bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilisation of E-Waste, Fly Ash in Manufacturing of Paver Blocks and Tiles
Authors:   M.Tech in Environmental science at G.H. Raisoni College of engineering and management., Ingole Aniket Ravindra , Sonole Nilesh Naresh ,   M.Tech in Environmental science at G.H. Raisoni College of engineering and management., Thakur Chirag Ramesh ,   M.Tech in Environmental science at G.H. Raisoni College of engineering and management.
Published: August 2019

E-Waste that is increasing day by day turning into a major threat to public health and successively pollutes the setting. India ranks fifth in the world for e-waste generation; about a pair of million a lot of e-waste is generated associate rally and an unrevealed quantity of e-waste is foreign from alternative countries around the world. The aim of this project is to exchange cement with e-waste and fly ash in paver block, tiles and to chop back the worth of paver block and tiles compared thereto of convention concrete paver blocks and tiles. Use of concrete paver block and tiles square measure presently day after day turning into standard; they are used for paving of approaches, strategies and ton and collectively the pre-engineering building and pavements. Throughout this project, we've used e-waste in various proportions with quarry dirt and ash, coarse combination, compound, and metal-containing material and cement. This can be often one in every of the foremost effective ways that to avoid the buildup of e-waste which can be a non-degradable waste. This as an alternative saves the quanta of sand and clay that ought to be got eliminate from the dear stream beds. The e-waste getable in surplus quantity and thence the worth issue comes down. Collectively Coloring agents are added to the mixture to comprehend desired shades. Thence throughout this project, an endeavor is formed to review regarding the properties of the paver blocks and tiles that are ready-made pattern e-waste. The paver blocks and tiles were prepared and tested and so the results were mentioned.
The Mediating Effect of Knowledge Transfer in Construction Project
Authors:   Faculty of Management and Economics Sultan Idris Education University, Malaysia., Obaid Mohammed Hatem , Habidin Nurul Fadly ,   Faculty of Management and Economics Sultan Idris Education University, Malaysia.
Published: August 2019

The construction industry is a competitive high-risk industry with an unprecedented uncertainties in technology, budget, and development processes. It has become more dynamic in nature and the execution of projects have become more complex and difficult to manage. The need then evolved to develop a framework for project performance. This study investigates the factors affecting the project success and performance using a knowledge and resource-based approach. Data was collected from project managers, civil engineers, site managers, and architects. A total of 221 responses were collected. The data analysis was conducted using SPSS and Smart PLS. This results from this investigation revealed that knowledge transfer does not mediate the effect of strategic factors or employee factors on the project performance of Iraqi public construction projects. This finding indicated that the role of knowledge practices in Iraqi public project is still not matured. Top management are advised to effectively implement the knowledge management practices in public projects. Implementing knowledge management will avoid the organization the cost of repeating the same mistakes. Thus, it was concluded in this study that knowledge transfer is still in its infancy and currently it has no mediating effect between the variables of this study.
Kleinberg’s Hyper-Richness Based Fuzzy Partition Clustering for Efficient Bi-Temporal Data
Authors:   Research Scholar, Department of Computer Science, Jairams Arts and Science College, Karur – 639003,. Tamilnadu, India., Dhas L. Jaya Singh , Mukunthan B. ,   Research Supervisor, Department of Computer Science, Jairams Arts and Science College, Karur – 639003,Tamilnadu, India.
Published: August 2019

Clustering is the process used for partitioning the total dataset into different classes of similar objects. The group contains knowledge about their members and also helps to understand the structure of the dataset very easily. Clustering the bitemporal data is one of the major tasks in data mining since the bitemporal datasets are very large with various attribute counts. Hence the accurate clustering is still challenging tasks. In order to improve the clustering accuracy with less complexity, Kleinberg’s Hyper-richness Bitemporal property based fuzzy c means partition Clustering (KHBP-FCMPC) technique is introduced. The KHBP-FCMPC technique partition the bitemporal dataset into number of possible groups with an improved performance rate based on a distance metric. At first, the ‘c’ numbers of clusters are initialized. The KHBP-FCMPC technique uses the core data point module and authority sector module to minimize the execution time of clustering the data points. Core data point module served as the centroid of the cluster. Each cluster contains one core data point. After that, the distance is computed with the membership function. The authority sector module assigns the data points into the cluster with minimum distance. After that, the centroid is updated and the process iterated until the convergence is met. Finally, the Kleinberg’s Hyper-richness Bitemporal property is applied to verify the total dataset equals the partition of all the data points. This property used to group the entire data points into the cluster with higher accuracy. Experimental evaluation is carried out using a temporal dataset with different factors such as clustering accuracy, false positive rate, time complexity and space complexity with a number of data points. The experimental results show that the proposed KHBP-FCMPC technique increases the bitemporal data clustering accuracy with less false positive rate, time complexity as well as space complexity. Based on the results observations, KHBP-FCMPC technique is more efficient than the state-of-the-art methods.
Consequences of Body-Biasing Technique on SRAM Memory
Authors:   Department of ECE, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, India., Kumar Mukesh , Ubhi Dr. J. S. ,   Department of ECE, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, India.
Published: August 2019

