bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Classification Techniques on Medical Reports Classification
Authors: Mohamed Elfadil Abdalla , Saad Fathi H. , Mohamed Omer I. E.
Published: May 2018

Text classification is the process of assigning pre-defined category labels to documents based on what a classifications has learned from training examples. This paper investigates the partially supervised classification approach in the medical field. The approaches that have been evaluated include Rocchio, NaÃ¯ve Bayesian (NB), Spy, Support vector machine (SVM), and Expectation Maximization (EM). A combination of these methods has been conducted.Â  The experimental result showed that the combination which uses EM in step 2 is always produces better results than those uses SVM using small set of training samples. We also found that reducing the features based on tf-tdf values is decreasing the classification performance dramatically. Moreover, reducing the features based on their frequencies improve the classification performance significantly while also increasing efficiency, but it may require some experimentationÂ
CHBR: Contact History Based Routing in Time Varying Approach
Authors: S Patel Pravesh , Shah Hemal , Kosta Yogeshwar
Published: May 2018

In Delay tolerant network having intermittent connectivity so there is no guarantee of finding a complete communication path that connecting the source and destination. There no any end to end connectivity for delay-tolerant network selection of routing protocol is important to deliver the message in an efficient way and increases chance to deliver a message to the destination. Some existing routing protocols improve the delivery ratio but it also increases the overhead. Our paper proposed Contact History Based Routing (CHBR) that use Neighborhood Index and Time varying properties such as temporal distance, Temporal Diameter and centrality for benchmarking the existing routing protocol. First, temporal metrics are evaluated for synthetic and real trace data. Then CHBR protocol is compared with the Epidemic and PROPHET for delivery ratio, overhead and the number of messages dropped. This has been carried using Opportunistic Network Environment simulator under real and synthetic datasets.
CLONING DETECTION ON THE BASE OF TEXTUAL SIMILARITY USING NEURAL AS A CLASSIFIER
Authors: Kaur Kulbir , Singh Rasbir
Published: May 2018

Cloning refer to copying the data from one place and using it on another place. This particular work has made the task of the developers easy as it is often that the developers copy the content of one work and paste it into another but this particular procedure violets the rule of copyrights. Copying data is feasible upto one extent but copying entire data set or data or code from one place to another is a serious issue .This paper focuses on the introduction of the code cloning and data cloning and the ways to prevent the cloning.
Efficient Motion Detection Algorithm in Video Sequences
Authors: Mohammed Aree Ali
Published: May 2018

HumanÂ  motionÂ  analysisÂ  concernsÂ  the detection,Â  trackingÂ  andÂ  recognitionÂ  ofÂ  peopleÂ  behaviors,Â  from imageÂ  sequencesÂ  involvingÂ  humans. AÂ  referenceÂ  frameÂ  isÂ  initiallyÂ  usedÂ  andÂ  consideredÂ  asÂ  backgroundÂ  information. While a new object enters into the frame, the foreground information and background information are identified using the reference frame as background model.In this paper, an efficient algorithm is proposed for objects detection in real time video sequences. The method aims at tracking an object like (human) in motion using background subtraction technique. The tracked objects are subject to different pre and post image processing in order to extract the most important features (frame preprocessing is used for shadow removal using morphological operations). They can be used later for recognition in different security system such as (human detection for surveillance). Experimental results show that the proposed method is very efficient in terms of reliability and accuracy of detection.
Evaluating the Performance of Modified Watershed Algorithm Based on DBMF and DT.
Authors: Singh Inderpal , Kumar Dinesh
Published: May 2018

The image segmentation; segments a given image into separate regions and objects. It is widely used in various vision applications like face detections, motion detection etc. It has been found that the noise has affected the segmentation at a great extent; so to overcome this problem we have presented a modified watershed segmentation using Decision based median filtering (DBMF) and Dynamic thresholding (DT). DBMF has the ability to reduce the high density of noise in the image so will provide more efficient results. However DT has also refined segmentation process further. The comparisons have shown that the proposed algorithm provides quite significant results over the available methods.
An Analysis of the PROMISE and ISBSG Software Engineering Data Repositories
Authors: Cheikhi Laila , Abran Alain
Published: May 2018

There exist two ongoing large repositories of software projects in the software engineering community: the repository of the International Software Benchmarking Standards Group (ISBSG) and the Repository referred to as PROMISE (PRedictOr Models In Software Engineering). Researchers interested in using the datasets have to conduct their own analysis of the datasets within these repositories that figure out what contents are suitable for their purposes. Repositories designed without users (researchers and Industrial) needs in mind greatly are more challenging to use. This paper present an analysis of both repositories and provide users with additional information on these datasets by identifying the topics addressed, highlighting their descriptiveness, and their availability, and by indicating whether or not further details are available in order to enhance their reusability in further empirical studies. Recommendations to both PROMISE managers and datasets owners are also suggested to improve the usefulness of the data provided.
A Cooperative Computer Game for Public Efficiency Development
Authors: Prasad Sachchida Nand
Published: May 2018

