunjhunu (Rajasthan) Churella, Jhunjhunu (Rajasthan) Engineering and Research, Pune, Maharashtra
Published: January 2020

The cognitive radio and resource allocation techniques have been proposed for efficiently utilizing the radio resources. Cognitive radio is an emerging technology intended to enhance the utilization of the radio frequency spectrum and allocate the available resources correctly. The cooperative communication system, with the same total power and bandwidth of legacy wireless communication systems, can increase the data rate of the future wireless communication system. A combination of cognitive radio with resource allocation can further improve the future wireless network performance and reduces the energy consummation. Efficient resource allocation in cognitive radio network (CRN) is essential in order to meet the challenges of future wireless networks. In this Paper, we are going to discuss the different Localization Techniques, objectives and protocols used in the literature for resource allocation in CRN. This paper also highlights the use of power control, cooperation types, network configurations, and Energy consummation used in CRN. Finally, directions for future research are outlined of proposed algorithms for energy minimization.
Water Quality Assessment in a Watershed in Cusco, Peru using the Grey Clustering Method
Authors:   Department of Engineering, Mining Engineering Section, Pontificia Universidad Católica del Perú, Lima, Peru., Delgado Alexi , M. Acuña ,   Justano N., Llanos E.,EnvironmentalEngineeringFaculty, Universidad Nacional de Ingeniería, Lima, Peru., I. Puma ,   EngineeringProgram, Universidad de Ciencias y Humanidades, Lima, Peru.
Published: January 2020

Water quality assessment is a current issue of increasing concern in many countries around the world for reasons such as population health, national economic development and the environmental quality of ecosystems. At this juncture, the Grey Clustering method is used to assess water quality at discharge points, from the beginning to the end of the environmental monitoring process in the area of influence of the Anabi mining unit in the Chonta and Milos micro-watershed. The parameters evaluated were pH, dissolved oxygen, total suspended solids (TSS), iron and manganese. The results obtained through the Grey Clustering methodology showed a monitoring point with contamination from a treated water discharge. On the other hand, in order to obtain greater efficiency in the evaluation of water quality, national standard DS 004-2017-Minam (Water Quality Standards) and international standards were used through the PRATI index. Through the results obtained it was observed that (by means of the Prati index ) there is a better classification of the water quality in each point, therefore this research becomes an important tool for future studies to consider the Prati index for greater reliability of results.
Effect of Austenization Temperature on the Microstructure in Cr-Mn-Si Steel
Authors:   Nuclear Engineering Division Department of Physics, Sofia University James Bourchier 5 blvd, 1164 Sofia, Avdjieva Tatyana
Published: January 2020

This work is a part of research on the microstructure and mechanical properties of Cr-Mn-Si steels after various thermal treatments. In order to increase the resistance of the materials against failure it is necessary to possess simultaneously high strength and plasticity at the same time. Normally, in conventional metals, this is impossible. The purpose of the present study is to trace the polymorphic transformation of the microstructure and the redistribution of the trace elements in the corresponding microstructural transformations of the steel at each stage of applied heat treatment - austenization, quenching, austempering, tempering. The chosen sequence of applied heat treatments is to obtain a bainite structure of up to 50% in order to achieve high strength and toughness of the material.
Research Geodynamic Situation of the Ore Formation of the Ore Deposits
Authors:   Assistant professor Department of Geology, mineralogy and petrography, Tashkent state technical university, PhD University Street 2, Tashkent, Uzbekistan, Omonovich Janibekov Bobir , Kamalovich Turapov Mirali ,   State Enterprise "Institute of Mineral Resources" Head of the Tectonophysical Research Methods Sector, Doctor of Geological and Mineralogical Sciences, Professor, Russian Federation Academician of Natural Sciences, T.Shevchenko Street 11a, Tashkent, Uzbekistan,, Asatovich Akbarov Khabibulla ,   Professor of the department of geology, Prospecting and exploration of mineral deposits, Academician of the Academy of Sciences of the Republic of Uzbekistan Tashkent State Technical University, University Street 2, Tashkent, Uzbekistan, Shermatovna Tulyaganova Nargiza ,   Head of Department of Geology, mineralogy and petrography, Tashkent state technical university,University Street 2, Tashkent, Uzbekistan, Lecturer Abdullaev Abror Khushmurotovich Senior ,   Department of Urban Roads and Streets, Tashkent Institute of Design, Construction and Maintenance of Automobile Roads A.Temur Street, 20, Tashkent, Uzbekistan,
Published: January 2020

