IJACSA Vol. 6 Issue 2 (2015)

1

Effective Strategies for ROI and Image Matching

Author 1: Dr. Khaled M. G. Noaman Author 2: Dr. Jamil Abdulhamid M. Saif

The paper presents an exceptional four matching strategies: systematic, random, gradient and simulated annealing using diferent metrics. We consider two kinds of image matching algorithms. The first one oriented on the whole image matching where we compare corresponding pixels or chosen image characteristics. The second one is oriented on finding the region in the target image (region of interest ROI) , which match best the ROI given in the template image. For our experiments we take the list of target images, directly from the atlas, and a subset of these images as the template images.

systematic random gradient simulated annealing

Abstract doi.org/10.14569/IJACSA.2015.060201 PDF

2

kEFCM: kNN-Based Dynamic Evolving Fuzzy Clustering Method

Author 1: Shubair Abdulla Author 2: Amer Al-Nassiri

Despite the recent emergence of research, creating an evolving fuzzy clustering method that intelligently copes with huge amount of data streams in the present high-speed networks involves a lot of difficulties. Several efforts have been devoted to enhance traditional clustering techniques into on-line evolving fuzzy able to learn and develop continuously. In line with these efforts, we propose kEFCM, kNN-based evolving fuzzy clustering method. kEFCM overcomes the problems of computational cost, dynamic fuzzy evolving, and clustering complexity of traditional kNN. It employs the least-squares method in determining the cluster center and influential area, as well as the Euclidean distance in identifying the membership degree. It enhances the traditional kNN algorithm by involving only cluster centers in making classification decisions and evolving on-line the clusters when a new data arrives. For evaluation purpose, the experimental results on a collection of benchmark datasets are compared against other well-known clustering methods. The evaluation results approve a good competitive level of kEFCM.

Evolving Fuzzy Logic Clustering k-NN

Abstract doi.org/10.14569/IJACSA.2015.060202 PDF

3

Constraint on Repair Resources, Optimal Number of Repairers and Optimal Size of a Serviced System

Author 1: Marin Todinov

The focus of this paper is the analysis of the constraint on the repair resources caused by breakdowns of components in large systems. The study has been conducted by creating a very efficient discrete-event simulator, based on a min-heap data structure, for determining the probability of constraint on the repair resources. In finding the right balance between the number of repairers and salary costs, an exact optimisation algorithm has been proposed for the first time. The algorithm determines the optimal number of repairers which guarantees that the probability of constraint on the repair resources will not exceed an acceptable tolerable level. In addition, an exact optimisation algorithm has been proposed for the first time, for determining the maximum size of the system that can be serviced by a specified number of repairers so that the probability of constraint on the repair resources remains below a specified tolerable level. Unlike heuristic optimisation algorithms, the proposed algorithms are exact and always guarantee optimal solutions. The presented results are of significant importance to operators of computer networks, production systems, transportation networks, water distribution systems, electrical distribution networks etc. They are a solid basis for management decisions regarding the optimal number of maintenance personnel needed to service the breakdowns in large systems. Increasing the number of repairers beyond the optimal level leads to high salary costs while reducing the number of repairers below the optimal number leads to a poor quality of service.

constraint on the repair resources discrete-event simulation optimization repairs optimal size of a system

Abstract doi.org/10.14569/IJACSA.2015.060203 PDF

4

Supporting Self-Organization with Logical-Clustering Towards Autonomic Management of Internet-of-Things

Author 1: Hasibur Rahman Author 2: Theo Kanter Author 3: Rahim Rahmani

One of the challenges for autonomic management in Future Internet is to bring about self-organization in a rapidly changing environment and enable participating nodes to be aware and respond to changes. The massive number of participating nodes in Internet-of-Things calls for a new approach in regard of autonomic management with dynamic self-organization and enabling awareness to context information changes in the nodes themselves. To this end, we present new algorithms to enable self-organization with logical-clustering, the goal of which is to ensure that logical-clustering evolves correctly in the dynamic environment. The focus of these algorithms is to structure logical-clustering topology in an organized way with minimal intervention from outside sources. The correctness of the proposed algorithm is demonstrated on a scalable IoT platform, MediaSense. Our algorithms sanction 10 nodes to organize themselves per second and afford high accuracy of nodes discovery. Finally, we outline future research challenges towards autonomic management of IoT.

autonomic management Future Internet Internet-of-Things self-organization logical-clustering MediaSense

Abstract doi.org/10.14569/IJACSA.2015.060204 PDF

5

Data Center Governance Information Security Compliance Assessment Based on the Cobit Framewok

Author 1: Andrey Ferriyan Author 2: Jazi Eko Istiyanto

One of control domain of Cobit describes information security lies in Deliver and Support (DS) on DS5 Ensure Systems Security. This domain describes what things should be done by an organization to preserve and maintain the integrity of the information assets of IT where this all requires a security management process. One of the process is to perform security monitoring by conducting periodic vulnerability assessment to identify weaknesses. Because Cobit is not explained technically so it needs a method to utilizes data that has been standardized. One of the standardized database for vulnerability is CVE (Common Vulnerabilites and Exposures).This study aims to assess current condition of Data Center on Department of Transportation, Communication and Information Technology at Sleman Regency and assess the maturity level of security as well as providing solutions in particular on IT security. Next goal is to perform vulnerability assessment to find out which are the parts of the data center that may be vulnerable. Knowing weaknesses can help evaluate and provide solutions for better future. Result from this research is to create tool for vulnerability assessment and tool to calculate maturity model.

