Search results for: public support
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2773

Search results for: public support

2413 The Effects of Media Campaigns on Different Cultures

Authors: B. Al-Jenaibi

Abstract:

The paper examines the Most public relations spots and advertisements dealing with drugs. For this reason, public service advertisements show Americans in activities with drugs and alcohol. The way that the advertisements are produced, viewers from the Middle East say these ads are not for them. They recognize the ads as strictly for Americans trying to overcome their problems with drugs and alcohol. Also, this paper explores the development of the advertisements which are ineffective in other cultures like the Islamic because the limited scope of the message does not have a major effect on the Islamic beliefs and practices.

Keywords: Arab media campaign, Middle easy Advertisements, Islamic culture and American campaigns.

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2412 Designing Social Care Policies in the Long Term: A Study Using Regression, Clustering and Backpropagation Neural Nets

Authors: Sotirios Raptis

Abstract:

Linking social needs to social classes using different criteria may lead to social services misuse. The paper discusses using ML and Neural Networks (NNs) in linking public services in Scotland in the long term and advocates, this can result in a reduction of the services cost connecting resources needed in groups for similar services. The paper combines typical regression models with clustering and cross-correlation as complementary constituents to predict the demand. Insurance companies and public policymakers can pack linked services such as those offered to the elderly or to low-income people in the longer term. The work is based on public data from 22 services offered by Public Health Services (PHS) Scotland and from the Scottish Government (SG) from 1981 to 2019 that are broken into 110 years series called factors and uses Linear Regression (LR), Autoregression (ARMA) and 3 types of back-propagation (BP) Neural Networks (BPNN) to link them under specific conditions. Relationships found were between smoking related healthcare provision, mental health-related health services, and epidemiological weight in Primary 1(Education) Body Mass Index (BMI) in children. Primary component analysis (PCA) found 11 significant factors while C-Means (CM) clustering gave 5 major factors clusters.

Keywords: Probability, cohorts, data frames, services, prediction.

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2411 Assessment of Green and Smart IT Level: A Case Study on Public Research Institute

Authors: Han-Gook Kim, Dong-Suk Hong

Abstract:

As the latest advancement and trend in IT field, Green & Smart IT has attracted more and more attentions from researchers. This study focuses on the development of assessing tools which can be used for evaluating Green & Smart IT level within an organization. In order to achieve meaningful results, a comprehensive review of relevant literature was performed in advance, then, Delphi survey and other processes were also employed to develop the assessment tools for Green & Smart IT level. Two rounds of Delphi questionnaire survey were conducted with 20 IT experts in public sector. The results reveal that the top five weighted KPIs to evaluate maturity of Green & Smart IT were: (1) electronic execution of business process; (2) shutdown of unused IT devices; (3) virtualization of severs; (4) automation of constant temperature and humidity; and (5) introduction of smart-work system. Finally, these tools were applied to case study of a public research institute in Korea. The findings presented in this study provide organizations with useful implications for the introduction and promotion of Green & Smart IT in the future

Keywords: Assessment, Case Study, Delphi, Green & Smart

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2410 An Approach Based on Statistics and Multi-Resolution Representation to Classify Mammograms

Authors: Nebi Gedik

Abstract:

One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: Wave atom transform, statistical features, multi-resolution representation, mammogram.

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2409 Comparison of Polynomial and Radial Basis Kernel Functions based SVR and MLR in Modeling Mass Transfer by Vertical and Inclined Multiple Plunging Jets

Authors: S. Deswal, M. Pal

Abstract:

Presently various computational techniques are used in modeling and analyzing environmental engineering data. In the present study, an intra-comparison of polynomial and radial basis kernel functions based on Support Vector Regression and, in turn, an inter-comparison with Multi Linear Regression has been attempted in modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ multiple plunging jets (varying from 1 to 16 numbers). The data set used in this study consists of four input parameters with a total of eighty eight cases, forty four each for vertical and inclined multiple plunging jets. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 along with corresponding root mean square error values of 0.0025 and 0.0020 were achieved by using polynomial and radial basis kernel functions based Support Vector Regression respectively. An intra-comparison suggests improved performance by radial basis function in comparison to polynomial kernel based Support Vector Regression. Further, an inter-comparison with Multi Linear Regression (correlation coefficient = 0.973 and root mean square error = 0.0024) reveals that radial basis kernel functions based Support Vector Regression performs better in modeling and estimating mass transfer by multiple plunging jets.

