bluuebunny/crossref_metadata_2025 huggingface dataset:
Can Ali Pass the Program? An Empirical Study of a Blind ICT Student challenges at Arab Open University
Authors: AlSoufi Ali
Published: May 2018

We live in visually oriented society, in which the computer is becoming as commonplace and integral part of every studentâ€™s educational experience. It plays essential role in transforming the way in which postsecondary programs educate and communicate with their students. Faculty is encouraged, often strongly, to incorporate more computer technology and web-enhanced components in their courses as well as to develop distance education courses and programs. Recently many textbooks include CDs that contain additional course material, course assignments, animated visual aids and tests to support both faculty and the students. Students usually use their computers to write papers, register a course and communicate with faculty and other students. These actions constitute challenges for students that are visually impaired or blind. People with disabilities are often misunderstood and discriminated against when it comes to education and especially when they pursue their higher education. The purpose of study is to explore challenges with respect to the course materials used in the first degree in IT at Arab Open University. To achieve this a blind student, who is the first experience at the university, is used as a case through studying his background and monitoring his progress in the first year of study, while a comprehensive analysis on the course material, that he will be covering in the 4 years of the program, was conducted to predict whether he will able to complete his studies successfully in the IT program. Furthermore the challenges explored would be used to enhance the program delivery for visually impaired students.
Generation of test cases using UML models
Authors: Singh Gurpreet , Singh Rasbir
Published: May 2018

Software Testing plays an important role in Software development because it can minimize the development cost. UML is widely used in the software development, there consists of the designing and coding of the software. Designing phase is done with the help of the UML models, which consists of the sequence diagrams, activity diagrams, use case diagrams, state chart diagrams etc. After designing of the system, the next task is coding. Since the software development is time and human resource consuming, the reduction of consumption is done with the help of the code generation automatically. This work mainly focus on the UML sequence diagram and state chart diagram as the model. We Propose a Technique for Test Case Generation using UML Models. UML models give a lot of Â information that should not be ignored in testing. An innovative approach of generating test cases from the combination of UML design diagrams has been discussed in this paper. Present work used an approach where sequence diagram and state chart diagram has been used to generate test cases. The test cases thus generated are suitable for dynamic testing of system.
Users behaviors: The Heritage of Digital World
Authors: Danesh Moghadam Atefeh , Alagha Alireza
Published: May 2018

In the advent of information era, not only digital world is going to expand its territories, it is going to penetrate into the traditional notions about the meaning of the words and also valorize new concepts. According to Oxford Dictionary, the word heritage is defined: The history, tradition and qualities that a country or society has had for many years and that are considered an important part of its character. In order to present how emerging patterns, as the consequences of technology development, are going to be considered as the new concept of heritage, we follow four steps. In the first step, we present the convergence of Information, Communication and Technology (ICT) and a concise history of its convergence. In the second step, we argue how convergence has culminated in emerging patterns and also has made changes in digital world. In the third step, the importance of users behaviors and its mining is surveyed. Finally, in the fourth step; we illustrate User Generated Contents (UGC) as the most prominent users behaviors in digital world.
Development of Personalized Learning Environment (PLE) for Malaysian School Environment Based on ADDIE Model
Authors: Mohd Che Ku Nuraini Che Ku , Shahbodin Faaizah
Published: May 2018

Personalized Learning Environment (PLE) is a new concept in designing and developing an online learning. PLE is more focused on individual learning rather than the instructor, facilities, resources and tools. PLE has also played an active role in improving the effectiveness of learning. This paper aims to share the development and preliminary findings on PLE in teaching Form 2 Science. The samples involved are Form 2 students at secondary schools. The study group was composed of 90 students. The topic chosen is Nutrition. In this study, the development process of the environment was examined according to the Analyze, Design, Develop, Implement, Evaluate, Instructional Design Model (ADDIE). There are divided into three phases. Phase one is Analysis which includes literature survey and collection of preliminary analysis data. Second phase is Designing and Development which adopt ADDIE model as a basis for multimedia development. The last phase is Testing and Evaluation.
Simulation Tool for Assignment Models: SIMASI
Authors: Saxena Pratiksha , Anjali Smt.
Published: May 2018

In this paper, an integrated simulation optimization model for the assignment problems is developed. An effective algorithm is developed to evaluate and analyze the back-end stored simulation results. This paper proposes simulation tool SIMASI (Simulation of assignment models) to simulate assignment models. SIMASI is a tool which simulates and computes the results of different assignment models. This tool is programmed in DOT.NET and is based on analytical approach to guide optimization strategy. Objective of this paper is to provide a user friendly simulation tool which gives optimized assignment model results. Simulation is carried out by providing the required values of matrix for resource and destination requirements and result is stored in the database for further comparison and study. Result is obtained in terms of the performance measurements of classical models of assignment system. This simulation tool is interfaced with an optimization procedure based on classical models of assignment system. The simulation results are obtained and analyzed rigorously with the help of numerical examples.
Parametric Study of Silicon Based Optical Leaky-Wave Antenna
Authors: Hummadi Ali A. , Fyath R. S.
Published: May 2018