The research reveals the goals and tasks of the science of geodynamics. A new technique is being considered aimed at studying the geodynamic situation of ore deposits in ore formation processes. The results of the reconstruction of the geodynamic conditions of the area of the Daugiztau deposit during ore deposition are presented.
Accident Prevention and Traffic Control by Otsu Method and Haar-Cascade Hand Detector
Authors:   Department of CSE, Sree Vidyanikethan Engineering College, Tirupati, India., Suma Dr. K. G. , Sunitha Dr. G. ,   Department of CSE, Sree Vidyanikethan Engineering College, Tirupati, India., Avanija Dr. J. ,   Department of CSE, Sree Vidyanikethan Engineering College, Tirupati, India.
Published: January 2020

The rapid development of economy and continuous improvement of people's purchase ability in every country, purchasing the motor vehicles is increasing rapidly, so as the traffic accidents and accident death rate, which says the road traffic situation in everywhere, is worse day by day. Traffic and Accident control is a complex activity in developing countries shows in increasing number of riders and automobiles every day. The prediction and prevention of traffic accidents is an important part of the traffic safety, the purpose of prediction is to achieve the objective of reducing traffic accidents. The work proposes by using the existing video through the cameras positioned on highways, traffic signal and busy roads that can detect the incidents/events. The system can also be proposed with the ability to read and track the vehicle number helps in searching of vehicles violating the rules by finding the License plate number using Optical Recognition method which finds the alpha numeric character from the segmented image. Counting the vehicles passed through the mentioned place using Haar-cascade hand detector which helps to count the number of vehicles passed through can perform Traffic control system.
Consumer Strategies for Adoption of Performance Analysis of 4g Mobile Services
Authors:   Designation- Research Scholar, Institute of Business & Computer Studies, Siksha 'O' Anusandhan (Deemed To be University) Bhubaneshwar, Odisha, Mohapatra Sandeep Kumar , Mishra Dr. Uma Sankar ,   Designation- Professor, Institute of Business & Computer Studies, Siksha 'O' Anusandhan (Deemed To be University) Bhubaneshwar, Odisha
Published: January 2020

We use a preference test to determine the ability of consumers to pay for mobile services enhancements with an emphasis on changes to four-gyms and roaming networks. Increasing mobile Internet speed (eventually, with 4 G), unlimited mobile Internet, improved quality (possible with 4 G) and unrestricted use in two neighboring countries are the characteristics of improved mobile services we are investigating. (unrestricted roaming). The results show that uncontrolled roaming services are most important to people. The next move to do is to increase the speed and infinite attributes at 1 per cent. . The statistically insignificant effect of improved quality at the rate of 5percent indicates that users are satisfied with the current quality level which they achieve with 3G. To research 4 G network recognition of mobile and web consumers. To analyze how the use of 4 G technologies viewed smartphone and internet consumers. Research the factors affecting smartphone and web users ' behavioural expectations (BI) through 4G. Mobile User necessities are rising faster than constantly and the limitations of the existing mobile communication systems have required the researchers to emanate up with additional advanced and proficient technologies. 4G and 4G-LTE mobile technology is the next step in this trend. This is next generation of wireless networks 4G-LTE that will completely replace 3G networks. it is responsible for its customers with enhanced speed and entirely IP based multimedia services. 4G-LTE is completely approximately an integrated, global network that will be intelligent to afford a complete IP solution where voice, data and streamed multimedia can be specified to users on a basis. But there is a pronounced essential of deploying such technologies that can incorporate entirely these systems into a single combined system. The aim of this paper is to focus the benefits, challenges in deployment and opportunity of technologies. Comparative analysis of 4G-LTE based on performance in new communication trend and generations in India.
Combating PUE Attack in Cognitive Radio Networks using RSSI Based EKF and UKF
Authors:   Ph.D Scholor, Electronics and Communication, Sri Satya Sai University of Technology and Medical Sciences, Sehore, Madhya Pradesh India., Mergu Kattaswamy
Published: January 2020

