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Item Energy Efficient Topology Control in Multi-hop Wireless Networks based on One-hop and Two-hop Neighbor Information(2016-07) Maw, Min Min Thet; Kunagorn KunavutTopology control in multi-hop wireless networks is a technique used to control nodes' activities to construct a topology with an acceptable level of network connectivity while minimizing energy consumption. It can be broadly classified into two main paradigms which are State Scheduling and Transmission Power Control. Both of them have received lots of attention from many researchers for decades. According to Transmission Power Control technique, most of them take into account only one-hop neighbor information to optimize transmission power and control topology in multi-hop wireless networks. In this paper, an energy efficient topology control based on both one-hop and two-hop neighbor information is proposed to reduce energy consumption without degrading network performances. A number of simulation scenarios are constructed in this work to study energy consumption as well as other network performances that are endto- end delay, throughput, and packet delivery ratio of the proposed algorithm.Item IT Design Skills Selection for Professional Development(2016-02)IT professionals in these days need to obtain multidisciplinary skill sets in order to succeed in their career. Design skill is considered as one of important characteristic for IT professionals. Many researches addressed design skill sets differently. This results in an increasing numbers of design skill items, in which some of those items have their meaning slightly different from each other. These long lists of design skill items can cause to long range of questionnaire. This study evaluates three techniques used for items selection which help reducing the number of skill items but with expect to remain their value within the selected items. The comparative studies used in this work are random selection, statistics selection, and effective coverage-based selection. The study found that the proposed technique provides the most satisfy result comparing to the other two techniques. According to this, the reduction rate by using this model is better than random and statistics algorithms about 47.83% and 34.78% respectively. Moreover, the percent coverage by using the proposed model is higher than the traditional methods approximately 13-26 %.Item Exploring the Effects of Openness to Experience and Theory of Consumption Values on Online Learning Adoption(2016-04) Watjatrakul, B.Personality traits and perceived product values are increasingly used to explain how people adopt innovative technologies. However, their relationships and effects on online learning adoption are ill-defined. This study investigates one of the common personality trait - openness to experience - and the value dimensions of theory of consumption values - functional (quality and monetary) value, social value, emotional value, epistemic value, and conditional value - to understand students’ intentions to adopt online learning. The study used a structural equation modelling technique (SEM) to analyze the data gathered from university students. The results indicate that students who are highly open to experience pay attention to monetary value and conditional value of online learning. Students, who perceived online learning as a quality method of learning (quality value), an interesting method of learning (emotional value), and an online learning community (social value), will have good intention to adopt online learning. Interestingly, the results contend that the five values of theory of consumption values are interrelated and contributed to online learning adoption differently. This study provides guidance to universities for planning and developing online courses/programs that will be considered valuable by students who are open to new experience leading to the increment in online learning students. The analysis results and implications for theory and practice are discussed. The paper concludes with the study limitations and directions for future studies.Item Dimension Independent Cosine Similarity for Collaborative Filtering using MapReduce(2016-02) Shen, Fei; Rachsuda JiamthapthaksinDIMSUM, an efficient and accurate all-pair similarity algorithm for real-world large scale dataset, tackles shuffle size problem of several similarity measures using MapReduce. The algorithm uses a sampling technique to reduce `power items' and preserves similarities. This paper presents an improved algorithm DIMSUM+ with a complex sampling technique to enhance DIMSUM so that it is able to further reduce `power users'. The algorithm generates k-nearest-neighbor matrix that are used in collaborative based Recommender systems. The evaluations of algorithm on MovieLens dataset with 1 million movie ratings and Yahoo! Music dataset with 700 million song ratings show significant improvement that DIMSUM+ outperforms DIMSUM at least 1.4x faster.Item A System for Popular Thai Slang Extraction from Social Media Content with N-Gram Based Tokenization (KST 2016)(2016-02) Rachsuda Jiamthapthaksin; Pisal Setthawong; Nitipan Ratanasawadwat; Assumption University. Martin de Tours School of Management and EconomicsWith increased penetration of smart devices and internet connectivity, many Thais are more readily engaged in social media, online forums, and chat groups. As there is an increased consumption of social media content, there is a shift from the consumption of traditional medias in which formal language are used regularly such as broadcast and traditional print medias. Social media posts