bluuebunny/crossref_metadata_2025 huggingface dataset:
Improvements in Web Based ERP Software Architecture as Implemented on the Cloud
Authors: Kanade Shruti Makarand
Published: June 2018

Cloud computing is the buzz word in today’s Information Technology. It can be used in various fields like banking, health care and education. Some of its major advantages that is pay-per-use and scaling, can be profitably implemented in development of Enterprise Resource Planning or ERP. There are various challenges in implementing an ERP on the cloud. In this paper, we discuss some of them like ERP software architecture by considering a case study of a manufacturing company.
Design Patterns and Expert System for Online Admission Systems
Authors: Pant Madhuri Prashant
Published: June 2018

After presenting Optimized framework for Online Admission Systems with Reference to Professional Programmes in previous research paper this paper presents Design patterns and Expert System for Online Admission Systems. Framework addressed using design pattern is easier to reuse, maintain, flexible and extensible. Strategy pattern and proxy pattern are used in the system. For requirements collection an expert system is developed which asks few questions regarding the requirements for the system and gives suggestions and approximate budget for the system to be build. Depending on number of students, system suggests three types of online admission systems namely Basic Admission System, Advanced Admission System and Premium Admission System. CLIPS tool is used to develop this expert system.
Effective Concentrated Web Crawling Approach Path for Google
Authors: Kumar Ashwani , Kumar Anuj , Mishra Rahul
Published: June 2018

A concentered crawler crosses the World Wide Web, choosing out applicable pages to a predefined topic and forgetting those out of concern. Collecting domain specific documents employing focused crawlers has been considered one of most crucial schemes to detect applicable data. While browsing the Internet, it is unmanageable to act with extraneous pages and to anticipate which associates lead to quality pages. However most focused crawler use local explore algorithmic program to crisscross the web space, but they could easily entrapped within bounded a sub graph of the web that surrounds the starting URLs also there is problem related to applicable pages that are miss when no associates from the starting URLs. There is some applicable pages are miss. To address this problem we design a focused crawler where calculating the absolute frequency of the topic keyword also calculate the equivalent word and sub equivalent word of the keyword. The weight table is constructed agreeing to the user query. To check the resemblance of web pages with respect to topic keywords and priority of extracted associate is computed.
Automatic Age Estimation Based on LBP and GLCM Features Using SVM
Authors: RAMPAY VENKATARAO
Published: June 2018

Face is generally considered as the reference frame of mind. Therefore, to estimate the feeling of the mind, many authors have considered the emotions from the facial expressions into consideration to identify the state of mind of an individual. Hence in this article we proposed a methodology for automatic age estimation based on Local Binary Pattern (LBP) and Grey Level Co- Occurrence Matrix (GLCM). The facial features are extracted using LBP and GLCM and these features are given as input’s to the Support Vector Machine (SVM) for age estimation. The experimentation on proposed method is carried out using FG-NET database and Mean Absolute Error (MAE) is calculated to compare the proposed method with state-of-the-art algorithms. Finally, the proposed methodology demonstrates the classification accuracy above 88%.
A Research on user Recommendation System Based upon Semantic Analysis
Authors: Kaur Lovedeep , Kumari Naveen
Published: June 2018

Recommender system applied various techniques and prediction algorithm to predict user interest on information, items and services from the tremendous amount of available data on the internet. Recommender systems are now becoming increasingly important to individual users, businesses and specially e-commerce for providing personalized recommendations. Recommender systems have been evaluated and improved in many, often incomparable, ways. In this paper, we review the evaluation and improvement techniques for improving overall performance of recommendation systems and proposing a semantic analysis based approach for clustering based collaborative filtering to improve the coverage of recommendation. The basic algorithm or predictive model we use are – simple linear regression, k-nearest neighbours(kNN), naives bayes, support vector machine. We also review the pearson correlation coefficient algorithm and an associative analysis-based heuristic. The algorithms themselves were implemented from abstract class recommender, which was extended from weka distribution classifier class. The abstract class adds prediction method to the classifier.
Technique for Text Region Detection in Image Processing
Authors: Shivani . , Bansal Dipti
Published: June 2018