COBIT CVE maturity model

Abstract doi.org/10.14569/IJACSA.2015.060205 PDF

6

Intelligent Traffic Information System Based on Integration of Internet of Things and Agent Technology

Author 1: Hasan Omar Al-Sakran

In recent years popularity of private cars is getting urban traffic more and more crowded. As result traffic is becoming one of important problems in big cities in all over the world. Some of the traffic concerns are congestions and accidents which have caused a huge waste of time, property damage and environmental pollution. This research paper presents a novel intelligent traffic administration system, based on Internet of Things, which is featured by low cost, high scalability, high compatibility, easy to upgrade, to replace traditional traffic management system and the proposed system can improve road traffic tremendously. The Internet of Things is based on the Internet, network wireless sensing and detection technologies to realize the intelligent recognition on the tagged traffic object, tracking, monitoring, managing and processed automatically. The paper proposes an architecture that integrates internet of things with agent technology into a single platform where the agent technology handles effective communication and interfaces among a large number of heterogeneous highly distributed, and decentralized devices within the IoT. The architecture introduces the use of an active radio-frequency identification (RFID), wireless sensor technologies, object ad-hoc networking, and Internet-based information systems in which tagged traffic objects can be automatically represented, tracked, and queried over a network. This research presents an overview of a framework distributed traffic simulation model within NetLogo, an agent-based environment, for IoT traffic monitoring system using mobile agent technology.

Intelligent Traffic Internet-of-Things RFID Wireless Sensor Networks Agent Technology

Abstract doi.org/10.14569/IJACSA.2015.060206 PDF

7

Development of a Decision Support System for Handling Health Insurance Deduction

Author 1: Shakiba Khademolqorani Author 2: Ali Zeinal Hamadani

Effective hospital management involves such activities as monitoring the flow of medication, controlling treatment, and billing for the patient’s treatment. A major challenge between insurance companies and hospitals lies in the way medical treatment expenses for insured patients are reimbursed. In some cases, the insurance deduction leads to the loss of revenues by hospitals. This paper proposes a framework for the handling insurance deduction that integrates three major methodologies: Decision Support Systems, Data Mining, and Multiple Criteria Decision Making. To exemplify the practical utility of the framework, it is used to study hospital services and insurance deductions are extracted from 200,000 documents in 150 hospitals in Iran. To classify the kinds of services, decision trees are developed to mine hidden rules in the data which are then modified on the basis of some performance measures. The rules are then extracted and ranked using the TOPSIS method. The results show that the proposed framework is capable of effectively providing objective and comprehensive assessments of insurance deductions.

Hospital Management Insurance Deduction Decision Support Systems Data Mining Multiple Criteria Decision Making

Abstract doi.org/10.14569/IJACSA.2015.060207 PDF

8

A Multi-Label Classification Approach Based on Correlations Among Labels

Author 1: Raed Alazaidah Author 2: Fadi Thabtah Author 3: Qasem Al-Radaideh

Multi label classification is concerned with learning from a set of instances that are associated with a set of labels, that is, an instance could be associated with multiple labels at the same time. This task occurs frequently in application areas like text categorization, multimedia classification, bioinformatics, protein function classification and semantic scene classification. Current multi-label classification methods could be divided into two categories. The first is called problem transformation methods, which transform multi-label classification problem into single label classification problem, and then apply any single label classifier to solve the problem. The second category is called algorithm adaptation methods, which adapt an existing single label classification algorithm to handle multi-label data. In this paper, we propose a multi-label classification approach based on correlations among labels that use both problem transformation methods and algorithm adaptation methods. The approach begins with transforming multi-label dataset into a single label dataset using least frequent label criteria, and then applies the PART algorithm on the transformed dataset. The output of the approach is multi-labels rules. The approach also tries to get benefit from positive correlations among labels using predictive Apriori algorithm. The proposed approach has been evaluated using two multi-label datasets named (Emotions and Yeast) and three evaluation measures (Accuracy, Hamming Loss, and Harmonic Mean). The experiments showed that the proposed approach has a fair accuracy in comparison to other related methods.

Classification Data mining Multi-label Classification

Abstract doi.org/10.14569/IJACSA.2015.060208 PDF

9

Developing Software Bug Prediction Models Using Various Software Metrics as the Bug Indicators

Author 1: Varuna Gupta Author 2: Dr. N. Ganeshan Author 3: Dr. Tarun K. Singhal

The bug prediction effectiveness reasonably contributes towards enhancing quality of software. Bug indicators contribute significantly in determining the bug prediction approaches and help in achieving software reliability. Various comparative research studies have indicated that Depth of Inheritance (DIT), Weighted Method per Class (WMC), Coupling between Objects (CBO) and Lines of Code (LoC) have significantly established themselves as reliable bug indicators for comprehensive bug predictions. The researchers have carried out a quantitative research and have developed prediction models using above bug indicators as models input and have applied these models on open source projects (Camel and Ant). During this research, the results demonstrates that there is significant correlation between size oriented metrics (bug indicators) such as DIT, WMC, CBO, LoC and bugs. Overall, DIT takes dominance in achieving better impact on predicting bugs than WMC, CBO and LoC. The outcomes of the present research study would be of significance to software quality practitioners worldwide and would help them in prioritizing the efforts involved in bug prediction.

Bug Prediction DIT WMC CBO LoC SRGM

Abstract doi.org/10.14569/IJACSA.2015.060209 PDF

10

The Effects of Different Congestion Management Algorithms over Voip Performance

Author 1: Szabolcs Szilágyi

This paper presents one of the features of DS (Differentiated Services) architecture, namely the queuing or congestion management. Packets can be placed into separate buffer queues, on the basis of the DS value. Several forwarding policies can be used to favor high priority packets in different ways. The major reason for queuing is that the router must hold the packet in its memory while the outgoing interface is busy with sending another packet. The main goal is to compare the performance of the following queuing mechanisms using a laboratory environment: FIFO (First-In First-Out), CQ (Custom Queuing), PQ (Priority Queuing), WFQ (Weighted Fair Queuing), CBWFQ (Class Based Weighted Fair Queuing) and LLQ (Low Latency Queuing). The research is empirical and qualitative, the results are useful both in infocommunication and in education.

