bluuebunny/crossref_metadata_2025 huggingface dataset:
DSS FOR IMPLEMENTING SYSTEMIC APPROACH TO FORECASTING
Authors: Gozhjy Aleksander Peter , Bidyuk Peter , Trofymchuk Alexander , Bidyuk Alexei
Published: May 2018

A computer based decision support system is proposed the basic tasks of which are modeling and forecasting of financial processes and credit risk estimation. The system is developed on the basis of system analysis principles, i.e. it has hierarchic architecture, there exists the possibility for taking into consideration some stochastic and information uncertainties, forming alternatives for models and forecasts, and tracking the computing procedures during all stages of data processing. A modular architecture is implemented that provides a possibility for the further easy enhancement and modification of the system functional possibilities with new forecasting and parameter estimation techniques, and the risk models. High quality of final result is achieved thanks to appropriate tracking of the computing procedures at all stages of data processing: preliminary data processing, model constructing, and forecasts estimation with appropriate sets of statistical quality criteria. Example is given for modeling selected processes and credit risk estimation. The example presented shows that the system developed has good perspectives for practical use.
Comparative Neural Network Models on Material Removal Rate and surface Roughness in Electrical Discharge Machining
Authors: Amalnik Morteza Sadegh , Mirzaei M. , Momeni Farzad
Published: May 2018

Electro-discharge machining (EDM) is increasingly being used in many industries for producing molds and dies, and machining complex shapes with material such as steel, cemented carbide, and engineering ceramics. The stochastic nature of EDM process has frustrated number of attempts to model it physically. Artificial neural networks (ANNs), as one of the most attractive branches in Artificial Intelligence (AI), has the potentiality to handle problems such as prediction of design and manufacturing cost, material removal rate (MRR), diagnosis, modeling, and adaptive control in a complex design and manufacturing systems. This paper uses Back Propagation Neural Network (BP) and Radial Basis Function (RBF) approach for prediction of material removal rate and surface roughness and presents the results of the experimental investigation. Charmilles Technology (EDM-ROBOFORM200) in he mechanical engineering department is used for machining parts. The networks have four inputs of current (I), voltage (V), Period of pulse on (Ton) and period of pulse off (Toff) as the input processes variables. Two outputs results of material removal rate (MRR) and surface roughness (Ra) as performance characteristics. In order to train the network, and capabilities of the models in predicting material removal rate and surface roughness, experimental data are employed. Then the output of MRR and Ra obtained from neural net compare with experimental results, and amount of relative error is calculated.
PSO-based Optimal PID Controller for Twin Rotor MIMO System
Authors: Marie Mehdi J. , AL-Suhai Ghaida A. , Latif Wisam A.
Published: May 2018

Optimum design methods based on soft computing have proved their excellence in industrial automatic control systems. In this paper, a proposed system is presented to treat the tuning of proportional, integral and derivative (PID) controller parameters to control the behavior of the Twin Rotor Multi-Input-Multi-Output (MIMO) System (TRMS). The system can be decoupled into two paths the main and the tail. The use of Particle Swarm Optimization (PSO) algorithm for tuning the controller parameters aims to get a stable control system. The simulation results reveal significant improvements in the step response characteristic such as reducing the steady state error, rise time, settling time and the number of overshoots in position control of the TRMS. Thus, the PSO based PID controller in this system proves better performance compared to the traditional existing PID one.
EVALUATION OF SOFTWARE METRICS FOR SOFTWARE PROJECTS
Authors: Chopra Kunal , Sachdeva Monika
Published: May 2018

Software metrics are developed and used by the many software organizations for the evaluation and confirmation of good code, working and maintenance of the software product. Software metrics measure and identify various types of software complexities such as size metrics, control flow metrics and data flow metrics. One of the significant objective of software metrics is that it is applicable to both a process and product metrics. Ndepend is the most advanced as well as flexible tool available in the market. We have ensured the Quality of the project by using Ndepend metrics. So we have concluded that software metrics are easy to understand and applicable on the software, so favourable among software professionals.It is most prevalent and important testing metrics used in organizations. Metrics are used to improve software productivity and quality. This thesis introduces the most commonly used software metrics proposed and reviews their use in constructing models of the software development process.
A Reference Model and a vision for manufacturing system for 2030
Authors: Amalnik Morteza Sadegh
Published: May 2018