The circuit changes the threshold voltage effectively with a definite delay and power by altering the body biasing of the transistors. The body bias is employed to govern the frequency and leakage of the memory device. The threshold voltage of individual transistor is decreases by applying the reverse body bias (RBB) and increases with forward body bias (FBB). This paper presents the viability of RBB to decrease the leakage power and increase in the speed of operations for SRAM circuit. The investigation of RBB dependencies on various performance parameters are analyzed. It is observed that the leakage power improves by 30.32% on applying RBB voltage compared to zero body bias while the transient power increases by 3.22% but decrease of delay by 84.56% dominates on it. Because of this the overall energy consumption reduces by 84.06%. Further the simulation work is carried out to see effect of supply voltage variation on leakage power at different RBB voltage and temperature. Therefore, the RBB scheme is beneficial for devices of low leakage, low energy and high speed of operation but this RBB voltage is limited by band-to-band tunneling current.
Ant Colony Optimization Based Routing Scheme in Vehicular Delay Tolerant Networks
Authors:   Department of Information Technology, National Institute of Technology Raipur, Raipur, India., Sonkar Nidhi , Pandey Sudhakar ,   Department of Information Technology, National Institute of Technology Raipur, Raipur, India., Kumar Sanjay ,   Department of Information Technology, National Institute of Technology Raipur, Raipur, India.
Published: August 2019

Delay Tolerant Networks finds its application in variety of environments and addresses issues like intermittent connection, long and variable delays and high latency. Vehicular Delay Tolerant Networks was introduced due to its various characteristic matches with DTNs. In particular class of VDTN there are two types of nodes: Stationary and Mobile nodes. Stationary nodes are deployed along the roadside and mobile nodes are constrained to move over the roads with variable speeds. This letter presents a new routing algorithm based on Ant Colony Optimization in Vehicular Delay Tolerant Network. We performed extensive simulation in ONE simulator and compare with Probabilistic Bundle Relaying Scheme to gauge the benefits of Ant Colony Optimization based scheme over Probabilistic Bundle Relaying scheme.
Practical Scrutiny for Concrete Strength Properties of Ready-Mix Concrete Plant from Waste Concrete Aggregate
Authors:   Ph.D. from VIT, VIT Vellore,, Shelar Abhay B. , Mahindrakar Dr Amit ,   Professor in the Civil Engineering dept., VIT Vellore..
Published: August 2019

The rise in the awareness of climate change and the increasing environmental concerns has led to research in the areas of using the waste materials from Ready Mix Plants. This paper is an attempt to focus on the use of these wastes as using ready mix concrete plant waste aggregates obtained by crushing, and finding motorized assets of concretes complete by using many aggregates proportions with various proportions. Recycling materials is an efficient way to increase the life cycle of the material and contributes to environmental protection.
Diabetic Retinopathy Detection Using Neural Network
Authors:   Computer Science Department, Karnataka University Dharwad, India., Gurani Vijay Kumar , Ranjan Abhishek ,   Dean and Head of Institution, Botho University, Lesotho., Chowdhary Chiranji Lal ,   Department of Information Technology, VIT Vellore, India.
Published: August 2019

Now-a-days diabetics are affecting many people and it causes an eye disease called “diabetics retinopathy” but many are not aware of that, so it causes blindness. Diabetes aimed at protracted time harms the blood vessels of retina in addition to thereby affecting seeing ability of an individual in addition to leading to diabetic retinopathy. Diabetic retinopathy is classified hooked on twofold classes, non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). Finding of diabetic retinopathy in fundus imaginary is done by computer vision and deep learning methods using artificial neural networks. The images of the diabetic retinopathy datasets are trained in neural networks. And based on the training datasets we can detect whether the person has (i)no diabetic retinopathy, (ii) mild non-proliferative diabetic retinopathy, (iii) severe non-proliferative diabetic retinopathy and (iv) proliferative diabetic retinopathy.
Cluster Associations as a Factor of Innovative and Integrative Development of the Economy
Authors:   Department of entrepreneurship, finance and taxation, University of the State Fiscal Service of Ukraine, Ukraine, Bakulina Oksana , Legan Iryna ,   Department of entrepreneurship, finance and taxation, University of the State Fiscal Service of Ukraine, Ukraine, Bakhov Ivan ,   Interregional Academy of Personnel Management, Ukraine
Published: August 2019