CBWFQ congestion CQ FIFO LLQ Pagent PQ queuing WFQ

Abstract doi.org/10.14569/IJACSA.2015.060210 PDF

11

Study of Gamification Effectiveness in Online e-Learning Systems

Author 1: Ilya V. Osipov Author 2: Evgeny Nikulchev Author 3: Alex A. Volinsky Author 4: Anna Y. Prasikova

Online distance e-learning systems allow introducing innovative methods in pedagogy, along with studying their effectiveness. Assessing the system effectiveness is based on analyzing the log files to track the studying time, the number of connections, and earned game bonus points. This study is based on an example of the online application for practical foreign language speaking skills training between random users, which select the role of a teacher or a student on their own. The main features of the developed system include pre-defined synchronized teaching and learning materials displayed for both participants, along with user motivation by means of gamification. The actual percentage of successful connects between specifically unmotivated and unfamiliar with each other users was measured. The obtained result can be used for gauging the developed system success and the proposed teaching methodology in general.

elearning gamification marketing monetization viral marketing virality

Abstract doi.org/10.14569/IJACSA.2015.060211 PDF

12

The Real-Time Research of Optimal Power Flow Calculation in Reduce Active Power Loss Aspects of Power Grid

Author 1: Yuting Pan Author 2: Yuchen Chen Author 3: Zhiqiang Yuan Author 4: Bo Liu

In order to research how to availably reduce the active power loss value in power grid system when the power system is operating, it offers a quantitative research in theory through conceiving the unbalanced losses of power grid system under the overloading bus as the investigative object, and establishing an active power loss mathematical model. It carries out online real-time optimal flow calculation within the condition that meets the control variables and state variables of the equality and inequality constraints. For some branches with larger network loss, it respectively adopts three methods, including voltage regulation method, reactive power compensation method, changing the branch’s cross-sectional area method, to reduce the general active power loss values. Moreover, it compares the compensation equivalent of three methods during the recovery process of the general active power loss in the power grid. Taking IEEE14 as an example, it verifies the effectiveness of the proposed methods. It not only can offer a reasonable measure to reduce the losses of power grid, but can provide some reliable reference for the power grid dispatching personnel.

optimal power flow voltage regulation reactive power compensation cross-sectional area active power loss

Abstract doi.org/10.14569/IJACSA.2015.060212 PDF

13

Assessment of Potential Dam Sites in the Kabul River Basin Using GIS

Author 1: RASOOLI Ahmadullah Author 2: KANG Dongshik

The research focuses on Kabul River Basin (KRB) water resources infrastructure, management and development as there are many dams already in the basin and many dams are planned and are being studied with multi-purposes objectives such as power generation, irrigation and providing water to industry and domestics. KB has been centralized all water resources related information in an integrated relational geo-database this KB is centralized repository for information river basin management with the main objectives of optimizing information collection, retrieval and organization. In addition, in this paper information and characteristics of the KRB has been presented such as drainage network or hydrology, irrigation, population, climate and surface pattern other necessary features of the basin by the use of GIS in order to invest and implement infrastracture projects. The first step in doing any kind of hydrologic modeling involves delineating streams and watersheds, and getting some basic watershed properties such as area, slope, flow length, stream network density, etc. Traditionally this was (and still is) being done manually by using topographic/contour maps. With the availability of Digital Elevation Models (DEM) and GIS tools, watershed properties can be extracted by using automated procedures. The processing of DEM to delineate watersheds is referred to as terrain pre-processing. Besides that, it produced the necessary thematic maps, base maps and other detailed maps for illustrating of basin characteristics and features GIS Based.

Geographical Information System (GIS) Kabul River Basin (KRB) Digital Elevation Model (DEM) Map

Abstract doi.org/10.14569/IJACSA.2015.060213 PDF

14

The Examination of Using Business Intelligence Systems by Enterprises in Hungary

Author 1: Peter Sasvari

Data are one of the key elements in corporate decision-making, without them, the decision-making process cannot be imagined. As a consequence, different analytical tools are needed that allow the efficient use of data, information and knowledge. These analytical tools are commonly called Business Intelligence systems that are introduced into the opeartion of enterprises to make access to business data easier, faster and broader in line with the needs of a given enterprise. Based on the findings of an empirical survey, this paper aims to give a deeper insight of the causes and purposes of using BI systems by Hungarian enterprises. It is revealed that such systems are mostly used for risk analysis, financial analysis, market analysis and controlling while their potential to make predictions is usually overlooked. One important conclusion of the paper is that the faster spread of BI systems would be facilitated by reducing costs, simpler parameter settings and a higher level of data protection.

Business Intelligence Hungary Enterprises

Abstract doi.org/10.14569/IJACSA.2015.060214 PDF

15

Sentiment Analysis Based on Expanded Aspect and Polarity-Ambiguous Word Lexicon

Author 1: Yanfang Cao Author 2: Pu Zhang Author 3: Anping Xiong

This paper focuses on the task of disambiguating polarity-ambiguous words and the task is reduced to sentiment classification of aspects, which we refer to sentiment expectation instead of semantic orientation widely used in previous researches. Polarity-ambiguous words refer to words like” large, small, high, low ”, which pose a challenging task on sentiment analysis. In order to disambiguate polarity-ambiguous words, this paper constructs the aspect and polarity-ambiguous lexicon using a mutual bootstrapping algorithm. So the sentiment of polarity-ambiguous words in context can be decided collaboratively by the sentiment expectation of the aspects and polarity-ambiguous words’ prior polarity.At sentence level, experiments show that our method is effective in sentiment analysis.