are a reflection of the trend, where posts usually made by younger generations usually involve communication in slang and non-formal language which is not typically available in formalized dictionaries. As the Thai population like to follow trends, one of behaviors of that many Thai social media users engage in, is to follow the latest popular social media trends in slang and word usage. As slang are changed and evolved over time, it is usually useful to have an online mining tool in which could capture the trends of emerging and popular slang. This paper proposes an approach that extracts popular Thai slang by comparing social media posts and utilizing tokenization, a dictionary based approach to extract unknown words, before expanding it by using n-gram approach to figure what are currently trending and popular slang words.Item Clustering Analysis on Alumni Data Using Abandoned and Reborn Particle Swarm Optimization(2016-02) Paulus Mudjihartono; Thitipong Tanprasert; Rachsuda JiamthapthaksinAlumni data is one of the most important data that university management uses for developing the learning process decisions. This paper applies the idea of Abandoned and Reborn PSO (AR-PSO) to convert a clustering problem into the optimization form with an objective function to minimize the ugliness of the desired clusters. This algorithm of Clustering using AR-PSO (CAR-PSO) is slightly adapted to the cluster problem domain. The generated clusters need to be examined to decide if they are acceptable. There are three evaluations; the closeness, the separation and the purity. Finally, the experiment results show that the CAR-PSO is comparable with &-means in both types of alumni data while leaving the other two clustering algorithms.Item A Novel Adaptive Topology Control in Mobile Ad Hoc Networks based on Connectivity Index(2015-11) Kunagorn KunavutMobile ad hoc networks or MANETs are infrastructureless wireless networks where each node can freely move and directly connect to the other nodes located within its transmission range to form the topology in any arbitrary pattern. Hence, to ensure network connectivity, each node tends to use the maximum transmission power to extend its transmission range. However, this maximized transmission range typically consumes more energy and consequently drains battery faster on mobile devices in these networks. Topology control is an effective technique proposed in ad hoc networks to ensure network connectivity while reducing energy consumption to prolong operation lifetime. In this work, a novel technique is proposed for an adaptive topology control to allow each node to optimize its transmission range while obtaining the compromising level of network connectivity. This novel topology control can be effectively carried out by allowing nodes to maintain the predefined value of Connectivity Index (CI) which is a famous topological index used in the field of mathematic, physic, chemistry, biology and telecommunications.Item Distance measurement with smartphone using acceleration model of hand movement(2016-02) Eakawat Tantamjarik; Thitipong TanprasertThis paper proposes a novel method to obtain the displacement of a smartphone movement. The method utilizes genetic algorithm to synthesize a mathematical model of acceleration based on behavior of a person's hand movement from the raw acceleration data. Then, double integration is performed on the synthesized acceleration model, which is significantly less affected by the noise accumulation. The raw acceleration of the hand's movement is calibrated initially using acceleration-time graph analysis and a modified version of peak detection based on moving average is used to obtain the constraints for genetic algorithm. The obtained experiment results showed that the method is very effective at determining displacement with high accuracy.Item Multi-class contour preserving classification(2012-08) Piyabute Fuangkhon; Thitipong TanprasertThe original contour preserving classification technique was proposed to improve the robustness and weight fault tolerance of a neu- ral network applied with a two-class linearly separable problem. It was recently found to be improving the level of accuracy of two-class classi- fication. This paper presents an augmentation of the original technique to improve the level of accuracy of multi-class classification by better preservation of the shape or distribution model of a multi-class problem. The test results on six real world multi-class datasets from UCI ma- chine learning repository present that the proposed technique supports multi-class data and can improve the level of accuracy of multi-class classification more effectively.Item A Self-Growing and Self-Organizing Batch Map with Automatic Stopping Condition(2013) Kim, Se Won; To, Tang VanThis paper proposes a model of self-growing and self-organizing feature map designed to alleviate the difficulty of predetermining an appropriate size and shape of the feature map suitable for the input data in the applications of the Self-Organizing Map. The proposed model progressively builds a feature map by incremental growing of the network in a way that maintains two-dimensional regular grid structure and gradual adaptation of the reference vectors by coordinated competitive learning dynamics of the Batch Map algorithm. Experimental results based on iris data set and Italian olive oil data set show that the proposed model is effective in discovering an appropriate size and shape of the network grid to manifest a suitable feature map for the input data and that the resultant feature maps are comparable to feature maps produced by the standard SOM algorithm