The image processing is the technique which is applied to process the digital information stored in the image. The OCR is the technique of image processing which will access the optical character information in the image. In the base paper, the technique is applied which will detect the text portion from the input image. The twp step are applied to detect the text portion, in the first back ground information is extracted and in the second step, technique of deep learning is applied which will mark the text region. In the proposed work, SIFT algorithm is applied which will mark the key points for the key description. In the second step, technique of deep learning is applied which will mark the text area in the input image. The proposed and existing algorithms are implemented in MATLAB and it is been analyzed that accuracy of proposed algorithm is more as compared to existing algorithm.
Fog Computing: A Primer
Authors: Sadiku Matthew N. O. , Tembely Mahamadou , Musa Sarhan M.
Published: June 2018

Fog computing (FC) was proposed in 2012 by Cisco as the ideal computing model for providing real-time computing services and storage to support the resource-constrained Internet of Things (IoT) devices. Thus, FC may be regarded as the convergence of the IoT and the Cloud, combining the data-centric IoT services and pay-as-you-go characteristics of clouds.  This paper provides a brief introduction of fog computing.
Routing Protocols for WMNs: A Survey
Authors: Singh Amar , Kumar Shakti , Walia Sukhbir Singh
Published: June 2018

Routing is one of the most challenging issues encountered in the Wireless Mesh Networks (WMNs) due to the dynamic nature of WMNs. The survey observes that literature is rich with wide range of routing protocols. Each protocol has its own features which we have briefly discussed. The routing protocols could be divided into three categories i.e. reactive, proactive and hybrid. In this paper we have reviewed wide range of existing routing protocols which are being applied for wireless mesh networks. The literature survey also points to the rising popularity of soft computing based approaches to the optimal cost path evaluation as compared to the classical or hard computing based approaches.
Selenium Broken Links Automation Testing
Authors: Singh Gursimran , Kaur Harpreet
Published: June 2018

With the growth of website content it is become difficult to manage relations between Individual webpage and keep track of their hyperlinks within a website. This causes some Hyperlink become dead or broken. A broken Link  is a  link on a web page that no longer works. It is difficult to find out the broken link manually by checking each hyperlink individually because it is time consuming and tedious work. So to eliminate this we can use the selenium web driver tool and java code to automate testing of each hyperlink individually. The objective of this thesis is to automate finding of broken links using selenium web driver tool.
Performance Investigations of Electrocardiogram Signal Using Distributed Arithmetic Mixed Signal Filter
Authors: Jaware Tushar H
Published: June 2018

A Distributed Arithmetic mixed signal filter is proposed simple moving arithmetic operations the response can be improved for real time QRS detection. Signal preprocessing and detection algorithm involves different classification methods such as wavelet based de-noising procedure which reduces noise from ECG signal. The complete structure of proposed algorithms gives accurate detection of QRS wave with high memory efficiency and speed. Algorithm performance was evaluated against the Arrhythmia Database. The numerical results indicates that Proposed algorithm finally achieved minimum false detection rate for the standard database, is functionally reliable under the condition of poor signal quality in the measured ECG data.
A Novel Approach on Towards Effective Bug Triage and Improve the Quality of Bug Data
Authors: Praveen G , Reddy V. Sridhar , Nabi Shaik Abdul
Published: June 2018

In order to diminution the time cost in physical work, text classification practices are pragmatic to conduct automatic bug triage. Presently, software companies spend over 45 percent of cost in dealing with software bugs. A foreseeable step of fixing bugs is bug triage, which ambitions to decorously consign a developer to a new bug. In this scheme, it is addressed the problem of data reduction for bug triage, to reduce the scale and progress the reputation of bug data. It is here combined with instance selection with feature selection to simultaneously reduce data scale on the bug dimension and the word dimension. To define the order of applying instance selection and feature selection, it is extract attributes from historical bug data sets and build a predictive model for a new bug data set. It is practically scrutinized the enactment of data reduction on totally 600,000 bug reports of two large open source projects, namely Eclipse and Mozilla. The work provides an approach to leveraging techniques on data processing to form reduced and high-quality bug data in software development and maintenance.
An Efficient Hybrid Forecasting Approach for Wind Speed Time Series
Authors: Munnaluri Bhargavi , Reddy K. Ganesh
Published: June 2018