polarity-ambiguous word aspect sentiment analysis

Abstract doi.org/10.14569/IJACSA.2015.060215 PDF

16

GPS-Based Daily Context Recognition for Lifelog Generation Using Smartphone

Author 1: Go Tanaka Author 2: Masaya Okada Author 3: Hiroshi Mineno

Mobile devices are becoming increasingly more sophisticated with their many diverse and powerful sensors, such as GPS, acceleration, and gyroscope sensors. They provide numerous services for supporting daily human life and are now being studied as a tool to reduce the worldwide increase of lifestyle-related diseases. This paper describes a method for recognizing the contexts of daily human life by recording a lifelog based on a person’s location. The proposed method can distinguish and recognize several contexts at the same location by extracting features from the GPS data transmitted from smartphones. The GPS data are then used to generate classification models by machine learning. Five classification models were generated: a mobile or stationary recognition model, a transportation recognition model, and three daily context recognition models. In addition, optimal learning algorithms for machine learning were determined. The experimental results show that this method is highly accurate. As examples, the F-measure of the daily context recognition was approximately 0.954 overall at a tavern and approximately 0.920 overall at a university .

component Lifelog machine learning GPS healthcare

Abstract doi.org/10.14569/IJACSA.2015.060216 PDF

17

Age Estimation Based on AAM and 2D-DCT Features of Facial Images

Author 1: Asuman Günay Author 2: Vasif V. Nabiyev

This paper proposes a novel age estimation method - Global and Local feAture based Age estiMation (GLAAM) - relying on global and local features of facial images. Global features are obtained with Active Appearance Models (AAM). Local features are extracted with regional 2D-DCT (2- dimensional Discrete Cosine Transform) of normalized facial images. GLAAM consists of the following modules: face normalization, global feature extraction with AAM, local feature extraction with 2D-DCT, dimensionality reduction by means of Principal Component Analysis (PCA) and age estimation with multiple linear regression. Experiments have shown that GLAAM outperforms many methods previously applied to the FG-NET database.

2D-DCT AAM Age estimation PCA Regression

Abstract doi.org/10.14569/IJACSA.2015.060217 PDF

18

Personal Health Book Application for Developing Countries

Author 1: Seddiq Alabbasi Author 2: Andrew Rebeiro-Hargrave Author 3: Kunihiko Kaneko Author 4: Ashir Ahmed Author 5: Akira Fukuda

We introduce a Personal Health Book application that is used as a portable repository for Personal Health Records (PHR) in order to alleviate healthcare organizational problems in developing countries. The Personal Health Book application allows low literate people to access and carry their own medical history from a rural healthcare provider to an urban healthcare provider. This will improve the efficiency of medical care and lower costs for health clinics in underserved areas. This paper introduces a software application that can be ported onto a USB Smart Card or/and managed by smartphone or personal computer connected to cloud computing environment. The Portable Health Book application aims to ease the problem of interoperability between health clinics by accepting any file format and contents and applies a decomposed database to categorize, group and reorganize the data. Querying the application’s database, the consumer can create a unified report presentation that is understandable by the consumer, family, and healthcare provider. We tested the Personal Health Book framework by importing PHRs in an extensible markup language (XML) format with a basic structure, without checking the PHR content from the Grameen Portable Health Clinic database in Bangladesh and from different departments from a hospital in Japan. The Personal Health Book was able to generate a human readable output as its database reorganize and store any type of PHR including sensor device data.

Personal health records Patient centered healthcare Database design Developing countries Extensible markup language

Abstract doi.org/10.14569/IJACSA.2015.060218 PDF

19

En-Route Vehicular Traffic Optimization

Author 1: Saravanan M Author 2: Ashwin Kumar M

The pathways of information are changing, the physical world itself is becoming a type of information system. In what’s called the Internet of Things (IoT), sensors and actuators embedded in physical objects—from roadways to pacemakers—are linked through wired and wireless networks, often using the same Internet Protocol (IP) that connects the Internet. When objects can both sense the environment and communicate, they become tools for understanding complexity and responding to it swiftly. The revolutionary part in all this is that these physical information systems are now beginning to be deployed, and some of them even work largely without human intervention. This paper has addressed the traffic congestion problem with the help of Internet of Things. Increase in the number of vehicles in cities caused by the population and development of economy, has stimulated traffic congestion problems. It is becoming more serious day after day in the present scenario of developing countries. The reason for the same could be categorized as mismanagement of vehicular movement, ineffective system for controlling the mobility of vehicles, uneven roads and traffic snarl-up. Unexpected vehicular queuing is a major concern leading to wasting time of passengers and thwarting ambulance to reach the destination in time. In addition to that, traffic congestion makes it difficult to forecast the travel time accurately causing drivers to allocate more time in travel than scheduled previously. To ease these mounting traffic problems a demonstration is made on the Proof of Concept (POC) using the smart city data set provided by Telecom Italia of Milan city, to verify that these concepts have the potential for real world application and could be used by the government sectors or private transport organizations to ameliorate the passenger’s comfort on road which are as follows. A central node is developed which sets the speed limit and predicts a normalized speed separately for each locality from the available data set. For efficient control in mobility of vehicles an advanced dynamic digital board is introduced, which displays the speed limit set by the central node time to time. The normalized speed could be used to estimate the effective time taken between destinations precisely. By comparing normalized speed with real time values anomalies in the locality like congestion and presence of uneven roads is predicted. Accident detection model is integrated with the central node which sends a message to dynamic board indicating location of the accident along with the time taken. It even improves traffic flow around the accident occurred location. Central node together with navigation tools could provide re-routed path to the drivers during congestion or accident.

IoT IP POC Central Node Dynamic Board Accident detection model

Abstract doi.org/10.14569/IJACSA.2015.060219 PDF

20

Developement of Bayesian Networks from Unified Modeling Language for Learner Modelling

Author 1: ANOUAR TADLAOUI Mouenis Author 2: AAMMOU Souhaib Author 3: KHALDI Mohamed

First of all, and to clarify our purpose, it seems important to say that the work we are presenting here lie within the framework of learner modeling in an adaptive system understood as computational modeling of the learner .we must state also that Bayesian Networks are effective tools for learner modeling under uncertainty. They have been successfully used in many systems, with different objectives, from the assessment of knowledge of the learner to the recognition of the plan followed in problem solving. The main objective of this paper is to develop a Bayesian networks for modeling the learner from the use case diagram of the Unified Modeling Language. To achieve this objective it is necessary first to ask the Why and how we can represent a Learner model using Bayesian networks? How can we go from a dynamic representation of the learner model using UML to a probabilistic representation with Bayesian networks? Is this approach considered experimentally justified? First, we will return to the definitions of the main relationships in the diagram use cases and Bayesian networks, and then we will focus on the development rules on which we have based our work. We then demonstrate how to develop a Bayesian network based on these rules. Finally we will present the formal structure for this consideration. The prototypes and diagrams presented in this work are arguments in favor of our objective. And the network obtained also promotes reusing the learner modeling through similar systems.