The manufacturing enterprises are now experiencing high pressure of competition. In addition, the advancement in computer software, hardware, networks, information technologies and integration has been gradually reshaping the manufacturing companies by shifting from the industrial age to the information and knowledge era. Due to these elevated competitiveness and advanced computer technology, a number of new manufacturing and management strategies (e.g., Lean production, Just in time, Kaizen, Concurrent Engineering (CE), Cellular Manufacturing (CM), Agile manufacturing, Business process re-engineering (BPR), Agent-based systems (ABS), Computer Integrated Manufacturing (CIM), virtual manufacturing system have emerged for the innovation of manufacturing industries. The developments in organizational concepts created new concepts such as Smart organizations, Centers of excellence, Intelligent enterprises, Integrated enterprises, Virtual enterprises, Virtual enterprises networks, Dynamic enterprises, Extended enterprises, Agile enterprises, Lean enterprises, Process-driven organizations, e-enterprises, Borderless enterprises, Complicated or complex manufacturing systems, Flat structures and others. These terms have been used by researchers to describe various aspects of enterprises and its operational aspects. Although they have different definitions and scopes, there are several common issues: integration of enterprise functions; integration of enterprise resources; and collaboration. In addition Various vendors produced software applications such as Materials Requirement Planning (MRP), Manufacturing Resource Planning (MRP II), Enterprise Resource Planning (ERP),CAD/CAM systems, Manufacturing Execution System (MES), Advanced Planning & Scheduling System (APS), Supply Chain Execution (SCE), Customer Relationship Management (CRM), Advanced Order Management (AOM), Warehouse Management Systems (WMS), Transport Management System (TMS) and others. This paper proposes a Reference Model and vision for Manufacturing System for 2030 and discussed various aspects of future manufacturing enterprise..It supports the inter-enterprise functions/resources integration and collaboration over the networked environment.
To investigate the Temporal and Spatial correlation behavioral characteristics of MIMO fading channels
Authors: Mahey Rachna
Published: May 2018

This paper deals with the analysis of performance bounds of narrowband multiple-input multiple-output (MIMO) fading channels considering the transmission links from the mobile station (MS) to the base station (BS) through non-line-of-sight (NLOS) propagation conditions. It is assumed that an infinite number of local scatterers surround the MS and the BS. The Temporal as well as Spatial correlation properties of channel models are explored along with their capacity. The effect of number of scatterers; Doppler frequency; and isotropic/non-isotropic scattering conditions, on MIMO channel models is investigated in terms of statistical properties of one ring and two ring models, i.e. Time Autocorrelation Function (ACF) and two-dimensional (2D) Space Cross-correlation Function (CCF).Â
Comparison Studies for Different Shortest path Algorithms
Authors: Tamimi Abdelfatah Aref
Published: May 2018

While technological revolution has active role to the increase of computer information, growing computational capabilities of devices, and raise the level of knowledge abilities, and skills. Increase developments in science and technology. In graph used the shortest path algorithms for solving the shortest path problem. The shortest path can be single pair shortest path problem or all pairs shortest path problem. This paper discuss briefly the shortest path algorithms such as Dijkstra's algorithm, Bellman-Ford algorithm,Floyd- Warshall algorithm, and johnson's algorithm. It describes the previous algorithms for solving the shortest path problem. The goal of this paper is to investigate and comparison the impacts of different shortest path algorithms. The study shows that the efficiency varies among algorithms, helps to suggest which one of them ought to be used to solve a specific variant of the shortest path problem.
A Comparative Study of Software Firewall on Windows and Linux Platform
Authors: Prajapati Gourishankar , Khare Nilay
Published: May 2018

Nowadays, the communication through World Wide Web (WWW) is growing rapidly. All the gadgets, computer and handheld devices are connected via wire or wireless media and communicated to each others. Thus, network security is the essential requirement of an organization or individuals. Organizations are protecting their communication from unauthorized access by introducing network firewalls. A Firewall is an application program which runs on any platform such as windows, Linux, Solaris, Macintosh etc and protected the networks or systems via implementing policies and rules. In this paper, the performance of firewall is measured and compared on Windows and Linux platform individual. To evaluate the performance, a private network has been setup in which three machines are connected via a switch; one Windows machine running windows firewall, one Linux machine running Linux firewall (IPTable) and one more machine that acting as a client. On both the platforms, the performance is measured in two situations: first when network is traffic free and second network with traffic. When network is traffic free then both the platforms reflect the common normal processing behavior in context of time and packet received per second; and when packets are pumped at a very high speed in the network then the processing time and packet received per second increases exponentially in both the platforms.
Secure SDN Framework for Data Exfiltration via Video Steganography
Authors: C P SHANTALA , Viswanatha K.V
Published: May 2018

The popularity of steganography in the data exfiltration of private corporate sensitive data is increased. So it is important to detect such malicious activity. Becausethe data being transferred can hide the large amount of data in video becoming increasingly attractive. To ensure privacy and security we proposed an effective steganalysis method to detect hidden data in video by using the SDN framework policy. The main objective of this paper is to prevent the illegal data transmission from the compromised private network by the malicious users.
NondestructiveApproachforDetermination of Steel MechanicalProperties
Authors: MARTINEZ EDGAR LOPEZ , JuÃ¡rez-ChÃ¡vez JazmÃ­n Y. , Serna S. , Campillo B.
Published: May 2018

