Now showing items 1-20 of 24

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    Adaptive Location Update Schemes for Continuous Cell Zooming Algorithm in Wireless Networks 

    Tun, Khin Cho; Kunagorn Kunavut (2015)

    Continuous cell zooming algorithm is a potential dynamic cell zooming algorithm for energy-efficient operation of mobile wireless networks. In this algorithm, location management strategy (location update process) is required to know the location of the farthest user in each cell to perform cell zooming. However, the application of conventional periodic update scheme in continuous cell zooming algorithm can lead to a high signaling cost. Therefore, in this paper, two adaptive location update schemes, namely, Time-Adaptive Periodic Update ...
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    Alternating Least Squares with Incremental Learning Bias 

    Aung, Than Htike; Rachsuda Jiamthapthaksin (2015)

    Recommender systems provide personalized suggestions for every individual user in the system. Many recommender systems use collaborative filtering approach in which the system collects and analyzes users' past behaviors, activities or preferences to produce high quality recommendations for the users. Among various collaborative recommendation techniques, model-based approaches are more scalable than memory-based approaches for large scale data sets in spite of large offline computation and difficulty to update the model in real time. In this ...
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    A Collaborative Filtering Recommendation Based on User Profile and User Behavior in Online Social Networks 

    Lu, Yang; Gopalakrishnan, Anilkumar Kothalil (2014)

    This paper aims to present and discuss the similarity among users in a social network based on CF (Collaborative Filtering) algorithm and SimRank (Similarity Based on Random Walk) algorithm. The CF algorithm used to predict the relationship between users based on the user rating on items (movies and books) and the user’s profile. The SimRank algorithm calculates the similarity among users through finding the nearest neighbors for each user in the social network. At last, the combination of these two algorithms will be used to get “people ...
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    Deletion and Selection Model for Test Case Selection 

    Adtha Lawanna; Jittima Wongwuttiwat; Benjawan Srisura (2016)

    Deletion and selection model is planned for improving the ability of selecting the relevant test cases of the modified programs by comparing the outcomes with the well-known traditional methods, which are random, dataflow, slicing, model based, code based, and coverage based analysis. This is because after adapting the programs for several times, numbers of test case will increase that can drop the whole performance of the new version. The problems are time consuming and producing bugs and other failures when using the updated software. The ...
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    Domain-oriented two-stage aggregation: generating baseball play-by-play narratives 

    Baldwin, James; Songsak Channarukul (2015)

    This paper presents an end-to-end natural language generation system that performs aggregation in two stages: the first takes advantage of the information implicit in the source knowledge base in order to aggregate event components into complex sentences. The second stage examines the developing context of the text in order to aggregate similar adjacent events into more fluent text. The source knowledge base is the Retrosheet collection of play-by-play baseball scoresheets encoded in machine-readable form. The output is reasonably fluent ...
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    The Effect of Transmission Range in Multi-hop Wireless Networks 

    Kunagorn Kunavut (2014)

    Transmission or communication range is an important factor for successful data delivery in wireless communications including multi-hop wireless networks. Typically, transmission range can be technically adjustable by configuring the transmitting power (Tx Power) or changing the antenna height. For the same antenna height, if transmission range is minimized or adjusted to be shorter by lowering Tx power, there is less energy consumption but the networks are likely to be unconnected which consequently degrades the network performance such ...
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    An Effective Model for Case-Based Maintenance in Cased-Based Reasoning Systems 

    Adtha Lawanna (2015-11)

    Case-based reasoning systems have been applied for machine learning, artificial intelligence, knowledge-based systems and other related fields in order to provide the right solution to the right problem regarding the four processes, which are the process to retrieve, reuse, revise, and retain cases. This paper focuses on the last process because it produces two main problems, which are the size of a case base increase and the ability of preserving the competency decreases. These critical issues are occurring when repeating the cycles of ...
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    An Effective Test Case Selection for Software Testing Improvement 

    Adtha Lawanna (2015-11)

    One problem of testing software is selecting the suitable test cases from the test suit regarding the size of the programs. If the size of selected test cases is big, then it can affect the whole performance of software development life cycle. Accordingly, it increases testing time and produce many bugs. Therefore, this paper proposes the improvement of software testing for selecting the appropriate and small number of test cases by considering the amounts of the functions modified, lines of code changed, and numbers of bugs produced after ...
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    Enhanced Fuzzy-based Handover Decision System Design for Wireless Mobile Networks 

    Thanachai Thumthawatworn; Piyakul Tillapart; Pratit Santiprabhob (2015)

    Numerous fuzzy-based algorithms have been suggested to enhance the intelligence of handover decision system for wireless mobile networks. However, most existing algorithms are based on a monolithic fuzzy engine design resulting in a large algorithm execution time, if a number of decision parameters is large and gives a poorer network selection performance, when dealing with different traffic types. In this paper, an enhanced fuzzy-based handover decision system design is proposed to address the above issues. The proposed design is presented ...
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    Experimental Study on Image Reconstruction from Spatial Correlation-based Optical Flow Motion Vector over Non Gaussian Noise Contamination using Reversed Confidential with Bilateral Filter 

    Darun Kesrarat; Vorapoj Patanavijit (2016)

