Search results for: Data Collection

Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed where located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urban area in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recent years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood events in 2013 as the worst studied case for all those communities in this municipality. Moreover, other problems are also faced in this watershed, such shortage water supply for domestic consumption and agriculture utilizations including a deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of the appropriated application of some short period rainfall forecasting model as they aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in a short period of 7-10 days in advance during rainy season instead of real time record. The IDV product can be present in an advance period of rainfall with time step of 3-6 hours was introduced to the communities. The result can be used as input data to the hydrologic modeling system model (HEC-HMS) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as the water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at the dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfying. The product of rainfall from IDV was fair while compared with observed data. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: Global rainfall, flood forecasting, hydrologic modeling system, river analysis system.

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Authors: H. Baazaoui Zghal, S. Faiz, H. Ben Ghezala

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Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented.

Keywords: Databases, data mining, multi-agent, spatial datamart.

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Authors: Jenny Hall, Alison Jaquet

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Universities’ push toward the production of high quality research is not limited to academic staff and experienced researchers. In this environment of research rich agendas, Higher Degree Research (HDR) students are increasingly expected to engage in the publishing of good quality papers in high impact journals. IFN001: Advanced Information Research Skills (AIRS) is a credit bearing mandatory coursework requirement for Queensland University of Technology (QUT) doctorates. Since its inception in 1989, this unique blended learning program has provided the foundations for new researchers to produce original and innovative research. AIRS was redeveloped in 2012, and has now been evaluated with reference to the university’s strategic research priorities. Our research is the first comprehensive evaluation of the program from the learner perspective. We measured whether the program develops essential transferrable skills and graduate capabilities to ensure best practice in the areas of publishing and data management. In particular, we explored whether AIRS prepares students to be agile researchers with the skills to adapt to different research contexts both within and outside academia. The target group for our study consisted of HDR students and supervisors at QUT. Both quantitative and qualitative research methods were used for data collection. Gathering data was by survey and focus groups with qualitative responses analyzed using NVivo. The results of the survey show that 82% of students surveyed believe that AIRS assisted their research process and helped them learn skills they need as a researcher. The 18% of respondents who expressed reservation about the benefits of AIRS were also examined to determine the key areas of concern. These included trends related to the timing of the program early in the candidature and a belief among some students that their previous research experience was sufficient for postgraduate study. New insights have been gained into how to better support HDR learners in partnership with supervisors and how to enhance learning experiences of specific cohorts, including international students and mature learners.

Keywords: Data management, enhancing learning experience, publishing, research higher degree students.

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Authors: Jian-hua Yeh, Shi-yi Kuo

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This paper discusses the classification process for medical data. In this paper, we use the data from ACM KDDCup 2008 to demonstrate our classification process based on latent topic discovery. In this data set, the target set and outliers are quite different in their nature: target set is only 0.6% size in total, while the outliers consist of 99.4% of the data set. We use this data set as an example to show how we dealt with this extremely biased data set with latent topic discovery and noise reduction techniques. Our experiment faces two major challenge: (1) extremely distributed outliers, and (2) positive samples are far smaller than negative ones. We try to propose a suitable process flow to deal with these issues and get a best AUC result of 0.98.

Keywords: classification, latent topics, outlier adjustment, feature scaling

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Authors: Srikiat Anansawat, Pitsamai Ubonsri

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The purpose of this study was to study postpartum breastfeeding mothers to determine the impact their psychosocial and spiritual dimensions play in promoting full-term (6 month duration) breastfeeding of their infants. Purposive and snowball sampling methods were used to identify and recruit the study's participants. A total of 23 postpartum mothers, who were breastfeeding within 6 weeks after giving birth, participated in this study. In-depth interviews combined with observations, participant focus groups, and ethnographic records were used for data collection. The Data were then analyzed using content analysis and typology. The results of this study illustrated that postpartum mothers experienced fear and worry that they would lack support from their spouse, family and peers, and that their infant would not get enough milk It was found that the main barrier mothers faced in breastfeeding to full-term was the difficulty of continuing to breastfeed when returning to work. 81.82% of the primiparous mothers and 91.67% of the non-primiparous mothers were able to breastfeed for the desired full-term of 6 months. Factors found to be related to breastfeeding for six months included 1) belief and faith in breastfeeding, 2) support from spouse and family members, 3) counseling from public health nurses and friends. The sample also provided evidence that religious principles such as tolerance, effort, love, and compassion to their infant, and positive thinking, were used in solving their physical, mental and spiritual problems.