Parametric study is presented for 1550 nm CMOS compatible optical leaky wave antenna. The antenna is designed with Si3N4 waveguide perturbed periodically with silicon. The silicon perturbations are used to transform the guided mode into a leaky mode radiated to the surrounding space. Simulation results are obtained using the commercial software package CST STUDIO SUITE 2012 and indicate clearly the strong dependence of radiation parameters on the number and dimensions of the silicon perturbations.
Pso Optimization algorithm for Task Scheduling on The Cloud Computing Environment
Authors: Elmana Zahraa Tarek Abdelhamed , Zakria Magdy , Omara Fatma A.
Published: May 2018

The Cloud computing is a most recent computing paradigm where IT services are provided and delivered over the Internet on demand. The Scheduling problem for cloud computing environment has a lot of awareness as the applications tasks could be mapped to the available resources to achieve better results. One of the main existed algorithms of task scheduling on the available resources on the cloud environment is based on the Particle Swarm Optimization (PSO). According to this PSO algorithm, the applications tasks are allocated to the available resources to minimize the computation cost only. In this paper, a modified PSO algorithm has been introduced and implemented for solving task scheduling problem in the cloud. The main idea of the modified PSO is that the tasks are allocated on the available resources to minimize the execution time in addition to the computation cost. This modified PSO algorithm is called Modified Particle Swarm Optimization (MPOS).The MPOS evaluations have been illustrated using different time, and cost parameters and their effects in the performance measures such as utilization, speedup, and efficiency. According to the implementation results, it is found that the modified MPOS algorithm outperforms the existed PSO.
Role of Biometric security for The Enhancement of Data Security
Authors: Gupta Himanshu , Chauhan Kapil
Published: May 2018

In today's society, data security is the big problem for every business organization or an individual. Most found threat is theft of personal data and information. With time digital data become more prevalent, personnel try to secure their information by using highly encrypted passwords and authentication identities, but, the misuse and theft of these security measures are rising in lot of theft cases Taking advantage of security flaws in authentication identities ends up in cards being duplicated or counterfeited and hence misused. This increasing fight with cyber security has been the sole reason ofÂ  makingÂ  biometric security systems, theÂ  important area of concern is that how doÂ  one can implement the biometric security for increasing of data security.Â  First unique feature which is found different in every human is Fingerprints; Humans have used fingerprints for personal identification. Presently, most of the organisation useÂ  fingerprint recognition for authentication processÂ  it is one of the oldest and most commonly used biometrics, with high accuracy & generally easy and efficient and fast.Â  In this paper we propose the idea to use fingerprint recognition along with the user authentication password or to access the data or information. Since the only person who can access information is the person linked to it, no thief can gain access. It also makes your data, very hard for cyber criminals to hack into.
A Survey on Green Computing using GPU in Image Processing
Authors: Handa Pooja , Kalra Meenu , Sachdeva Rajesh
Published: May 2018

Green computing is the process of reducing the power consumed by a computer and thereby reducing carbon emissions. The total power consumed by the computer excluding the monitor at its fully computative load is equal to the sum of the power consumed by the GPU in its idle state and the CPU at its full state. Recently, there have been tremendous interests in the acceleration of general computing applications using a Graphics Processing Unit (GPU). Now the GPU provides the computing powers not only for fast processing of graphics applications, but also for general computationally complex data intensive applications. On the other hand, power and energy consumptions are also becoming important design criteria. Consequently, software designs have to consider the power/energy consumptions together with performance when they are developing software.The GPU therefore does the 100% of the CPU work in its idle state .Hence the power consumed by the GPU will be low. Also when the GPU is doing all the work the CPU will remain at a load less than its idle load. Hence the power consumed will be equal to the power consumed by the CPU at a load less than its idle load plus the power consumed by a GPU.Â Â
A SURVEY ON PERFORMANCE OF FREE SPACE OPTICAL COMMUNICATION LINK
Authors: Thakur Er. Sushila , Thakur Er. Rajeev
Published: May 2018

