bluuebunny/crossref_metadata_2025 huggingface dataset:
Squid Species Matching using Fuzzy Edge Based Algorithm
Authors:   Associate Professor, Computer Science., Dept. of Computer Science, Sri Venkateswara College of Engineering, Tirupati., Himabindu* K. , Anitha Raju ,   Assoc. Prof., Dept. of Computer Science and Engineering in Koneru Lakshmaiah Education Foundation., Sekar K. ,   Professor, Departmentsof Computer Science and Engineeering, S.V. College of Engineering, Tirupati., Vasavi G. ,   Assistant Professor, department of Computer Science and Engineering at Hyderabad Institute of Technology and Management, Hyderabad.
Published: April 2020

In the area of Commercial species identification, Squids species identification is significant because Squids plays an important role in Marine food chain. The identification of Squid species requires information about their morphometric features. Body shape feature is one of the important morphometric features for Squids. Hence, we consider only shape feature of Squid. Edge detection is an important technique to extract the shape feature for Squid images. Squid images contains uncertainty because of the problems occurs in the data acquisition and its complex structure. Hence, to avoid above mentioned uncertainties occurs in the Squid images consider Fuzzy edge map. In this work Fuzzy Edge Based Retrieval Algorithm is proposed for the query based Squid image retrieval from Squid’s database. In the process of Fuzzy Edge Based Retrieval Algorithm, first Fuzzy Edge map is constructed for Squid images later the Euclidian distance similarity measure performs between Query image and the candidate images in the Squids database. Based on the similarity metric the relevant Squid images are matched with query image are retrieved. The performance of proposed algorithm analysed with precision recall graphs.
Perceptual Digital Gaps in Generations between Adoption and Usage of Different Modes of Payment in Digital Economy
Authors:   Research Scholar, Banasthali University, Jaipur, India., Jakhiya Mukund , Gaur Bhawna ,   Department of Management, and Commerce, Amity University, Dubai, UAE., Bashir Raeesa ,   Department of Management, and Commerce, Amity University, Dubai, U.A.E
Published: April 2020

The Mobile payment revolution has led to 55% increase in digital payments in India in the past one year. Currently there are 10 million locations that accept digital payments in the country. Though, internet connectivity, digital literacy and perceptual gaps in generations have proved to be the major hurdles for service providers to capture the full market potential for digital payments. This study holistically approaches the topic by critically analyzing the data collected from different strata based on age groups. It was observed that all the generations are readily adopting digital payments whereas there is still a perceptual gap that exist in the regular usage of mobile payments among the elderly and the young generations. Data analysis also reveals that mobile payments are mostly used for the low value purchase by the customers in comparison to the high value purchase as there is high risk and high channel cost associated with mobile transactions and also government regulations do not support very high value transactions. Another trend observed was Impulsive purchase behavior in customers (especially millennial) using mobile payments as these purchases are unplanned, unintentional and unthoughtful. These facts can be used as an input by the Government departments and the financial service providers to design strategies to bring convenience in the adoption and usage of digital transactions, to bridge the gap in the adoption of digital payments between young and old generations.
Enhancing Building Design Strategies to Contribute in Wireless Communications
Authors:   Faculty, Amity School of Planning & Architecture, Amity University, Dubai., Rajput* Banafsha Quadri , Chaudhry Amna Rafi ,   Faculty, Amity School of Planning & Architecture, Amity University, Dubai., Ruhela Sonakshi ,   Assistant Professor, Amity University, Dubai
Published: April 2020

Wireless communication in building application and design currently act as two separate platforms of communication for inhabitants. Users utilize information sent and received through wireless technology unaffected by the space they are residing. As a means of data exchange and transfer objective information this method of communication serves its expected purpose. On the contrary in the case of personal communication, the surrounding space becomes an insignificant contributor. Also in a situation of wireless system failure the built space does not act as back-up support to all running functions. This paper questions the extensive reviews and is based on focus expert interviews (Qualitative methods) on building designs with specific objectives i.e. a) To allow building design to act as a backup for effective communication in case of wireless system failure b) To assess the building design for enhanced communication. For the purpose of data collection ten expert Architects were called for a focused group interview. The themes and sub themes from the focused group interview were assessed through thematic analysis and the results are discussed below in section VI.
Classification of Brain Tumour in MRI Images using BWT and SVM Classifier
Authors:   Swami Vivekanand College of Engineering Indore M.p., India., Agrawal* Yash , Birchha Vijay ,   Swami Vivekanand College of Engineering Indore M.p., India.
Published: April 2020