The purpose of the article is to substantiate the motivational preferences of the cluster formation participants, as well as to determine the influence of clusters on the enterprise's performance and socio-economic development of regions. Based on the study of the preferences of the creation and functioning of the clusters, it has been revealed that cluster formations allow each of the participants to benefit from the synergy effect arising in the course of combining efforts for the sake of production scaling. The obtained results show that cluster formations are characterized by an emphasis on increasing employee satisfaction due to the integration of motivational preferences of the cluster association participants (production, financial, marketing, innovative, personnel, socio-psychological, environmental, and other preferences) and the formation of qualitatively new opportunities for the implementation of corporate and personal needs of employees. The assessment of the possibilities of forming clusters made it possible to identify the most important factors, such as the development of entrepreneurial culture, which in turn affected the formation of the enterprise’s image, the trust of communities, the implementation of innovations, and access to new markets. Based on the conducted study, the authors have determined the formation mechanism of cluster associations, which includes economic, organizational, social, and environmental components.
Measuring Security for Applications Hosted in Cloud
Authors:   Jawahar Lal Nehru Technological University, Kakinada, India., Chauhan Nitin Singh , Saxena Dr. Ashutosh ,   CRRAO-AIMSCS, UoH Campus, Hyderabad, India., Murthy Dr. J.V.R ,   CSE Dept., Jawahar Lal Nehru Technological University, Kakinada, India.
Published: August 2019

Despite the numerous benefits of cloud computing, concerns around security, trust and privacy are holding back the cloud adoption. Lack of visibility and tangible measurement of the security posture of any cloud hosted application is a disadvantage to cloud service customers. Decision to migrate workloads on the Cloud requires thoughtful analysis about security implications and ability to measure the security controls after hosting. In this paper, we propose a framework to quantitatively measure different aspects of information security for Cloud applications. This framework has a system through which we can define applications specific controls, gather information on control implementation, calculate the security levels for applications and present them to stakeholders through dashboards. Framework also includes detailed method to quantify the security of a Cloud application considering different aspects of security, control criticalities, stakeholder responsibilities and cloud service models. System and method provide visibility to Cloud customer on the security posture of their cloud hosted applications.
Two-Phase Security Framework for Network Layer Communication in Ad Hoc Clouds
Authors:   Department of CSEA, IGIT, Saranga, Odisha, India., Pani Niroj Kumar , Mahapatra Satyasundara ,   Department of CSE, Pranveer Singh Institute of Technology, Kanpur, UP, India., Dash Rati Ranjan ,   Department of Mech Engg., CET, Bhubaneswar, Odisha, India.
Published: August 2019

An ad hoc cloud computing environment on the infrastructure point of view is formed by consuming resources from existing occasionally available computing setups that are primarily used for some other purposes, for example, personal computers, mobile phones and such similar devices connected to the internet. In this paper, we propose a mechanism to secure the network layer communications particularity routing and data packet forwarding in ad hoc cloud environment. The paper details the proposed scheme and analyses its robustness on the security perspective.
License Plate Recognition with Feature Salience and Neural Network
Authors:   Department of Electronics and Communication Engineering, Saveetha School of Engineering, Chennai, India., G Uganya , M.B Sudhan ,   Department of Electronics and Communication Engineering, VINS Christian College of Engineering, Chunkankadai, Kanyakumari, India., P.S Shijin Kumar ,   Department of Electronics and Communication Engineering, Marri Laxman Reddy Institute of Technology and Mangement, Dundigal, Hyderabad, India.
Published: August 2019

Character recognition algorithm is considered as a core component of License Plate Recognition (LPR) systems. Numerous methods for License Plate (LP) recognition have been developed in recent years. However, most of them are not advanced enough to recognize in complex background and still demand improvement. This paper introduces a novel system for LPR by analyzing vehicle images. Accurate segmentation of license plate and character extraction from the plate is accomplished. In the plate segmentation module, Hough transform is put forwarded to identify plate edges using line segments. Radon transform adjusts the skew between LP and the viewer, thereby improve the recognition result. Four features are extracted from the LP image, and best features are selected using feature-salience theory. Histogram projection is performed horizontally and vertically to isolate individual characters in the LP. Finally, Back Propagation Neural Network (BPNN) is used to identify the characters present in the LP. From experimental results, it is evident that the proposed system can recognize LP more efficiently and establish a good background for future advancements in LPR.
E-commerce Sites with Outfit Composition using Deep Learning Method
Authors:   Computer Engineering Department, ZCOER, Pune, India,, Mote Aparna V. , Patil Pratima ,   Computer Engineering Department, Trinity Academy of Engineering, Pune, India
Published: August 2019