The modern era of communication needs a system with high bandwidth and high speed datarates.To fulfill rapidÂ  demands in todayâ€™s technology era, Free space optical (FSO) communication system has become very attractive technology, because they provides high bandwidth, license free spectrum using infrared beam, and are a reliable means of communications. The first part of the paper introduces the FSO system its block diagram and also the reason behind its usage. The second part informs about the factors which impairs the performance of the system. The third part will define the factors which enhance the performance of FSO system. The fourth part here will discuss which type of frequency is better for FSO system. The last part will describe about the different modulation techniques and which Â modulation is good for FSO system.Â
Algorithm of Ontology Similarity Measure Based on Similarity Kernel Learning
Authors: Linli Zhu , Min Xiaozhong , Gao Wei
Published: May 2018

Ontology, as a structured conceptual model of knowledge representation and storage, has widely been used in biomedical and pharmaceutical research. The nature of the ontology application is to get the similarity between ontology vertices, and thus reveal the similarity of their corresponding concepts and intrinsic relationships. The similarity for all pairs of vertices forms a similarity matrix of ontology, and the aim of ontology algorithm is to obtain the optimal similarity matrix. In this paper, we propose a new algorithm to get a similarity matrix in terms of learning the optimal similarity kernel function for ontology. The simulation experiment is designed for biology â€œGoâ€ ontology application, and the result data reveal that new algorithm is efficient for such task.
REVISED LOAD BALANCING ALGORITHM IN CLOUD COMPUTING
Authors: Bharti Settu , Singh Naseeb
Published: May 2018

Cloud computing is one of the latest and upcoming paradigm that offers huge benefits such as reduced time to market, unlimited computing power and flexible computing capabilities. It is a model that provides an on-demand network access to a shared pool of computing resources It comprises a large number of concepts primarily Load Balancing, Scheduling, etc. This paper discusses load balancing as a mechanism to distribute the workload evenly to all nodes in the system to achieve a higher resource utilization and user satisfaction. It helps in allocation and de-allocation of instances of applications withoutÂ  Â failure. This paper reports a new load balancing technique and its comparison with existing algorithm providing better results.Â
A NOVEL APPROACH OF HYBRID MODEL OF ENCRYPTION ALGORITHMS AND FRAGMENTATION TO ENSURE CLOUD SECURITY
Authors: Kaur Amandeep , Luthra Mr. Pawan
Published: May 2018

Cloud is a term used as a metaphor for the wide area networks (like internet) or any such large networked environment. It came partly from the cloud-like symbol used to represent the complexities of the networks in the schematic diagrams. 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. Data segregation is done by encrypting data of users, but encryption is not complete solution. In the proposed work, we have tried to increase the cloud security by using encryption algorithms like AES and RSA along with OTP authentication. We have also fragmented the data by using data distribution at the server end.
Prediction Of Long Term Living Donor Kidney Graft Outcome: Comparison Between Different Machine Learning Methods
Authors: Fouad Maha , Abd ellatif Dr.Mahmoud M. , Hagag Prof.Mohamed , Akl Dr.Ahmed
Published: May 2018

Predicting the outcome of a graft transplant with high level of accuracy is a challenging task In medical fields and Data Mining has a great role to answer the challenge. The goal of this study is to compare the performances and features of data mining technique namely Decision Tree , Rule Based Classifiers with Compare to Logistic Regression as a standard statistical data mining method to predict the outcome of kidney transplants over a 5-year horizon. The dataset was compiled from the Urology and Nephrology Center (UNC), Mansoura, Egypt. classifiers were developed using the Weka machine learning software workbench by applying Rule Based Classifiers (RIPPER, DTNB),Decision Tree Classifiers (BF,J48 ) and Logistic Regression. Further from Experimental Results, it has been found that Decision Tree and Rule Based classifiers are providing improved Accuracy and interpretable models compared to other Classifier.
A Statistical Analysis and Datamining Approach for Wind Speed Predication
Authors: K Mahesh , Vijayakumar Dr M V , Y.H . Gangadharaiah.
Published: May 2018

The wind power industry has seen an unprecedented growth in last few years. The surge in orders for wind turbines has resulted in a producers market. This market imbalance, the relative immaturity of the wind industry, and rapid developments in data processing technology have created an opportunity to improve the performance of wind farms and change misconceptions surrounding their operations. This research offers a new paradigm for the wind power industry, data-driven modeling. Each wind Mast generates extensive data for many parameters, registered as frequently as every minute. As the predictive performance approach is novel to wind industry, it is essential to establish a viable research road map. This paper proposes a data-mining-based methodology for long term wind forecasting (ANN), which is suitable to deal with large real databases. The paper includes a case study based on a real database of five years of wind speed data for a site and discusses results of wind power density was determined by using the Weibull and Rayleigh probability density functions. Wind speed predicted using wind speed data with Datamining methodology using intelligent technology as Artificial Neural Networks (ANN) and a PROLOG program designed to calculate the monthly mean wind speed.
Large-scale, Distributed, Multilingual, Electronic Meetings: A Pilot Study of Usability and Comprehension
Authors: Posey Jamison , Aiken Milam
Published: May 2018