The improvement in medical image dispensation is increasing in an incredible manner. The speed of increasing ailment by method of reverence to various types of cancer and other related human exertion pave the way for the increase in biomedical research. as a result giving elsewhere and analyzing these medical descriptions is of high significance for scientific diagnosis. This work focus on the stage effectual categorization of brain tumour descriptions and segmentation of exist illness images employing the planned mixture bright techniques. The challenge as well as objectives lying on design of mark extraction, characteristic collection in addition to image classification and segmentation for medical images are discuss The tentative results of intended method contain been appraise and validate for arrangement in addition to superiority examination on magnetic clatter brain images, based on accuracy, sensitivity, specificity, and dice comparison directory coefficient. The experimental marks achieved 91.73% accuracy, 91.76% specificity, and 98.452% sensitivity, demonstrating the efficiency of the proposed method for identify normal and nonstandard tissues from intelligence MR images.
Efficient and Reliable Communication to Reduce Broadcast Storm in Rural and Urban Scenario using RGHN and UGHN Protocol
Authors:   Department of ECE, Agni College of Technology, Chennai, India., lmurugan* V. Ve , manickam J. Martin leo ,   Department of ECE, St. Joseph’s College of Engineering, Chennai, India.
Published: April 2020

In order to reduce overhead and to improve throughput an effective in Rural Group Head Node(RGHN) and Urban Group Head Node (UGHN) protocol can be implemented in the respective rural and urban scenarios. The first section deals with the efficient implementation of RGHN and UGHN protocols in VANET. In the next phase, working of RGHN in rural areas and UGHN protocol in urban areas are described and the performance analyzed. The developed protocol RGHN and UGHN needs comparison with the standard protocols under both the scenarios. The performance of the proposed protocol RGHN in rural scenario is compared with that of Dynamic Source Routing (DSR) and UGHN in urban scenario is compared with Ad-hoc On demand Distance Vector (AODV) shows the proposed technique providing a better result in terms of throughput, packet delivery ratio, delay and packet loss ratio in the network.
LabVIEW Based Model of Switched Reluctance Motor using PI Controller
Authors:   Department of EEE, DBIT, B’lore, India., Kulakarni* Padmashree V. , Koujalagi Dr. Jyoti ,   Dept of EEE, Dr. AIT, B’lore, India., S. Babitha ,   Dept of ECE, DBIT, B’lore, India.
Published: April 2020

This paper presents new and novel approach towards the development of mathematical model of SRM and controller using Lab VIEW platform Application of PI Controller in Lab VIEW Platform is presented in this paper to reduce settling time and torque ripple, for different combination of Kp and Ki values. All simulation are completely documented with their block diagram and Lab VIEW Subsystem. In Lab VIEW platform, pi controller vi subsystem is developed which helps in reducing torque ripple and settling time..
Allocation of Tasks in Crowdsourcing Problem using Parallel Tasking
Authors:   Department of Computer Science, SVN College, Madurai, Tamilnadu.., Punitha* A. , Visagan A.R. ,   Department of Computer Science, MKU College, Madurai, Tamilnadu., Mahesh R.P. ,   Department of Information Technology, SVN College, Madurai, Tamilnadu
Published: April 2020

Crowdsourcing is a moderately new wonder in software engineering and programming designing. In crowdsourcing, a task is conveyed to a crowd of participants who will work on this task. Task allocation is then a significant aspect in the context of crowdsourcing. If done properly, it conveys victories dependent on the appropriate responses gave by the crowd. However, task allocation in crowdsourcing is certainly not an inconsequential issue. Factors like a task’s prerequisites, the knowledge required for its goals, and the size and heterogeneity of the participants in the crowd all impact task allocation, and subsequently, the expected quality of the task results. Right now, the execution of actions from a plan, that assists the dynamic task allocation in crowdsourcing systems, becomes relevant as an alternative solution. This paper formalizes task allocation in crowdsourcing scenarios as Allocation of Tasks in Crowdsourcing problem (ATCP). The fundamental objective of this paper is to allocate suitable tasks for appropriate workers with the dynamic profile creation of the user and the tasks.
Impact of Internet Banking on the Customer Satisfaction: Evidence from the Indian Banking Sector
Authors:   Assistant Professor, Department of Accounting and Finance, Jaipuria Institute of Management, Jaipur, India., Hada* Dr. Bhupendra Singh
Published: April 2020

Internet Banking is about using the infrastructure for digital age to create opportunities, both in local & global market. IT enables the considerable lowering of transaction cost and the creation of new types of banking opportunities that address the obstacles of time and distance. Banking opportunities are local, global and immediate in internet banking. Internet banking is an online payment system that enables customers of a bank or other financial institutions to conduct a range of financial transactions through websites of financial institutions. Internet banking has many advantages over other traditional banking delivery methods. Internet banking provides banks with an increased customer base, cost savings, mass customization, product innovations, improved marketing, and communication, the ability to develop non-core businesses, and the ability to offer services regardless of geography and time constraints, viewing account balances, recent transactions, ordering cheque books and many more. With the development of new technology, Internet banking is expected to become a major banking method for customers. Internet banking reduces costs by providing customers with another means of accessing their accounts without physically visiting a bank. The main purpose of this study is to analyze various online facilities provided by major public and private banks in India and to measure their impact on customers in terms of customer satisfaction.
Forecasting the Finest Firmness of Biocomposites using Response Surface Design Methodology
Authors:   Department of Mechanical Engineering, Faculty of Engineering and Technology, Annamalai University, Tamil Nadu, India., Parre* A. , Karthikeyan B. ,   Department of Mechanical Engineering, Faculty of Engineering and Technology, Annamalai University, Tamil Nadu, India., Balaji A. ,   Department of Mechanical Engineering, A.V.C College of Engineering, Mayiladuthurai, Tamil Nadu, India., Sudhagar P. ,   Department of Chemical Engineering, Faculty of Engineering and Technology, Annamalai University, Tamil Nadu, India., Udhayasankar R. ,   Department of Mechanical Engineering, Faculty of Engineering and Technology, Annamalai University, Tamil Nadu, India.
Published: April 2020