Keywords: Mass transfer, multiple plunging jets, polynomial and radial basis kernel functions, Support Vector Regression.

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2408 JConqurr - A Multi-Core Programming Toolkit for Java

Authors: G.A.C.P. Ganegoda, D.M.A. Samaranayake, L.S. Bandara, K.A.D.N.K. Wimalawarne

Abstract:

With the popularity of the multi-core and many-core architectures there is a great requirement for software frameworks which can support parallel programming methodologies. In this paper we introduce an Eclipse toolkit, JConqurr which is easy to use and provides robust support for flexible parallel progrmaming. JConqurr is a multi-core and many-core programming toolkit for Java which is capable of providing support for common parallel programming patterns which include task, data, divide and conquer and pipeline parallelism. The toolkit uses an annotation and a directive mechanism to convert the sequential code into parallel code. In addition to that we have proposed a novel mechanism to achieve the parallelism using graphical processing units (GPU). Experiments with common parallelizable algorithms have shown that our toolkit can be easily and efficiently used to convert sequential code to parallel code and significant performance gains can be achieved.

Keywords: Multi-core, parallel programming patterns, GPU, Java, Eclipse plugin, toolkit,

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2407 Genetic-based Anomaly Detection in Logs of Process Aware Systems

Authors: Hanieh Jalali, Ahmad Baraani

Abstract:

Nowaday-s, many organizations use systems that support business process as a whole or partially. However, in some application domains, like software development and health care processes, a normative Process Aware System (PAS) is not suitable, because a flexible support is needed to respond rapidly to new process models. On the other hand, a flexible Process Aware System may be vulnerable to undesirable and fraudulent executions, which imposes a tradeoff between flexibility and security. In order to make this tradeoff available, a genetic-based anomaly detection model for logs of Process Aware Systems is presented in this paper. The detection of an anomalous trace is based on discovering an appropriate process model by using genetic process mining and detecting traces that do not fit the appropriate model as anomalous trace; therefore, when used in PAS, this model is an automated solution that can support coexistence of flexibility and security.

Keywords: Anomaly Detection, Genetic Algorithm, ProcessAware Systems, Process Mining.

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2406 A Sequential Pattern Mining Method Based On Sequential Interestingness

Authors: Shigeaki Sakurai, Youichi Kitahara, Ryohei Orihara

Abstract:

Sequential mining methods efficiently discover all frequent sequential patterns included in sequential data. These methods use the support, which is the previous criterion that satisfies the Apriori property, to evaluate the frequency. However, the discovered patterns do not always correspond to the interests of analysts, because the patterns are common and the analysts cannot get new knowledge from the patterns. The paper proposes a new criterion, namely, the sequential interestingness, to discover sequential patterns that are more attractive for the analysts. The paper shows that the criterion satisfies the Apriori property and how the criterion is related to the support. Also, the paper proposes an efficient sequential mining method based on the proposed criterion. Lastly, the paper shows the effectiveness of the proposed method by applying the method to two kinds of sequential data.

Keywords: Sequential mining, Support, Confidence, Apriori property

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2405 Development of a Support Tool for Cost and Schedule Integration Managment at Program Level

Authors: H. J. Yang, R. Z. Jin, I. J. Park, C. T. Hyun

Abstract:

There has been gradual progress of late in construction projects, particularly in big-scale megaprojects. Due to the long-term construction period, however, with large-scale budget investment, lack of construction management technologies, and increase in the incomplete elements of project schedule management, a plan to conduct efficient operations and to ensure business safety is required. In particular, as the project management information system (PMIS) is meant for managing a single project centering on the construction phase, there is a limitation in the management of program-scale businesses like megaprojects. Thus, a program management information system (PgMIS) that includes program-level management technologies is needed to manage multiple projects. In this study, a support tool was developed for managing the cost and schedule information occurring in the construction phase, at the program level. In addition, a case study on the developed support tool was conducted to verify the usability of the system. With the use of the developed support tool program, construction managers can monitor the progress of the entire project and of the individual subprojects in real time.