Keywords: health promotion, mental health, spiritual health, breastfeeding

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Authors: Md Tasbirul Islam, Pablo Dias, Nazmul Huda

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E-waste/Waste electrical and electronic equipment (WEEE) is one of the fastest growing waste streams across the globe. This paper aims to compare the e-waste management system in Switzerland and Australia in terms of four features - legislative initiatives, disposal practice, collection and financial mechanisms. The qualitative content analysis is employed as a research method in the study. Data were collected from various published academic research papers, industry reports, and web sources. In addition, a questionnaire survey is conducted in Australia to understand the public awareness and opinions on the features. The results of the study provide valuable insights to policymakers in Australia developing better e-waste management system in conjunction with the public consensus, and the state-of-the-art operational strategies currently being practiced in Switzerland.

Keywords: E-waste management, WEEE, awareness, pro-environmental behavior, Australia, Switzerland.

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Authors: N. Paparisteidi, D. Rodamitou

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This article focuses on the skills development and path planning of students studying computer science at EPITECH: French private institute of higher education. We examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: Active learning, blended learning, higher education, skills development.

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Authors: J. D. D. Daniel, K. N. Goh, S. M. Yusop

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Trends in business intelligence, e-commerce and remote access make it necessary and practical to store data in different ways on multiple systems with different operating systems. As business evolve and grow, they require efficient computerized solution to perform data update and to access data from diverse enterprise business applications. The objective of this paper is to demonstrate the capability of DTS [1] as a database solution for automatic data transfer and update in solving business problem. This DTS package is developed for the sales of variety of plants and eventually expanded into commercial supply and landscaping business. Dimension data modeling is used in DTS package to extract, transform and load data from heterogeneous database systems such as MySQL, Microsoft Access and Oracle that consolidates into a Data Mart residing in SQL Server. Hence, the data transfer from various databases is scheduled to run automatically every quarter of the year to review the efficient sales analysis. Therefore, DTS is absolutely an attractive solution for automatic data transfer and update which meeting today-s business needs.

Keywords: Data Transformation Services (DTS), ObjectLinking and Embedding Database (OLEDB), Data Mart, OnlineAnalytical Processing (OLAP), Online Transactional Processing(OLTP).

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Authors: P. S. Hiremath, Siddu P. Algur

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With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.

Keywords: Web data records, web data regions, web mining.

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Authors: H. W. Ker

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Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance.

Keywords: Data exploration, exploratory analysis, HLMs/LMEs, longitudinal data, visual-graphical methods.

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Authors: H. Ahmad, S. Kermanshahani, A. Simonet, M. Simonet

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The data exchanged on the Web are of different nature from those treated by the classical database management systems; these data are called semi-structured data since they do not have a regular and static structure like data found in a relational database; their schema is dynamic and may contain missing data or types. Therefore, the needs for developing further techniques and algorithms to exploit and integrate such data, and extract relevant information for the user have been raised. In this paper we present the system OSIX (Osiris based System for Integration of XML Sources). This system has a Data Warehouse model designed for the integration of semi-structured data and more precisely for the integration of XML documents. The architecture of OSIX relies on the Osiris system, a DL-based model designed for the representation and management of databases and knowledge bases. Osiris is a viewbased data model whose indexing system supports semantic query optimization. We show that the problem of query processing on a XML source is optimized by the indexing approach proposed by Osiris.

Keywords: Data integration, semi-structured data, views, XML.

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: Startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship.