Natural fibers are considered likely to be used in polymer composite materials as reinforcing agents because of their main advantages such as fine strength and rigidity, low cost, environmentally friendly, degradable and renewable material. A study was conducted to assess the impact of properties of bicomposite made from cardanol resin banana fibers. The banana fiber extracted from the banana stem was treated with alkali to enhance the interfacial linkage around fiber and cardanol resin. Biocomposite was manufactured using formaldehyde mixed with cardanol oil to form cardanol resin mixed with banana fiber using compression moulding Techniques with different process factors such as fiber weight (5%, 10%, 15%, 20%, and 25%) different fiber length (5, 10, 15, 20, and 25 in mm) and alkali treatment (varying in 1%, 3%, 5%, 7% and 9%. The developed banana fiber reinforced composite were then characterized by impact testing showing strong significance and association in DOE using 15.2% fiber weight response surface methodology with 15.3 mm fiber length and 4.7% alkaline treated. Thus we examined the effect of the above factors on impact and suggested the best combinations of factors for composite processing.
Wormhole Attack Isolation Access from Mobile Ad hoc Network with Delay Prediction Method
Authors:   Department of Electronics & Communication, Jaipur National University, Jaipur, India,, Thapar* Shruti , Sharma Sudhir Kumar ,   Department of Electronics & Communication, Jaipur National University, Jaipur, India.
Published: April 2020

The moveable ad hoc networks are untrustworthy and inclined to any intrusion due to their wireless interaction approach. Therefore the information from these networks can be stolen very easily just by introducing the attacker nodes in the system. The straight route extent is calculated with the help of hop count metric. For this purpose, routing protocols are designed. The wormhole attack is considered to be the hazardous one among several attacks. This intrusion is commenced with the help of couple attacker nodes. These nodes make a channel by placing some sensor nodes between transmitter and receiver. The accessible system observes the wormhole intrusions in the absence of intermediary sensor nodes towards the target. This mechanism is significant for the areas where the route distance amid transmitter and receiver is two hops merely. This mechanism is not suitable for those scenarios where multi hops remain amid transmitter and receiver. In the projected study, a new technique is implemented for the recognition and separation of attacker sensor nodes from the network. The wormhole intrusions are triggered by these attacker nodes in the environment. The projected scheme is utilized in NS2 and it is depicted by the reproduction outcomes that the projected scheme shows better results in comparison with existing approaches.
The Role of Bukhara in the Development of the Global Karakul Sheep Industry
Authors:   Independent Researcher, Department of History of Uzbekistan, Karshi Engineering Economics Institute, Karshi City, Uzbekistan., Abdirakhmonovich* Akhmedov Bekzod , Esonovna Muminova Gavkhar ,   Professor, Department of World History, Karshi State University, Karshi City, Uzbekistan.
Published: April 2020

This article analyses the role of Bukhara in the development of Karakul sheep breeding as a part of world agriculture, including the export of sheep from the Emirate to a number of European and Asian countries; Opinions on such issues.
Deep learning in Dermatology for skin Diseases Detection.
Authors:   Department of CS & Eng. Bhabha Institute of Technology Kanpur Dehat, India., Yadav* Ms Upma , Kumar Mr Ashok ,   Department of CS Banasthali Vidyapith Rajasthan, India., Tiwari Miss. Anamika ,   Department of CS & Eng. Bhabha Institute of Technology Kanpur Dehat, India., Dr Saurabh  ,   Department of CS Banasthali Vidyapith Rajasthan, India.
Published: April 2020

Dermatology is a medical field that treats skin health and diseases. People feeling disease symptoms of an affecting the skin must consult a dermatologist if this stipulation does not respond to home remedy. Early detection and treatment can correct most skin disorders. Basal Cell Carcinoma (BCC), Melanoma and Squamous Cell Carcinoma (SCC) are typically appearing type of skin cancers. The purpose of this effort is to provide a system that can be deployed to classify dermatoscopic images to predict skin diseases with early detection and higher accuracy . This work is a concrete effort to accomplish higher degree of accuracy for clinical usage by implementing advances in soft computing and image processing like deep learning and in-depth neural networks in an early stage for 7 class classification for HAM10000 dataset.
A Probabilistic and Deterministic based Defect Prediction through Defect Association Learning in Software Development
Authors:   pursued Bachelor of Computer Engineering from Bharati Vidyapeeth Deemed University College of Engineering, Pune, India, Jadhav* Prof. R.B. , Joshi Prof. Dr. S. D ,   completed PhD in Computer Engineering from Bharati Vidyapeeth deemed to be University, Pune- 43 India., Thorat Mr. Umesh ,   pursued Bachelor of Mechanical Engineering from Sinhagad College of Engineering, Pune, India
Published: April 2020