It was proposed the design of an artificial neural network (ANN) to estimate the yield strength in the welding zone of HSLA experimental steels. The input parameters of the ANN were the chemical composition and hardness. The information needed to training and testing the ANN was obtained by searching the literature of the yield strength as a function of the input parameters. The design was of the type perceptron multilayer with a rule learning of backpropagation type and sigmoidal transfer function, varying the number of nodes in the hidden layer. It was determined that the design of the ANN with 11 nodes is able to estimate the yield strength of high strength low alloy steels and ultra-high strength steels according to their chemical composition and hardness.
Discovering Mexican Birth Rate Patterns Using Machine Learning Techniques
Authors: Somodevilla Maria , Cantu David Limon , Pineda Ivo , PÃ©rez de Celis ConcepciÃ³n , VilariÃ±o Darnes
Published: May 2018

In this research, we attempt to discover patterns that describe and predict the birth rate in Mexico by using data mining techniques based on relevant demographic and economic information about Mexico. More than twelve million births data obtained from the General Directorate of Health Information in the period 2008-2013 were analyzed. The acquired knowledge allows us to say that in Mexico the birth rate is affected by the social welfare, education and marginality at county level. Due to the diversity of the population and the large number of socioeconomic factors involved in Mexican society, it is difficult to find general impact factors for this issue. The results of this research are not intended to be definitive but its aim is to provide indicators that may influence decisions about birth control in Mexico.
Loop Structures Optimization and Reordering for Efficient Parallel Processing
Authors: Vancea Alexandru , Ciaca Monica , Avornicului Mihai
Published: May 2018

The problem of choosing an optimal sequence of transformations, leading to the most efficient parallel version of a program remains an open question. Related to this, compilers of the moment only manage to incorporate a set of heuristic decisions. This article treats the transformation of the program, addressing and analyzing the range of transformations of loop structures, that we consider most appropriate today. We tried to exemplify these transformations in case of groups of companies.Â
Simulation and Analysis of Distributed Gateway System for First-Hop Redundancy
Authors: Naqvi Haidlir Achmad , NaningHertiana Sofia , Negara Ridha Muldina , Rohmatullah Rohmatullah
Published: May 2018

Internet is expected to be available every time, so that the services run on it are able to be used any time. To achieve high availability Internet network, redundancy is used by employing more than one gateway so if one gateway is down, the other gateway will take the job of it. In the access layer, we use first-hop redundancy as the redundancy system. In this research, author design a system that has first-hop redundancy. The system is designed using software defined networking paradigm. The system uses POX as controller and Openflow as Controller Data-path Protocol Interface between switches and controller. The system is simulated on the mininet to examine the capability of the system by measuring some parameters: fail over delay, resource utilization and overhead on the bipartite topology. Of the examination results and analysis, the system is able to run the first-hop redundancy which yields fail-over delay below 140 ms for single flow.
Enhancement of quality of service (QoS) in IEEE 802.11
Authors: Rasul Ababakr Ibrahim , Fadhil Diyar Salah
Published: May 2018

Today everyone is living in a gold rush of wireless communication worldwide. If we look around, we will find wireless communication happening everywhere. In our home, small routers are providing us with wireless access to the internet in offices, shopping centers, cafes, universities, and so on. In this article, a mechanism has been introduced by combining service differentiation and packet aggregation in IEEE 802.11-based WMNs. The result is IEEE802.11b is the most reliable standard among all other wireless standards. Changes required in modulation techniques so that their overhead can be decreased and data can travel in more effective and efficient way.
A bi-objective algorithm for a reactive multi-skill project scheduling problem
Authors: Dhib Cheikh , Soukhal Ameur , NÃ©ron Emmanuel , Mohamed-Babou Hafedh , Kerim Bedine
Published: May 2018

The aim of this paper is to present project scheduling problem met in a an industrial context. The focus is mainly to the reactive model. In fact, the predictive case was studied in previous works, and this paper presents a solution for a reactive version of the model studied before. We proposed a linear mathematical model for the problem and then we show that this model cannot be used in practice to the solve problem. Then we present a bi-objectve genetic algorithm proposed to solve this problem. Experiment results are provided also.
EEG Analysis for Differentiating between Brain Death and Coma in Humans
Authors: CUI Gaochao , ZHU Li , WANG Dongsheng , CAO Jianting
Published: May 2018