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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Authors: Minsoo Lee, Yearn Jeong Kim, Yun-mi Kim, Sujeung Cheong, Sookyung Song

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Bio-chips are used for experiments on genes and contain various information such as genes, samples and so on. The two-dimensional bio-chips, in which one axis represent genes and the other represent samples, are widely being used these days. Instead of experimenting with real genes which cost lots of money and much time to get the results, bio-chips are being used for biological experiments. And extracting data from the bio-chips with high accuracy and finding out the patterns or useful information from such data is very important. Bio-chip analysis systems extract data from various kinds of bio-chips and mine the data in order to get useful information. One of the commonly used methods to mine the data is classification. The algorithm that is used to classify the data can be various depending on the data types or number characteristics and so on. Considering that bio-chip data is extremely large, an algorithm that imitates the ecosystem such as the ant algorithm is suitable to use as an algorithm for classification. This paper focuses on finding the classification rules from the bio-chip data using the Ant Colony algorithm which imitates the ecosystem. The developed system takes in consideration the accuracy of the discovered rules when it applies it to the bio-chip data in order to predict the classes.

Keywords: Ant Colony System, DNA chip data, Classification.

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Authors: Nicole M. Martino

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Reinforced concrete bridge deck condition assessments primarily use visual inspection methods, where an inspector looks for and records locations of cracks, potholes, efflorescence and other signs of probable deterioration. Sounding is another technique used to diagnose the condition of a bridge deck, however this method listens for damage within the subsurface as the surface is struck with a hammer or chain. Even though extensive procedures are in place for using these inspection techniques, neither one provides the inspector with a comprehensive understanding of the internal condition of a bridge deck – the location where damage originates from.  In order to make accurate estimates of repair locations and quantities, in addition to allocating the necessary funding, a total understanding of the deck’s deteriorated state is key. The research presented in this paper collected infrared thermography and ground penetrating radar data from reinforced concrete bridge decks without an asphalt overlay. These decks were of various ages and their condition varied from brand new, to in need of replacement. The goals of this work were to first verify that these nondestructive evaluation methods could identify similar areas of healthy and damaged concrete, and then to see if combining the results of both methods would provide a higher confidence than if the condition assessment was completed using only one method. The results from each method were presented as plan view color contour plots. The results from one of the decks assessed as a part of this research, including these plan view plots, are presented in this paper. Furthermore, in order to answer the interest of transportation agencies throughout the United States, this research developed a step-by-step guide which demonstrates how to collect and assess a bridge deck using these nondestructive evaluation methods. This guide addresses setup procedures on the deck during the day of data collection, system setups and settings for different bridge decks, data post-processing for each method, and data visualization and quantification.

Keywords: Bridge deck deterioration, ground penetrating radar, infrared thermography, NDT of bridge decks.

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Authors: Klaus Stranacher, Vesna Krnjic, Thomas Zefferer

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The public sector holds large amounts of data of various areas such as social affairs, economy, or tourism. Various initiatives such as Open Government Data or the EU Directive on public sector information aim to make these data available for public and private service providers. Requirements for the provision of public sector data are defined by legal and organizational frameworks. Surprisingly, the defined requirements hardly cover security aspects such as integrity or authenticity. In this paper we discuss the importance of these missing requirements and present a concept to assure the integrity and authenticity of provided data based on electronic signatures. We show that our concept is perfectly suitable for the provisioning of unaltered data. We also show that our concept can also be extended to data that needs to be anonymized before provisioning by incorporating redactable signatures. Our proposed concept enhances trust and reliability of provided public sector data.

Keywords: Trusted Public Sector Data, Integrity, Authenticity, Reliability, Redactable Signatures.

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Authors: Agneta Sundström, Zahra Ahmadi, Akmal Hyder

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The purpose of this paper is to develop a typology based on market orientation (MO) and innovation orientation (IO), and to illustrate to what extent housing companies in Sweden fit within this framework. A qualitative study on 11 public housing companies in the central part of Sweden has been conducted by the help of open and semi-structured questions for data collection. Four public housing company types- i.e. reactive prospector, proactive prospector, reactive defender and proactive defender have been identified by the combination of MO-IO dimensions. Future research can include other dimensions like entrepreneurship and network to observe how it particularly affects MO. An empirical study can compare public and private housing companies on the basis of MO and IO dimensions. One major contribution of the paper is the proposition of typology which can be used to describe public housing companies and deciding their future course of actions.

Keywords: Customer-led, economy, innovativeness, market orientation.