The United Nations, the European Union, and many other organizations must conduct meetings in many languages, but typically employ human interpreters with their accompanying cost. In addition, these oral discussions require participants to take turns speaking, lengthening the process. Many studies have shown that group support systems can reduce meeting time and increase productivity, and the addition of automatic translation into this process could support these multilingual groups. However, prior studies have typically used only a few languages with group members face to face. This study investigates how well a large multilingual group can use electronic meeting software in a geographically dispersed environment. Results show that the group members were able to understand comments exchanged in 66 languages when translated to English, and they believed the multilingual meeting system was useful for such discussions.
A Simple and Efficient Mechanism to Detect and Avoid Wormhole Attacks in IP network through LOLS
Authors: Divekar Anuja Sanjay , Borade Deepali , Bugad Vivek
Published: May 2018

It has been observed that IP networks are vulnerable to many kinds of attacks. Among the various attacks possible in  IP networks wormhole attack is one which is treated as a very severe attack. In LOLS, multiple failures are handled but network attack is not detected. LOLS cannot handle any kind of attack and this is the reason why we are working on wormhole attack and its detection by using AOMDV algorithm. In this attack a harmful node records packets at one end in the network and tunnels them to another harmful node which is present in the other end of the network. In this paper, we have proposed an algorithm which detects andÂ  avoids the wormhole attack while data transfer . In this paper one mechanism is used, which is based on the total round trip time (RTT) of current route and the average round trip times This mechanism works for both mobile ad hoc networks and wireless ad hoc networks.
A REVIEW OF ELEMENTS FOR ASSESSMENT OFE-LEARNING READINESS IN LIBYA UNIVERSITIES
Authors: Saleh Mohamed Munser , Wahid Fauziah Abdul
Published: May 2018

The e-learning is developing rapidly in the world nowadays, where technology has replaced the traditional educational approach in many universities around the world. This is because e-learning can save time and cost in educational approach as a whole. This phenomenon has spread to many developing countries like Libya with the main aim to improve the educational system. However, there seems to be lack of study on the readiness of implementing e-learning in Libya universities. Therefore, this paper will shed some light on elements needed to be evaluated to study the e-learning implementation readiness in Libya universities.
A Seismic Data Processing System based on Fast Distributed File System
Authors: Li Jun , Pan Changsen , Lu Menghan
Published: May 2018

Big data has attracted an increasingly number of attentions with the advent of the cloud era, and in the field of seismic exploration, the amount of data created by seismic exploration has also experienced an incredible growth in order to satisfy the social needs. In this case, it is necessary to build a highly-effective system of data storage and process. In our paper, we aim at the properties of the seismic data and the requirement to the performance of IO, and establish a distributed file system with the goal of processing seismic data based on the Fast Distributed File System (Fast DFS), then test our system through a series of operations such as file write and read, and the results show that our file system is very proper and effective when processing seismic data.
Application Of Signed Graph In Decision Making
Authors: Pal Anita , Banerjee Debanjan
Published: May 2018

A signed graph may be defined as an ordered pair (G, Ïƒ) where G= (V, E) is the graph and Ïƒ is a function called signature or sign mapping from E to the sign group {+, -}. People or friends are considered as the vertices and the relationships between these friends are considered as the edges. '+' sign is assigned to the edge for good relationship and '-' sign for bad relationship between the friends. Two terms friendship matrix or â€œjudgement matrix and character point C.P are introduced in this paper. Using the concept of friendship matrix and C.P in various fields the characteristics or performances could be evaluated. In this paper different problems have been considered and analysed with the help of signed graph.
Demand of Wireless Network and Security in Current Research
Authors: Prabhakar Abhishek , Tiwari Amod , Pathak Vinay Kumar
Published: May 2018

Wireless security is the prevention of unauthorized access to computers using wireless networks .The trends in wireless networks over the last few years is same as growth of internet. Wireless networks have reduced the human intervention for accessing data at various sites .It is achieved by replacing wired infrastructure with wireless infrastructure. Some of the key challenges in wireless networks are Signal weakening, movement, increase data rate, minimizing size and cost, security of user and QoS (Quality of service) parameters... The goal of this paper is to minimize challenges that are in way of our understanding of wireless network and wireless network performance.
Comparative Study on Sybil Attack Detection Schemes
Authors: Hamdan Salam , Al-Qassas Raad S. , Tedmori Sara
Published: May 2018