The problem of spectrum scarcity in wireless communication can be reduced by Cognitive Radio (CR) technology in which the spectrum holes or unused spectrum can be allocated to the secondary or unlicensed users. But the major problem in CR is providing security. Various security issues are present at different layer. One of the major wide spread security issue in the cognitive radio is the Primary user emulsion attack in which the malicious secondary user emulated as primary user to get spectrum resources for a long time. One of way to avoided PUEA is, by obtaining the location of malicious user. The conventional location detection techniques such as time of arrival, time difference of arrival and direction of arrival, will give better performance when the user is stationary. Even though Received Signal Strength Indicator along RF fingerprint technique gives the better location of mobile user but it requires the more hardware. Hence the cost is high. In this paper, the author proposed an algorithm to locate the attacker using EKF and UKF with RSSI. In this algorithm, the initial position of user can be obtained by Received Signal Strength Indicator. This initial position integrated to EKF and UKF to track the location of primary user, which is a mobile user so that PUE Attack can be identified and avoided. The author also compares the performance of Extended Kalman Filter with Unscented Kalman Filter by Matlab software.
Design of a Sampler circuit for Flash ADC using 45nm Technology
Authors:   Electronics and Telecommunication Engineering, Terna Engineering College, Mumbai University, Navi Mumbai, India., Soman Vanitha , Mande Sudhakar S ,   Professor, Electronics and Telecommunication Engineeing, Don Bosco Institute of technology, Mumbai, India.
Published: January 2020

This paper presents design of a sampler circuit for folding flash ADC. There is a desire for Low power high performance ADC for communication. For low power the size of the ADC should be minimized and for the fast performance flash can be used. Hence to reduce the number of transistors in flash ADC folding network is proposed here. Sampling is the important technique used in the ADC part. In this discussion the sampler circuit includes a differential track and hold switch followed by a variable gain amplifier with a gain of 1 db, a buffer and a folding network. An input voltage of1 V and the sampling frequency of 1GS/s is applied to the sampler circuit. Effective number of bits of more than 5.7 bits is achieved also THD is below -35db in VGA. Buffer achieves a ENOB of 10bits with THD less than -65db. This sampler circuit is designed with the technology of 45nm for coherent sampling. Worst case SNDR is calculated.
VOTE: Verifiable Auditing for Outsourced Database with Token Enforced Cloud Storage
Authors:   CSE, University Visvesvaraya College of Engg, Bangalore University, Bangalore, India., Mara Geeta C , N Rashmi B ,   CSE, University Visvesvaraya College of Engg, Bangalore University, Bangalore, India, C Nikhil R ,   ASE, Jain University, Bengaluru, India., Buyya Rajkumar ,   CSE, The University of Melbourne, Australia., R Venugopal K ,   Bangalore University, Bangalore, India.
Published: January 2020