The fashion industry has developed in many fields and its growth is making an enormous promote in article of clothing company and e-commerce entity. The difficult task for IT industry in this field is designing the predictive system of data mining to model this. E-commerce uses electronic communication as well as information technology in many transactions for creating, transforming or for redefining the relationships between individuals and organizations. It simply means buying of products, services and information and selling them through computer network. It is totally changing the traditional approach of business. The main change in business is noticeable growth and it has many significant effects on environment as well. This is the reason why it is so preferred in business nowadays. The important part of the proposed system is to rate the fashionable outfit individual and it is considers appearances as well as meta-data. Our approach has first implemented a system of encoding visual characteristics with the help of deep convolution network for complicated contents because it is not possible to list or to label every attribute of a image. Secondly, we proposed a multi-model deep learning framework for rich contexts of fashion outfit. We propose a system which will recommend with review comments and which product should purchase and the system will display a rating of the product.
Knowledge Based System using Ontology for Accessing Sentiments of Indian Railways Tweets
Authors:   PhD scholar in CSE Dept NIT Patna, India., Donthi Rakesh kumar , Haider Md. Tanwir Uddin ,   MTech., and PhD degree in CSE Dept NIT Patna, India.
Published: August 2019

The interactions in social networks like Twitter are reflecting sentiments of people at large. Especially opinion mining has wherewithal to provide social feedback that complements traditional feedback for making strategic decisions. The sentiments data is basically stored in the Relational Data Base. But the demerits of this data base is that it comes back with an answer at most once and it is very difficult to address complex queries over the data, lagging inherent properties such as transitivity or symmetry. It also has closed world assumption i.e., what is not known to be true in the data base is by default considered as false because knowledge represented in the data base is assumed to be complete. To overcome all these demerits, we have developed knowledge-based system using ontology, for accessing sentiments of Indian Railways tweets. Indian Railways (IR) is very huge organization which consistently strives to improve its services from time to time. In our prior work, a framework was proposed and implemented using sentiment analysis for Indian railways tweets. The results were grouped into clusters based on five attributes pertaining to IR such as Cleanliness, Staff Behaviour, Punctuality, Security and Timeliness. These clusters are being updated from time to time to reflect up to date social feedback. However, the problem with the existing system is that, its accessibility and ease of use to stakeholders is not easy. So, we proposed a knowledge based system which will represent clusters for a universal and interoperable data representation that is from database to RDF schema to ontology and apply inference rules and query using SPARQL. This system is accessible to humans and also programs in heterogeneous Machine-to-Machine (M2M) environments. We proposed a methodology to achieve this and the knowledge is made available for further processing and stakeholders can access. The proposed system is evaluated with a prototype application and found to be useful and flexible.
Literary trends in Cyber Space: Portrayal of the Metamodern “wings of Poesy”
Authors:   Research Scholar, Department of English, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, Kerala, India., G Amritha. , Suresh Manasi ,   PG Student, Department of English, Amrita School of Arts and Sciences , Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, Kerala, India., B Indu. ,   Assistant Professor, Department of English, Amrita School of Arts and Sciences , Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, Kerala, India.
Published: August 2019

English literature, after sailing through different courses down the history, has now entered a new space, which may affect its further cruise. The growth of technological space has given rise to a new genre called cyber literature, which plays a significant role in the promotion of literary works. Cyber literature refers to written literary texts, distributed and read on electronic screens. This electronic space provides a more flexible and convenient platform for the artistic expressions of aspiring and budding authors. Cyber literature which emerged towards the end of the 1990s through blogging, later expanded in social media platforms like Facebook, Instagram, Twitter, Myspace etc. While the means and modes of expression changed, literature was again moulded into something else, satisfying the needs of a modern reader. This paper explores the possibility of social media and online communities as the new alternative to print publication, and it also aims at studying the present and upcoming literary trends in the cyber space through a few examples. The case study includes an analysis of the works of Rupi Kaur, an author who paved her way for fame using Instagram; Terribly Tiny Tales and other pages in Facebook which seized the young hearts with relatable snippets and prose poems; applications like “Haiku jam” which bring together people from all over the world to write a Haiku in unison. The modern generation which upgrades their lifestyle along with the technological evolution, and the contemporary issues that affect them, brings out a new literary culture. The unrestrained author-reader interaction further decreases the former gap which held back the readers from voicing their opinions. While it possesses both positive and negative effects, it creates a space where everyone can be a writer, though only the fittest will survive.
A Robust Isolated Automatic Speech Recognition System using Machine Learning Techniques
Authors:   Department of Electronics Engineering, J. C. Bose UST, Faridabad, India, Mendiratta Sunanda , Turk Neelam ,   Department of Electronics Engineering, J. C. Bose UST, Faridabad, India., Bansal Dipali ,   ECE Department, FET, Manav Rachna International Institute of Research and Studies, Faridabad, India.
Published: August 2019