To have an accuracy and fast diagnosis of brain death is very urgent for patients especially for distinguishing brain death from coma circumstance. Electroencephalogram is a method of invasive recording brain signals with high temporal resolution. So in clinics, EEG is taken as the most reliable method to estimate the brain death state of affairs. The objective of this paper is to find out the statistical rule on brain death and coma detection through EEG signal processing technology analysis on 20 patientsâ€™ medical data (10 for brain death group, 10 for coma group) and then hope to give aid diagnosis conclusions in clinical practice. First, the independent component analysis (ICA) has been applied to solve artifact removal problem combined with wavelet decomposition method to compute the signal noise ratio (SNR). Moreover, the Fourier transform is calculated to compare the power spectrum of the two groups. In addition, we applied the multi-scale permutation entropy into comparison with complexity of brain death and coma patientsâ€™ data in different brain inter-rhythms. Finally, the Wilcoxon rank sum has been used to test their statistics significant differences. We proposed our understanding and conclusions on this experiment results. Specially, the real-time brain death and coma patientsâ€™ distinguishing is discussed based on parallel computational idea such as cloud computing on Hadoop.
MODELING OF AN E-BUSINESS SYSTEM
Authors: HALILI Festim HALILI , RUSTEMI Avni
Published: May 2018

Always before we start creating or accessing a particular system, it is more than necessary to have a clearer picture of how to create, respectively, how to approach a certain system, in this case of a e-business system. It is much easier as for systems makers, as well as for ordinary users when they have before them a model of how to be accessed in such a system, because such a thing will orient users much easier to purchase products online through various systems on the one hand, but on the other hand it would help makers of systems create much easier such systems when they have already before them the right design. Modeling systems may be done in different ways, depending on the context of its research, but we in this paper we will use UML diagrams for modeling online system where we will make a comparison between UML diagrams and we will present each type of UML diagram in terms of customer access in online systems. Also using predictive techniques as CPM and PERT techniques in the paper we will present the main activities required for access to an online system by different users, and their graphic presentation and critical path finding, which shows the best way to approach such a system. There shall not fail and the description of business models and the introduction of some e-business models that are commonly used in practice in the days of today.
Artificial Intelligent techniques for Flow Bottom Hole Pressure Prediction
Authors: Awadalla M , Yousef H , Al-Shidani A , Al-Hinai A
Published: May 2018

This paper proposes Radial Basis and Feed-forward Neural Networks to predict the flowing bottom-hole pressure in vertical oil wells. The developed neural network models rely on a large amount of available historical data measured from actual different oil fields. The unsurpassed number of neural network layers, the number of neurons per layer, and the number of trained samples required to get an outstanding performance have been obtained. Intensive experiments have been conducted and the standard statistical analysis has beenÂ  accomplished on the achieved results to validate the modelsâ€™ prediction accuracy. For the sake of qualitative comparison, empirical modes have been developed. The obtained results show that the proposed Feed-Forward Neural Network models outperforms and capable of estimating the FBHPaccurately.The paper showed that the accuracy of FBHP estimation using FFNN with two hidden layer model is better than FFNN with single hidden layer model, Radial Basis neural network, and the empirical model in terms of data set used, mean square error, and the correlation coefficient error. With best results of 1.4 root mean square error (RMSE), 1.4 standard deviation of relative error (STD), correlation coefficient (R) 1.0 and 99.4% of the test data sets achieved less than 5% error. The minimum sufficient number of data sets used in training ANN model can be low as 375 sets only to give a 3.4Â  RMES and 97% of the test data achieved 90% accuracy.
Review: Automatic Semantic Image Annotation
Authors: Hussein Shereen A. , Naby Howida Youssry Abd El , Youssif Aliaa A. A.
Published: May 2018

There are many approaches for automatic annotation in digital images. Nowadays digital photography is a common technology for capturing and archiving images because of the digital cameras and storage devices reasonable price. As amount of the digital images increase, the problem of annotating a specific image becomes a critical issue. Automated image annotation is creating a model capable of assigning terms to an image in order to describe its content. There are many image annotation techniques that seek to find the correlation between words and image features such as color, shape, and texture to provide an automatically correct annotation words to images which provides an alternative to the time consuming work of manual image annotation. This paper aims to cover a review on different Models (MT, CRM, CSD-Prop, SVD-COS and CSD-SVD) for automating the process of image annotation as an intermediate step in image retrieval process using Corel 5k images.
Fractal Antennas (Study and Review)
Authors: Al-Zabee Ahmed Azeez Khudhair , Jabbar Saba Qasim , Wang Desheng
Published: May 2018

In recent years, great demands for an antenna with many falsities like miniaturization, multiband and wideband antenna with high gain and low profile antenna for modern wireless communication services and applications. Fractal antenna paves the way for these requirements. In this survey, we will attempt to study and review the existing fractal antennas designs and to classify them with different techniques used and additional insight into these unique structures with the most used simulation softwares for designing of fractal antenna applications.
Forecasting the ranks of sites suitable for power plant installations
Authors: Sambhoo(Salla) Dr. Kalyani , Kadam Dr. Sanjay
Published: May 2018