Database deploying is one of the remarkable utilities in cloud computing where the Information Proprietor (IP) assigns the database administration to the Cloud Service Provider (CSP) in order to lower the administration overhead and preservation expenditures of the database. Regardless of its overwhelming advantages, it experiences few security problems such as confidentiality of deployed database and auditability of search outcome. In recent past, survey has been carried out on the auditability of search outcome of deployed database that gives preciseness and intactness of search outcome. But in the prevailing schemes, since there is flow of data between IP and the clients repeatedly, huge communication cost is incurred at the Information Proprietor side. To address this challenge, we introduce Verifiable Auditing of Outsourced Database with Token Enforced Cloud Storage (VOTE) mechanism based on Merkle Hash Tree (MHT), Invertible Bloom Filter(IBF) and Counting Bloom Filter(CBF). The proposed scheme reduces the huge communication cost at the Information Proprietor side and achieves preciseness and intactness of the search outcome. Experimental analysis show that the proposed scheme has totally reduced the huge communication cost at the Information Proprietor side, and simultaneously achieves the preciseness and intactness of search outcome though the semi- trusted CSP deliberately sends a null set.
Adaptive Technique for Salt and Pepper Noise Removal through Functional Link Artificial Neural Network
Authors:   Asst. Prof., Department of ECE, I.T.E.R, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India., Sarangi Sunita , Sarangi Suchitra ,   Asst. Prof., Department of ECE, R.I.T.E., Bhubaneswar, India.
Published: January 2020

In this paper, an adaptive method for removing salt and pepper noise from images is proposed. A second order difference operator is used to locate the corrupted pixels in images by comparing with a threshold, which is selected adaptively using the image properties. A functional link artificial neural network (FLANN) based method is proposed to set a threshold for each corrupted image for identification of noisy pixels using recursive zero attracting least mean square (RZALMS) as the updating algorithm. Median filter is used to eliminate noise from the detected pixel locations.
Identification of Park Effect Probability in Wave Energy Conversion System using Multi Criteria Decision Making Method (AHP) and Neural Network Model (GMDH Shell)
Authors:   Research Scholar, Department of School of Hydro Informatics Engineering, NIT Agartala Jirania, Tripura (W), India, Saha *Mr. Satyabrata , Majumder Dr. Mrinmoy ,   Assistant Professor, Department of School of Hydro Informatics Engineering, NIT Agartala Jirania, Tripura (W), India, Pal Dr. Manish ,   Associate Professor, Department of Civil Engineering, NIT Agartala Jirania, Tripura (W), India.
Published: January 2020

The present research work demonstrates the trend of Park Effect to the Wave Energy Conversion system or in wave energy converter. The Park Effect occurred due to various reasons in a real field application of Wave Energy Conversion. Park Effect occurred in wind energy as well as wave energy. All possible factors are considered to find out the Park Effect. To analyze the Park Effect probability, Analytical Hierarchy Process (AHP) is used, from the result a model is generated through Neural Network software named GMDH Shell. There are significant uncertainties arising in particular from the lack of field tested result to calculate the Park Effect proximity on the devices. However, applying various hypotheses for design and physical parameters, it was found that the benefits of Park Effect influenced factors are all non-beneficiary to Park Effect trend. After all the calculations it can predict the proximity of the Park Effect in a Wave Energy Conversion system.
Classification of Imbalanced Big Data using SMOTE with Rough Random Forest
Authors:   Department of Information Technology, Gauhati University Institute of Science and Technology, Guwahati, Assam – 781014, India., Das Tanuja , Khan Abhinandan ,   Department of Computer Science and Technology, University of Calcutta, Acharya Prafulla Chandra Roy Siksha Prangan, JD-2, Sector-III, Saltlake, Kolkata – 700106, India., Saha Goutam ,   Department of Information Technology, North-Eastern Hill University, Shillong – 793022, Meghalaya, India.
Published: January 2020