In order to make fast communication between human and machine, speech recognition system are used. Number of speech recognition systems have been developed by various researchers. For example speech recognition, speaker verification and speaker recognition. The basic stages of speech recognition system are pre-processing, feature extraction and feature selection and classification. Numerous works have been done for improvement of all these stages to get accurate and better results. In this paper the main focus is given to addition of machine learning in speech recognition system. This paper covers architecture of ASR that helps in getting idea about basic stages of speech recognition system. Then focus is given to the use of machine learning in ASR. The work done by various researchers using Support vector machine and artificial neural network is also covered in a section of the paper. Along with this review is presented on work done using SVM, ELM, ANN, Naive Bayes and kNN classifier. The simulation results show that the best accuracy is achieved using ELM classifier. The last section of paper covers the results obtained by using proposed approaches in which SVM, ANN with Cuckoo search algorithm and ANN with back propagation classifier is used. The focus is also on the improvement of pre-processing and feature extraction processes.
Collusion Attacks in XOR Based RG-VSS
Authors:   CSED, MNNIT ALLAHABAD, Prayagraj, India., Yadav Mainejar , Ranvijay  ,   CSED, MNNIT ALLAHABAD, Prayagraj, India.
Published: August 2019

Visual secret sharing (VSS) is a well-known technique from the past few decades for data security. Recently, XOR based VSS has attracted many researchers due to its lossless or good visual quality of reconstructed secret image. Cheating in visual cryptography based VSS was introduced by Horng et. al. in 2006. Cheating occurs when a dishonest participant presents fake share and performs stacking of fake share with honest participants who have genuine share, thereby revealing the fake secret image instead of the original secret image. Cheating occurs when some XOR based VSS are exposed to collusion attacks. Here, in this paper, we have demonstrated and proved that there is a security issue in existing XOR based VSS schemes.
Mechanical Behavior of Coir Fiber Reinforced Epoxy Composites with Variable Fiber Lengths
Authors:   Research Scholar, Dept. of Mechanical Engg., Koneru Lakshmaiah Education Foundation, Guntur, India., Jagadale Mr. V. S. , Padhi Dr. S. N. ,   Professor, Dept. of Mechanical Engg., Koneru Lakshmaiah Education Foundation, Guntur, India.
Published: August 2019

Most studies on the application of natural fibers as reinforcement in polymer composites are growing as a result of the changes in characteristics that fibers can provide for the product. This can be achieved by manufacturing of composites using Hand Layup process. The 2% NaOH fiber treatment was performed to improve fiber-matrix interfaces making spathe- fibre-reinforced composites better mechanical characteristics. Filler loadings as 5% by volume of coir fiber are selected as reinforcement in composites. The varying lengths of fiber chosen as 5mm, 10mm & 15mm and resin-hardner ratio are maintained as 10:0.8. A total 3 numbers of plates with volume as 300 х 300 х 4 mm3 were produced and specimens as per the various ASTM standard were tested to determine the ultimate various Mechanical properties for different configuration. The strength of epoxy resin / coir fiber composites was noticed at a maximum 15 mm (15.27 N / mm2) fiber length. The maximum impact strength of the charpy was also 15 mm fiber length (9.87 kJ / m2).The Experimental results were validated using a numerical method technique in FEA software. The obtained results by experimentation and Finite Element Analysis are very much closer to each other. The results show good mechanical properties and hint us as a replacement for conventional materials in industrial applications.
Design of a Roller Bearing Grease Removal Device
Authors:   Mechanical Engineering, GMR institute of technology, Rajam, India., Vamsi Anupoju Sai , Veerendra Singavarapu ,   Mechanical Engineering, GMR institute of technology, Rajam, India., Rao Seela Chiranjeeva ,   Mechanical Engineering, GMR institute of technology, Rajam, India.
Published: August 2019

In the present Scenario, The manual method for Removing grease from the Roller Bearing used in the railway department became a major problem. Chemicals will effect humans while cleaning the railway bearings in manual method. In order to reduce human effect and increase efficiency in cleaning, we are aimed to design a machine which will automatically clean the bearings and will decrease the time of cleaning. In the overhauling process, which will be done manually will be directly apply the kerosene and the compressed air. This suggested machine will clean the bearing automatically by providing kerosene and compressed air with high velocity. The compressed air with high velocity will be provided to rotate the bearing continuously and kerosene will be applied simultaneously, Thus the cleaning of the bearing. Will be done automatically. It works on principle that kerosene air mixture will reduce the density and remove the grease from the bearing completely and it is collected in a drain. After the overhauling process, the parts will be assembled in the railway coaches. So this machine can reduce the time in the working process and avoids the human problems in manual method.
The Importance And Necessity Of Establishing Strong Cooperation Between Businesses And Universities In Uzbekistan
Authors:   Management and Marketing, Tashkent university of Information Technologies named after Muhammad al-Khwarizmi/ Tashkent, Uzbekistan., Ismoilova Gulnora , Dehqonov G’ayrat ,   Management and Marketing, Tashkent university of Information Technologies named after Muhammad al-Khwarizmi/ Tashkent, Uzbekistan., Nabieva Feruza ,   Management and Marketing, Tashkent university of Information Technologies named after Muhammad al-Khwarizmi/ Tashkent, Uzbekistan.
Published: August 2019