An increase in the number of decision parameters used for ranking of sites for a power plant installation using the soft computing techniques leads to complex formulations that are computationally expensive[41]. Amongst a large number of decision parameters, if some of the parameters do not significantly contribute towards the ranking process, then we need not consider these for decision making. Moreover, it is very tedious to form fuzzy sets for all the 87 decision parameters from several environmental experts, which serve as inputs to certain soft computing techniques used for ranking. The decision parameters comprise of some parameters used to describe air quality, water quality, land suitability, socioeconomic and ecological suitability. We have made an attempt to reduce the number of input decision parameters so that the processing is computationally fast without significantly degrading the accuracy of the end results. We have also attempted to predict futuristic values of some of the relevant parameters to infer site suitability and/or ranking, futuristically (subsequent five years) which can act as a planning tool.
Nano Topological Analysis For Power System Control
Authors: EL-Sayed M.Kamel
Published: May 2018

In this paper,we introduce an approach for analysis of information concerning electrical power system. The suggested method is a result of hybridizing rough set concepts with nano topology constructed on the set of all data using the boundary of uncertain decision sets and its lower approximation. Bases of nano topologies are used as indicators for selecting effective features in information system of a power control. This method is applied using the main experimental data which make the suggested model near from the real life information.
A REVIEW ON CONTENT BASED IMAGE RETRIEVAL
Authors: Seth Nitika , Jindal Sonika
Published: May 2018

Image retrieval means to recover the original image from the reconstructed image, here in this paper we have discussed latest techniques in the field of image retrieval for image processing. Content Based Image Retrieval (CBIR) is one of the most exciting and fastest growing research areas in the field of Image Processing. The techniques presented are Boosting image retrieval, soft query in image retrieval system, content based image retrieval by integration of metadata encoded multimedia features, and object based image retrieval and Bayesian image retrieval system. Some probable future research directions are also presented here to explore research area in the field of image retrieval
A FUZZY BASED APPROACH FOR EARLY REQUIREMENT PRIORITIZATION
Authors: Muqeem Mohd , Rizwan Beg Dr. Md.
Published: May 2018

The importance of the prioritization in commercial software development has been analyzed by many researchers. The gathered requirements are required to be put into an order of some priority. In other words we can say that there is a need to prioritize the requirements. It is evident that most of the approaches and techniques proposed in recent research to prioritize the requirements have not been widely adopted. These approaches are too complex, time consuming, or inconsistent and difficult to implement In this paper we propose a fuzzy based approach for requirement prioritization in whichÂ  requirement are prioritized in early phase of requirement engineering as post elicitation step. This category of prioritization is known as early requirement prioritization. The proposed fuzzy based approach considers the nature of requirements by modeling their attributes as fuzzy variables. As such, these variables are integrated into a fuzzy based inference system in which the requirements represented as input attributes and ranked via the expected value operator of a fuzzy variable.
Using Fuzzy Set as a Controller on the Lateral Dynamic of Autopilot to Reducing the Effect of the Atmospheric Disturbance
Authors: Saleh Muna Hadi , Raheem Noor Abdul Razzaq
Published: May 2018

In this paper, used fuzzy set as a controller to control roll and yaw angles in lateral dynamic of the autopilot system for jet transport using MATLAB/SIMULINK. Autopilot systems are complex devices that demand exact control and stability. In this paper explained the lateral dynamic on automatic pilot and studied the effect of atmospheric disturbances on the stability then designed the fuzzy set controller to reduce three type of disturbance which faced the pilot during the flight.
Enhancement of Sales promotion using Clustering Techniques in Data Mart
Authors: Gopalakrishnan Vithya
Published: May 2018

Clustering is an important research topic in wide range of unsupervised classification application. Clustering is a technique, which divides a data into meaningful groups. K-means algorithm is one of the popular clustering algorithms.  It belongs to partition based grouping techniques, which are based on the iterative relocation of data points between clusters.  It does not support global clustering and it has linear time complexity of O(n2).  The existing and conventional data clustering algorithms were nâ€™t designed to handle the huge amount of data. So, to overcome these issues Golay code clustering algorithm is selected.  Golay code based system used to facilitate the identification of the set of codeword incarnate similar object behaviors.  The time complexity associated with Golay code-clustering algorithm is O(n).  In this work, the collected sales data is pre processed by removing all null and empty attributes, then eliminating redundant, and noise data.  To enhance the sales promotion, K-means and Golay code clustering algorithms are used to cluster the sales data in terms of place and item. Performances of these algorithms are analyzed in terms of accuracy and execution time.  Our results show that the Golay code algorithm outperforms than K-mean algorithm in all factors.
Coloured Image Segmentation Using K-Means Algorithm
Authors: Fenwa Olusayo Deborah , O. ALO O. , S. FALOHUN A.
Published: May 2018