This paper presents a design case study of SIDES: Design Interfaces to Develop Effective Public Efficiency. SIDES is a tool designed to help adolescents in Public group therapy, specifically individuals with Asperserâ€™s Syndrome, practice effective group work efficiency using a four-player cooperative computer game that runs on computer games technology. We are represent the design process and evaluation of SIDES conducted over a period of six months with a middle school Public group therapy class. Our findings indicate that   computer games   are a motivating and supported tool for effective group work among. My target population and reveal different design lessons to inform the development of similar systems.
Performance Evaluation of Distributed Database Systems
Authors: Maabreh Khaled Saleh
Published: May 2018

Distributed database management systems manage a huge amount of data as well as large and increasingly growing number of users through different types of queries. Therefore, efficient methods for accessing these data volumes will be required to provide a high and an acceptable level of system performance. Â Data in these systems are varying in terms of types from texts to images, audios and videos that must be available through an optimized level of replication. Distributed database systems have many parameters like data distribution degree, operation mode and the number of sites and replication. These parameters have played a major role in any performance evaluation study. This paper investigates the main parameters that may affect the system performance, which may help with configuring the distributed database system for enhancing the overall system performance.
An Evaluation of Mobility Effect on Tiny Service Discovery Protocol for Wireless Sensor Networks
Authors: Salim Ahmed , El Khatib Akram
Published: May 2018

In mobile sensors environment, nodes change their positions this leads to crucially affects service discovery of wireless sensor networks (WSNs). Therefor the accuracy of most service discovery can be limited to just small area of movement, or demands considerable maintenance efforts in term of neighbor nodes allocation. A large waiting time of wireless sensor applications spent in node discovery, as nodes need to periodically advertise their presence and be awake to discover other nodes for services. The optimization of waiting time, which is generally a hard task in static wireless sensor networks, is even harder in mobile wireless sensor networks, where the neighboring nodes also change over time. In this paper, the effect of node mobility on the performance of Tiny Service Discovery Protocol (TinySDP) in WSNs has been analyze. In order to measure and evaluate the performance of TinySDP in mobile WSNs (MWSN), three major metrics of evaluation has been considered such as, Success ratio, Number of transmitted messages and Average waiting time. Simulation results show that the success ratio and average waiting time of TinySDP in mobile WSNs had decreased and the number of transmitted message increased.
Transmission Performance Investigation of IR-UWB Signals over Existing optical fiber Transmission link
Authors: Kadum Jaffar Emad , Fyath Raad Sami
Published: May 2018

Recently there is increasing interest in using optical fiber links to distribute impulse radio-ultrawideband (IR-UWB) signals in order to increase the coverage area. This paper investigates the transmission performance of these signals over existing fiber links and addresses the possibility of increasing the coverage area beyond 30 km.The transmission link consists of a single- mode fiber, dispersion compensating fiber (DCF) and, optical amplifiers. Simulation results are presented using Optisystem (version 13.0) software package for both Gaussian monocycle and 5th-order derivative Gaussian systems, each operating with ON-OFF keying (OOK) and biphase modulation (BPM) formats. The results reveal that extending the coverage area for 625 Mb/s UWB signal toward 100 km is possible for the UWB signals and modulation formats adopted in this study.
EFFICIENT MANET- INTERNET INTEGRATION FOR MOBILE DEVICES
Authors: Tiwari Mahesh kumar , SHANKAR UDAI , KUMAR AJAY
Published: May 2018

A mobile ad hoc network (MANET) consists of wireless mobile nodes without having a fixed infrastructure support. The communication between these mobile nodes is carried out without any centralized control. The communication among the nodes within the infrastructure less networks is done through Ad-Hoc routing protocols, But whenever any mobile node want to communicate to a node in a network that is outside the ad hoc network such as internet, there should be an appropriate mechanism for establishing this connection with the internet node or host. Gateway discovery is a fundamental process in connecting MANET with the internet. A mobile node can connect to the internet by discovery of some specialized nodes called as gateway nodes. These Gateway nodes act as a bridge between the mobile ad hoc networks node and the internet. The basic aim of the gateway discovery approach is to modify the route discovery process so that it is not only used for discovery of destination mobile nodes but also the gateways. In this paper we are going to present a review of various gateway discovery approaches which are used for establishing the interconnection of mobile ad hoc networks and internet and going to propose a algorithm that reduce the discovery time of the gateway by selective forwarding and simultaneously also optimize the gateway discovery control overheads.
A Modified Leach Algorithm Using Hard and Soft Threshold in Wireless Sensor Network: A Review
Authors: Kaur Gurpreet , Arora Vishal
Published: May 2018