Today, efficiently implementing innovations in entrepreneurship is vital. The root of innovation stems from education that needs investment. This thesis analyzes the current trends of entrepreneurship, factors influencing on it and ways of improving its status in Uzbekistan. The article also suggests and encourages industries and entrepreneurs to invest university research sections so that to hold university and entrepreneurs’ partnershipfor reaching optimum solutions to current issues.
Development of High Quality Color Image Compression using Block Transformation
Authors:   Department of Computer Science and Engineering, Barkatullah University, Bhopal(M.P)., India., Parashar Prashant , Singh Dr. Divakar ,   Department of Computer Science and Engineering, Assistant Professor in BUIT, Barkatullah University, Bhopal(M.P)., India.
Published: August 2019

The upcoming era of social media will be highly equipped with the images and the videos. Images or multimedia content sharing and storing services are still costly for common man which is need to be resolved to cover all the users either middle class or high society users. Various online platforms have filled the gaps for freedom of expression for everyone. demand of the multimedia data sharing telecommunication networks has increased. images has changed the requirements for effective transmission and storage media. With the convenience of accessibility of press tools and digital image web exchange, there has been a dramatic increase. Image is the least component of multimedia information and includes a important portion of the velocity of communication for multimedia data Developments in image compression techniques have therefore developed potential requirement. For all pictures, a fundamental concept of image formation is that the pixels are linked and comprise extremely useless data afterwards. The primary objective of this job is to discover in the image reduced associated pixel intensities. In this work an adaptive frequency domain block processing for color image compression has developed and simulated.
Bearing Strength and Failure Modes Analysis of Carbon Reinforced Aluminium Laminate
Authors:   Doctoral research in the area of fiber reinforced composites at Vel Tech University, Chennai., Sathyaseelan P. , Karthik S. ,   Assistant Professor in the Department of Mechanical Engineering at Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai., Alphonse Mathew ,   assistant professor in the department of mechanical engineering at Vel Tech University, Chennai., Kumar R. Ramesh ,   Faculty of mechanical engineering at Vel Tech University, Chennai.
Published: August 2019

Objective of this paper is study the bearing strength and failure modes of the Fiber Metal Laminates prepared by hand layup technique in two different stacking sequences. Parameters like ratio of hole distance to hole diameter (e/D), ratio to the width of composite to hole diameter (W/D) are varied during the experiment. Hole diameter is kept constant as 6mm and e value is taken as 6mm, 12mm, 18mm, 24mm, 30mm and 36mm. Similarly the width of the FML specimen is maintained as 24mm and 36mm respectively. Results show that laminate with [Ca0°/Ca90°/Al/Ca90°/Ca0°]s orientation is having a bearing strength 3.94% higher than that of [Al/Ca0°/Ca90°/Al/Ca0°]s orientation. In terms of failure modes the specimens with distance-diameter ratio greater than 3 and the two width- diameter ratio 4 and 6 exhibited bearing failure. For smaller ratios, the failure is due to shear out which involves combination of bearing and net tension failure.
Implementation of Security Enhancement in AES by Inducting Dynamicity in AES S-Box
Authors:   Department of CSE, SSCET Badhani (Pathankot) Gurdaspur, Punjab, India, Nissar Gousia , Garg Dinesh Kumar ,   Department of CSE, SSCET Badhani (Pathankot) Gurdaspur, Punjab, India, Khan Burhan Ul Islam ,   Department of ECE, Kulliyyah of Engineering, UIAM Gombak, Malaysia.
Published: August 2019

Advance Encryption Standard (AES) supersedes Data Encryption Standard (DES) and is the best known and most widely used block cipher. As for now, there are no known practical attacks that would allow anyone to read correctly implemented AES encrypted data. However, several theoretical attacks have been announced until now. A theoretical attack called Biclique Attack is known to have broken Full AES and requires 2126.1, 2189.7, 2254.4 operations to recover an AES-128, AES-192, AES-256 respectively. Biclique Attack is faster than Brute force attack by a factor of four. As such, these theoretical attacks are of high computational complexity; they do not threaten the practical use of AES in any way. However, attacks always get better; they never get worse. As the technology evolves, successful attacks (using Quantum Computing and faster GPU) against AES may turn up, and they may be difficult to ignore. In this study, we aim to enhance the security prospects of AES with the inclusion of Dynamicity character in AES S-Box for increased resilience against Brute Force Attack and Biclique Attack, and hashing technique is combined with AES algorithm to achieve variance in security using MD4, SHA3 or SHA5. The novel key dispersion technique is introduced to increase the avalanche effect of AES algorithm.
Handling Multifacets of Trust Management in Cyber Physical Systems
Authors:   Asst. Prof. CSE Dept., Pragati Engineering College(A),Surampalem,A.P.,India ., Yogi Manas Kumar
Published: August 2019