Learner Modeling Bayesian networks Cognitive diagnosis Uncertainty

Abstract doi.org/10.14569/IJACSA.2015.060220 PDF

21

High Accuracy Arabic Handwritten Characters Recognition Using Error Back Propagation Artificial Neural Networks

Author 1: Assist. Prof. Majida Ali Abed Author 2: Assist. Prof. Dr. Hamid Ali Abed Alasad

This manuscript considers a new architecture to handwritten characters recognition based on simulation of the behavior of one type of artificial neural network, called the Error Back Propagation Artificial Neural Network (EBPANN). We present an overview of our neural network to be optimized and tested on 12 offline isolated Arabic handwritten characters (???????????????? ?,?,???) because the similarity of some Arabic characters and the location of the points in the character. Accuracy of 93.61% is achieved using EBPANN which is the highest accuracy achieved during Offline Handwritten Arabic Character Recognition. It is noted that the EBPANN in general generates an optimized comparison between the input samples and database samples which improves the final recognition rate. Experimental results show that the EBPANN is convergent and more accurate in solutions that minimize the error recognition rate.

Character Recognition Neural Network Classification Error Back Propagation Artificial Neural Network

Abstract doi.org/10.14569/IJACSA.2015.060221 PDF

22

The Parents' Perception of Nursing Support in their Neonatal Intensive Care Unit (NICU) Experience

Author 1: Amani F. Magliyah Author 2: Muhamamd I. Razzak

NICU is an environment that has many challenges in information receiving and understanding. The infants that are cared for might have serious and complex medical problems. For Parents the NICU experience is filled with stress, fear, sadness, guilt and shock of having a sick baby in NICU. The aim of this research was to explore and describe parents' experience when their infant is admitted to the NICU. And assess their perception of nursing support of information provision and according to their emotional feelings. This study was undertaken at Neonatal Intensive Care Unit in King Abdulaziz Medical City (KAMC), Jeddah, Saudi Arabia which is part of National Guard Health Affairs (NGHA) organization in the kingdom. The study utilized a self-report questionnaire with likert scale measurement and telephone interview with closed questions. One hundred and four parents agree to be the part of study and provided their consent to include their children in the study. The majority of respondents were mothers (76%), the remaining (24%) from the total sample were Fathers. All their infants have been admitted to the NICU at 2014. Many parents did not able to receive enough information easily from the unit; most of them found the information by nurses was difficult to understand. The majority of parent's perceived high stress and anxiety level according to this information. Also, Most Parents was not agreed about the nurses' support towards their emotional feeling and care. Additional finding indicate that a decrease in support level being associated with an increase in stress and anxiety level. In order to provide a high level of support and decrease the level of stress, there is a need for developing support strategies. One strategy is through a technology to develop an automatic daily summary for parent.

parents stress anxiety NICU nurse support neonate infant

Abstract doi.org/10.14569/IJACSA.2015.060222 PDF

23

Hybrid PSO-MOBA for Profit Maximization in Cloud Computing

Author 1: Dr. Salu George

Cloud service provider, infrastructure vendor and clients/Cloud user’s are main actors in any cloud enterprise like Amazon web service’s cloud or Google’s cloud. Now these enterprises take care in infrastructure deployment and cloud services management (IaaS/PaaS/SaaS). Cloud user ‘s need to provide correct amount of services needed and characteristic of workload in order to avoid over – provisioning of resources and it’s the important pricing factor. Cloud service provider need to manage the resources and as well as optimize the resources to maximize the profit. To manage the profit we consider the M/M/m queuing model which manages the queue of job and provide average execution time. Resource Scheduling is one of the main concerns in profit maximization for which we take HYBRID PSO-MOBA as it resolves the global convergence problem, faster convergence, less parameter to tune, easier searching in very large problem spaces and locating the right resource. In HYBRID PSO-MOBA we are combining the features of PSO and MOBA to achieve the benefits of both PSO and MOBA and have greater compatibility.

Cloud Computing Profit Maximization Admission Control SLA Optimization Hybrid Particle Swam Optimization – Multi Objective Bat Algorithm

Abstract doi.org/10.14569/IJACSA.2015.060223 PDF

24

Semantic Web Improved with the Weighted IDF Feature

Author 1: Mrs. Jyoti Gautam Author 2: Dr. Ela Kumar

The development of search engines is taking at a very fast rate. A lot of algorithms have been tried and tested. But, still the people are not getting precise results. Social networking sites are developing at tremendous rate and their growth has given birth to the new interesting problems. The social networking sites use semantic data to enhance the results. This provides us with a new perspective on how to improve the quality of information retrieval. As we are aware, many techniques of text classification are based on TFIDF algorithm. Term weighting has a significant role in classifying a text document. In this paper, firstly, we are extending the queries by “keyword+tags” instead of keywords only. In addition to this, secondly, we have developed a new ranking algorithm (JEKS algorithm) based on semantic tags from user feedback that uses CiteUlike data. The algorithm enhances the already existing semantic web by using the weighted IDF feature of the TFIDF algorithm. The suggested algorithm provides a better ranking than Google and can be viewed as a semantic web service in the domain of academics.