Learning from datasets is an important research topic today. Amongst the various data mining tools available for the purpose, none works satisfactorily in the case of imbalanced data mainly because this type of data gives rise to various minority classes, which may affect the learning process. In addition to the large volume, characteristics of Big Data also include velocity and variety. The Synthetic Minority Oversampling Technique (SMOTE) is a widely used technique to balance imbalanced data. Here, we have focussed on extending this concept to conform to the Big Data environment by combining it with the concepts of rough random forest (RRF). This hybrid approach comprising SMOTE and RRF algorithms for learning from imbalanced datasets has been applied on various benchmark datasets from the KEEL Dataset Repository. The results obtained are satisfactory. The velocity aspect of Big Data has been handled by this method on the dynamic dataset of the stock market. The results obtained have been verified using popular online websites related to stock markets.
Closed Loop Control of Wind Power Based on Trans Quasi-Zsourceinverter
Authors:   Assistant Professor, Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India., Sonar Santosh
Published: January 2020

The paper presents a wind generator output power appropriately monitored using a closed loop controller engaging the buck-boost competency of Trans qZSI and is fed to grid. The converter getting all benefits of conventional ZSI and exchanges the traditional inverter in the arrangement. Moreover, the Trans qZSI has the exceptional benefits of minimum component count and lower component ratings. The feed forward controller cautiously controls the wind generator output power. It monitors the short circuit duty cycle of inverter using third harmonic injected control technique to create a boosted output. Simulation of the complete circuit is performed on MATLAB and results are discussed. It offers an exclusive voltage regulation by creating proper choice of shoot through duty ratio under variable wind speed. The proposed control system is suitable for transient and steady state operation retaining the preferred level of output.
Ionospheric Modeling and Forecasting Services of GNSS
Authors:   Associate Professor, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vijayawada, A.P INDIA, Pachipala Dr Yellamma , K Dr Amarendra ,   Professor, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vijayawada, A.P INDIA, Nagesh Puvvada ,   Assistant Professor, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vijayawada, A.P INDIA, Vamsi K Sri Rama ,   Student, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vijayawada, A.P INDIA
Published: January 2020

The study of ionospheric variability is vital for refining and predicts services of GNSS (Global Navigation Satellite System) applications. The GNSS service provides an explicitly obtainable resource GNSS information, goods and services in support of the earthly reference structure. GNSS is provides an Earth observation, navigation, positioning, timing and other applications that an assistance Society and Science. To investigate the variations in the daily averaged TEC (Total Electron Content) by taking several model components such as solar activity component, geomagnetic activity and periodic components at different latitudes ranging from 10˚N to 26˚N for the year 2018. The presented results would be useful to download, processing and analysis the IGS (International GNSS Service) data. MSSA model can reproduce quite well the observed values of GPS-TEC by utilizing only the first 4 singular modes and constitutes 99% of the total variance. The data is transformed into the singular values which are used for forecasting a noiseless time series. The proposed system results show that higher accuracy is achieved by MSSA (Multivariate Singular Spectrum Analysis) based model. It can also be noted that the training of MSSA is much faster and achieves higher learning accuracy, lowest training time. MSSA is effective even the space weather conditions are active during different solar phase periods.
Student Dropout Prediction & Educational Data Mining
Authors:   Research Scholar, Department of Computer & Information Science, Annamalai University, Chidambaram, Tamil Nadu, India., Mardolkar Mahesh , Kumaran Dr. N. ,   Department of Computer & Information Science, Annamalai University, Chidambaram, Tamil Nadu, India.
Published: January 2020

Educational data like students performance is very important to study and analyze and to improve the quality of education. The study concerned to data mining techniques with educational data is known as Educational Data Mining (EDM). This study finds knowledge and interesting patterns in educational organization. Students performance are the subject mainly concerned to find the qualitative model based on student’s personal and social factors then classify and predict the student performance. Proper counseling to underperforming students can reduce dropout ratio and help them to continue their studies.
Real Time Cyberbullying Detection
Authors:   Pursuing Post-Graduation student, computer science program, Rajasthan College of Engineering for Women, Jaipur., Prashar Shalni , Bhakar Suman ,   Assistant Professor, Computer Science Department, Rajasthan College of Engineering for Women, Jaipur.
Published: January 2020