Trust should be learnt from history and context sensitive. It should not be absolute in nature. Due to the conglomeration of various technologies in a secure cyber physical system it is quite a challenge to handle trust issues in a cyber physical system. Trust management in cyber physical system is needed due to increase in the degree of autonomy, decentralized policies ,dynamic environment, decision-making based on social rules,customs,laws,values, and ethics. This chapter brings light into the existing strategies already applied by few organizations, their inherent benefits and consequent shortcomings too. There are many factors contributing towards the establishment, expression, evaluation ,maintenance of trustworthiness. In this chapter we advocate a novel framework for trust management which stands up to the research directions of how to build a unified framework for trust management, how to modify the way we compute trust, how to decide the right granularity for a trust model.
An Insight on Sentiment Analysis Research from Text using Deep Learning Methods
Authors:   Research Scholar, School of Computing Science and Engineering, VIT Chennai Campus, Chennai, 600127, India., Daniel D. Christy , Shyamala L. ,   Associate Professor, School of Computing Science and Engineering, VIT Chennai Campus, Chennai, 600127, India.
Published: August 2019

Nowadays, Deep Learning (DL) is a fast growing and most attractive research field in the area of image processing and natural language processing (NLP), which is being adopted across several sectors like medicine, agriculture, commerce and so many other areas as well. This is mainly because of the greater advantages in using DL like automatic feature extraction, capability to process more number of parameters and capacity to generate more accuracy in results. In this paper, we have examined the research works which have used the DL based Sentiment Analysis (SA) for the social network data. This paper provides the brief explanation about the SA, the necessities of the pre-processing of text, performance metrics and the roles of DL models in SA. The main focus of this paper is to explore how the DL algorithms can enhance the performance of SA than the traditional machine learning algorithms for text based analysis. Since DL models are more effective for NLP research, the text classification can be applied on the complex sentences in which there are two inverse emotions which produces the two different emotions about an event. Through this literature appraisal we conclude that by using the Convolutional Neural Network (CNN) technique we can obtain more accuracy than others. The paper also brings to the light that there is no major focus on mixed emotions by using DL methods, which eventually increases the scope for future researches.
Enhanced Medical Tweet Opinion Mining using Improved Dolphin Echolocation Algorithm Based Feature Selection
Authors:   Research scholar, Department of Computer Science and Engineering, Kongu Engineering College, Perundurai, Erode, Tamil Nadu- 638060, India., Anuprathibha T. , Selvi Dr. C. S. Kanimozhi ,   Associate Professor, Department of Computer Science and Engineering, Kongu Engineering College, Perundurai, Tamil Nadu- 638060, India.
Published: August 2019

Extraction and analysis of public opinions from social network data can provide interesting outcomes and inferences about product, service, event or personality. Twitter is one of the most popular medium for analyzing the public sentiment through user tweets. Feature specific opinion analysis provides highly accurate and effective classification and categorization of public opinions. This paper focuses on developing an opinion mining framework for automated analysis of tweet opinions using efficient feature selection and classification algorithms. For this purpose, an Improved Dolphin Echolocation Algorithm (IDEA) is developed by enhancing the optimization performance of the Dolphin Echolocation Algorithm (DEA). The limitations of DEA are the insufficient exploration and exploitation properties in local optimum solutions and also impact the convergence rate. These shortcomings are overcome by the proposed IDEA algorithm. In this work, first the tweets are collected and pre-processed to extract the features using Part-of-Speech (POS) tagging and n-grams aided by a dictionary. Using IDEA, the feature subset candidates are selected and the outcomes are fed as input to the baseline classifiers to obtain highly accurate opinion classification. The evaluation of the k-Nearest Neighbor (KNN), Naïve Bayes (NB) and Support Vector Machine (SVM) classifiers using the two feature selection approaches of DEA and IDEA are performed over cancer and drug tweets datasets and the results illustrate that the classification accuracy of opinions is enhanced significantly through the IDEA based feature selection than the traditional DEA algorithm. These results justify the utilization of the proposed IDEA algorithm for improving the opinion mining applications in different fields.
Effect of Yoga on Physical and Physiological Parameters
Authors:   Department of Biomedical Engineering, North Eastern Hill University, Shillong, India., Sahai Nitin , Chandran Adarsha B. ,   Department of Biomedical Engineering, North Eastern Hill University, Shillong, India., Bhuyan Akashitara ,   Department of Biomedical Engineering, North Eastern Hill University, Shillong, India., Das Bikash ,   Department of Biomedical Engineering, North Eastern Hill University, Shillong, India., Mandal Sushil ,   Department of Biomedical Engineering, North Eastern Hill University, Shillong, India., Sarma Tribedi ,   Department of Biomedical Engineering, North Eastern Hill University, Shillong, India.
Published: August 2019