Wind forecasting is one of the best efficient ways to deal with the challenges of wind power generation. Due to the depletion of fossil fuels renewable energy sources plays a major role for the generation of power. For future management and for future utilization of power, we need to predict the wind speed.  In this paper, an efficient hybrid forecasting approach with the combination of Support Vector Machine (SVM) and Artificial Neural Networks(ANN) are proposed to improve the quality of prediction of wind speed. Due to the different parameters of wind, it is difficult to find the accurate prediction value of the wind speed. The proposed hybrid model of forecasting is examined by taking the hourly wind speed of past years data by reducing the prediction error with the help of Mean Square Error by 0.019. The result obtained from the Artificial Neural Networks improves the forecasting quality.
Characterization of Ischemic Stroke in CT Images using Image Processing
Authors: Alzain Amal , Alameen Suhaib , Elmaki Rani , Gar-Elnabi Mohamed E. M.
Published: June 2018

This study concern to characterize the brain tissues to ischemic stroke, gray matter, white matter and CSF using texture analysisto extract classification features from CT images. The First Order Statistic techniques included sevenfeatures. To find the gray level variation in CT images it complements the FOS features extracted from CT images withgray level in pixels and estimate the variation of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level of images. The results show that the Gray Level variation and   features give classification accuracy of ischemic stroke 97.6%, gray matter95.2%, white matter 97.3% and the CSF classification accuracy 98.0%. The overall classification accuracy of brain tissues 97.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate brain tissues names.
A Comparative Study of Various Techniques used for Melanoma Detection
Authors: K Raina Raju , Kumar S. Swapna
Published: June 2018

Skin cancer is one of the most fatal disease. It is easily curable, when it is detected in its beginning stage. Early detection of melanoma through accurate techniques and innovative technologies has the greatest potential for decreasing mortality associated with this disease. Mainly there are four steps for detecting melanoma which includes preprocessing, segmentation, feature extraction and classification. The preprocessing stage will remove all the artifacts associated with the lesion. The exact boundaries of lesion are identified from normal skin through segmentation method. Feature extraction stage is used for calculating and obtaining different parameters of the lesion region. The final stage is to classify the lesion as benign or malignant.  In this paper different types of segmentation methods and classification methods are described. Both of these stages are accurately implemented to reach the final detection of the lesion.
DIGITAL CITIZENSHIP
Authors: Sadiku Matthew N. O. , Tembely Mahamadou , Musa Sarhan M.
Published: June 2018

Digital media and digital infrastructures keep playing an important role in promoting social interaction and responsible citizenship. The Internet has been a vital space for interaction, mentoring, and informal learning. Digital citizenship refers to the ability to participate in online society. It promotes equality and equal participation in all areas of life regardless of race, gender, and ethnicity. This paper provides a brief introduction to the concept of digital citizenship, its opportunities and challenges.
NATURAL LANGUAGE PROCESSING IN HEALTHCARE
Authors: Sadiku Matthew N.O. , Zhou Yu , Musa Sarhan M.
Published: June 2018

Natural language processing (NLP)  refers to the process of using of computer algorithms to identify key elements in everyday language and extract meaning from unstructured spoken or written communication.  Healthcare is the biggest user of the NLP tools. It is expected that NLP tools should  be able to bridge the gap between the mountain of data generated daily and the limited cognitive capacity of the human mind.  This paper provides a brief introduction on the use of NLP in healthcare.
Performance Analysis of Fingerprint Based Image Enhancement and Minutiae Extraction
Authors: Jain Rajneesh , Sharma Sheelesh Kr. , Agrawal Pankaj
Published: June 2018

Extracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. Minutiae are local discontinuities in the fingerprint pattern, mainly terminations and bifurcations. In this work we have propose a method for fingerprint image enhancement. Using histogram equalization over filtering and then minutia are calculated. The   results   achieved   are compared   with   those   obtained   through   some   other methods.  The Results show some improvement in the minutiae extraction in terms of quantity.
A Review on the New Speed 5G
Authors: Shrivastava Trishla , Sharma Archana
Published: June 2018

This paper is an attempt to throw light on 5g technology that is existing in the market today. this paper is a review on the advantages and disadvantages of 5g. It also includes a brief history on how the world reached to 5g.In this fast growing world where the demand of everything has increased to a different level, a requirement to stay connected with the world is at atmost priority, which requires a high sped internet. This connectivity can be provided by the 5g as it is promised.The coming of 5G technologies will change the way  how the most users access their phones.In past few decades things have changed alot, so lets a peek through to what they lacked and how this will be fulfilled by this new technology 5g.To realize 5G, evolution and revolution both approaches are being employed.Looks for new innovations and technologies. Frequency spectrum, network densification, MIMO, carrier aggregation, CentralizedRAN, HetNets, and Network Functionality Virtualization are the key enablers. This paper spreads information about what research and developments are going on in 5G technology.
Swarm Intelligence: A Primer
Authors: Sadiku Matthew N. O. , Tembely Mahamadou , Musa Sarhan M.
Published: June 2018