Software development is a multitasking activity by an individual or group of team. Every one activity engages diverse tasks and complication. To accomplish quality improvement, it is essential to make every activity task free of defects. But locating and correcting defects is more expensive and time-intense. In the past, many potential methods have been used to predict potential drawbacks in the program based on the theory of probability facts. Because the probability method applies a random variable and probability distributions to find a solution, the result is always in a possible range that can be true at some time or may also be wrong. Therefore, an additional calculation method coupled with the probability of making it more accurate and new in predicting the defect of the program. In this paper, we propose a Probabilistic and Deterministic based Defect Prediction (PD-DP) through Defect Association Learning (DAL). The PD-DP implements a Probability association method (PAM) and Deterministic association method (DAM) to predict the software defect accurately in software development. The experimental evaluation of the PP-DP in compare to existing prediction methods shows enhancement in prediction accuracy.
Accurate Breast Cancer Prediction using Machine Learning Techniques
Authors:   Department of Computer Science and Engineering, Mookambigai College of Engineering, Tamilnadu, India., E*. Vinoth S. M. , Valarmathi Dr. P. ,   Professor and Head Department of Computer Science and Engineering, Mookambigai College of Engineering, Tamilnadu, India.
Published: April 2020

Applications of machine learning (ML) have been increasing widely in various fields like recommendation, fault identification and disease prediction. In ML, different algorithms were available and utilized in disease prediction such as heart disease prediction, cancer prediction and other forms disease prediction. In our proposed work, breast cancer prediction using ML has been implemented. Initially breast cancer images have been taken as input, preprocessing steps will be done to remove noisy and irrelevant data from image. Then 2D median filter is a nonlinear operation often used in image processing to reduce "salt and pepper" noise. To increase contrast of image contrast-limited adaptive histogram equalization is used. Segmentation has been implemented and GLCM feature extraction is deployed based on this information classification is implemented. For accurate classification Artificial neural network (ANN) is used to predict whether the patient is affected by breast cancer or not. Compared to other existing method our method predicts results in accurate way.
Optimized design and Performance Analysis of Three Phase Induction Motor using Maxwell Software
Authors:   Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India,., Nandhakumar* A. , kumar R.Senthil ,   Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India, kumar K V Santhosh ,   Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India, Raja T Alex Stanley ,   Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
Published: April 2020

Three phase induction motors are ac motors which are widely employed as a prime mover in most of the industrial applications such as centrifugal pumps, conveyers, compressors crushers, and drilling machines, textile mills etc. In this paper the performance of an 2.2kW, 400 V, four pole, three phase induction motor was analyzed using RMxprt. RMxprt uses a combination of analytical and magnetic circuit equations to predict the performance of this three-phase induction motor.
Multi Constraints Optimal Path based on Routing Protocols in VANETs
Authors:   Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, Uttarakhand, India, Oberoi Vibha , Chaturvedi Praveena ,   Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, Uttarakhand, India
Published: April 2020

Vehicular Ad-hoc network (VANETs) is a type of ad hoc network which has faced many challenges for its implementation such as Technical issues which include are Large Size area, Routing, Security, Congestion, High Mobility, Limited road topology, Intermitted connectivity, Continuous power transmission for significant computing communication & sensing of the network & On road issues include narrow road, unstructured road, all roads are not allowed for all vehicles, busy road, no defined speed on road, no road maintenance, high frequency of accidents, poor sign board, no road side amenities, multiple numbers of toll booths etc. In order to enhance the performance of the desired real time network link between the nodes must be stable and reliable so that information can be transmitted reliably to the desired destination. This paper has experimentally studied the optimal path for different routing protocols in VANETs. This paper clearly concludes which routing protocol is better under different parameters such as number of hops, average hop count, total packet send and received for the realistic environment.
An Efficient Supervised Method for Fake News Detection using Machine and Deep Learning Classifiers
Authors:   Assistant Professor, Sri Krishna College of Technology, Department of Computer Science and Engineering., S Sruthi. M. , R Rahul ,   UG student, Sri Krishna College of Technology, Department of Computer Science and Engineering, G Rishikesh ,   UG student, Sri Krishna College of Technology, Department of Computer Science and Engineering
Published: April 2020

This paper comes up with the applications of Machine learning and deep learning algorithms for police work the 'fake news', that is, dishonorable news stories that come from the unauthorized article writers. This approach was enforced as software and tested against an information set. Aim is to separate the faux news, among the news spread in the articles. It’s required to create a model which is able to differentiate between “Real” news and “Fake” news. The model was created exploitation numerous deep and machine learning strategies. LSTM technique outperforms different classifiers and achieves the accuracy of 94%.
Cloud Based Water Reservoir Quality Monitoring System
Authors:   Department of Electronics & Communication,Graphic Era deemed to be University,Dehardun (U.K) ,India, Ahmad* Anzar , Shekhar* Shashi ,   Department of Electronics & Communication Engineering, Graphic Era deemed to be University, Dehardun (U.K) ,India, Roy* Abhijeet ,   Department of Mechanical Engineering,Graphic Era deemed to be University,Dehardun (U.K) ,India
Published: April 2020