Keywords: Cost∙Schedule integration management, Supporting Tool, UI, WBS, CBS, introduce PgMIS (Program Management Information System), PMIS (Project Management Information System)

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2404 Privacy Issues in Pervasive Healthcare Monitoring System: A Review

Authors: Rusyaizila Ramli, Nasriah Zakaria, Putra Sumari

Abstract:

Privacy issues commonly discussed among researchers, practitioners, and end-users in pervasive healthcare. Pervasive healthcare systems are applications that can support patient-s need anytime and anywhere. However, pervasive healthcare raises privacy concerns since it can lead to situations where patients may not be aware that their private information is being shared and becomes vulnerable to threat. We have systematically analyzed the privacy issues and present a summary in tabular form to show the relationship among the issues. The six issues identified are medical information misuse, prescription leakage, medical information eavesdropping, social implications for the patient, patient difficulties in managing privacy settings, and lack of support in designing privacy-sensitive applications. We narrow down the issues and chose to focus on the issue of 'lack of support in designing privacysensitive applications' by proposing a privacy-sensitive architecture specifically designed for pervasive healthcare monitoring systems.

Keywords: Human Factors, Pervasive Healthcare, PrivacyIssues

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2403 Use of Personal Rhythm to Authenticate Encrypted Messages

Authors: Carlos Gonzalez

Abstract:

When communicating using private and secure keys, there is always the doubt as to the identity of the message creator. We introduce an algorithm that uses the personal typing rhythm (keystroke dynamics) of the message originator to increase the trust of the authenticity of the message originator by the message recipient. The methodology proposes the use of a Rhythm Certificate Authority (RCA) to validate rhythm information. An illustrative example of the communication between Bob and Alice and the RCA is included. An algorithm of how to communicate with the RCA is presented. This RCA can be an independent authority or an enhanced Certificate Authority like the one used in public key infrastructure (PKI).

Keywords: Personal rhythm, public-key encryption, authentication, digital signature, keystroke dynamics.

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2402 Electronic Government around the World: Key Information and Communication Technology Indicators

Authors: Isaac Kofi Mensah

Abstract:

Governments around the world are adopting Information and Communication Technologies (ICTs) because of the important opportunities it provides through E-government (EG) to modernize government public administration processes and delivery of quality and efficient public services. Almost every country in the world is adopting ICT in its public sector administration (EG) to modernize and change the traditional process of government, increase citizen engagement and participation in governance, as well as the provision of timely information to citizens. This paper, therefore, seeks to present the adoption, development and implementation of EG in regions globally, as well as the ICT indicators around the world, which are making EG initiatives successful. Europe leads the world in its EG adoption and development index, followed by the Americas, Asia, Oceania and Africa. There is a gradual growth in ICT indicators in terms of the increase in Internet access and usage, increase in broadband penetration, an increase of individuals using the Internet at home and a decline in fixed telephone use, while the mobile cellular phone has been on the increase year-on-year. Though the lack of ICT infrastructure is a major challenge to EG adoption and implementation around the world, in Africa it is very pervasive, hampering the expansion of Internet access and provision of broadband, and hence is a barrier to the successful adoption, development, and implementation of EG initiatives in countries on the continent. But with the general improvement and increase in ICT indicators around the world, it provides countries in Europe, Americas, Asia, Arab States, Oceania and Africa with the huge opportunity to enhance public service delivery through the adoption of EG. Countries within these regions cannot fail their citizens who desire to enjoy an enhanced and efficient public service delivery from government and its many state institutions.

Keywords: E-government development index, e-government, indicators, information and communication technologies.

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2401 Exploring the Availability and Distribution of Public Green Spaces among Riyadh Residential Neighborhoods

Authors: Abdulwahab Alalyani, Mahbub Rashid

Abstract:

Public green space promotes community health including daily activities, but these resources may not be available enough or may not equitably be distributed. This paper measures and compares the availability of public green spaces (PGS) among low, middle, and high-income neighborhoods in the Riyadh city. Additionally, it compares the total availability of PGS to WHO standard and Dubai availability of PGS per person. All PGS were mapped using geographical information systems, and total area availability of PGS compared to WHO and Dubai standards. To evaluate the significant differences in PGS availability across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences. As a result, by comparing PGS of Riyadh neighborhoods to WHO and Dubai-availability, it was found that Riyadh PGS were lower than the minimum standard of WHO and as well as Dubai. Riyadh has only 1.13 m2 per capita of PGS. The second finding, the availability of PGS, was significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of PGS should be focused on increasing PGS availability and should be given priority to those low-income and unhealthy communities.

Keywords: Spatial equity, green space, healthy city, quality of life, income, built environment.