Swarm intelligence is the emergent collective intelligence of groups of simple agents.  It belongs to the emerging field of bio-inspired soft computing. It is inspired from the biological entities such as birds, fish, ants, wasps, termites, and bees. Bio-inspired computation is a field of study that is closely related to artificial intelligence. This paper provides a brief introduction to swarm intelligence.
An Ethical Approach of Big Data & Machine Learning Using Innovation of Python
Authors: Bathla R. K. , Srivastva Jitender Nath
Published: June 2018

Big Data has gained much concentration from the academic world and the IT industry. In the digital and computing world, in order is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people world wide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. Cloud computing has opened up new opportunities for testing departments. New technology and social connectivity trends are creating a perfect storm of opportunity, enabling cloud to transform internal operations, Customer relationships and industry value chains. To ensure high quality of cloud applications under development, developer must perform testing to examine the quality and accuracy whatever they design. Business users are drawn to clouds simplified, self- service experience and new service capabilities. In this research paper, we address a testing environmental architecture with valuable key benefits, to perform execution of test cases and used testing methodologies to enhance quality of cloud applications.
A Novel Study on (AI) Robotics
Authors: Khandelwal Ankit , Udawat Tanushree
Published: June 2018

The Artificial intelligence and mechanical autonomy both are similarly imperative in building forthcoming clever operators and gives imperative improvements in the present condition. Late examinations, research or study gives us clear picture of our cutting edge time of wise agents. Robotics is the teach of computerized reasoning that arrangements with the investigation of making smart and productive robots. Just the missing component is the essential comprehension of how robots respond with human instinct. Mechanical autonomy is a branch of innovation that arrangements with the planning, development, task and PC framework for data preparing.
Machine Learning in Agriculture
Authors: Sadiku Matthew N. O. , Kotteti Chandra M. M , Musa Sarhan M.
Published: June 2018

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.
A Framework of Security and Performance Enhancement for Hadoop
Authors: Tyagi Adhishtha , Sharma Sonia
Published: June 2018

Hadoop framework has been emerged as the most effective and widely adopted framework for Big Data processing. Map Reduce programming model is used for processing as well as generating large data sets. Data security has become an important issue as far as storage is concerned. By default theres no security mechanism in hadoop and it is the first choice of the business analyst and industrialists to store and manage data as well as theres a need to introduce security solutions to Hadoop in order to secure the important data in the Hadoop environment. We implemented and evaluated Dynamic Task Splitting Scheduler (DTSS) which explores the tradeoffs between fairness and data performance by splitting the tasks dynamically before processing in hadoop along with AES-MR (an Advanced Encryption Standard based encryption using mapreduce) encryption in MapReduce paradigm. This paper would be useful for beginners and researchers for understanding DTSS scheduling along with security.
An Improved Method of Subgraphs Extraction in a Large Graph Database in a Distributed System by considering both Graph Topology and Set Similarity
Authors: Yadav Ritu , Varshney Samarth
Published: June 2018

Since many real applications such as web connectivity, social networks, and so on, are emerging now-a-days, thus graph databases have been widely used as important tools to model and query complex graph data wherein each vertex(node) in a graph usually contains information, which can be modelled by a set of tokens or elements. The method for subgraphs extraction by considering set similarity query over a large graph database has already been proposed, which retrieves subgraphs that are structurally isomorphic to the query graph, and meanwhile satisfy the condition of vertex pair matching with the (dynamic/fixed) weighted set similarity in a centralized system. This paper explains the efficient implementation of subgraphs extraction in a large graph database in a distributed environment by considering both vertex set similarity and graph topology which offers a better price/performance ratio and increases availability using redundancy when parts of a system fail than centralized systems in case of a large dataset (i.e., a graph with millions/billions of nodes wherein each node contains some information) by performing parallel processing.
An Enhanced Technique for Classification of Fruits using Shape Color and Texture Features
Authors: Jitarwal Yashpal , Khan Tabrej Ahamad , Mangal Pawan
Published: June 2018