Very large collections of images are growing ever more common. From stock photo collections to proprietary databases to the Web, these collections are diverse and often poorly indexed; unfortunately, image retrieval systems have not kept pace with the collections they are searching. The shortcomings of these systems are due both to the image representations they use and to their methods of accessing those representations to find images: (i) When users generally want to find images containing particular objects, most existing image retrieval systems represent images based only on their low-level features (â€œstuffâ€) with little regard for the spatial organization of those features. (ii) Systems based on user querying are often unintuitive and offer little help in understanding why certain images were returned and how to refine the query. Often the user knows only that he has submitted a query for, say, a bear and retrieved very few pictures of bears in return. (iii) For general image collections, there are currently no systems that automatically classify images or recognize the objects they contain. Hence, in this paper K-means algorithm was used to segment colors in two common skin diseases; Ringworm and Scabies. The results obtained showed other identifiable region which are needed for proper diagnosis by the consulting physician. However, Scabies skin diseases could not yield more and accurate results due to poor lighting effect of the image. This shows that light plays a major role in the segmentation of images based on color.
Enhanced Tree Based Real Time Intrusion Detection System in Big Data
Authors: JOSEPH S.J.SATHISH AARON , BALASUBRAMANIAN R.
Published: May 2018

Intrusion detection is one of the major necessities of the current networked environment, where every information is available in its corresponding digital form. This paper presents an enhanced tree based approach that can be used to perform intrusion detection faster and with better accuracy. The training data is subject to the random forest algorithm. This algorithm is a combination of tree predictors, and each tree depends upon the random vector generated. Spark based implementations of the Random Forest algorithm is used in a Hadoop cluster on datasets with varied imbalance to obtain the results. It has been observed that the classifier provided results in real time with an accuracy >90%, hence is more appropriate for online intrusion detection.
Twig Pattern Minimization Based on XML Schema Constraints
Authors: Gao Yuan , Liao Husheng , Gao Hongyu
Published: May 2018

Twig pattern is one of the core components of XQuery. Twig usually includes redundancy nodes which can be optimized. Schema feature is used to judge whether the node of Twig pattern is redundancy. In this paper, we propose sufficient Schema constraints and specific rules. In this paper, we have designed more determination conditions to optimize, then we will get the most efficient results. By a large number of test case, we finally get the practical limits of minimization.
Solution of a Fuzzy Assignment Problem by using Branch-and-Bound Technique with application of linguistic variable
Authors: Gotmare Anil
Published: May 2018

In this paper Branch and bound technique is applied to assignment problem with fuzzy cost with objective to minimise cost, fuzzy cost is assumed as triangular fuzzy number, Yagerâ€™s ranking method has been used for ranking the fuzzy numbers, after transforming assignment problem into a crisp one using linguistic variables, assignment problem is solved by branch and bound technique. To deal with fuzzy assignment problem with qualitative data, linguistic variable helps to convert qualitative data into quantitative data.
Effects of Rainfall Attenuation on Frequencies 1 and 3 GHZ in Nigeria
Authors: P Ogherohwo, E. , B Bukar, , D. Baba, D.
Published: May 2018

Mobile communications are part of our everyday life. The non-ideal environment which is filled with many attenuation factors affects the electromagnetic waves, which radio communication depends. This study considers the spectral range of 1 and 3GHz. At these frequencies, interesting phenomena due to rain are supposed to happen. The study of this frequency spectrum has been undertaken in an attempt to evaluate the frequency dependence of rain effects on electromagnetic waves. The study of rain effects on communication presented in this study relied solely on rainfall data collected from Nigeria Metrological Agency (NiMet) station in Lagos, Nigeria. The months for January to December for 1981-2011 were summed together and the averages were determined. The average is then used to calculate the rain rate and rainfall attenuation using the extracted results for all the locations (Bauchi, Ikeja, Jos, Kebbi, Maiduguri and Warri). The results show that Warri has the highest rainfall rate followed by Lagos. Kebbi and Maiduguri has the least while Jos and Bauchi demonstrated moderate rainfall rates. This also deduced that attenuation has less impact on lower frequencies but increase with higher frequencies. The study reveals that at higher frequencies, the rainfall attenuation is observed to be greater.
Enhanced Feature-Based Automatic Text Summarization SystemUsingSupervised Technique
Authors: Ali Madhi Ahmed , Al-Dahoud Ali A. , Hawashin Bilal H.
Published: May 2018

In this work, we propose an efficient text summarization methodby ranking sentences according to their scores that use a combination of existing and improved sentence features.Â  Many works in the literature proposed improvements to text summarization but this field still needs more improvement. For this purpose, we propose improvements to Sentence position, Sentence length, and Key wordsentence features. Afterwards, we find the optimal combination between these features and some existing features such as Term frequency, Sentence centrality, Title similarity, and Upper case of word. By usingmachine learning techniques, mainly SVM, Naive Bayes and Decision Tree classifiersour paper evaluates two feature groups: a combination of seven features without any improvements,and the same seven features after making some improvements onSentence position, Sentence length, and Key word sentence features to enhance the performance of text summarization system.Experimental results showed that making enhancements on some features improved the accuracy.
Identifying Effective Factors on Using Service Oriented Achitecture in E-Banking
Authors: Siadat Seyed Hossein , Shokohyar Sajjad , Shafahi Sara
Published: May 2018