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2400 Qualitative Profiling in Practice: The Italian Public Employment Services Experience

Authors: L. Agneni, F. Carta, C. Micheletta, V. Tersigni

Abstract:

The development of a qualitative method to profile jobseekers is needed to improve the quality of the Public Employment Services (PES) in Italy. This is why the National Agency for Active Labour Market Policies (ANPAL) decided to introduce a Qualitative Profiling Service in the context of the activities carried out by local employment offices’ operators. The qualitative profiling service provides information and data regarding the jobseeker’s personal transition status, through a semi-structured questionnaire administered to PES clients during the guidance interview. The questionnaire responses allow PES staff to identify, for each client, proper activities and policy measures to support jobseekers in their reintegration into the labour market. Data and information gathered by the qualitative profiling tool are the following: frequency, modalities and motivations for clients to apply to local employment offices; clients’ expectations and skills; difficulties that they have faced during the previous working experiences; strategies, actions undertaken and activated channels for job search. These data are used to assess jobseekers’ personal and career characteristics and to measure their employability level (qualitative profiling index), in order to develop and deliver tailor-made action programmes for each client. This paper illustrates the use of the above-mentioned qualitative profiling service on the national territory and provides an overview of the main findings of the survey: concerning the difficulties that unemployed people face in finding a job and their perception of different aspects related to the transition in the labour market. The survey involved over 10.000 jobseekers registered with the PES. Most of them are beneficiaries of the “citizens' income”, a specific active labour policy and social inclusion measure. Furthermore, data analysis allows classifying jobseekers into a specific group of clients with similar features and behaviours, on the basis of socio-demographic variables, customers' expectations, needs and required skills for the profession for which they seek employment. Finally, the survey collects PES staff opinions and comments concerning clients’ difficulties in finding a new job and also their strengths. This is a starting point for PESs’ operators to define adequate strategies to facilitate jobseekers’ access or reintegration into the labour market.

Keywords: Labour market transition, Public Employment Services, qualitative profiling, vocational guidance.

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2399 One-Class Support Vector Machines for Protein-Protein Interactions Prediction

Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

Abstract:

Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.

Keywords: Bioinformatics, Protein-protein interactions, One-Class Support Vector Machines

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2398 Globalization and Public Policy Analysis: A Case Study of Foreign Policy of ASEAN Member States

Authors: Nattapol Pourprasert

Abstract:

This study has an objective to analyze foreign policy of member states in globalization current, aiming to answer that the foreign policy of member states have been changed or remained the same and there are any factors affecting changing of foreign policy of the member states. From the study results, it is found that the foreign policy of Thailand is a friendly foreign policy with all states. The policy of Indonesia is more opened because of a change in leader, allowing more democratic development in the country; the government has proceeded with friendly foreign policy with the states in order to bring funds into the state. The foreign policy of Malaysia is not much changed as there is no changing in the leader; the policy of Malaysia has reconciled relations with main city of Indian and Chinese residing in the country in order to bring investments into the country and to relieve tensions in the country. The foreign policy of the Philippines has proceeded with policy under the ASEAN framework and emphasized on international Islam communities. The foreign policy of Singapore has the least changed as the Singapore's policy focuses on internal trade since the state was found. As for the foreign policy of Brunei Darussalam, Brunei has a little role in the international stage; the state having closest relationship as from the view of history is Singapore as the Singaporean has invested in retailing business in Brunei. The foreign policy of Vietnam has emphasized on an omnidirectional foreign policy in order to compete with several states in global stage. The foreign policy of Myanmar has proceeded with a friendly foreign policy with all ASEAN member states, the East-west Corridor transportation line from Myanmar through Thailand and Lao to Vietnam has been developed. As for the foreign policy of Lao, In 2001, the Thai government and Lao government held a discussion which Thailand reaffirmed the position not to support the anti-Lao group. The foreign policy of Cambodia has proceeded with more openness, having good relation with China, Russia and USA as these states has invested in the state, especially the US company.

Keywords: Globalization, Public Policy Analysis, Foreign Policy, ASEAN Member States.

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2397 Face Recognition with PCA and KPCA using Elman Neural Network and SVM

Authors: Hossein Esbati, Jalil Shirazi

Abstract:

In this paper, in order to categorize ORL database face pictures, principle Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) methods by using Elman neural network and Support Vector Machine (SVM) categorization methods are used. Elman network as a recurrent neural network is proposed for modeling storage systems and also it is used for reviewing the effect of using PCA numbers on system categorization precision rate and database pictures categorization time. Categorization stages are conducted with various components numbers and the obtained results of both Elman neural network categorization and support vector machine are compared. In optimum manner 97.41% recognition accuracy is obtained.

Keywords: Face recognition, Principal Component Analysis, Kernel Principal Component Analysis, Neural network, Support Vector Machine.