in their quality.Item AIDE-adaptive instructional design model for E-learning(2009-11) Thotsapon Sortrakul; Nida DenphaisarnToday, the new teaching and learning environment are changing because of an active usage of information technology. However, no matter how much technology becomes the essential element in learning, instructional designer has to consider the most appropriate methods to support an effective learning. The primary goal of instructional design is to guarantee the quality of online learning services by using technology-based instruction. In other words, the instructional design should be able to promote, facilitate, inspire deep learning and promote innovative students services through the active and engaging use of educational technologies. Instructional designers are those who evaluate learning needs, objectives and develop and effective delivery system (1) The AIDE (Advance Instructional Design Model for E-learning) is the framework which was developed in accordance with the ADDIE model and DISC behavior model. Its goal is to provide the educator with framework that can help them develop more effective e-learning system. The simulation of AIDE implementation is given and the prototype that simulate how to improve the system design by using AIDE also present in this report.Item Attitudes toward Using Communication Technologies in Education: A Comparative Study of Email and SMS(2009-12) Boonlert WatjatrakulEducational institutions deploy email and short message service (SMS) to maintain efficient communication with their students. This research examines factors influencing students' attitudes toward using SMS and email, and compares the differences in the proposed factors between email and SMS. The results show that information richness and mobility affect students' perceived utility of email and SMS while information privacy and perceived utility affect the students' attitudes toward using email and SMS. Social pressure has found no impact on the research model. Students also perceive that email provides rich information and utility higher that SMS but SMS possesses mobility more than email. In addition, students have attitudes toward using email more that SMS to maintain communication with their institutions. The paper concludes with a discussion of findings, implications and limitations.Item Diagnosing prostate cancer using backpropagation neural network and greedy decision procedure(2010-05) Gopalakrishnan, Anilkumar Kothalil; Thitipong Tanprasert; Faculty of Science and TechnologyA novel procedure for diagnosing prostate cancer (PC) based on Back propagation Neural Network (BPNN) is proposed. Elderly men with symptoms such as urinary retention, urinary hesitancy, urinary dribbling, burning urination, hematuria, etc. are considered as primary attributes. Prostate-specific antigen (PSA) level and Gleason score are the secondary attributes. Initial dataset is generated based on the clinical database. The BPNN assigns symptom levels of a set of patients based on their primary attributes. A greedy decision procedure predicts tumor stages of patients based on their strong symptom levels and secondary attributes. The simulation shows that the proposed procedure is an effective way for diagnosing prostate tumor stages.Item Self-similarity measurement using percentage of angle similarity on correlations of face objects(2009-07) Darun Kesrarat; Paitoon PorntrakoonA 2D face image can be used to search the self-similar images in the criminal database. This self-similar search can assist the human user to make the final decision among the retrieved images. In previous self-similar search, a 2D face image comprises of objects and object correlations. The attribute values of objects and their correlations are measured and stored in the face image database. The similarity percentage is specified to retrieve the self-similar images from the database. The problem of previous self-similar search is that the percentage of the angle differentiation among the objects in different part is different although their angle differentiation is exactly the same. The proposed model is introduced to improve the stability of the similarity percentage by reducing the number of face objects, object correlations, and the degree calculation. After testing over 100 samples, the proposed method illustrated that the stability of similarity percentage is improved especially for the left side objects of the face image.Item An incremental learning algorithm for supervised neural network with contour preserving Classification(2009-05) Piyabute Fuangkhon; Thitipong TanprasertThis paper presents an alternative algorithm for integrating the existing knowledge of a supervised learning neural network with the new training data. The algorithm allows the existing knowledge to age out in slow rate as a neural network is gradually retrained with consecutive sets of new samples, resembling the change of application locality under a consistent environment. The algorithm also utilizes the contour preserving classification algorithm to increase the accuracy of classification. The experiment is performed on 2-dimension partition problem and the result convincingly confirms the effectiveness of the algorithm.Item An Adaptive Learning Algorithm for Supervised Neural Network with Contour Preserving Classification(2009-11) Piyabute Fuangkhon; Thitipong TanprasertA study of noise tolerance characteristics of an adaptive learning algorithm for supervised neural network is presented in this paper. The algorithm allows the existing knowledge to age out in slow rate as a supervised neural network is gradually retrained with consecutive