One of the common problems of most banks in information technologyÂ  in banking area is the lack of software integrity and data banks. For integrating goals, various methods and technologies have been developed. Service oriented architecture (SOA) is among the state of art technologies. The most important goal of employing SOA in e-banking includes enhancing the re-usage level and flexibility of information services, flexibility of information technology in response to continuous business changes, standardization and integration of systems and IT infrastructures. In spite of this, unluckily, most banks experience failure in employing this technology. According to the recent surveys, one of the bankâ€™s failure reasons, is the lack of a comprehensive framework which comprises all effective factors of this architecture. Thus, the goal of this paper is to detect and analyze the effective factors on service oriented architecture in e-banking and providing a comprehensive framework which encompass all factors. This conceptual framework is essential for banks in implementing SOA properly in e-banking area. In this research,Â  first, in this researchÂ  effective factors of using SOA wasÂ  detected by a case study,Â  then most repeated factors were classified. By using statistical software, e.g. SPSS, Excel, statistical tests, e.g. validity and reliability testsÂ  and descriptiveÂ  statisticalÂ  tests were conducted and the most important factors were detected and a prioritized. As a result of this prioritization, the integration factor of systems had the most and organization features had the least significant effect on using SOA in e-banking.
A new Approach for Obtaining Optimal Solution of Unbalanced Fuzzy Transportation Problem
Authors: Joshi Nidhi , Chauhan Surjeet Singh
Published: May 2018

The present paper attempts to study the unbalanced fuzzy transportation problem so as to minimize the transportationcost of products when supply, demand and cost of the products are represented by fuzzy numbers. In this paper, authorsuse Roubast ranking technique to transform trapezoidal fuzzy numbers to crisp numbers and propose a new algorithm tofind the fuzzy optimal solution of unbalanced fuzzy transportation problem. The proposed algorithm is more efficient thanother existing algorithms like simple VAM and is illustrated via numerical example. Also, a comparison between the resultsof the new algorithm and the result of algorithm using simple VAM is provided.
Data Flow Diagrams of an Electronic Medical Record System in Mansoura Hospital
Authors: Asakr Ali , Mosab Diana T
Published: May 2018

This paper develops an Electronic Medical Record System in the Neurosurgical Unit of Mansoura General Hospital using Data Flow Diagrams. Data Flow Diagrams are the first step to design the system blueprint as they represent users requirements. The paper creates a context-aware fisheye view as it is more successfully communicate the information contained in a set of Data Flow Diagrams (DFD) than a traditional context-free presentation. A case study and experimental results show that our context-aware fisheye DFD's are well suited for application in developing Electronic Medical Record System. This makes the expert system more reliable and faster response
DEVELOPING A CONCEPTUAL MODEL OF FACTORS AFFECTING SOCIAL MEDIA NETWORKING USAGE IN E-LEARNING AT TALAL ABU GHAZELEH UNIVERSITY COLLEGE OF BUSINESS (TAGUCB) IN BAHRAIN
Authors: Albarghouthi Mohammed
Published: May 2018

Social networking has become pervasive in all sectors in the 21st century. The Kingdom of Bahrain is experiencing a big wave in reference to the use of social media networking in the context of a classroom.Â  Indisputably, an innovative learning environment will be provided if this technology is astutely used. Within the e-learning environment, the technology acceptance model (TAM) has been heavily used to examine the acceptance of different types of technologies.As such, this study aims at discussing the main factors that affect usage of social media networking in e-learning by students and educators at the Talal Abu-Ghazaleh University College of Business (TAGUCB). Based on TAM, a proposed conceptual model of social media usage in e-learning is developed
Intention to purchase behavior on social e-commerce website across cultures (case study: Iranian online purchaser)
Authors: Rezaeian Ali , Shokouhyar Sajjad , Yousefi Shahabedin
Published: May 2018