Cloud computing is emerging as the new dimension for computer networks and for the world as a whole. It is touching every aspect of our life. It is changing the way we live. Cloud based water storage quality checking structure is an approach by which we can perceive quality of water supply by using a couple of sensors like Ph sensor, Turbidity Sensor, Oxygen level sensor, Temperature Sensor, Salinity Sensor and using WIFI Module. Using a PAN or WAN sensor system we can get collected message on email and received content can be identified ,analyzed for easy reference and after analysis they are sent to the database of the cloud with the goal that the expert and user mutually can be easily able to know the quality of reserved water.
Enhanced Convolution Neural Network for Tomato Leaf Disease Classification
Authors:   Assistant Professor, Department of CSE, Coimbatore Institute of Engineering and Technology ,Coimbatore,Tamil Nadu, India., Saranya* C.P. , Rajan Dr.D.Palanivel ,   Professor, Department of CSE, C M R Engineering College, Hyderabad, Telangana, India., Mythili M. ,   Assistant Professor, Department of Information Science and Engineering, Vemana Institute of Technology, Bengaluru, Karnataka, India., Pushpalatha Dr.K. ,   Associate Professor, Department of IT, Coimbatore Institute of Engineering and Technology ,Coimbatore, Tamil Nadu, India, Saranya. V. ,   Assistant Professor, Department of CSE, Tamil Nadu College of Engineering, Coimbatore, Tamil Nadu, India
Published: April 2020

When plants and crops are affected by pests it affects the agricultural production of the country. Agricultural productivity depends heavily on the economy. This is one of the reasons why plant disease detection plays a major role in agriculture. Usually farmers or experts observe the plants with naked eye for detection and identification of disease. But this method can be time processing, expensive and inaccurate. Detection of crop disease using a few instantaneous strategy is helpful as it decreases comprehensive surveillance job in huge crop farms and locates disease side effects quite soon, i.e. if they tend on leaves and stems. Enhanced Convolutional neural networks (ECNN) have demonstrated great performance in object recognition and image classification problems. Using a public dataset images of infected and healthy Tomato leaves collected under controlled conditions, we trained a deep convolutional neural network to identify diseases in tomato. As the result, few diseases that usually occur in tomato plants such as Late blight, Gray spot and bacterial canker are detected.
Effect of Impeller Parameters on the Flow inside the Centrifugal Blower using CFD
Authors:   is currently working as Assitant Professor in department of Mechanical Engineering at R C Patel Institute of Technology, Shirpur India, Pathak* Yogesh R , Deore Kailas D ,   is currently working as Assitant Professor in department of Mechanical Engineering at R C Patel Institute of Technology, Shirpur India, Ozarkar Rohan R ,   is currently working as Assitant Professor in department of Mechanical Engineering at R C Patel Institute of Technology, Shirpur India
Published: April 2020

A numerical analysis is carried out to understand the flow characteristics for different impeller configurations of a single stage centrifugal blower. The volute design is based on constant velocity method. Four different impeller configurations are selected for the analysis. Impeller blade geometry is created with point by point method. Numerical simulation is carried out by CFD software GAMBIT 2.4.6 and FLUENT 6.3.26. GAMBIT work includes geometry definition and grid generation of computational domain. This process includes selection of grid types, grid refinements and defining correct boundary conditions. Processing work is carried out in FLUENT. The viscous Navier-Stokes equations are solved with control volume approach and the k-ε turbulence model. In this three dimensional numerical analysis is carried out with steady flow approach. The rotor and stator interaction is solved by mixing plane approach. Results of simulation are presented in terms of flow parameters, at impeller outlet and various angular positions inside the volute. Also, the contours of flow properties are presented at the outlet plane of fluid domain. Results suggest that for the same configurations of centrifugal blower, as we change geometrical parameter of impeller the flow inside the blower get affected.
Side-by-Side Analysis of Key Exchange Algorithms for Load Optimized Security in MQTT Protocol
Authors:   Department of IT, Jain University, Bangalore, India., Mathews* Suja P , Gondkar Dr. Raju R ,   Department of PG Studies, CMR University, Bangalore, India.
Published: April 2020