Vehicular Ad Hoc Network (VANET) is a wireless network formed between a collection of vehicles connected through wireless connections. VANETs can help increase the passengers comfort, safety, efficiency and convenience by providing them with information about the ongoing road status and other relevant road information. VANETs, similar to other networks, face numerous security threats. One such threat is the Sybil attack, a critical threat that can impair the proper functioning of VANETs. In a Sybil attack, a malicious node illegitimately claims multiple identities and simultaneously exploits these fake identities in order todisturb the functionality of the VANET by disseminating false information. In the presence of a Sybil node, any kind of attack can be launched on the VANET. This paper provides a comprehensive review and comparison of the different techniques that have been proposed in the literature to prevent or reduce the adverse effects of Sybil attacks.
THE IMPORTANCE OF NORMALIZATION METHODS FOR MINING MEDICAL DATA
Authors: Mihaela Gheorghe , Ruxandra Petre Stefania
Published: May 2018

Over the past decades, the field of medical informatics has been growing rapidly and has drawn the attention of many researchers. The digitization of different medical information, including medical history records, research papers, medical images, laboratory analysis and reports, has generated large amounts of data that need to be handled. As the rate of data acquisition is greater than the rate of data interpretation, new computational technologies are needed in order to manage the resulted repositories of medical data and to extract relevant knowledge from them. Such methods are provided by data mining techniques, which are used for discovering meaningful patterns and trends within the data and help improving various aspects of health informatics. In order to apply data mining techniques, the data needs to be cleansed and transformed, normalization being one of the most important pre-processing methods that accomplish this purpose.This paper aims to present the impact of applying different data normalization methods, on the performance obtained with the K-Nearest Neighbour algorithm on medical data sets.
Imprementation of Sochastic Searching for Complex Processes Identification
Authors: Nikolic Kostantin , Sad Novi
Published: May 2018

This paper presents implementation of stochastic searching method for complex technological process identification. As the first step of control systems design is identification of a process mathematcal model. The author uses certain stochastic algorithms created & explained in some of his earlier published papers. The basis of the said algorithms is a non-linear stochastic searching. From general math process description this paper considers a process steady state property as an object of identification. Some of presented examples are useful to observe possible problems most of control system designers face through attempts to solve control problems or to modify process technology. As fas as the implemented algorithms are concerned certain advantages & efficiency have been obtained vs regular gradient methods. Since the said algorithms are with some modification useful for training of artificial neural networks, the future development could be toward an inteligent control systems design & implementation. Numerical procedures have been processed by using MATLAB.
A New Similarity Measure for User-based Collaborative Filtering in Recommender Systems
Authors: Srikanth T. , Shashi M.
Published: May 2018

Collaborative filtering is a popular approach in recommender Systems that helps users in identifying the items they may like in a wagon of items. Finding similarity among users with the available item ratings so as to predict rating(s) for unseen item(s) based on the preferences of likeminded users for the current user is a challenging problem. Traditional measures like Cosine similarity and Pearson correlationâ€™s correlation exhibit some drawbacks in similarity calculation. This paper presents a new similarity measure which improves the performance of Recommender System. Experimental results on MovieLens dataset show that our proposed distance measure improves the quality of prediction. We present clustering results as an extension to validate the effectiveness of our proposed method.
A Feature Vector Compression Approach for Face Recognition using Convolution and DWT
Authors: Sagar Ganapathi , Y Barker Savita , Raja K B , Babu K Suresh , K R Venagopal
Published: May 2018

The biometric identification of a person using face trait is more efficient compared to other traits as the co-operation of a person is not required. In this paper, we propose a feature vector compression approach for face recognition using convolution and DWT.The one level DWT is applied on face images and considered only LL band. The normalized technique is applied on LL sub band to reduce high value coefficients into lower range of values ranging between Zero and one. The novel concept of linear convolution is applied on original image and LL band matrix to enhance quality of face images to obtain unique features. The Gaussian filter is applied on the output of convolution block to reduce high frequency components to generate fine-tuned feature vectors. The numbers of feature vectors of many samples of single person are converted into a single vector which reduces number of features of each person. The Euclidean distance is used to compare test image features with features of database persons to compute performance parameters. It is observed that the performance recognition rate is high compared to existing techniques.
Voltage Flicker Parameters Estimation UsingShuffled Frog Leaping Algorithm (SFLA) andImperialistic Competitive Algorithm (ICA)
Authors: Jalilzadeh Saeid , Golchin Shahriar
Published: May 2018