With the increasing popularity of social media, millions of users use social media services in the space such as Facebook, Twitter, MySpace, etc. Following that many organizations see this phenomenon as an opportunity to create new business and know this is known as social commerce. This phenomenon is not only due to the growth of social media, but is also because of users' participation in the fate of the marketing and sale of products. So, e-commerce has undergone a revolution, which is affected by the adoption of web 2 functionalities to increase customer participation and achieve greater economic value. Therefore, studying the behavior of buyers in the social commerce platforms can create more value for owners of e-commerce in the context of social commerce. For this reason, attempts were made to obtain more accurate findings regarding the behavior of e-commerce purchasers in social networks by taking into account the moderating influence of culture on it (Iranian online purchasers).This is an applied study. It also considered a descriptive cross-sectional study with regards to the way data are collected. The analysis of data collected from 184 active professionals in the IT industry and users of social networks indicates the moderating effect of culture and the mediating role of trust in a social network community in terms of social identity, trust transference (Familiarity), social influence (intimacy and friendship), cognitive style and the intention to purchase in the social business environment. Moreover, these findings also show that trust transference affects intention to purchase in social networks considering the aspects of familiarity, social identity and cognitive style. But the direct effect of social influence (feel close to) on the purchase intention has been rejected.
Multi-Layered Dynamic Encryption Security Scheme for Cloud Data Storage
Authors: Rodriguez Stephen , Centonze Paolina
Published: May 2018

This journal article discusses our Dynamic Encryption Key Security Scheme (DEKSS) and the purpose it serves in providing a new security architecture for protecting databases used in technology stacks involving Mobile and Cloud based devices. Our security scheme is a novel architectural strategy that implements a full-stack architecture for the dispatching and management of data between several Cloud Service Providers (CSP) and any number of mobile devices. This strategy can promise data security needs for both mobile devices and cloud service providers without impacting the security requirements of the other party. While there are limitations in being truly secure, such as those recognized by WhiteHat security in their annual report[1], we believe that our security scheme can effectively circumvent potential threats and secure data through folding data using any number of encryption layers for every table and column of data to be stored. Through this approach, we have found our work to be applicable to a variety of different audiences within the cloud security space.
ALLOCATION OF HETEROGENOUS CLOUDLETS ON PRIORITY BASIS IN CLOUD ENVIRONMENT
Authors: Kaur Sumanpreet , Ghumman Mr. Navtej Singh
Published: May 2018

Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. In the natural environment, the cloudlets will be processed in the FIFO (First in First Out approach). We propose an improved load balancing algorithm for job scheduling in the Grid environment.  Hence, in this research work, various types of leases have been assigned to the cloudlets like cancellable, suspendable and non-preemtable. The leases have been assigned on the basis of cost assigned to them and the requirement specified by the user. The datacenter broker will receive the list of all the virtual machines and will categorize them into two classes i.e. Class A and Class B. Class A will have high end virtual machines and will process the non-preemptable cloudlets. Class B will contain the low end virtual machines and will process the suspendable and cancellable cloudlets. The machines in each class will be further sorted in descending order according to their MIPS. Multiple parameters have been evaluated like waiting time, turnaround time, execution time and processing cost.  Further, this research also provides the anticipated results with the implementation of the proposed algorithm. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. The main contributions of the research work are to balance the entire system load while trying to minimize the make span of a given set of jobs. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.
Concept and Dimensions of Web 4.0
Authors: Almeida Fernando Luis
Published: May 2018

Web 4.0 is a new evolution of the Web paradigm based on multiple models, technologies and social relationships. The concept of Web 4.0 is not totally clear and unanimous in literature, because it is composed by several dimensions. In this sense, this study uses a systematic review approach to clarify the concept of Web 4.0 and explore its various dimensions, analyzing if they have elements in common. The findings indicate that the number of studies published from 2009 to 2017 on this field significantly increased, having reached a peak in 2014. Furthermore, we identified five dimensions associated with the Web 4.0 paradigm, in which the terms â€œpervasive computingâ€ and â€œubiquitous computingâ€ are the most widely used in the literature. On the other side, terms such as â€œWeb 4.0â€, â€œsymbiotic Webâ€ and â€œWeb social computingâ€ are not often used.
The Analysis on the Key Factors of Fire Rescue Course Content Design A Case Study of Miaoli County
Authors: Chang Hung-Teng , Lo Chih-Yao , Tu Wen-Chia kevin
Published: May 2018

This study discussed the factors affecting the design of the fire rescue and training courses for firefighters in Miaoli County. A questionnaire survey was conducted on firefighters. The content of the fire rescue courses held by Miaoli County Fire Bureau was discussed. Based on literature review and expert opinions upon Delphi method, this study analyzed the indicators of influencing factors. A hierarchical architecture was established. The weights affecting the design factor indicators affecting the fire rescue courses were obtained with the survey and analytic hierarchy process, and then were summarized and analyzed to establish a weight system.
Real Time Shipment Tracking System Using RFID
Authors: H Medhat , Awadalla A
Published: May 2018

This paper presents a viable system for online shipment tracking using RFID technology. It aims to find the location where exactly it is at an instance of time, from the time of shipment to the time of delivery. The system has a developed web-based database-driven application that facilities its management and provides useful information about the shipment. A complete prototype of the proposed system was implemented and tested to validate the system functionality. The results show that the system is promising for on line shipment tracking.