The Information Technology has evolved and we have reached at an era of Internet of Things (IoT). According to International Telecommunication Union’s Global Standards Initiative (GSI), it is the network of all kinds of ‘things’ embedded with electronics, sensors, actuators, software etc. Things connected in open Internet poses high security risks. Majority of these devices use Message Queuing Telemetry Transport (MQTT) protocol for exchanging information. Most of the devices with limited storage and computing power are connected using MQTT. Since the protocol doesn't provide any mechanism for encryption, the security aspect of the protocol is really weak. This paper describes the need for empowering security in MQTT. In this research work, we benchmark different cryptographic algorithms and propose the best possible algorithm to enable higher level of security in MQTT. This work further demonstrates how to use the proposed algorithm to enable lightweight key exchange mechanism among MQTT devices.
Abnormal Human Activity Detection using Unsupervised Machine Learning Techniques
Authors:   CSE, V R Siddhartha Engineering College, Vijayawada, India., Chalapati Mounika , Pratap A Raghuvira ,   CSE, V R Siddhartha Engineering College, Vijayawada, India.
Published: April 2020

Nowadays there is a significant study effort due to the popularity of CCTV to enhance analysis methods for surveillance videos and video-based images in conjunction with machine learning techniques for the purpose of independent assessment of such information sources. Although recognition of human intervention in computer vision is extremely attained subject, abnormal behavior detection is lately attracting more research attention. In this paper, we are interested in the studying the two main steps that compose abnormal human activity detection system which are the behavior representation and modelling. And we use different techniques, related to feature extraction and description for behavior representation as well as unsupervised classification methods for behavior modelling. In addition, available datasets and metrics for performance evaluation will be presented. Finally, this paper will be aimed to detect abnormal behaved object in crowd, such as fast motion in a crowd of walking people
Smart Electric Sensing in Infrastructure
Authors:   Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India., kumar* K. Prem , Sagana R. ,   Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India., Sharon E. ,   Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India., Prianga S. ,   Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India., Mary M. Sushma Suvetha ,   Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
Published: April 2020

Smart homes utilize advanced systems to bring comfort and convenience to our living experiences. Most of the current frameworks are now trying to move towards automation such as smart homes, smart warehouses. This paper focuses on monitoring the wiring system of modern infrastructure as it is very important while moving into advanced systems. In order to reduce the labour involved in replacement of wires from the main board when fault occurs due to overload, short-circuit, arcing, equipment failure. we have provided a model called SESI, Smart Electric Sensing in Infrastructure, which uses the transistors and the Arduino to find the faults in the electric system. Although, many measures have been taken in smart homes to conserve electricity, there is no means to monitor them. Monitoring them would help us to conserve it more efficiently and also reduces the risk of fire accident
Machine Learning Techniques in RFID Datasets
Authors:   Dept. of Computer Science and Engineering The NorthCap University, Gurugram, Sharma* Meghna , Tomer Manjeet Singh ,   Dept. of Computer Applications J C Bose University of Science and Technology, YMCA, Faridabad, Vashisht Priyanka ,   Dept. of Computer Science and Engineering The NorthCap University, Gurugram
Published: April 2020

In today’s world of wireless communication, technologies like Wi-Fi, Global Positioning Systems (GPS), Radio Frequency Identification (RFID) and Wireless Sensor Networks (WSN) play a vital role in various applications for the benefit and convenience of the society. A widespread application of RFID networks based on automatic data capture technology is supply chain management. In RFID enabled supply chain process lot of possibilities of outliers or anomaly generation due to technical or environmental factors exist. This work mainly focuses on identifying various techniques used for outlier detection in RFID datasets in supply chain process. Most of literature studies are related to objects tracking and product management in the domain of supply chain but very few researchers have worked on the abnormal condition or outlier detection while monitoring of RFID tagged objects. Outliers are any kind of deviation in supply chain processes from its normal processing or behavior. Our research is specific to the supply-chain process using RFID system specifically for the abnormality detection in the localization process in supply-chain process. Inaccurate localization of objects can be due to several reasons like theft, counterfeiting, traffic problem, environmental factors or malfunctioning of the vehicle carrying RFID tagged objects.
Synthesis and Microstructural Characterization of Cu2MnSnS4/Se4 Nano-Thermoelectric Material
Authors:   Mechanical Engineering Department, Qassim University, Buraidah 51452, Saudi Arabia., Ammar* Hany R. , Sivasankaran S. ,   Mechanical Engineering Department, Qassim University, Buraidah 51452, Saudi Arabia, Alaboodi Abdulaziz S. ,   Mechanical Engineering Department, Qassim University, Buraidah 51452, Saudi Arabia.
Published: April 2020

In the present study Cu2MnSnS4/Se4 nanostructured material is synthesized using mechanical alloying. The elemental powders were alloyed in a high-energy ball mill under the following conditions: milling time 25 hours, ball-to-powder mass ratio (BPR) 10:1 and a rotation speed of 300 rpm. Detailed investigation of the microstructure of the synthesized alloy was carried out. The starting elemental powders size and morphology were characterized using Apreo field emission gun scanning electron microscope (FEGSEM). Elemental mapping of the synthesized alloy was characterized using energy dispersive spectroscopy (EDS) attached to FEGSEM system. Analysis of microstructure was performed using EDAX-TEAM advanced software. A dynamic laser light scattering was used for particle size analysis. The results showed that Cu2MnSnS4/Se4 nanostructured is successfully synthesized by ball milling. The Z-average size distribution of the particle reveals that ball milling results in a considerable refining in the particle size from 44 micron down to 923.5 nm. Further, it was observed that 94.4% showed an average size of 725.8±233 nm. Microstructural analysis confirmed the formation of a homogenous structure of Cu2MnSnS4/Se4 alloy in the powder and green samples. The elemental mapping confirmed the formation of solid solution of the processed alloy with homogenous distribution of all elements in the examined region. Quantitative analysis performed by EDAX-TEAM software confirmed the chemical composition and homogeneity of the processed material.
Improving the Performance of Brain-Computer Interface using Deep Learning Algorithms and Event-Related Spectral Perturbation
Authors:   Computer Science Department, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia, Alsufyani* Abdulmajeed
Published: April 2020