Wireless sensor networks have become increasingly popular due to their wide range of application. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. Minimizing the energy consumption of a wireless sensor network application is crucial for effective realization of the intended application in terms of cost, lifetime, and functionality. However, the minimizing task is hardly possible as no overall energy cost function is available for optimization. In this paper, we have proposed a modified alogirthm of leach where hard and soft threshold values will be applied for improving the overall throughput and network lifetime.
Communication Architecture design for an Interoperable Machine-to-Machine System
Authors: Talavera Guillermo
Published: May 2018

In recent years, we have witnessed a continuous increase in the number of embedded devices with communication capabilities that are changing the way we live, work and play.Â  Smart grids, remote monitoring and control of all kinds of consumer devices and industrial equipment, vehicular telematics and e-health devices, are some examples of this revolution.Â  The communication between those devices (Machine-to-Machine communication) is leading to a complexity explosion and a strongly fragmented market. The goal of our work is to design an architecture for a generic communication system enabling many kinds of services and devices to function together in a distributed M2M ecosystem regardless of the application domain. This paper presents an initial communication architecture design for an interoperable Machine-to-Machine (M2M) system. The architecture of the system itself is divided into three main components: gateways, distributed servers and communication overlay. Gateways are designed to enable interoperability with various external systems that are, for some reason, unable to directly become parts of the M2M overlay. Servers are required to act as central points for relaying messages, providing authorization, enforcing security policies such as channel encryption and so on. Multiple intercommunicating servers, or server federation, is supported and considered an essential part of the interoperable M2M system. The overlay component refers to the logical M2M network, which is built on top of the existing ICT infrastructure.Â
Fingerprint Image Enhancement Algorithms for Identification in an Electoral Process
Authors: Olatubosun Olabode , O.A Fasoranbaku
Published: May 2018

Electoral process in many developing nations is characterized with fraud and failure as a result of inefficient and effective system of voterâ€™s register and voting system. This usually leads to crises. This paper presents enhancement algorithms of Denoising fingerprint images using Moving Average Filter, the Segmentation of Fingerprint using Chen algorithm, Gradient-Based Local Ridge Orientation, Binarization using Otsu Algorithm, Thinning of Fingerprint Image using the linear interactive approach and Minutiae Extraction using the minutiae location and minutiae angles for the purpose of verification and Identification in electoral process. The input to the system is a Gray-scale Fingerprint image of electorate and it detailed information while the Output is a Verified and enrolled fingerprint image with matching score and details of electoratesâ€™ information store as Template using the Matlab 2013a.
Expert system for Diagnosing Kidney diseases
Authors: Fleaih Laith R.
Published: May 2018

The system mainly contains two modules one is Information System and the other is Expert Advisory system. The Information System contains the static information about different diseases in the field of Nephrology. This information system helps the patients /users to know about the problems related to kidneys. The Nephrology Advisory system helps the Patients /users to get the required and suitable advice depending on their queries.This research describes how the neural computing system designed to support the medical decision process using medical imaging databases and creating the optimal systems for ministry of the health to help the physician to making the correct decision with high certainty also give suitable medical device and can use for training the medical stuff easily either in hospital or in the clinical center. the main aim of the proposed system is the ability to diagnose of the kidney disease by questionnaire and clinical data of the patient. The proposed system makes a differential diagnosis among the main kidney diseases. The diagnosis is made taking into account the clinical exam (the symptoms that can be seen of felt) and the preclinical exam (the results of laboratory tests). This system is designed to give help to a medical expert (doctor) in making the appropriate diagnosis of a patient. The kidney diseases have a lot of common symptoms and many of them are very much alike, and that makes it very difficult even for a kidney doctor (specialist) to put a right diagnosis. The main operation of the proposed system is ability to diagnosis kidney disease by using symbol and friendly user interface and also has ability to explain the result and the answer of most two questions how the proposed system reaches to the results and why the proposed system to reaches to this results.
Do search engine data improve financial time series volatility predictions in different market periods? An empirical analysis on major world financial indices.
Authors: Risteski Dimche , Davcev Danco
Published: May 2018