Measurement of magnitude and frequency ofthe voltage flicker is very important for monitoring and controlling voltage flicker efficiently to improve the network power quality. This paper presents two new methods for measurement of flicker signal parameters using Shuffled Frog Leaping Algorithm (SFLA) and Imperialist Competitive Algorithm (ICA). This paper estimates fundamental voltage and flicker magnitudes and frequencies with proposed methods. The goal is to minimize the error ofthe estimated magnitudes and frequencies via a designed fitness function. At first we introduce voltage flicker and its measuring techniques. Then voltage flicker model is analyzed. At the next part a review of SFLA and ICA is presented these methods are applied to a test voltage signal and the results are given and analyzed.
LEGAL FRAMEWORK FOR THE ENFORCEMENT OF CYBER LAW AND CYBER ETHICS IN NIGERIA.
Authors: Umejiaku Nneka Obiamaka , Anyaegbu Mercy Ifeyinwa
Published: May 2018

Cyber law deals with codified rules that govern the exchange of communication and information for the protection of intellectual property rights, freedom of speech and public access to information in cyber space. Cyber ethics on the other hand is the application of responsible behavior on the Internet. Currently in Nigeria, the Cyber Crime Act was promulgated in 2015 to tackle online offences. This paper examined the legal framework which regulates public access to information in the cyber space in Nigeria. The paper also highlights lapses inherent in Nigerian legal system. Based on the findings, the paper proffers a number of recommendations. It also observes that due to rapid development in technology, law and ethics should be combined to protect the society from the menace of cybercrime.
AN IMPLEMENTATION OF CARBON EFFICIENT VM PLACEMENT AND MIGRATION TECHNIQUE IN CLOUD ENVIRONMENT
Authors: Grover Sakshi , Ghumman Mr. Navtej Singh
Published: May 2018

Electricity consumption is set to rise 76% from 2007 to 2030 and datacenters are the main contributors of an importantÂ portion of this increase, emphasizes the importance of reducing energy consumption in clouds. Increase in the level ofÂ carbon dioxide in our ecosystem is another consequence of this increasing amount of energy consumption by theÂ datacenters. According to Gartner, the Information and communication industry produces 2% of global carbon dioxideemission [10]. Hence, there is a great requirement of making use of more environmentally friendly computing calledÂ â€œGreen Cloud Computingâ€ to minimize operational and energy consumption costs and also to reduce the environmentalimpact. In this paper, we have implemented the carbon efficient VM placement and migration technique in cloud simÂ simulator.
The Impact of Undiagnosed Synaesthesia on the Interpretation of Structural and Functional MRI Images Connectivity Maps and Resulting Diagnoses
Authors: Zayed Nourhan
Published: May 2018

Synathesia is a condition in which stimulation of a sensory modality triggers another sensation in the alike or an unalike sensory modality. Currently, synaesthesia is deemed a neurological condition that engages unwanted transfer of signals between brain regions from one sense to another â€œcrosstalk activationâ€. The probability that undiagnosed synaesthesia may impact the results of structural magnetic resonance imaging (MRI), Diffusion Tensor imaging (DTI), functional magnetic resonance imaging (fMRI) and resting state connectivity studies is high, given the multiple anatomical and functional connections within the brain. In this paper, the currently available literature to mark which sensations adjured by synaesthesia and how could this impact MRI different modalities. Our study found that synaesthesia can have an opaque impact on fMRI studies of sensory, memory and cognitive functions, and there is testimony to suggest structural connections in the brain are also mutated DTI measurements especially, it shows enhanced structural connectivity for synesthetes between brain regions, higher Fractional anisotropy (FA), as well as increased in the white matter integrity between some regions.. Given the low dispersal of synaesthesia, the likelihood of synaesthesia being a perplexing factor in DTI, fMRI studies of patient groups is small; however, determining the existence of synaesthesia is paramount for investigating individual patients especially Shizoherenia, and autistic patients.
Remove the black-hole attack in mobile ADHOC network using Threshold Based Technique
Authors: Yadav Sanjay , Singh Kaptan
Published: May 2018

In this paper enhanced the AODV routing protocol for the prevention of black hole attack. The enhanced AODV routing protocol based on the principle of thresholding. The thresholding using the concept of reference node selection process. The reference node selection process creates two group of node one is path altered group and other is stable path with sensibility. The sensibility path estimates the hop count and packet sequence number. If the number of hop count is not changed or the sequence of packet is also not lost is called sensitivity path of network. The function of threshold generated by the node distance formula based on the Euclidean distance derivation. The enhanced AODV protocol simulate in NS2.34 simulators and measure some standard parameter such as PDR, throughput, overload and E2E delivery ratio.
POWER SAVING LOAD BALANCING STRATEGY USING DVFS IN CLOUD ENVIRONMENT
Authors: Grover Sakshi , Ghumman Mr. Navtej Singh
Published: May 2018