Brain Computer Interface allows disabled people to communicate with the external world by using their brain signals. The main goal of a BCI is to provide patients who suffer form any neuromuscular disorders whith a communication channel based on their brain signals. In this paper, the aim is to explore the effects of applying deep learning algorithms and Event Related Spectral Perturbation analyses on the performance of different EEG-based BCI paradigms. Two paradigms were investigated: one is based on the Matrix paradigm (known as oddball); and the other one utilizes the Rapid serial visual Presentation (RSVP) for presenting the stimuli. Deep learning algorithms of convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) were utilized to evaluate the two paradigms. Our findings showed that Matrix paradigm is more effective in detecting P300 signal. In terms of classification methods, deep learning of CNN algorithm has shown superiority performance in comparison with the other machine learning algorithms.
Mechanical Properties of Thermal Ash Aggregate Content in Geopolymer Concrete
Authors:   Resarch Scholar, Department of Civil Engineering, Dr MGR Educational and Research Institute,, K E* Brightlin , T Dr Felixkala ,   Dean-Student affairs and Professor , Department of Civil Engineering, Dr MGR Educational and Research Institute
Published: April 2020

Elimination of cement in concrete was found to get increased with the introduction of geopolymer concrete. In that geopolymer concrete, natural aggregate was replaced by artificial thermal ash aggregate. The mix design was arrived by trail. The replacement level of artificial aggregate was 20, 40, 60, 80 and 100 percentages by weight of natural aggregate. The results of workability and mechanical properties of the mixes are find to be good. About 135% in compressive strength, 15% in split tensile strength and 987% in flexural strength was find to be increased.
Multi-Model Biometric Authentication System for Smart Attendance
Authors:   CSE department, GITAM University, Bangalore, India., Teja* K.Ravi , S H Brahmananda ,   CSE department, GITAM University, Bangalore, India., Jain T J Swasthika ,   CSE department GITAM University, Bangalore, India.
Published: April 2020

To increase the success rate in academics, attendance is an essential aspect for every student in schools and degree colleges. In olden days, this attendance is manually taken by teachers with pen and paper method, which consumes more amount of time in their busy management scheduling era. To make this attendance taking more comfortable and more accurate, a multi model biometric system for attendance monitoring system is proposed using a Raspberry Pi single-board computer. The camera and biometric device which is connected to the system gathers Information regarding the students by recognizing their faces and their fingerprint simultaneously. If both of them match with the student details stored in the database, then the system will be sending an alert about the student presence in the class. The student details which is stored into the database is collected from the students initially. By using these details like images and fingerprints the system is trained by using a Convolutional Neural Network (CNN) Machine Learning Algorithm.
Buckling Sensitivity of Ultra Fine Grained Material AA2618 Connecting Rod
Authors:   Mechanical Engineering Department, Sagar Institute of Science and Technology, Gandhi Nagar, Bhopal, India., Chaurasiya* Prem Kumar , Sahu Nitin Kumar ,   Mechanical Engineering Department, Sagar Institute of Science and Technology, Gandhi Nagar, Bhopal, India., Dwivedi Rashmi ,   Mechanical Engineering Department, Sagar Institute of Science and Technology, Gandhi Nagar, Bhopal, India., Singh Sanjay Kumar ,   Mechanical Engineering Department, Sagar Institute of Science and Technology, Gandhi Nagar, Bhopal, India, Chhalotre Sanjay ,   Mechanical Engineering Department, Sagar Institute of Science and Technology, Gandhi Nagar, Bhopal, India.
Published: April 2020

The objective of the work is to evaluate the best design parameters of connecting rod using Ultrafine Grained Material AA2618. The critical buckling stress for existing material (C70S6) is high and the primary objective is to optimize connecting rod in terms of reduction of weight and stress. The numerical investigation has been carried out using ANSYS. Modeling of connecting rod is done in Solid works designing software. The analysis is performed on Ansys to calculate the critical buckling stress and Von-mises stress is calculated in the stress analysis by applying the maximum external load. The analysis results are plotted graphically and results are compared to find the useful outcomes which are used to predict the structural behavior of connecting rod under given load.
Autonomous Robot for Delivering The Orders in Restaurants By using Raspberry Pi
Authors:   Student at SVERI’s COE, Pandharpur, India, Katkar* Miss.Anjali P. , Bhaldar Mr. Husain ,   Research Scholar, BKIT, Bhalki, VTU Belgavi &Asst Prof. SVERI’s COE, Pandharpur, India, A.More Miss.Kirti ,   Student at SVERI’s COE, Pandharpur, India, Yelasange Miss.Anjali M. ,   Student at SVERI’s COE, Pandharpur, India
Published: April 2020