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Authors: Ekachai Phaisangittisagul, Rapeepol Chongprachawat

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Obtaining labeled data in supervised learning is often difficult and expensive, and thus the trained learning algorithm tends to be overfitting due to small number of training data. As a result, some researchers have focused on using unlabeled data which may not necessary to follow the same generative distribution as the labeled data to construct a high-level feature for improving performance on supervised learning tasks. In this paper, we investigate the impact of the relationship between unlabeled and labeled data for classification performance. Specifically, we will apply difference unlabeled data which have different degrees of relation to the labeled data for handwritten digit classification task based on MNIST dataset. Our experimental results show that the higher the degree of relation between unlabeled and labeled data, the better the classification performance. Although the unlabeled data that is completely from different generative distribution to the labeled data provides the lowest classification performance, we still achieve high classification performance. This leads to expanding the applicability of the supervised learning algorithms using unsupervised learning.

Keywords: Autoencoder, high-level feature, MNIST dataset, selftaught learning, supervised learning.

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Authors: A. S. Haruna, M. U. Tambawal, A. A. Salawu

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The psychological impact of peer influence on its individual group members, can make them resist HIV/AIDS counselling and testing. This study investigated the correlate of peer influence and resistance to HIV/AIDS counselling and testing among students in tertiary institutions in Kano state, Nigeria. To achieve this, three null hypotheses were postulated and tested. Cross- Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841.Simple Random Sampling was used in the selection. A self-developed 20-item scale called Peer Influence and Psychological Resistance Inventory (PIPRI) was used for data collection. Pearson Product Moment Correlation (PPMCC) via test-retest method was applied to estimate a reliability coefficient of 0.86 for the scale. Data obtained was analyzed using t-test and PPMCC at 0.05 level of confidence. Results reveal 26.3% (397) of the respondents being influenced by their peer group, while 39.8% showed resistance. Also, the t-tests and PPMCC statistics were greater than their respective critical values. This shows that there was a significant gender difference in peer influence and a difference between peer influence and resistance to HIV/AIDS counselling and testing. However, a positive relationship between peer influence and resistance to HIV/AIDS counselling and testing was shown. A major recommendation offered suggests the use of reinforcement and social support for positive attitudes and maintenance of safe behaviour among students who patronize HIV/AIDS counselling.

Keywords: Peer influence, HIV/AIDS counselling and testing, Resistance.

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Authors: M. Klimavicius

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This paper proposes a modeling methodology for the development of data analysis solution. The Author introduce the approach to address data warehousing issues at the at enterprise level. The methodology covers the process of the requirements eliciting and analysis stage as well as initial design of data warehouse. The paper reviews extended business process model, which satisfy the needs of data warehouse development. The Author considers that the use of business process models is necessary, as it reflects both enterprise information systems and business functions, which are important for data analysis. The Described approach divides development into three steps with different detailed elaboration of models. The Described approach gives possibility to gather requirements and display them to business users in easy manner.

Keywords: Data warehouse, data analysis, business processmanagement.

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Authors: Waralak Vongdoiwang Siricharoen, Nattanun Siricharoen

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The objectives of this study are to determine the role of media that influence the values, attitudes and behaviors of Thai youths. Analytical qualitative research techniques were used for this purpose. Data collection based techniques was used which were individual interviews and focus group discussions with journalists, sample of high school and university students, and parents. The results show that “Social Media" is still the most popular media for Thai youths. It is also still in the hands of the marketing business and it can motivate Thai youths to do so many things. The main reasons of media exposure are to find quality information that they want quickly, get satisfaction and can use social media to get more exciting and to build communities. They believe that the need for media and information literacy skills is defined as making judgments, personal integrity, training of family and the behavior of close friends.

Keywords: Media and Information Literacy, Making Judgments, Personal integrity, Behavior of close friends

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Authors: Muslihah Wook, Zawiyah M. Yusof, Mohd Zakree Ahmad Nazri

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Data mining has been integrated into application systems to enhance the quality of the decision-making process. This study aims to focus on the integration of data mining technology and Knowledge Management System (KMS), due to the ability of data mining technology to create useful knowledge from large volumes of data. Meanwhile, KMS vitally support the creation and use of knowledge. The integration of data mining technology and KMS are popularly used in business for enhancing and sustaining organizational performance. However, there is a lack of studies that applied data mining technology and KMS in the education sector; particularly students- academic performance since this could reflect the IHL performance. Realizing its importance, this study seeks to integrate data mining technology and KMS to promote an effective management of knowledge within IHLs. Several concepts from literature are adapted, for proposing the new integrative data mining technology and KMS framework to an IHL.