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.
Real Time Implementation of Optical Character Recognition Based TTS System using Raspberry pi
Authors: K Sagar G. , T Shreekanth
Published: June 2018

Thetext to speech (TTS) conversion technology is proposed to help the blind people and people with poor vision. According to survey done by World Health Organization (WHO) there are about 286 million blind people in this world and about 91% of them reside in developing countries. So there is necessity of portable TTS converter which should be affordable to help the blinds. To help the blind community a smart reader is proposed in this paper. It includes a web cam to capture input text page which is then processed by TTS unit installed in raspberry pi and the output is then amplified by audio and given out on speaker.
An Algorithm to Mitigate the Attacker by Applying Homomorphic Encryption
Authors: Kaur Manmeet , Kaur Amrit
Published: June 2018

K-Modes is an eminent algorithm for clustering data set with categorical attributes. This algorithm is famous for its simplicity and speed. The KModes is an extension of the K-Means algorithm for categorical data. Since K-Modes is used for categorical data so ‘Simple Matching Dissimilarity’ measure is used instead of Euclidean distance and the ‘Modes’ of clusters are used instead of ‘Means’.The major drawback of k-mode is that the user needs to define the centroid points. To overcome this problem, k-mode with entropy based similarity coefficient was introduced in order to find good initial center points and the accurate result of the clustering is to be obtained. The nature-inspired harmonic algorithm is hybridized to optimize the k-mode algorithm. Harmonic K-Mode Algorithm is proposed in this work that reduces the computation time and improves the accuracy for cluster generation. The performance is evaluated using different output parameters such as execution time, space complexity, accuracy, precision and recall on different datasets such as amazon book review, news aggregator, online retail, seed and wholesale consumer.
Effect of Black Hole Attacks on Wireless Sensor Networks
Authors: Lalar Sachin , Monika . , Yadav Arun Kumar
Published: June 2018

Wireless sensor networks (WSNs) establish a new popular of ambient supervision with many latent packages. The environment of wireless sensor networks prone to different forms of attacks as networks are prepared in open and unsecured surroundings. This paper analyses the overall performance of AODV whilst attacked by black hole, through varying the mobility of the nodes within the community. The overall performance metrics which can be used to do the analysis are LPR, packet delivery ratio & Packet loss. The simulation consequences display that the overall performance of each AODV degrades in the presence of black hole attack.
Investigation of Different Constraints in Cybercrime & Digital Forensics
Authors: Kotwal Shallu , Manhas Jatinder
Published: June 2018

With rapid changes in technology and its increased use in different organizations, the cybercrime and digital forensics methods are also making advancement in new ways to tackle the latest trends in cyber crime. Cybercrime refers to any crime that involves a computer network or any public or private system. Cyber crime is emerging as a serious threat worldwide. The government organizations, police departments and various intelligence units of different countries have started to act accordingly. To control and investigate cybercrime, the investigators use various Digital forensics methods and mechanisms. Digital forensics is the procedure of investigating computer crimes in cyber world. Many researchers have been done a lot in this area to help forensic investigators to resolve the existing challenges with different methodologies designed by them. Experts provided with different tools and technologies to resolve the threats related to cyber crime in a more efficient and speedy manner with minimum loss to the victim. Still the desired technologies and tools are not that much efficient that they can control the occurrence of different types of cyber crime activities. This paper reviews the complete details regarding the growth of cybercrime and its various modes of occurrence at different level.  Authors in this paper tries to bring few facts and figures which would be an eye-opener for computer and internet users. Therefore, the current manuscript provides the understanding of various types of cyber crimes and its impact on different section of the society.
Real Time Person Recognition and Attendance Marking Using Holistic Based Approach
Authors: P Reshma , VK Muneer , P Muhammed Ilyas
Published: June 2018

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.
A Survey Report on Wireless Sensor Network
Authors: Kaur Harjot , Tejpal Gaurav , Sharma Sonal
Published: June 2018