Cloud Computing is a technology that provides a platform for the sharing of resources such as software, infrastructure, application and other information. Cloud Computing is being used widely all over the world by many IT companies as it provides benefits to the users like cost saving and ease of use.Â  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 resulting in carbon dioxide emissions.Â  Power consumption is a key concern in data centers. That type of critical issues not only reduces the profit margin, but also has effect on high carbon production which is harmful for environment and living organisms. Reducing power consumption has been an important requirement for cloud resource providers not only to reduce operating costs, but also to improve system reliability. In research work, we have arranged the virtual machines in ascending order of the load. Cloudlets would be assigned to that virtual machine that has lesser load. Cloudlets are divided into three categories like high, medium and low on the basis of their instruction length. Dvfs approach which has been implemented in the paper would scale the power according to the length of the cloudlets. Three modes of Dvfs have been implemented in the research work. Various parameters like processing time, processing cost and total power consumed by all the cloudlets at the data center have been computed and analyzed. Cloudsim a toolkit for modeling and simulation of cloud computing environment has been used to implement and demonstrate the experimental results.
A comparative study of chain based routing algorithms in wireless sensor networks
Authors: Salim Ahmed , Badran Asmaa Ahmed
Published: May 2018

Many routing algorithms for Wireless Sensor Networks (WSNs) are designed and presented in the literature. The main target of these algorithms is to improve the performance of WSNs. In this paper, a comparative study of chain-based routing algorithms has been done. In this study, we compare the performances of PEGASIS [3], COSEN [6], IECBSN [8], CHAIN-BASED [15], CRA [12] and EAPHRN [9] algorithms when the mobile base station (BS) is used. We perform analytical simulations in terms of network lifetime and average energy consumption.
A NOVEL APPROACH OF OPTIMIZING PERFORMANCE USING K-MEANS CLUSTERING IN CLOUD COMPUTING
Authors: Kamboj Sheenam , Ghumman Mr. Navtej Singh
Published: May 2018

Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. 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.Â
Predicting Machine Translation Comprehension with a Neural Network
Authors: Aiken Milam , Posey Jamison , Garner Bart , Reithel Brian
Published: May 2018

Comprehension of natural language translations is dependent upon several factors including textual variables (grammatical, spelling, and word choice errors, sentence complexity, etc.) and human variables (language fluency, topic knowledge, motivation, dyslexia, etc.). An individual readerâ€™s understanding of machine-generated translations can vary widely because of the lower accuracy usually associated with this technology. Prior studies have had mixed results in predicting which variables have the greatest influence on translation comprehension. In the current study, we employ an artificial neural network to analyze survey responses and reading test scores, resulting in a significantly correlated forecast of reading comprehension. Thus, we are able to offer better predictions to identify which readers might have a better grasp of content from garbled translations.
SIMULATED ANNEALING ALGORITHM FOR FEATURE SELECTION
Authors: Rosario Francisca , Thangadurai Dr. K.
Published: May 2018

In the process of physical annealing, a solid is heated until all particles randomly arrange themselves forming the liquid state. A slow cooling process is then used to crystallize the liquid. This process is known as simulated annealing. Simulated annealing is stochastic computational technique that searches for global optimum solutions in optimization problems. The main goal here is to give the algorithm more time in the search space exploration by accepting moves, which may degrade the solution quality, with some probability depending on a parameter called temperature. In this discussion the simulated annealing algorithm is implemented in pest and weather data set for feature selection and it reduces the dimension of the attributes through specified iterations.
An Evaluation of Topology Effect on Tiny Service Discovery Protocol for Wireless Sensor Networks
Authors: Kahloot Khalid , ElKhatib Akram A.
Published: May 2018

In the literature of wireless sensor networks (WSNs), a well studied problem is that of achieving full sevice discovery within a region according to the topology model of coverage. 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. Uniformly random distributions are widely accepted models for the location of the nodes in WSNs. Depending on the application, it may also be possible to place sensors in a four models of topologies; random, square, tringle and hexagon.Â There is a rich literature on throughput capacity for WSNs topologies in general, but we want to specifically study Service Discovery Protocol and how proper node deployment scheme can reduce the complexity of problems. In this paper, the effect of node topology on the performance of Tiny Service Discovery Protocol (TinySDP) in WSNs has been analyzed. In order to measure and evaluate the performance of TinySDP within variant shapes of topologies, We compared in terms of success ratio, number of transmitted messages and average waiting time. Simulation results showed that hexagon topology has a high data success ratio and a very low average waiting time, which are major requirements for disaster management scenarios.Â Â
Forecasting based on Bayesian type models
Authors: Bidyuk Peter , Gozhjy Aleksander Peter , Rofymchuk Alexandr T
Published: May 2018