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2396 Supporting Technology Transfer with Communities and Social Software Solutions

Authors: G. Schuh, S. Aghassi

Abstract:

In order to bridge the gap between research and industry, promoting technology and knowledge transfer becomes increasingly important. Especially small- and medium-sized enterprises, having only little R&D resources themselves, depend on external technology development activities for remaining innovative. Academia research on the other hand needs potential industrial partners, who are capable and willing to commercialize their technologies as most public funding programs require some sort of technology transfer or dissemination activities. Modern web technologies offer more and more “social” functionalities and open up new ways of user interaction. In the past years several technology transfer platforms were developed, making use of modern web technologies in order to enable and support technology transfer. In this paper we report on the results of a state-of-the art analyses of existing technology transfer platforms, point out their advantages and deficits and give a perspective to the development of an improved technology transfer platform.

Keywords: Knowledge transfer, social software, technology management, technology transfer.

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2395 An Exact Solution to Support Vector Mixture

Authors: Monjed Ezzeddinne, Nicolas Lefebvre, Régis Lengellé

Abstract:

This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.

Keywords: Identification, Learning systems, Mixture ofExperts, Support Vector Machines.

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2394 Dissolved Oxygen Prediction Using Support Vector Machine

Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

Abstract:

In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, Water Temperature, and Conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: Dissolved oxygen, Water quality, predication DO, Support Vector Machine.

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2393 Decision Support System for a Pilot Flash Flood Early Warning System in Central Chile

Authors: D. Pinto, L. Castro, M.L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

Abstract:

Flash Floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: Decision Support System, Early Warning Systems, Flash Flood, Natural Hazard.

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2392 Comparison of Domain and Hydrophobicity Features for the Prediction of Protein-Protein Interactions using Support Vector Machines

Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

Abstract:

The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.

Keywords: Bioinformatics, protein-protein interactions, support vector machines, protein features.

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2391 Drug Combinations with Steroid Dispensing in Drugstores: A Study in the Center Area of Bangkok, Thailand

Authors: P. Thongmuang

Abstract:

The purposes of this research were 1) to survey the number of drugstores that unlawful dispense of asthma prescription drugs, in form of drug combinations in the Phaya Thai district of Bangkok, 2) to find the steroids contained in that drug combinations, 3) to find a means for informing general public about the dangers of drugs and for a campaign to stop dispensing them. Researcher collected drug combinations from 69 drugstores in Phaya Thai district from Feb 15, 2012 to Mar 15, 2012. The survey found 30.43%, 21, drug stores, sold asthma drug combinations to customers without a prescription. These collected samples were tested for steroid contamination by using Immunochromatography kits. Eleven samples, 52.38%, were found contaminated with steroids. In short, there should be control and inspection of drugstores in the distribution of steroid medications. To improve the knowledge of self health maintenance and drug usage among public, Thai Government and Department of Public Health should educate people about the side effects of using drug combinations and steroids.

Keywords: Dispensing, Drug Combinations, Steroids

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2390 Addressing Scalability Issues of Named Entity Recognition Using Multi-Class Support Vector Machines

Authors: Mona Soliman Habib

Abstract:

This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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2389 The Use Support Vector Machine and Back Propagation Neural Network for Prediction of Daily Tidal Levels along the Jeddah Coast, Saudi Arabia

Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati

Abstract:

Sea level rise threatens to increase the impact of future  storms and hurricanes on coastal communities. Accurate sea level  change prediction and supplement is an important task in determining  constructions and human activities in coastal and oceanic areas. In  this study, support vector machines (SVM) is proposed to predict  daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal  parameter values of kernel function are determined using a genetic  algorithm. The SVM results are compared with the field data and  with back propagation (BP). Among the models, the SVM is superior  to BPNN and has better generalization performance.

 

Keywords: Tides, Prediction, Support Vector Machines, Genetic Algorithm, Back-Propagation Neural Network, Risk, Hazards.

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2388 A Collaborative Platform for Multilingual Ontology Development

Authors: Ahmed Tawfik, Fausto Giunchiglia, Vincenzo Maltese

Abstract:

Ontologies provide a common understanding of a specific domain of interest that can be communicated between people and used as background knowledge for automated reasoning in a wide range of applications. In this paper, we address the design of multilingual ontologies following well-defined knowledge engineering methodologies with the support of novel collaborative development approaches. In particular, we present a collaborative platform which allows ontologies to be developed incrementally in multiple languages. This is made possible via an appropriate mapping between language independent concepts and one lexicalization per language (or a lexical gap in case such lexicalization does not exist). The collaborative platform has been designed to support the development of the Universal Knowledge Core, a multilingual ontology currently in English, Italian, Chinese, Mongolian, Hindi and Bangladeshi. Its design follows a workflow-based development methodology that models resources as a set of collaborative objects and assigns customizable workflows to build and maintain each collaborative object in a community driven manner, with extensive support of modern web 2.0 social and collaborative features.