In this paper, we investigate the different influence of search engine data in different market periods on the improvement of the prediction of the financial time series volatility. We use the EGARCH and the EGARCH-SVI model. We analyze weekly data from the Dow Jones, FTSE 100 and Nikkei 225 market indices and the weekly search volume index (SVI) from google trends for market indices keywords. The main contribution of this paper is introducing limitations of the EGARCH-SVI model for forecasting the weekly volatility of the market index. Our results show that i) search engine dataÂ improve financial time series volatility predictions of the EGARCH-SVI model in market crisis periods with the bigger price volatility; and ii) search engine data is not improving the prediction of the financial time series volatility of the EGARCH-SVI model in a non-crisis periods with low price volatility in the market. This result also confirms the predictive power of the EGARCH-SVI model in crisis periods for different financial markets.
ADVANCED FILE BASED SECURITY MECHANISM IN CLOUD COMPUTING: A REVIEW
Authors: Nisha Nisha , Singh Naseeb
Published: May 2018

Cloud computing is a broad solution that delivers IT as a service. Cloud computing uses the internet and the central remote servers to support different data and applications. It is an internet based technology. It permits the users to approach their personal files at any computer with internet access. The cloud computing flexibility is a function of the allocation of resources on authoritys request. It represents all the complexities of the network which may include everything from cables, routers, servers, data centers and all such other devices. Cloud based systems saves data off multiple organizations on shared hardware systems. In this paper the attempt to secure data from unauthorized access. The Method of data security is AES algorithm for providing data security by encrypting the given data based on the AES. It is based on a design principle known as a substitution-permutation network, and is fast in both Software and Hardware. The algorithms used in AES are so simple that they can be easily implemented using heap processors and a minimum amount of memory and this data then can only be decrypted by authorized person by using his private key.
Optimum Space Utilization Approach to Improve Persistence of WSNs
Authors: Modi Anuja , Prajapati Gourishankar
Published: May 2018

Wireless Sensor Networks (WSNs) are consists of huge number of sensor nodes, restricted with limited power, Â for provide services with cooperation to sense data and send to server. Various routing techniques are introduced for managing data transmission in WSNs in last decade. This work proposes novel method with compare distance of sensor nodes to base station in heterogeneous WSN. The sensor nodes near to base station are likely to send data direct to base station and nodes are long distance to base station would form cluster to send data using Stable Election Protocol (SEP) method. This work considers distance parameter to compare with base station position to decide whether need for nodes clustering or not. The proposed method further compare with existing Low Energy adaptive clustering hierarchy (LEACH) protocol and SEP protocol for WSN data transmission. The proposed method simulation results show the effectiveness with compare to existing methods.
Choosing Automated or Manual Testing in Extreme Programming with the Analytical Hierarchy Process
Authors: Alshehri Sultan , Aljuhani Abdulmajeed , Benedicenti Luigi
Published: May 2018

Extreme Programming (XP) has been called one of the most successful methods in software development. XP comprises a set of practices designed to work together to provide value to the customer. During the XP lifecycle, developers and customers regularly encounter situations in which they need to make decisions or evaluate factors. This affects the development process and team productivity. We propose to use the Analytic Hierarchy Process (AHP) as a means to systematize and streamline the decision process. AHP eliminates conflict because it elaborates input from every member of the team. Thus, the adoption of AHP can help accomplish XP values and fulfill team needs. This paper presents an example of applying the AHP to decide which testing technique to adopt depending on a series of project-specific parameters.
INTELLECTUAL FREEDOM AND CENSORSHIP IN THE EYES OF NIGERIAN LAW
Authors: ANYAEGBU DR. MERCY IFEYINWA , Obiamaka Umejiaku, Nneka
Published: May 2018

Intellectual freedom according to Article 19 of United Nations Universal Declaration of Human Rights is the right to freedom of thought and of expression of thought. Intellectual freedom guarantees everyone the right to freedom of opinion and expression. This right includes the freedom to hold opinions without interference and to seek, receive and impact information and ideas through any media and regardless of frontiers. Thus intellectual freedom encompasses the freedom to hold, receive and disseminate ideas. Whereas censorship is the suppression of ideas and information that individuals, groups or government officials find objectionable or dangerous. Censors usually achieve this through state powers via public institutions such as schools, libraries, information centres among others. Through the instrumentality of the law, such public institutions are prohibited from making censored materials easily accessible to the public or to targeted audience. This paper x-rayed those international and Nigerian laws that encourage or impinge access to information for one and all in Nigeria. It also made recommendations that will enhance easy flow of information to all information seekers in Nigeria.
How influential is negative informational influence? Evidence from online consumer changes in attitudes
Authors: Shih Meng-Lin , Chuang Shu-Hui
Published: May 2018