A review of some Bayesian data analysis models is proposed, namely the models with one and several parameters. A methodology is developed for probabilistic models construction in the form of Bayesian networks using statistical data and expert estimates. The methodology provides a possibility for constructing high adequacy probabilistic models for solving the problems of classification and forecasting. An integrated dynamic network model is proposed that is based on combination of probabilistic and regression approaches; the model is distinguished with a possibility for multistep forecasts estimation. The forecast estimates computed with the dynamic model are compared with the results achieved with logistic regression combined with multiple regression. The best results were achieved in this case with the combined dynamic net model.Â
Soft Compactness and Soft Topological Separate axioms
Authors: Fu Li , Fu Hua
Published: May 2018

In this paper, we further discuss soft compactness and soft separation axioms in the soft topological space over the roughÂ soft formal context T = (G;M;R; F). We define the compact soft topological space , give soft separation axioms of soft roughÂ topological space and study their relationship in the soft topological space over the rough soft formal context.
A MULTI AGENT DECISION TREE ALGORITHM FOR SUPPLY CHAIN MANAGEMENT
Authors: Balasubramaniam C.P.
Published: May 2018

The issue of interest here is the behavior of decision agents in supply chain management. The study uses a managerial framework to organize supply-related tasks to the behavior of specific instantiations of decision agents. The reasons why organizations might elect to invest supply chain management responsibilities in decision agents rather than humanÂ functionaries are illustrated. Finally, this research presents a final construct for optimal agent-based decision making opportunities. The implication is that a shift of power from humans to computers is shown to be quite effective on technically tractable decision situations.
Mobile Health Monitoring System using Fuzzy Logic
Authors: Rao Naseem , Kumar Anil , Abbasi T. A.
Published: May 2018

This paper was tested on a set of data in order to prove its effectiveness. Simulation gives promising results in detecting the activity of the person. This is efficient system for health monitoring as compare with conventional system. In this paper, to identify personâ€™s activity fuzzy logic is used. It is found that this system is quick, easy to handle and robust in health monitoring.
Improving Friends Matching in Social Networks Using Graph Coloring
Authors: Murad Omayya , Sleit Azzam , Sharaiah Ahmad
Published: May 2018

Recently, most of people have their own profiles in different social networks. Usually, their profiles have some brief description about their personnel picture, family members, home town, career, date of birth etc. which indicate other people know some general information about others. In social networks, usually friends recommendation is done by finding the most mutual friends and suggest them to be friends. In this paper, we will introduce an algorithm, with a linear time complexity, that helps people to get not only good friends but alsoÂ  have same characteristics.Â
LOAD BALANCING IN CLOUD ENVIRONMENT: A REVIEW
Authors: Kamboj Sheenam , Ghumman Mr. Navtej Singh
Published: May 2018

An essential role of cloud computing platform is to dynamically balance the load among the different servers in order to improve resource utilization and to avoid hotspots. Load balancing (LB) is done on both sides i.e. on provider as well as on consumer side. On provider side, load balancing is the problem of allocating virtual machines to servers at runtime. Virtual Machine need to be reassigned so that servers do not get overloaded as demand changes. On consumer side application load can be balanced which provides efficiency to the consumers. On cloud computing platform, load balancing of the entire system can be dynamically handled by  using virtualization technology through which itÂbecomes 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.
STABILITY OF VISCOUS FLOW IN A CURVED CHANNEL WITH RADIAL TEMPERATURE GRADIENT
Authors: Pandey Sadhana , Rai Neelabh
Published: May 2018

In this paper, the stability of Deanâ€™s problem in the presence of a radial temperature gradient is studied for narrow gap case. The analytical solution of the eigen value problem is obtained by using the Galerkinâ€™s method. The critical values of parameters and Î› are computed, where Â is wave number and Î› is a parameter determining the onset of stability from the obtained analytical expressions for the first, second and third approximations. It is found that the difference between the numerical values of critical Î› corresponding to the second and third approximations is very small as compared to the difference between first and second approximations. The critical values of Î› obtained by the third approximation agree very well with the earlier results computed numerically by using the finite difference method. This clearly indicates that for the better result one should obtain the numerical values by taking more terms in approximation. Also, the amplitude of the radial velocity and the cell-patterns are shown on the graphs for different values of the parameter M, which depends on difference of temperatures of outer cylinder to the inner one i.e. on (), whereÂ is the temperature of inner cylinder and Â is the temperature of outer cylinder.