Yoga is an ancient science which is practiced by an individual as a physical and mental exercise to become fit and healthy. In current study we perform various YOGA exercises to see its effects on various physiological parameters. The main objective of this study is to analyze the effect of karma yoga on physical (strength of quadriceps group of muscles) and physiological parameters such as blood oxygen saturation level (SpO2), heart rate and blood pressure. Healthy subjects are selected randomly for yoga session. SpO2, heart rates are measured using pulse oximeter and blood pressure using blood pressure apparatus. We used Electromyogram (EMG) acquisition and analysis software to acquire EMG signal from the quadriceps muscle. The variations in the physical and physiological parameters after performing karma yoga for a period of time are observed. The study concludes that there is a significant improvement in the strength of quadricep muscle but reduction in the pulse rate, SpO2, systolic and diastolic blood pressure after practicing the scheduled yoga. The significant results of these experiments show that if yoga exercises will be performed by any individual then its helps in improving their physiological parameters.
Hybrid RF-FSO System Cascaded with UWOC Link
Authors:   Department of Electronics and Communication Engineering, Indian Institute of Information Technology Guwahati, Assam, India., Anees Sanya , Baruah Smriti Rekha ,   Department of Electronics and Communication Engineering, Indian Institute of Information Technology Guwahati, Assam, India., Sarmah Pallab ,   Department of Electronics and Communication Engineering, Indian Institute of Information Technology Guwahati, Assam, India.
Published: August 2019

This work presents outage analysis of a hybrid communication system, where radio frequency (RF) and free space optical (FSO) communication links transmit in parallel to the then cascaded underwater wireless optical communication (UWOC) link forming a RF/FSO-UWOC cooperative system. Optical wireless communication (OWC) is being used as a viable communication technology by researchers due to its advantages such as fast speed, cost effectiveness, and highly secure transmission. The proposed architecture connects the terrestrial and the underwater regions to form an end-to-end cooperative system. This hybrid RF/FSO back-haul link makes the system more reliable as the optical link is highly susceptible to weather conditions. The channel models considered are Nakagami-m distributed fading, Double Generalized Gamma (DGG) distributed atmospheric turbulence along with Rayleigh distributed misalignment losses and mixture of Exponential Generalized Gamma (EGG) distributed oceanic turbulence for RF, FSO, and UWOC links, respectively. Results show that outage performance is severely affected due to RF fading, DGG distributed irradiance, air bubble concentration, temperature gradient, and saltiness of water source.
Effective Data Analytics on Opinion Mining
Authors:   Professor CSE, ANURAG Engineering College , JNUTH , KODADA, INDIA., Kumar CH Naga Santhosh , Reddy K.S. ,   Researcher., Hyderabad India
Published: August 2019

Over the extent of the most recent couple of years, in setting on the augmentation being utilized Internet, bit of client's opinion has stretched out that has led to the growth in motivation towards opinion mining. Opinion Mining is fundamental for the two people and affiliations. People like to see the opinions given by different clients about a specific thing or alliance. Affiliations need to break down the duty of its clients so as to improve its future choices. Concentrates on the Internet about a specific subject can be in millions that makes it premonition to comprehend a client's opinion and necessities. End examination enables us to center audits and present the structure that could be useful for certified investigating and thing improvement. In this paper, we complete an examination of Opinion Mining, covering different procedures in doubt examination and difficulties that show up in this field.
Internship: A Realistic Job Preview and Selection Mechanism
Authors:   Research Scholar, School of Management, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India, Srivastava Mr. Urvashi , Mohanty Dr. Namita ,   Professor, Department of Psychology, Vani Vihar, Utkal University, Bhubaneswar, , India., Mohanty Dr. Jitendra ,   Professor, School of Management, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India.
Published: August 2019

This paper aims to put forward the benefits and utility of internship programmes for organisations, employers and interning students. It suggests conceptualising internship as a realistic job preview experience for interns. It questions if “being in the situation” gives a new set of relevant reference points for future pragmatic decisions to an intern and the organisation in assessing work environment and benefits attached for self-development. It also underlines the importance of increasing the information quality in an internship programme to improve recruitment image of an organisation and create employability of an intern in the industry, which are mainly affected by the dynamic concepts of economies and employment. Approach: The paper adopts a discursive analysis to present the importance of increasing the information quality in internship programmes and increasing its contribution to recruitment and selection process and employability of individuals. Findings: Information quality in a general management sense emerges as the key to provide deeper meaning and contributes value to the processes created for transfer of skills and knowledge, and add value to the recruitment exercise, especially in nonlinear economies. Practical Implication: High-quality information programmes contribute to employability, career development for the intern and recruitment brand image for the host in the digital age. Originality: The relationship between internship, realistic job preview experience and information quality is one which bear the same cohesive structural functionality and are based on the utility for the emerging demands of the market.