While marketing scholars have emphasized the importance of informational influence, our understanding of how influential unfavorable information is still remains fragmental. The purpose of this study is to examine the direct and indirect impact of negative informational influence on consumer attitude toward e-commerce acceptance. We seek to prove that negative information about an e-vendor is composed largely of unfavorable reviews regarding product quality, product price, vendorâ€™s after-sales service, and vendorâ€™s trustworthiness, and not only has a direct effect on consumersâ€™ attitude toward the acceptance of that e-vendor, but also has an indirect effect on such attitude via their detrimental beliefs of perceived product quality, perceived price, perceived after-sales service, and consumer trust in vendor. Detailed findings and implications for academics and practitioners are presented
Economic Dispatch Optimization Using Imperialist Competitive Algorithm (ICA) and compare with PSO algorithm result
Authors: Jalilzadeh Saeid , Nikkhah Saman
Published: May 2018

Measurement Imperialist Competitive Algorithm (ICA) is aÂ  population based stochastic optimization technique, originallydeveloped by Eberhart and Kennedy, inspired by simulation of a social psychological metaphor instead of the survival of the fittest individual. In ICA, the system (imperialists) is initialized with a population of random solutions (colonies) and searches for optimal using cognitive and social factors by updating generations. ICA has been successfully applied to a wide range of applications, mainly in solving continuous nonlinear optimization problems. Based on the ICA, this paper discusses the use of ICA approach to optimize performance of economic dispatch problems. The proposed method is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects
A Review On Green Cloud Computing
Authors: Kaur Prabhpreet , Sachdeva Monika
Published: May 2018

With the increasing call for green cloud, reducing energy consumption has been an important requirement for cloud resource providers not only to reduce operating costs, but also to improve system reliability. Dynamic voltage scaling (DVS) has been a key technique in exploiting the hardware characteristics of cloud datacenters to save energy by lowering the supply voltage and operating frequency. Cloud Computing is being used widely all over the world by many IT companies as it provides various benefits to the users like cost saving and ease of use. However, with the growing demands of users for computing services, cloud providers are encouraged to deploy large datacenters which consume very high amount of energy and also contribute to the increase in carbon dioxide emission in the environment. Therefore, we require to develop techniques which will help to get more environment friendly computing i.e. Green Cloud Computing.
DESIGN OF PARALLEL COUPLED MICROSTRIP BAND-PASS FILTER
Authors: Hussain Ghasan Ali
Published: May 2018

Filters occupy important acts in several Radio Frequency microwave applications. Several applications such as wireless communications still challenge RF/microwave filters with strict requirements such as smaller size, higher performance, lighter weight, and lower cost. Microstrip Filters for RF/Microwave Applications offers a unique and comprehensive treatment of RF/microwave filters based on the microstrip structure. One of the most common methods in designing microwave filters is using of parallel-coupled microstrip. In this paperÂ  simulate and fabricate by using Ansoft Designer a two resonator microstrip band-pass filter suitable for Wi-Fi applications.Â  The results of simulation were quite good.
Hybrid Scheduling Scheme for Real Time Systems
Authors: Awadalla Medhat H A
Published: May 2018

Systems as asymmetric multiprocessor platforms are considered power-efficient multiprocessor architectures, efficient task partitioning (assignment) and play a crucial role in achieving more energy efficiency at these multiprocessor platforms. This paper addresses the problem of energy-aware static partitioning of periodic real time tasks on heterogeneous multiprocessor platforms. A hybrid approach of Particle Swarm Optimization variant and priority assignment based Min-Min algorithm for task partitioning is proposed. The proposed approach aims to minimize the overall energy consumption, meanwhile avoid deadline violations. An energy-aware cost function is proposed to be considered in the proposed approach. Extensive simulated experiments and comparisons with related approaches are conducted in order to validate the effectiveness of the proposed technique. The achieved results demonstrate that the proposed partitioning scheme significantly outperforms in terms of the number of executed iterations to accomplish a specific task in addition to the energy savings.
Empirical and Statistical Study of Elicitation Complications
Authors: Arshad Sidra , Fazal Hafiza Tahira , Nawaz Tahir
Published: May 2018