sets of new samples, resembling the change of application locality under a consistent environment. The algorithm utilizes the contour preserving classification algorithm to pre-process the training data to improve the classification and the noise tolerance. The experimental results convincingly confirm the effectiveness of the algorithm and the improvement of noise tolerance.Item Performance evaluation on multimedia traffic for DVB-RCS over satellite links(2009-12) Surasee PrahmkaewAdaptive Rate Control (ARC) is a successful algorithm to increase the throughput to The Digital View Broadcasting Return Channel via Satellite (DVB-RCS) but the throughput and dropped traffic did not meet the Quality of Service (QoS) for multimedia traffic standard [ETSI EN 300 421 v.1.1.2]. This paper will present the modified ARC algorithm to overcome the QoS problem for multimedia traffic by prioritize dropped traffic to retransmit as voice, video, and data through the system. This modified mechanism will guarantee a certain level of QoS to the end users. So Precedence Adaptive Rate Control (PARC) will be compared based on number of packet drop, mean queue time, and throughput with regular ARC mechanism. Finally we obtained the impressive results over PARC mechanism.Item Motion vector recovery for error concealment based on angular similarity(2009-07) Siriwhaddhanah PongpadpinitThis paper presents a motion vector (MV) recovery using the similarity of the angle of the corresponding surrounded MVs. The approach is based on the assumption that a group of macroblocks (MBs) which belongs to the same object and resides in the same region likely to move in the same direction. hence, those corresponded MVs that move in the same direction likely to have similar angle. As a result a lost motion vector can be estimated using a set of candidate MVs selected from the neighbouring MVs on the left, top-left, top, top-right, right, bottom-right, bottom and bottom-left. The experimental resuts for several test video sequences are compared with conventional error concealment methods and higher performance is achieved in both objective peak signal-to-noise ratio (PSNR) measurements and subjective visual quality.Item The impact of maketing communiation factors on consumers' purchasing decision of discout stores in Thailand(2009-12) Titida NochaiThe objective of this study is to investigate the marketing communication factors that impact on consumers' purchasing decision on discount store in Thailand. The multinomial logistic regression analysis was used and the attitude survey was conducted from 450 consumers have shopped among top three discount store operators: Tesco Lotus, Big C, and Carrefour. The results of this study show that the marketing communication factors in order to increase the customer base and make more market share in this segmentation. Tesco lotus should maintain a strategy about "Brochures and booklets" and "Sweepstakes" by distributing of brochures & booklets to customers continuously and include the sweepstakes in order to increase the customer base and still having an advantage over the competitors. Big C should maintain a strategy about "Events and Sponsorships" by supporting of the activities that joint to customer continuously in order to in order to increase potential in the competition in this discount store business. Carrefour should maintain a strategy about "Billboards", "Company websites", and "Weekly sale promotions by increasing of the number of billboards, update the company website continuously include developing of the website to attract theirs customers. Moreover, Carrefour should use the special sale promotion tools such as prices off, premiums, and point-of-purchase displays by weekly in order to attract.Item Applying logistic regression analysis: a study of the influential factors on consumers' purchasing decision toward mobile service provider in Bangkok, Thailand(2009-10) Titida NochaiLogistic regression analysis is one of multivariate analysis where the outcome of dependent variable is categorical variable and the independents are quantitative variables, categorical variables, or both. The objective of this study was to propose the application of logistic regression analysis in order to identify the influential factors on consumers' purchasing decision among top three mobile service providers in Thailand: Advanced Info Service Public Col, Ltd (AIS), Total Access communication Public Col, Ltd (DTAC), and True Corporation Public Col, Ltd (TRUE). The independent variables are the marketing mix factors: product, price, place and promotion. The results of this study indicate that influential factors that affect consumers' purchasing decision among three mobile service providers can be concluded as follows: There are product variety, launch new promotion often, easy to ask for new SIM card, have a bill payment via mobile, and convenient location to purchase that have an effect on consumers' purchasing decision on AIS. There are brand reputation, cost of using internet, and convenient location to purchase that have an effect on consumers' purchasing decision on DTAC. There are quality of signal, brand reputation, easy to change promotion, variety of VAS, and can check bill's history that have an effect on consumers' purchasing decision on TRUE. Moreover, it was found that the overall percent correctly predicted with logistic regression model seem moderating good at 51.9%. While the percent correctly classified for AIS, DTAC, and TRUE are 54.7%, 43.6%, and 57.3% respectively. This indicates that logistic regression analysis can give an accurate prediction of probabilities on the dependent outcome.