Keywords: Data mining, Institutions of Higher Learning, Knowledge Management System, Students' academic performance.

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data of the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as «signaling parameters» (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of COTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources, but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as rule. This report contains describing of the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems.

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Authors: Mohamed Elkholy, Ahmed Elfatatry

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Cloud computing has emerged as a flexible computing paradigm that reshaped the Information Technology map. However, cloud computing brought about a number of security challenges as a result of the physical distribution of computational resources and the limited control that users have over the physical storage. This situation raises many security challenges for data integrity and confidentiality as well as authentication and access control. This work proposes a security mechanism for data integrity that allows a data owner to be aware of any modification that takes place to his data. The data integrity mechanism is integrated with an extended Kerberos authentication that ensures authorized access control. The proposed mechanism protects data confidentiality even if data are stored on an untrusted storage. The proposed mechanism has been evaluated against different types of attacks and proved its efficiency to protect cloud data storage from different malicious attacks.

Keywords: Access control, data integrity, data confidentiality, Kerberos authentication, cloud security.

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Authors: W. Katsarapong, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

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National Biodiversity Database System (NBIDS) has been developed for collecting Thai biodiversity data. The goal of this project is to provide advanced tools for querying, analyzing, modeling, and visualizing patterns of species distribution for researchers and scientists. NBIDS data record two types of datasets: biodiversity data and environmental data. Biodiversity data are specie presence data and species status. The attributes of biodiversity data can be further classified into two groups: universal and projectspecific attributes. Universal attributes are attributes that are common to all of the records, e.g. X/Y coordinates, year, and collector name. Project-specific attributes are attributes that are unique to one or a few projects, e.g., flowering stage. Environmental data include atmospheric data, hydrology data, soil data, and land cover data collecting by using GLOBE protocols. We have developed webbased tools for data entry. Google Earth KML and ArcGIS were used as tools for map visualization. webMathematica was used for simple data visualization and also for advanced data analysis and visualization, e.g., spatial interpolation, and statistical analysis. NBIDS will be used by park rangers at Khao Nan National Park, and researchers.

Keywords: GLOBE protocol, Biodiversity, Database System, ArcGIS, Google Earth and webMathematica.

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Authors: Seo Young Kim, Toshimitsu Hamasaki

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Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.

Keywords: Gene expression, clustering, data preprocessing.

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Authors: Cathy SW. Chow, Kristina Shin, Faming Wang, B. C. L. So

Abstract:

During some dynamic giant puppet performances, an ergonomically designed load carrier system is necessary for the puppeteers to carry a giant puppet body’s heavy load with minimum muscle stress. A load carrier (i.e. prototype) was designed with two small wheels on the foot; and a hybrid spring device on the knee in order to assist the sliding and knee bending movements respectively. Thus, the purpose of this study was to evaluate the effect of three load carriers including two other commercially available load mounting systems, Tepex and SuitX, and the prototype. Ten male participants were recruited for the experiment. Surface electromyography (sEMG) was used to collect the participants’ muscle activities during forward moving and bouncing and with and without load of 11.1 kg that was 60 cm above the shoulder. Five bilateral muscles including the lumbar erector spinae (LES), rectus femoris (RF), bicep femoris (BF), tibialis anterior (TA), and gastrocnemius (GM) were selected for data collection. During forward moving task, the sEMG data showed smallest muscle activities by Tepex harness which exhibited consistently the lowest, compared with the prototype and SuitX which were significantly higher on left LES 68.99% and 64.99%, right LES 26.57% and 82.45%; left RF 87.71% and 47.61%, right RF 143.57% and 24.28%; left BF 80.21% and 22.23%, right BF 96.02% and 21.83%; right TA 6.32% and 4.47%; left GM 5.89% and 12.35% respectively. The result above reflected mobility was highly restricted by tested exoskeleton devices. On the other hand, the sEMG data from bouncing task showed the smallest muscle activities by prototype which exhibited consistently the lowest, compared with the Tepex harness and SuitX which were significantly lower on lLES 6.65% and 104.93, rLES 23.56% and 92.19%; lBF 33.21% and 93.26% and rBF 24.70% and 81.16%; lTA 46.51% and 191.02%; rTA 12.75% and 125.76%; IGM 31.54% and 68.36%; rGM 95.95% and 96.43% respectively.