Wireless Sensor Network (WSN) is the combination of various sensing nodes. WSN is used to produce meaningful information from raw local data collected by each sensor. The characteristics of sensor network create many new and existing application areas for remote sensing. Also now a day there is much application in many field and WSN faces security challenges so I have discussed it with architecture of WSN. With advancement in WSN, small and low cost sensor nodes become available, which have capabilities of wireless communication, sensing various types of environmental conditions and data processing. Now a day, we are living in advance technology environment, which has a great advantage on every person life. Wireless sensor network is one of them which is the collection of nodes organized into a cooperative network and in every node consist of processing capability, and may contains  multiple types of memory. In this paper there is review of introduction of Wireless Sensor Network and its application in various fields with security challenges. Also I have discussed various factors that affect the sensor network design. Wireless Sensor Network has tremendous advantages in the worlds which makes every person life much easier and also have various applications.
Prediction of Survivors in Titanic Dataset: A Comparative Study using Machine Learning Algorithms
Authors: Chatterjee Tryambak
Published: June 2018

The Titanic disaster which occurred in 1912 remains as one of the biggest tragedies that occurred in human endeavours. The objective of this paper is to apply different algorithms to check whether a passenger survived the Titanic disaster based on different attributes a passenger possess which is included in the dataset for testing. The results from the application of the different algorithms are compared and analysed.
Performance Analysis of Web Applications Working on Cloud Environment Using Workload Prediction Model Based on ANN
Authors: Sahi Supreet Kaur , Dhaka V. S.
Published: June 2018

Cloud computing is good fit for deployment of different applications but workload and instances requirement will vary depending upon type of applications. Workload estimation of cloud computing is tedious task.  In cloud computing number of instances of cloud need to be reserved based on certain parameters. If these instance are under estimated then performance of system will reduce and if over estimated then cost will increase. In order to optimize this cost there must be some algorithm working that can help in reserving number of instances based on certain parameters. Web applications have unpredictable workload. Certain steps of capacity planning need to follow for predicting workload of web applications. This paper analysis performance of ANN based workload estimation model for web applications on cloud environment. A brief survey of literature is also presented to find out different parameters necessary for capacity planning of website.
How Online Market Influencing the Youngster in Bhopal District of Madhya Pradesh
Authors: Sahu Mukesh , Tiwari Alka
Published: June 2018

Online shopping has changed the substance of showcasing all around. It has helped in less demanding, less difficult and quicker business exchanges. Today every single family unit is utilizing online shopping. India being an exceptionally populated nation is emphatically changing towards internet shopping. Along these lines there is an enormous extension for both business and youngsters in India for web based offering and purchasing family merchandise. As the Indian populace is including more instructed and master in web innovation, web based shopping is moving definitely. Online shopping has become a new trend of shopping nowadays and is quickly becoming an important part of lifestyle. Due to wide spread internet access by people online shopping has seen a massive growth in recent years. Young people have been the majority shoppers online. In this foundation, the present enlightening review is an endeavor to explore the critical variables affecting young person's conduct, state of mind and discernment towards Online shopping in Bhopal district of Madhya Pradesh.
Fast and Efficient Cloud Data Utilization with Deduplication
Authors: S Sunil , Shankar A Ananda
Published: June 2018

Cloud storage system is to provides facilitative file storage and sharing services for distributed clients.The cloud storage preserve the privacy of data holders by proposing a scheme to manage encrypted data storage with deduplication. This process can flexibly support data sharing with deduplication even when the data holder is offline, and it does not intrude the privacy of data holders. It is an effective approach to verify data ownership and check duplicate storage with secure challenge and big data support. We integrate cloud data deduplication with data access control in a simple way, thus reconciling data deduplication and encryption.We prove the security and assess the performance through analysis and simulation. The results show its efficiency, effectiveness and applicability.In this proposed system the upload data will be stored on the cloud based on date.This means that it has to be available to the data holder who need it when they need it. The web log record represents whether the keyword is repeated or not. Records with only repeated search data are retained in primary storage in cloud. All the other records are stored in temporary storage server. This step reduces the size of the web log thereby avoids the burden on the memory and speeds up the analysis.
Score Level Fusion of Multispectral Palmprint with Triangular Conorm
Authors: Afzal Maria , Ahad Mohd Abdul , Grover Jyotsana
Published: June 2018

Biometricplay vigorous role in the authentication of user by using his/her physical body traits. Unimodal biometric system uses single body traits and multimodal systems use multiple body traits. Multimodal biometric system have overcome the disadvantages that has occurred in unimodal systems. In this paper we are fusing the different spectral bandsof palm print (Red, Green and Blue) using T-conorm operators like Hamacher, Frank, Probabilistic and Scheiwer & Sklar. Experiment Results suggest that Scheiwer & Sklar gives the best results. Experimental Results ascertain that the proposed approach for the score level fusion outperforms the state-of-art.
A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control
Authors: Parhi Shreyanshu , Srivastava S. C.
Published: June 2018