Keywords: Knowledge Diversity, Knowledge Representation, Ontology Development.

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2387 Evaluation of the Quality of Education Offered to Students with Special Needs in Public Schools in the City of Bauru, Brazil

Authors: V. L. M. F. Capellini, A. P. P. M. Maturana, N. C. M. Brondino, M. B. C. L. B. M. Peixoto, A. J. Broughton

Abstract:

A paradigm shift is a process. The process of implementing inclusive education, a system constructed to support all learners, requires planning, identification, experimentation, and evaluation. In this vein, the purpose of the present study was to evaluate the capacity of one Brazilian state school systems to provide special education students with a quality inclusive education. This study originated at the behest of concerned families of students with special needs who filed complaints with the Municipality of Bauru, São Paulo. These families claimed, 1) children with learning differences and educational needs had not been identified for services, and 2) those who had been identified had not received sufficient specialized educational assistance (SEA) in schools across the City of Bauru. Hence, the Office of Civil Rights for the state of São Paulo (Ministério Público de São Paulo) summoned the local higher education institution, UNESP, to design a research study to investigate these allegations. In this exploratory study, descriptive data were gathered from all elementary and middle schools including 58 state schools and 17 city schools, for a total of 75 schools overall. Data collection consisted of each school's annual strategic action plan, surveys and interviews with all school stakeholders to determine their perceptions of the inclusive education available to students with Special Education Needs (SEN). The data were collected as one of four stages in a larger study which also included field observations of a focal students' experience and a continuing education course for all teachers and administrators in both state and city schools. For the purposes of this study, the researchers were interested in understanding the perceptions of school staff, parents, and students across all schools. Therefore, documents and surveys from 75 schools were analyzed for adherence to federal legislation guaranteeing students with SEN the right to special education assistance within the regular school setting. Results shows that while some schools recognized the legal rights of SEN students to receive special education, the plans to actually deliver services were absent. In conclusion, the results of this study revealed both school staff and families have insufficient planning and accessibility resources, and the schools have inadequate infrastructure for full-time support to SEN students, i.e., structures and systems to support the identification of SEN and delivery of services within schools of Bauru, SP. Having identified the areas of need, the city is now prepared to take next steps in the process toward preparing all schools to be inclusive.

Keywords: Inclusive education, special education, special needs.

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2386 Decision Support for the Selection of Electric Power Plants Generated from Renewable Sources

Authors: Aumnad Phdungsilp, Teeradej Wuttipornpun

Abstract:

Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society-s benefits of the electric power plant generation from different renewable sources. The multicriteria framework to multiattribute risk analysis technique and the decision analysis interview technique are applied in order to support the decisionmaking process for the implementing renewable energy projects to the Bangkok case study. Having analyses the local conditions and appropriate technologies, five renewable power plants are postulated as options. As this work demonstrates, the analysis can provide a tool to aid decision-makers for achieving targets related to promote sustainable energy system.

Keywords: Analytic Hierarchy Process, Bangkok, MultiattributeRisk Analysis, Renewable Energy Technology.

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2385 Civil Service Reforms in Kazakhstan and Its Influence on Modernization

Authors: Aliya Idrissova

Abstract:

Civil service (public administration) is an important social institution of society properties. Civil service institution had a significant impact on modernization processes in Kazakhstan through ensuring the functioning of all the subsystems of social life. This article is an attempt to analyze the reforms of public service institution in Kazakhstan and to assess its influence on modernization processes.

Keywords: Civil service, Kazakhstan, modernization, a national model of civil service, civil service reforms, bureaucracy.

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2384 A Dual Method for Solving General Convex Quadratic Programs

Authors: Belkacem Brahmi, Mohand Ouamer Bibi

Abstract:

In this paper, we present a new method for solving quadratic programming problems, not strictly convex. Constraints of the problem are linear equalities and inequalities, with bounded variables. The suggested method combines the active-set strategies and support methods. The algorithm of the method and numerical experiments are presented, while comparing our approach with the active set method on randomly generated problems.

Keywords: Convex quadratic programming, dual support methods, active set methods.

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