The performance of Requirement Engineering is like framework for software development process. All-inclusive software has four mainstays of requirement engineering processes i.e. Functional and non-functional requirements, design,implementation and testing build the complete software fortification on top of the mainstays. Requirement engineers have to face numerous challenges to develop successful and impressive software. Requirements Engineering (RE) leads software development process. Different constraints and needs of users are explored as well as hitches in previous system are depicted. The scope of this study is to exemplify the difficulties faced by users in the utmost maiden phase of RE Requirements Elicitation and a framework is presented as well. A survey was conducted in different campuses of Universities in Pakistan for this purpose. Questionnaire was distributed among project development students of various disciplines to gather and highlighted the problems during Requirements Elicitation. Finally the predictive statistical software SPSS was used to input the collected data for more precise calculations, the results of which are discussed in section 3.
Computer-Aided Diagnosis of Speech Disorder Signal in Parkinsonâ€™s Disease
Authors: Afify Heba M. , Ahmed Basma
Published: May 2018

Computer-aided diagnosis (CAD) can be used as a decision support system by physicians in the diagnosis and treatmentof disordered speech especially those who specialize in neurophysiology diseases. Parkinson's disease (PD) is aprogressive disorder of the nervous system that affects movement. It develops gradually, sometimes starting with a barelynoticeable tremor in speech. It has been found that 80% of persons with PD reported speech and voice disorders.Parkinson's disease symptoms worsen as the condition progresses over time. Therefore, Speech may become soft orslurred and these deficits in speech intelligibility impact on health status and quality of life. Different researchers arecurrently working in the analysis of speech signal of people with PD, including the study of different dimensions in speechsuch as phonation, articulation, prosody, and intelligibility. Here, we present the characteristics and features of normalspeech and speech disorders in people with PD and the types of classification for implementation of the efficacy oftreatment interventions. The results show that our classification algorithm using ANN is outperformed KNN and SVM. ANNis a practical and useful as a predictive tool for PD screening with a high degree of accuracy, approximately 96.1% of acorrect detection rate (sensitivity 94.7%, and specificity 96.6%). Based on the high levels of accuracy obtained by ourproposed algorithm, it can be used for enhancing the detection purpose to discriminate PD patients from healthy people.Our algorithm may be used by the clinicians as a tool to confirm their diagnosis.
ENHANCED MULTIQUERY SYSTEM USING KNN FOR CONTENT BASED IMAGE RETRIEVAL
Authors: Meenu Meenu , Jindal Sonika
Published: May 2018

Content Based Image Retrieval (CBIR) techniques are becoming an essential requirement in the multimedia systems with the widespread use of internet, declining cost of storage devices and the exponential growth of un-annotated digital image information available in recent years.  Therefore multi query systems have been used rather than a single query in order to bridge the semantic gaps and in order to understand userâ€™s requirements. Moreover, query replacement algorithm has been used in the previous works in which user provides multiple images to the query image set referred as representative images. Feature vectors are extracted for each image in the representative image set and every image in the database. The centroid, Crep of the representative images is obtained by computing the mean of their feature vectors. Then every image in the representative image set is replaced with the same candidate image in the dataset one by one and new centroids are calculated for every replacement .The distance between each of the centroids resulting from the replacement and the representative image centroid Crep is calculated using Euclidean distance. The cumulative sum of these distances determines the similarity of the candidate image with the representative image set and is used for ranking the images. The smaller the distance, the similar will be the image with the representative image set. But it has some research gaps like it takes a lot of time to extract feature of each and every image from the database and compare our image with the database images and complexity as well as cost increases. So in our proposed work, the KNN algorithm is applied for classification of images in the database image set using the query images and the candidate images are reduced to images returned after classification mechanism which leads to decrease the execution time and reduce the number of iterations. Hence due to hybrid model of multi query and KNN, the effectiveness of image retrieval in CBIR system increases. The language used in this work is C /C++ with Open CV libraries and IDE is Visual studio 2015. The experimental results show that our method is more effective to improve the performance of the retrieval of images.
DMS Implications for Universities
Authors: Bresfelean Vasile Paul , Mocean Loredana , Urean Claudia Andreea
Published: May 2018

Organizations have long been struggling with the large amount of paper documents to be effectively administered, stored and organized so as to allow their easy and fast retrieval. Furthermore, energy and paper costs, security, destruction or loss and the volume of space occupied by numerous documents, folders and cabinets are also challenging problems. Digitization of paper documents and Document Management Systems (DMS) emerged as a solution to these issues with numerous advantages (eco-friendly, decreased operational costs, increased productivity, better and fast service etc.) leading to more efficient organization processes. Cloud storage and applications are an up-to-date approach with lower costs for higher education institutions, which aspire to enhance their documents and records management from creation throughout their whole lifecycle (store, capture, distribute, retrieve). While knowledge management (KM) has a demanding mission in higher education institutions, ontologies are another novel ground for document management applications in education. This paper is an extended version of our latest research study [4] and aims to extend our universityâ€™s existing applications to a multifaceted Document Management System-as-a-Service (DMSaaS) with many benefits for the institution, where records and documents are to be managed based on novel technologies. DMSaaS can address the issues related to cost, environment, space, security, operability better than a classic DMS.
AN ENHANCED TASK ALLOCATION STRATEGY IN CLOUD ENVIRONMENT
Authors: Redishettywar Kavita , Thekiya Prof. Rafik Juber
Published: May 2018