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS.  The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.
Azardirachta Indica Leaves Ark’s as Green Corrosion Inhibitor for Aluminum in HCl Solutions
Authors: Desai P. S.
Published: June 2018

The purpose of this paper to find out the effect of Azardirachta indica (Neem) leaves ark’s on the corrosion of aluminum in 0.4, 0.5 and 0.6M hydrochloric acid (HCl), and elucidates the mechanism of the inhibition system. Gravimetric and galvanostatic polarization methods were used to investigate the effect of aluminum corrosion in HCl solutions. The outcome revealed that maximum inhibitor efficiency which corresponds to the lowest corrosion rate was obtained at most favorable inhibitor concentration of 1.25% with reduction in the corrosion rate observed to follow in order of increasing extract concentration. The adsorption study promote that Langmuir isotherm best described the metal surface interaction with the Azardirachta indica (Neem) leaves ark’s with the best exposure time for the Azardirachta indica (Neem) leaves ark’s to adsorb to the metal surface at all concentrations. Polarization study reveals that the inhibitors functions as a mixed inhibitor.
Analysis the Performance of Interconnection Network Topology C2 Torus Based on Two Dimensional Torus
Authors: Chauhan Prachi , Bhardwaj Manish
Published: June 2018

Mesh and Torus are most popular interconnection topologies based on 2D-mesh.Comparison between Mesh and Torus will be considered and new interconnection topology will be proposed to provide better performance. The C2Mesh, is an enhanced mesh interconnected network. This paper enhances the torus network based on the theme of C2Mesh. Topological Properties of new network will be analyzed and implemented by simulation. The new routing Algorithm will be designed for new proposed network (C2Torus). This manuscript performs Comparison between C2Torus and C2Mesh.
Study of Ultra-precision Finishing Techniques for Brittle Materials
Authors: Samra Partap Singh , Singh Sehijpal , Singh Lakhvir
Published: June 2018

Wide application of hard and brittle advanced ceramics, glasses and semiconductors in Mechanical, Optical and Electronic industry has led to the development of new ultra-precision finishing processes. With an increase in the applications of these materials, the need of finishing these materials has also become a great challenge. Dimensional and finish accuracies are the parameters that needs to be focused and improved with minimum time and cost. Another crucial parameter is the subsurface damages that are quiet common with these materials during finishing process.  New processes have been developed to overcome the drawbacks of the existing processes for Nano finishing. These processes can be classified as Conventional, Precision and Ultra-precision finishing based on the degree of dimensional accuracy and final surface finish. Both loose and bonded abrasives have been used for these processes. This paper deals with the study of some of the significant advances in ultra-precision finishing processes of hard and brittle materials.
A Secure Steganography Technique Using MSB
Authors: Sharma Aditi , Poriye Monika , Kumar Vinod
Published: June 2018

Steganography is the process of hiding secret message into a cover medium to conceal the existence of the message. The redundant nature of image pixels make them suitable medium to hide secret information. In this paper, a new improved technique that uses pixel indicator method to hide secret data bits in most significant bits (MSBs) of the cover image is proposed. Moreover, a central portion of image is selected to hide secret message for more security. Here, red channel is used as an indicator to hide secret message in 5th and 6th bits of either green channel or blue channel of RGB image. If the number of 1’s in red channel are even, green channel is used for embedding otherwise blue channel is used. The experimental results obtained by implementation of the proposed algorithm in MATLAB showed that the stego-images images are of high quality having high PSNR values. It provides better security and imperceptibility.
Review on Improving Network Topology Lifetime by Optimal Node Position Clustering
Authors: Shah Dhara Narendra
Published: June 2018

Wireless sensor network(WSN) is facing key challenges like extending network lifetime due to sensor nodes having limited power supplies. Extending WSN lifetime is complicated because nodes often experience differential power consumption. For example, nodes closer to the sink in a given routing topology transmit more data and thus consume power more rapidly than nodes farther from the sink. Inspired by the huddling behavior of emperor penguins where the penguins take turns on the cold extremities of a penguin “huddle”, we propose mobile node rotation, a new method for using low-cost mobile sensor nodes to address differential power consumption and extend WSN lifetime. Specifically, we propose to rotate the nodes through the high power consumption locations. We propose efficient algorithms for single and multiple rounds of rotations.
High Technology Entrepreneurship
Authors: Kaur Harjyot , Kaur Manjit
Published: June 2018