In today’s era most of the people prefer dinner in the restaurant. The use of robots as waiters in restaurants is an increasing trend in the service industry. The Waiter-robot is an exceptional autonomous robot which has the ability to follow a designated path by measuring the distance and reach its intended destination. It reducing effort, time, error, etc and increasing quality, capacity and efficiency in the delivering the food. This robotic application using a Raspberry-pi based kit mounted with ultrasonic sensors for mapping and localization of destination table.
E-Cart Design for Controlling Cart Abandonment in E-Commerce: A Conjoint Experiment
Authors:   Department of Management, Amrita Vishwa Vidyapeetham, Kochi, India., Paul* Gratel Anna , K Harsha ,   Department of Management, Amrita Vishwa Vidyapeetham, Kochi, India., G Rejikumar ,   Department of Management, Amrita Vishwa Vidyapeetham, Kochi, India.
Published: April 2020

This study attempted to understand the most important attributes and their preferred levels of an e-shopping cart for maximum utility perceptions by e-commerce customers. The research has significance in the backdrop of observations that online customers have multiple sorts of hesitation on purchase completions, and their cart abandonment tendencies are causing serious challenges to e-commerce firms across the world. Assuming that better e-cart design can minimize cart abandonment intentions, an eight attribute conjoint experiment with a total of nineteen levels was conducted to decide on an optimum cart design. The experiment concluded that online customers prefer an order summary page with product images, add to cart option without login, live chat feature in cart; add to cart button on both sidebar and top of the page; online payment options, security logo and social proof in e-cart, purchase history review option in the cart page, and delivery progress tracking bar in the cart page itself.
Optimization of a3D Aircraft Morphing Wing with highly controllable Aerodynamic Performance
Authors:   Aeronautical Engineering, Excel Engineering College, komarapalayam, India., Chaudhary* Anmol Krishna Mohan , C Deepan ,   Aeronautical Engineering, Excel Engineering College, komarapalayam, India., A Latshathipathi ,   Aeronautical Engineering, Excel Engineering College, komarapalayam, India., S R Arun ,   Assistant Professor, Aeronautical Engineering, Excel Engineering College, Komarapalayam, India., Shah Rakesh Kumar ,   Aeronautical Engineering, Excel Engineering College, Komarapalayam, India.
Published: April 2020

the sole purpose of this project is to compare the aerodynamic performance of the modernistic wing with morphing techniques to the conventional one (i.e. wing with ailerons and flaps). The morphing wing is capable of enhancing the mission profiles through its significant geometrical changes in the surface areas (upper and lower area of wing). The primary aspiration is to calculate the CL and CD (coefficient of lift and drag) of real aircraft with conventional control surfaces and to compare its result with morphing wing. The morphing techniques also enables various prevention of aerodynamic losses (drag, vortices, noise, etc) caused due to geometrical discontinuities of conventional wing with aileron and flap in operating conditions (take-off, cruise, loiter, landing).Catia modelling of proposed wing is analysed by CFD method and to compare and contrast the aerodynamic performance with the conventional (hinged) wing.
Automating Network Simulation Tool and Data Processing in Ad Hoc Networks
Authors:   SSL Lab, ENSIAS, University of Mohammed V, Rabat, Morocco., Berradi* Halim , Habbani Ahmed ,   SSL Lab, ENSIAS, University of Mohammed V, Rabat, Morocco., Souidi Mohammed ,   SSL Lab, ENSIAS, University of Mohammed V, Rabat, Morocco., Amraoui Hicham ,   SSL Lab, ENSIAS, University of Mohammed V, Rabat, Morocco., Mouchfiq Nada ,   SSL Lab, ENSIAS, University of Mohammed V, Rabat, Morocco.
Published: April 2020

One of the crucial and utilized simulator for mobile ad hoc network is the NS3 (Network Simulator). NS3 executes simulation scenarios and produces data regarding which flow monitor (flowMon) files are counted one of the important used format for estimating the research proposal. This article will introduce a novel framework to facilitate the simulation process in mobile ad hoc networks (MANETs). Generally speaking, when network researchers need to evaluate the experiments, there is generally the necessity to estimate the different models advantages by computing a set of QoS metrics to understand the network performance impact in such scenario. Network simulators, and NS3 specifically, need important program writing from the researcher to consolidate simulation results. This article states a contribution for NS3 composed of a new Framework that tends to make it less complicated to obtain and plot various QoS network performance metrics. This framework generates and runs simulations using common simulation parameters, such as velocity, mobility models, and number of nodes automatically. It also contains permits to parse through the generated flow that contain several essential metrics a researcher may need in order to analyze the simulation, such as end-to-end delay, lost packet, and throughput.