Text classification Semantic Web with weighted idf feature Expanded query New Semantic Web Algorithm Ranking Algorithm

Abstract doi.org/10.14569/IJACSA.2015.060224 PDF

25

Consuming Web Services on Android Mobile Platform for Finding Parking Lots

Author 1: Isak Shabani Author 2: Besmir Sejdiu Author 3: Fatushe Jasharaj

Many web applications over the last decade are built using Web services based on Simple Object Access Protocol (SOAP), because these Web services are the best choice for web applications and mobile applications in general. Researches and the results of them show how architectures and the systems primarily designed for use on desktop such as Web services calls with SOAP messaging, now are possible to be used on mobile platforms such as Android. The purpose of this paper is the study of Android mobile platform, more precisely the ability of this platform for consuming Web services and exploring existing alternatives for consuming Web services from this platform. People use their vehicles every day for transport and this of course leads to a constant demand for finding a parking lot. In this paper is proposed the system, named as MyParking through which it is aimed to facilitate users finding a parking lot for their vehicle depending on their current location. MyParking consists of three modules: Android client, administration and Web services.

Web application Web services Android platform Mobile devices MyParking

Abstract doi.org/10.14569/IJACSA.2015.060225 PDF

26

Improvement of Control System Performance by Modification of Time Delay

Author 1: Salem Alkhalaf

This paper presents a mathematical approach for improving the performance of a control system by modifying the time delay at certain operating conditions. This approach converts a continuous time loop into a discrete time loop. The formula derived is applied successfully to an applicable control system. The results show that the proposed approach efficiently improves the control system performance. The relation between the sampling time and the time delay is obtained. Two different operating conditions are examined to assess the proposed approach in improving the performance of the control system.

Distributed control system control delay sampling scheme control system performance

Abstract doi.org/10.14569/IJACSA.2015.060226 PDF

27

Use of Non-Topological Node Attribute Values for Probabilistic Determination of Link Formation

Author 1: Abhiram Gandhe Author 2: Parag Deshpande

Here we propose a probabilistic model for determining link formation, using Naïve Bayes Classifier on non-topological attribute values of nodes, in a social network. The proposed model gives a score which helps to determine the relationship strength in a non-formed link. In addition to Naïve Bayes Classifier, weighted Average of the Attribute value match helps to determine the friendship score of a non-formed link. With the increase in online social networks and its influence on people, more and more individuals are getting wider and enhanced social connect. Everyone tries to connect more to explore more. In this race of more, an individual needs better and definitive tools to help them grow their network. Wider is the network more is the possibility to explore. Here we present a novel approach for predicting a link (friendship) between two individuals (nodes) in a social network. The proposed approach uses non-topological attribute data values of both the nodes and predicts linkage possibility by applying Naïve Bayes Classifier on non-topological attribute data values of nodes in existing linkages. A linkage possibility is expressed using one quantitative measure FSCORE. We call it friendship score (FSCORE) between two unconnected individuals. FSCORE is used to predict linkage between two nodes. Higher FSCORE means a higher possibility of linkage between two nodes.

Non-Topological Attribute Link Prediction Naïve Bayes Classifier Weighted Average Graph Database Social Network Data Mining

Abstract doi.org/10.14569/IJACSA.2015.060227 PDF

28

Different Classification Algorithms Based on Arabic Text Classification: Feature Selection Comparative Study

Author 1: Ghazi Raho Author 2: Riyad Al-Shalabi Author 3: Ghassan Kanaan Author 4: Asmaa Nassar

Feature selection is necessary for effective text classification. Dataset preprocessing is essential to make upright result and effective performance. This paper investigates the effectiveness of using feature selection. In this paper we have been compared the performance between different classifiers in different situations using feature selection with stemming, and without stemming.Evaluation used a BBC Arabic dataset, different classification algorithms such as decision tree (D.T), K-nearest neighbors (KNN), Naïve Bayesian (NB) method and Naïve Bayes Multinomial(NBM) classifier were used. The experimental results are presented in term of precision, recall, F-Measures, accuracy and time to build model.

Text Classification Feature Selection Arabic Text Recall F-Measure

Abstract doi.org/10.14569/IJACSA.2015.060228 PDF

29

Implementation of ADS Linked List Via Smart Pointers

Author 1: Ivaylo Donchev Author 2: Emilia Todorova

Students traditionally have difficulties in implementing abstract data structures (ADS) in C++. To a large extent, these difficulties are due to language complexity in terms of memory management with raw pointers – the programmer must take care of too many details to provide reliable, efficient and secure implementation. Since all these technical details distract students from the essence of the studied algorithms, we decided to use in the course in DSA (Data Structures and Algorithms) an automated resource management, provided by the C++ standard ISO/IEC 14882:2011. In this work we share experience of using smart pointers to implement linked lists and discuss pedagogical aspects and effectiveness of the new classes, compared to the traditional library containers and implementation via built-in pointers.

abstract data structures C++ smart pointers teaching

Abstract doi.org/10.14569/IJACSA.2015.060229 PDF

30

A Review on Feature Extraction and Feature Selection for Handwritten Character Recognition

Author 1: Muhammad ‘Arif Mohamad Author 2: Haswadi Hassan Author 3: Dewi Nasien Author 4: Habibollah Haron

The development of handwriting character recognition (HCR) is an interesting area in pattern recognition. HCR system consists of a number of stages which are preprocessing, feature extraction, classification and followed by the actual recognition. It is generally agreed that one of the main factors influencing performance in HCR is the selection of an appropriate set of features for representing input samples. This paper provides a review of these advances. In a HCR, the set of features plays as main issues, as procedure in choosing the relevant feature that yields minimum classification error. To overcome these issues and maximize classification performance, many techniques have been proposed for reducing the dimensionality of the feature space in which data have to be processed. These techniques, generally denoted as feature reduction, may be divided in two main categories, called feature extraction and feature selection. A large number of research papers and reports have already been published on this topic. In this paper we provide an overview of some of the methods and approach of feature extraction and selection. Throughout this paper, we apply the investigation and analyzation of feature extraction and selection approaches in order to obtain the current trend. Throughout this paper also, the review of metaheuristic harmony search algorithm (HSA) has provide.