High Technology entrepreneurship is very important aspect in many debates, including those which are regarding launching new firms and development, regional economic development, section of stakeholders, selection of markets, educating managers and scientists.The purpose of this article is to define the high technology entrepreneurship, and identify its various aspects in relation with economics, entrepreneurship and management.High technology entrepreneurship is an investment in a project that uses various specialized individuals and various assets to create and capture the value of firm. Collaborative experiments and production of new products, assets and their attributes, which related to advances in scientific and technological knowledge and the firm’s asset ownership rights are the various factors which distinguishes Technology entrepreneurship from other entrepreneurship types (e.g. Social entrepreneurship, Small business and Self employment).
Factors Influencing the Acceptance of M-Learning by Students of Higher Education in Morocco
Authors: Lebzar Bouchra , Jahidi Rachid
Published: June 2018

The M-learning plays an increasingly important role in the development of teaching methods in higher education. However, the success of M-learning in higher education will depend on the acceptance of users of this technology. The purpose of this article is to study the factors that impact the intentions of college and university students to accept M-learning. Based on the Unified Theory of Acceptance and Use of technology (UTAUT) [18], this research proposes a model to identifying the factors that influence the acceptance of M- learning in the  Higher education  of Morocco. A structural equation model was used to analyze the data collected from 193 students. The findings of this study indicate that factors such as the  "ease of use" and the "quality of service" influence the intent to use M-learning while others like the "expected performance", the "  personal Innovativeness" and the "influence of professors” have no impact on the intent of using M-learning.
A Comparative Study of CSR in Selected Indian Public & Private Sector Organisations in Globalisation Period: A Research Finding
Authors: Ranjan Rajesh , Tiwary Pankaj Kumar
Published: June 2018

In the era of globalisation the corporate social responsibility is playing vital role not only to provide social services but also to popularise the organisation reputation. It is also a way of advertisement for industrial undertakings not only in India but also everywhere. The study has done to acknowledge the important activities as well as impact of CSR and conducted in ten reputed private and public sector organisations in the country. Different impediments and positive impacts have been analysed and interpreted in the study.
A Comprehensive Survey on SLA Compliant Energy Aware Resource Allocation in Cloud Datacenters
Authors: R Anitha , Raj C Vidya
Published: June 2018

Cloud Computing has achieved immense popularity due to its unmatched benefits and characteristics. With its increasing popularity and round the clock demand, cloud based data centers often suffer with problems due to over-usage of resources or under-usage of capable servers that ultimately leads to wastage of energy and overall elevated cost of operation. Virtualization plays a key role in providing cost effective solution to service users. But on datacenters, load balancing and scheduling techniques remain inevitable to provide better Quality of Service to the service users and maintenance of energy efficient operations in datacenters. Energy-Aware resource allocation and job scheduling mechanisms in VMs has helped datacenter providers to reduce their cost incurrence through predictive job scheduling and load balancing. But it is quite difficult for any SLA oriented systems to maintain equilibrium between QoS and cost incurrence while considering their legal assurance of quality, as there should not be any violations in their service agreement. This paper presents some state-of-the-art works by various researchers and experts in the arena of cloud computing systems and particularly emphasizes on energy aware resource allocations, job scheduling techniques, load balancing and price prediction methods. Comparisons are made to demonstrate usefulness of the mechanisms in different scenarios.
A Comparative Analysis of Spatial Indexing Schemes in PostGreSQL/PostGIS Using Java-API
Authors: Yadav Monika
Published: June 2018

There are several indexing techniques used in retrieval of spatial data. In this paper a comparative analysis is performed on three spatial indexing techniques- GiST (Generalized Search Tree), SP_GiST (Space partition Generalized Search Tree) and R-tree (Rectangle tree) in spatial database PostgreSQL/Postgre using Java API. The comparison is performed on five categories of spatial and non spatial queries ,namely Simple SQL, Geometry, Spatial Relational ship, Spatial Join and Nearest Neighborhood based on benchmark dataset of New York city. This paper performs experiment in all five categories and compares performance for each category on index structure.