Cloud computing is a vigorous technology by which a user can get software, application, operating system and hardware as a service without actually possessing it and paying only according to the usage. Cloud Computing is a hot topic of research for the researchers these days. With the rapid growth of Interne technology cloud computing have become main source of computing for small as well big IT companies. In the cloud computing milieu the cloud data centers and the users of the cloud-computing are globally situated, therefore it is a big challenge for cloud data centers to efficiently handle the requests which are coming from millions of users and service them in an efficient manner. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon clientâ€™s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.
COMPREHENSIVE STUDY ON CONTENT BASED IMAGE RETRIEVAL WITH THEIR FEATURES
Authors: Kaur Pritpal , Kaur Sukhvir
Published: May 2018

In current years, very huge collections of images and videos have grown swiftly. In parallel with this boom, content-based image retrieval and querying the indexed collections of images from the large database are required to access visible facts and visual information. Three of the principle additives of the visual images are texture, shape and color. Content based image retrieval from big sources has a wide scope in many application areas and softwareâ€™s. To accelerate retrieval and similarity computation, the database images are analyzed and the extracted regions are clustered or grouped together with their characteristic feature vectors. As a result of latest improvements in digital storage technology, it's easy and possible to create and store the large quantity of images inside the image database. These collections may additionally comprise thousands and thousands of images and terabytes of visual information like their shape, texture and color. For users to make the most from those image databases, efficient techniques and mechanisms of searching should be devised. Having a computer to do the indexing primarily based on a CBIR scheme attempts to deal with the shortcomings of human-based indexing. Since an automated process on a computer can analyze and process the images at a very quick and efficient rate that human can never do alone. In this paper, we will discuss the structure of CBIR with their feature vectors.
CLUSTERING IN WIRELESS SENSOR NETWORK: A REVIEW
Authors: Sekhon Harpinderjeet Kaur , Singh Vikramjit
Published: May 2018

WSNs are evolving as both a vital new domain in the IT environment and a hot research including system design, networking, and distributed algorithms, programming models, data management, security and social components. Wireless sensor networks are rapidly picking up the popularity as they are potentially low cost solutions. The fundamental thought of sensor network is to scatter minor sensing gadgets over a particular geographic zone for some specific purposes like target tracking, surveillance, environmental screening and so on. These tiny devices are equipped for sensing a few progressions of parameters and communicating with different units. Since the network is wireless, the nodes communicate with each other via means of wireless. The wireless sensor network is interfaced with the outside world by a gateway server or controlling server. This paper focuses on the detailed survey of various clustering approaches used in wsn.
AN ENHANCED CLUSTERING APPROACH FOR ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS
Authors: Sekhon Harpinderjeet Kaur , Mohita Dr.
Published: May 2018

Energy consumption is the core issue in wireless sensor networks (WSN). To generate a node energy model that can accurately reveal the energy consumption of sensor nodes is an extremely important part of protocol development, system design and performance evaluation in WSNs. In this paper, by studying component energy consumption in different node states and within state transitions, the authors present the energy models of the node core components, including processors, RF modules and sensors. One of the major issues in wireless sensor networks is developing a routing protocol which has a significant impact on the overall lifetime of the sensor network. The network area is divided into same sized smallâ€“small regions. Sensor nodes are randomly deployed in each predefined sub-area. Each region will have its region head (RH) and multiple member nodes. The member nodes in a specific region will send the data to the RH. RH within the region will be elected by distributed mechanism and will be based on fuzzy variables. It was found that the proposed algorithm gives a much improved network lifetime as compared to existing work. Based on our model, transmission tuning algorithm for cluster-based WSNs has been proposed to balance the load among cluster heads that fall in different regions. This algorithm is applied prior to a cluster algorithm to improve the performance of the clustering algorithm without affecting the performance of individual sensor nodes.
A Review on Load Balancing In Cloud Environment
Authors: Kaur Amandeep , Luthra Mr. Pawan
Published: May 2018

Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous computing systems. On cloud computing platform, load balancing of the entire system can be  dynamically handled  by  using  virtualization  technology through which it  becomes  possible  to  remap  virtual  machine  and physical resources  according  to  the  change  in  load. However, in order to improve performance, the virtual machines have to fully utilize its resources and services by adapting to computing environment dynamically.  The  load balancing  with  proper  allocation  of  resources  must  be guaranteed  in  order  to  improve  resource  utility.
Cloud Implementation and Cloud Integration
Authors: Kumar Lalit , Singh Dr. Gurdev , Jain Prince
Published: May 2018