HCR Feature Extraction Feature Selection Harmony Search Algorithm

Abstract doi.org/10.14569/IJACSA.2015.060230 PDF

31

Resource Provisioning in Single Tier and Multi-Tier Cloud Computing: “State-of-the-Art”

Author 1: Marwah Hashim Eawna Author 2: Salma Hamdy Mohammed Author 3: El-Sayed M. El-Horbaty

Cloud computing is a new computation trend for delivering information as long as an electronic device needs to access of a web server. One of the major pitfalls in cloud computing is related to optimizing the resource provisioning and allocation. Because of the uniqueness of the model, resource provisioning is performed with the objective of minimizing time and the costs associated with it. This paper reviews the state-of-the-art of managing resources of the cloud environments in theoretical research. This study discusses the performance and analysis for well-known cloud provisioning resources techniques, single tier and multi-tier.

Cloud Computing Resource Provisioning

Abstract doi.org/10.14569/IJACSA.2015.060231 PDF

32

Improving Web Movie Recommender System Based on Emotions

Author 1: Karzan Wakil Author 2: Rebwar Bakhtyar Author 3: Karwan Ali Author 4: Kozhin Alaadin

Recommender Systems (RSs) are garnering a significant importance with the advent of e-commerce and e-business on the web. This paper focused on the Movie Recommender System (MRS) based on human emotions. The problem is the MRS need to capture exactly the customer’s profile and features of movies, therefore movie is a complex domain and emotions is a human interaction domain, so difficult to combining together in the new Recommender System (RS). In this paper, we prepare a new hybrid approach for improving MRS, it consists of Content Based Filtering (CBF), Collaborative Filtering (CF), emotions detection algorithm and our algorithm, that presented by matrix. The result of our system provides much better recommendations to users because it enables the users to understand the relation between their emotional states and the recommended movies.

movie recommender system collaborative filtering content based filtering emotion CF CBF MRS

Abstract doi.org/10.14569/IJACSA.2015.060232 PDF

33

Service Design for Developing Multimodal Human-Computer Interaction for Smart Tvs

Author 1: Sheng-Ming Wang Author 2: Cheih-Ju Huang

A Smart TV integrates Internet and Web features into a TV, as well convergence between computer and TV and can utilize as a computer. Smart TV devices facilitate the curation of content by combining Internet-based information with content from TV providers. Many techniques, such as those that focus on speech, gestures, and eye movement, have been used to develop various human computer interfaces for Smart TVs. However, as suggested by several researchers, user scenarios and user experiences should be incorporated with development techniques to meet user demands on Smart TVs. Thus, this study applies the service design approach for scenario planning and user experience analysis of multimodal interaction development for Smart TVs. This research begins with the service design process and derives the Quality Function Deployment matrix (QFD Matrix) for initial decision-making. Analytical Hierarchy Process (AHP) is then applied to evaluate the priority and relevance of features proposed in the QFD Matrix. Research results show the service design approach is an efficient way for an interdisciplinary team to communicate. The proposed two-stage decision-making processes provide qualitatively analyze and quantitatively measure the priority and relevance of features derived from the service design process. The technique team can then develop prototypes that facilitate multimodal human-computer interaction on Smart TVs.

Smart TV Service Design Human-Computer Interaction Quality Function Deployment Analytical Hierarchy Process

Abstract doi.org/10.14569/IJACSA.2015.060233 PDF

34

A General Model for Similarity Measurement between Objects

Author 1: Manh Hung Nguyen Author 2: Thi Hoi Nguyen

The problem to detect the similarity or the differ-ence between objects are faced regularly in several domains of applications such as e-commerce, social network, expert system, data mining, decision support system, etc. This paper introduces a general model for measuring the similarity between objects based on their attributes. In this model, the similarity on each attribute is defined with different natures and kinds of attributes. This makes our model is general and enables to apply the model in several domains of application. We also present the applying of the model into two applications in social network and e-commerce situations.

object similarity multiple attributes similarity sim-ilarity measurement decision support.

Abstract doi.org/10.14569/IJACSA.2015.060234 PDF

35

Analysis of Significant Factors for Dengue Infection Prognosis Using the Random Forest Classifier

Author 1: A. Shameem Fathima Author 2: D.Manimeglai

Random forests have emerged as a versatile and highly accurate classification and regression methodology, requiring little tuning and providing interpretable outputs. Here, we briefly explore the possibility of applying this ensemble supervised machine learning technique to predict the vulnerability for complex disease - Dengue which is often baffled with chikungunya viral fever. This study presents a new-fangled approach to determine the significant prognosis factors in dengue patients. Random forests is used to visualize and determine the significant factors that can differentiate between the dengue patients and the healthy subjects and for constructing a dengue disease survivability prediction model during the boosting process to improve accuracy and stability and to reduce over fitting problems. The presented methodology may be incorporated in a variety of applications such as risk management, tailored health communication and decision support systems in healthcare

Data Mining Dengue Virus Machine learning Random Forest

Abstract doi.org/10.14569/IJACSA.2015.060235 PDF

36

Confinement for Active Objects

Author 1: Florian Kammuller

In this paper, we provide a formal framework for the security of distributed active objects. Active objects com-municate asynchronously implementing method calls via futures. We base the formal framework on a security model that uses a semi-lattice to enable multi-lateral security crucial for distributed architectures. We further provide a security type system for the programming model ASPfun of functional active objects. Type safety and a confinement property are presented. ASPfun thus realizes secure down calls.