Automated approaches for detecting cyberbullying on online platforms has remained a primary research concern over past years. Cyber bullying is defined as the use of electronic communication to bully a person, typically by sending messages of intimidating or threatening nature. The victims especially teenagers suffer from loss of confidence, depression, sleep disorder. The research on automated cyberbullying approach is mainly focused on data driven methods. Such methods work on a database of static texts, usually collected from online platforms and are not feasible for dynamic nature of a real-life social networking scenarios. The aim of our research is to develop a cyberbullying detection system using Fuzzy Logic. Three types of bullying emotions are considered in this research work namely aggression, abuse and threat. In the proposed approach chat between two users is continuously monitored and emotion present in each message is determined. Based on the emotion each user’s behavior is categorized as decent or bullying. If the detected bullying nature is higher than a defined threshold value the account of user is ceased and reported automatically. The proposed approach is tested with a chat application developed in Microsoft .Net Framework and approach can detect cyber bullying in good time. The proposed approach, if implemented with social networking platforms can serve as a useful aid for preventing online harassment. The developed algorithm can also be applied in surveillance and human behavioral analysis.
IoT with Cloud Centric Vehicle Detection and Counting System for Smart Traffic Surveillance
Authors:   Assistant Professor/Programmer Department of Computer and Information Science, Annamalai University, Chidambaram, India., Saravanan S. , Venkatachalapathy Dr. K. ,   Professor, Department of Computer and Information Science, Annamalai University, Chidambaram, India.
Published: January 2020

The efficient management of road traffic is one primary facet of many, in smart cities. Traffic overcrowding can be managed successfully, if prior estimation of the number of vehicles that will pass though a crowded junction in a specific time is known. This paper introduces a methodology which targets vehicle extraction on videos covering vehicles. To resolve the problem of current vehicle detection such as the need of detection accuracy and slow speed, an improved YOLOv3 vehicle detection is utilized. The k-means clustering used to group the bounding box around the vehicle in training dataset. The method for calculation of loss with respect to the length and width of the bounding boxes was recovered through the implementation of the batch normalization process. Finally, to improve the feature extraction of the network the high repeated convolution layer are removed. The experiment results are carried out on the BIT-vehicle validation datasets which shows the improvement of mean Average Precision (mAP) could certainly reach 95.6%.
Improvement of Power Quality in an Adaptive Boost PFC Converter with Generation of PWM Control Signal by Cascading Power Factor and Chaos Controller Circuits
Authors:   Department of ECE, CMR Institute of Technology, Bengaluru, India, N Naveen Kumar G. , N Sridhar ,   Department of ECE, CMR Institute of Technology, Bengaluru, India, P Sanath Kumar T ,   Department of EEE SKSVMA College of Engineering and Technology, Lakshmeshwar, India.
Published: January 2020

This work discusses about a digital controller system for reduced effect of chaos and improved power factor of a 1-phase AC-DC converter system. It is shown that, the proposed controller technique is able to suppress the chaos at variable load condition of a boost power factor correction (BPFC) converter. Furthermore, a systematic methodology based on bifurcation diagram from tuning the controller is proposed. To achieve improved power quality in BPFC converter, combination of average and peak inductor current mode control methods are performed. In the MATLAB/SIMULINK environment, simulation circuit for the BPFC converter with average current control method is developed to improve power factor. Further, to reduce the effect of chaos produced in converter, peak inductor current mode with delayed feedback control method is adopted. At an output power of 650 W operating at 130K Hz switching frequency, this converter provides Total Harmonic Distortion (THDi) reduction of 20% and improved Power Factor (PF) of input current compared to other conventional converter. For real time operation of the system, rapid prototyping test is carried out using DAQ (Data acquisition) board NI 6351. The delayed feedback control has a better performance than any other methods proposed earlier.