Cloud computing is innovated model which deliversconvenient and on-demand computing services over internetto requested end users. Cloud service engineering is adiscipline that combines the business and technology thinkingfor purposes of engineering a cloud. The structure of cloudservice engineering plays an important role in order to createusable and economic cloud. The cloud development life cycle(CDLC) is the one of the component in structure of cloudengineering along with Base, Tools & Techniques andManagement components. CDLC consists of six phases thatare flexible, isolated executable and having feedback. Thework of this paper focuses on the cloud Implementation andIntegration phase of the CDLC. The cloud implementation isrelated to actual creation, enablement of the cloud services ofa computing system. The cloud integration performs the taskof integrating the various cloud solution in one cloudenvironment and deploys various resource, web service andapplications to the cloud.
MODEL OF PERCEIVED INFLUENCE OF ACADEMIC PERFORMANCE USING SOCIAL NETWORKING
Authors: David Oye Nathaniel , Helou Adam Mahamat , Ab.Rahim Nor Zairah
Published: May 2018

Social networking sites have created a new social dimension where individuals can increase their social awareness by keeping in touch with old friends, making new friends, getting new data or products and gathering information in other aspects of everyday life. This helps individuals become more knowledgeable, which is very beneficial for students. Based on this, the paper proposed a model of perceived influence of academic performance using social networking. The proposed model was interpreted based on the academic performance of FSKSM (Faculty of computer Science and Information systems) students using SNSs in UTM. The study confirmed that majority of students agreed the social networking media have positive influence on their academic performance. Hence there is need for FSKSM policy makers to evolve strategies to guide and ensure that social networking sites are adopted mostly for academic purposes especially among the undergraduate students of the faculty.
Printed Arabic Characters Classification using A Statistical Approach
Authors: Zaqout Ihab
Published: May 2018

In this paper, we propose simple classifiers for printed Arabic characters based on statistical analysis. 109 printed Arabic character images are created for each one of transparent, simplified and traditional Arabic fonts. Images are preprocessed by the binarization and followed by sequence of morphological operations. A non-linear filter is applied on the thinned ridge map to extract termination and bifurcation features. The thinned ridge map vectors (TRMVs) are created using a freeman chain code template. The spatial distribution and statistical properties of the extracted features are calculated.
Finite State Testing and Syntax Testing
Authors: Singh Amandeep , Singh Harmanjit
Published: May 2018

This paper is concerned with the testing of the software which is being developed in a structured way. The advantages which accrue from a well-structured or modular organization of software depend upon an ability to independently test a module well before the full development of all the modules with which it communicates. This paper describes techniques (Finite State Testing & Syntax Testing) which effectively test various applications. With advanced computer technology, systems are getting larger to fulfill more complicated tasks, however, they are also becoming less reliable. Consequently, testing is an indispensable part of system design and implementation; yet it has proved to be a formidable task for complex systems. This motivates the study of testing finite state machines to ensure the correct functioning of systems and to discover aspects of their behavior. Finite state machines are widely used to model systems in diverse areas, including sequential circuits, certain types of programs, and, more recently, communication protocols. In a testing problem we have a machine about which we lack some information; we would like to deduce this information by providing a sequence of inputs to the machine and observing the outputs produced. Because of its practical importance and theoretical interest, the problem of testing finite state machines have been studied in different areas and at various times. Some old problems which had been open for decades were resolved recently, new concepts and more intriguing problems from new applications emerge. This paper reviews the fundamental problems in testing finite state machines and techniques for solving these problems, tracing progress in the area from its inception to the present and the state of the art. In addition, this paper covers syntax testing which is also called grammar based testing technique for testing various applications where the input data can be described formally.
Role of Adjacency Matrix & Adjacency List in Graph Theory
Authors: Singh Harmanjit , Sharma Richa
Published: May 2018

Today, graph theory has become major instrument that is used in an array of fields. Some of these include electrical engineering, mathematical research, sociology, economics, computer programming/networking, business administration and marketing. Indeed, many problems can be modeled with paths formed by traveling along the edges of a certain graph. Frequently referenced problems are efficiently planning routes for mail delivery, garbage pickup and snow removal, which can be solved using models that involve paths in graphs. Given these kinds of problems, graphs can become extremely complex, and a more efficient way of representing them is needed in practice. This is where the concept of the adjacency matrix & adjacency list comes into play.