Keywords: Exoskeleton, load carriage aid, giant puppet performers, electromyography.

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Authors: Dinh-Ha Tran, Chung-Ruey Yen, Yu-Kuang H. Chen

Abstract:

A collection of thirty cultivars/clones of a red pitaya was used to investigate flowering response to lighting supplementation in the winter season of 2013-2014 in southern Taiwan. The night-breaking treatment was conducted during the period of 10 Oct. 2013 to 5 Mar. 2014 with 4-continuous hours (22.00 – 02.00 hrs) of additional lighting daily using incandescent bulbs (100W). Among cultivars and clones tested, twenty-three genotypes, most belonging to the red-magenta flesh type, were found to have positively flowering response to the lighting treatment. The duration of night-breaking treatment for successful flowering initiation varied from 33- 48 days. The lighting-sensitive genotypes bore 1-2 flowering flushes. Floral and fruiting stages took 21-26 and 46-59 days, respectively. Among sixteen fruiting genotypes, the highest fruit set rates were found in Damao 9, D4, D13, Chaozou large, Chaozhou 5, Small Nick and F22. Five cultivars and clones (Orejona, D4, Chaozhou large, Chaozhou 5 and Small Nick) produced fruits with an average weight of more than 300 g per fruit which were higher than those of the fruits formed in the summer of 2013. Fruits produced during off-season containing total soluble solids (TSS) from 17.5 to 20.7oBrix, which were higher than those produced inseason.

Keywords: Flowering response, long-day plant, night-breaking treatment, off-season production, pitaya.

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Authors: Marinela Mircea

Abstract:

The development of information and communication technology, the increased use of the internet, as well as the effects of the recession within the last years, have lead to the increased use of cloud computing based solutions, also called on-demand solutions. These solutions offer a large number of benefits to organizations as well as challenges and risks, mainly determined by data visualization in different geographic locations on the internet. As far as the specific risks of cloud environment are concerned, data security is still considered a peak barrier in adopting cloud computing. The present study offers an approach upon ensuring the security of cloud data, oriented towards the whole data life cycle. The final part of the study focuses on the assessment of data security in the cloud, this representing the bases in determining the potential losses and the premise for subsequent improvements and continuous learning.

Keywords: cloud computing, data life cycle, data security, security assessment.

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Authors: Warunpun Kongsom, Chaiwat Kongsom

Abstract:

The objective of this study was to investigate the awareness, knowledge and consumer behavior towards organic products in Thailand. For this study, a purposive sampling technique was used to identify a sample group of 2,575 consumers over the age of 20 years who intended or made purchases from 1) green shops; 2) supermarkets with branches; and, 3) green markets. A questionnaire was used for data collection across the country. Descriptive statistics were used for data analysis. The results showed that more than 92% of consumers were aware of organic agriculture, but had less knowledge about it. More than 60% of consumers knew that organic agriculture production and processing did not allow the use of chemicals. And about 40% of consumers were confused between the food safety logo and the certified organic logo, and whether GMO was allowed in organic agriculture practice or not. In addition, most consumers perceived that organic agricultural products, good agricultural practice (GAP) products, agricultural chemicals free products, and hydroponic vegetable products had the same standard. In the view of organic consumers, the organic Thailand label was the most seen and reliable among various organic labels. Less than 3% of consumers thought that the International Federation of Organic Agriculture Movements (IFOAM) Global Organic Mark (GOM) was the most seen and reliable. For the behaviors of organic consumers, they purchased organic products mainly at the supermarket and green shop (55.4%), one to two times per month, and with a total expenditure of about 200 to 400 baht each time. The main reason for buying organic products was safety and free from agricultural chemicals. The considered factors in organic product selection were price (29.5%), convenience (22.4%), and a reliable certification system (21.3%). The demands for organic products were mainly rice, vegetables and fruits. Processed organic products were relatively small in quantity.

Keywords: Consumer behavior, consumer knowledge, organic products, Thailand.

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