Distributed active objects formalization security type systems

Abstract doi.org/10.14569/IJACSA.2015.060236 PDF

37

Processing the Text of the Holy Quran: a Text Mining Study

Author 1: Mohammad Alhawarat Author 2: Mohamed Hegazi Author 3: Anwer Hilal

The Holy Quran is the reference book for more than 1.6 billion of Muslims all around the world Extracting information and knowledge from the Holy Quran is of high benefit for both specialized people in Islamic studies as well as non-specialized people. This paper initiates a series of research studies that aim to serve the Holy Quran and provide helpful and accurate information and knowledge to the all human beings. Also, the planned research studies aim to lay out a framework that will be used by researchers in the field of Arabic natural language processing by providing a ”Golden Dataset” along with useful techniques and information that will advance this field further. The aim of this paper is to find an approach for analyzing Arabic text and then providing statistical information which might be helpful for the people in this research area. In this paper the holly Quran text is preprocessed and then different text mining operations are applied to it to reveal simple facts about the terms of the holy Quran. The results show a variety of characteristics of the Holy Quran such as its most important words, its wordcloud and chapters with high term frequencies. All these results are based on term frequencies that are calculated using both Term Frequency (TF) and Term Frequency-Inverse Document Frequency (TF-IDF) methods.

Holy Quran Text Mining Arabic Natural Lan-guage Processing

Abstract doi.org/10.14569/IJACSA.2015.060237 PDF

38

SOCIA: Linked Open Data of Context behind Local Concerns for Supporting Public Participation

Author 1: Shun Shiramatsu Author 2: Tadachika Ozono Author 3: Toramatsu Shintani

To address public concerns that threat the sustain-ability of local societies, supporting public participation by shar-ing the background context behind these concerns is essentially important. We designed a SOCIA ontology, which was a linked data model, for sharing context behind local concerns with two approaches: (1) structuring Web news articles and microblogs about local concerns on the basis of geographical regions and events that were referred to by content, and (2) structuring public issues and their solutions as public goals. We moreover built a SOCIA dataset, which was a linked open dataset, on the basis of the SOCIA ontology. Web news articles and microblogs related to local concerns were semi-automatically gathered and structured. Public issues and goals were manually extracted from Web content related to revitalization from the Great East Japan Earthquake. Towards more accurate extraction of public concerns, we investigated feature expressions for extracting public concerns from microblogs written in Japanese. To address a technical issue about sample selection bias in our microblog corpus, we formulated a metric in mining feature expressions, i.e., bias-penalized information gain (BPIG). Furthermore, we developed a prototype of a public debate support system that utilized the SOCIA dataset and formulated the similarity between public goals for a goal matching service to facilitate collaboration.

Semantic Web social computing natural language processing linked open data e-Participation

Abstract doi.org/10.14569/IJACSA.2015.060238 PDF

39

Timed-Release Certificateless Encryption

Author 1: Toru Oshikiri Author 2: Taiichi Saito

Timed-Release Encryption(TRE) is an encryption mechanism that allows a receiver to decrypt a ciphertext only after the time that a sender designates. In this paper, we propose the notion of Timed-Release Certificateless Encryption(TRCLE), and define its security models. We also show a generic con-struction of TRCLE from Public-Key Encryption(PKE), Identity-Based Encryption(IBE) and one-time signature, and prove that the constructed scheme achieves the security we defined.

timed-release encryption identity-based encryption one-time signature

Abstract doi.org/10.14569/IJACSA.2015.060239 PDF

40

Vehicle Embedded Data Stream Processing Platform for Android Devices

Author 1: Shingo Akiyama Author 2: Yukikazu Nakamoto Author 3: Akihiro Yamaguchi Author 4: Kenya Sato Author 5: Hiroaki Takada

Automotive information services utilizing vehicle data are rapidly expanding. However, there is currently no data centric software architecture that takes into account the scale and complexity of data involving numerous sensors. To address this issue, the authors have developed an in-vehicle data-stream management system for automotive embedded systems (eDSMS) as data centric software architecture. Providing the data stream functionalities to drivers and passengers are highly beneficial. This paper describes a vehicle embedded data stream processing platform for Android devices. The platform enables flexible query processing with a dataflow query language and extensible operator functions in the query language on the platform. The platform employs architecture independent of data stream schema in in-vehicle eDSMS to facilitate smoother Android application program development. This paper presents specifications and design of the query language and APIs of the platform, evaluate it, and discuss the results.

Android automotive data stream management system

Abstract doi.org/10.14569/IJACSA.2015.060240 PDF

41

Ontology-based Change Propagation in Shareable Health Information Applications

Author 1: Anny Kartika Sari Author 2: Wenny Rahayu

One of the most important challenges to be ad-dressed when establishing an integrated smart health environ-ment is the availability of shareable health data and knowledge which standardize the interoperability of components within the environment. Health ontologies are commonly utilized to enable interoperability between applications in such environment. However, the dynamic nature of health knowledge causes the need for frequent changes in health ontologies which then must be propagated to the relevant applications. A change propagation method that can efficiently streamline the change management from an ontology to all the applications which reference to it is proposed. A component called a mapper is used to manage the mapping between application terms and ontology concepts. The mapper is aimed to maintain the applications’ access to the most up-to-date ontology concepts and to improve the semantic mapping between the application terms and the ontology concepts. Some rules are developed for the change propagation process. The evaluation of the method shows that the mapper can improve the mapping list in terms of: (i) correctness, by proposing a new mapping entry to substitute an existing one which is not valid anymore because ontology concept is deleted or changed;(ii) currency maintenance, by recommending a better mapping between an application term and a new ontology concept based on the similarity value between the term and the new concept.

health information system ontology-based applica-tion ontology evolution

Abstract doi.org/10.14569/IJACSA.2015.060241 PDF

42

Similarity Calculation Method of Chinese Short Text Based on Semantic Feature Space

Author 1: Liqiang Pan Author 2: Pu Zhang Author 3: Anping Xiong

In order to improve the accuracy of short text similarity calculation, this paper presents the idea that use the history of short text messages to construct semantic feature space, then use the vector in semantic feature space to represent short text and do semantic extension, and finally calculate the short text similarity of corresponding vector in the semantic feature space. This method can represent the semantic information of short text message thoroughly so as to improve the accuracy of similarity calculation. We selected a large number of problem test sets for experiments. The results show that the method we proposed is reasonable and effective.

short text semantic feature space similarity semantic similarity

Abstract doi.org/10.14569/IJACSA.2015.060242 PDF