    In motion estimation, noise is a verity to degrade the performance in optical flow for determining motion vector. This paper examines the performance of noise tolerance model in spatial correlation-based optical flow for image reconstruction from motion vector where the source sequences are contaminated by non Gaussian noise. There are Poisson Noise, Salt & Pepper Noise, and Speckle Noise. In the experiment, several standard sequences in different styles are used and the applied combination model of reversed confidential with bilateral ...
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    False Test Case Selection: Improvement of Regression Testing Approach 

    Benjawan Srisura; Adtha Lawanna (2016)

    Regression testing has been considered as a time-consumed process in software testing. In a recent year, one of interesting research work initiated for minimizing testing time is finding a technique in selecting test cases from a large test suit. Most of test cases selection technique in literature considers test cases that are related to the requirement's changed. During executing test cases that are related to the modified part, a set of fail test case is accidentally emerged and make test suit has become larger. Therefore, this paper proposes ...
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    Feature Envy Factor A Metric for Automatic Feature Envy Detection 

    Kwankamol Nongpong (2015)

    As a software system evolves, its design get deteriorated and the system becomes difficult to maintain. In order to improve such an internal quality, the system must be restructured without affecting its external behavior. The process involves detecting the design flaws (or code smells) and applying appropriate refactorings that could help remove such flaws. One of the design flaws in many object-oriented systems is placing members in the wrong class. This code smell is called Feature Envy and it is a sign of inappropriate coupling and ...
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    Intelligent Handover Decision Based on Fuzzy Logic for Heterogeneous Wireless Networks 

    Piyakul Tillapart; Thanachai Thumthawatworn; Piboonlit Viriyaphol; Pratit Santiprabhob (2015)

    An intelligent hand over decision system (HDS) is essential to heterogeneous wireless mobile networks in order to fulfill user's expectations in terms of universal and seamless services. With emerging real-time services in heterogeneous networking environment, including multiple QoS parameters in hand over decision process seems essential. In this paper, fuzzy logic is applied to enhance the intelligence of HDS. A new fuzzybased HDS design with the aim to reduce design complexity of fuzzy engine without sacrificing handover decision ...
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    License Plate Extraction and Recognition of a Thai Vehicle Based on MSER and BPNN 

    Tao, Hong; Gopalakrishnan, Anilkumar Kothalil (2015)

    The extraction and recognition of a Thai vehicle license plate based on Maximally Stable Extremal Regions (MSER) and Back-Propagation Neural Network (BPNN) is presented. The license plate area is in a maximally stable extremal region of a car image. It can be effectively extracted from MSERs by multiple classifications. The feature extraction of characters from the license plate is based on Zernike moment. The feature is used as a training dataset for the BPNN to recognize the characters. The experimental results indicate that the proposed ...
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    Multi-class Contour Preserving Classification 

    Piyabute Fuangkhon; Thitipong Tanprasert (2012-08)

    The 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 ...
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    Myanmar Paper Currency Recognition Using GLCM and k-NN 

    Hlaing, Khin Nyein Nyein; Gopalakrishnan, Anilkumar Kothalil (2016-01)

    Paper currency recognition depends on the currency note characteristics of a particular country. And the features extraction directly affects the recognition ability. Paper currency recognition is one of the important applications of pattern recognition. This paper aims to present a model for automatic classification of currency notes using k-Nearest Neighbor (k-NN) classifier that is the most important and simplest method in pattern recognition. The proposed model is based on textural feature such as Gray Level Co-occurrence Matrix ...
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    Optimizing Player Throughput for Interactive Motion Based Kiosk Games – A Case Study from the PTT Technobots Campaign 

    Pisal Setthawong (2015)

    Maintaining booths that are attractive to exhibition attendees is one of the main goals of exhibitors. One of the popular tactics to attract attention is to utilize new and emerging technology to create fresh new types of interactive booths, in which motion-based kiosk games are gaining popularity in this domain. However motion-based kiosk games are usually designed using conventional computer game design principles and are not optimized for exhibitions which results in a low player throughput. This paper examines the issues behind conventional ...
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    Performance and Comparative Analysis of Energy Consumption for Mobile Ad Hoc Routing Protocols 

    Kunagorn Kunavut (2014)

    Mobile ad hoc networks are energy-constrained networks, nodes in these networks are usually mobile and they are typically implemented in the specific areas where electrical power source is not available. Thus, the operations of these nodes must only rely on battery power or other exhaustible sources of energy. In addition, most of power in each node is required for communication with other nodes or gateway connected to the wired networks, this usually includes transmission of data and control overhead generated by ad hoc routing protocols ...
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    Performance Evaluation of Adaptive Rate Control over Uncompressed High-Definition Content Transmission with Paralleled Digital Subscriber Lines 

    Surasee Prahmkaew; Siriwhaddhanah Pongpadpinit; Piboonlit Viriyaphol; Chanintorn J.nukoon (2015)

    High-Definition (HD) information is the consumed bandwidth application in Telecommunication network. The quality of service (QoS) on uncompressed High-Definition content transmission with Paralleled Digital Subscriber Lines is needed in smooth information transmission and most tasks on QoS are served by each telecommunication network operator. The Adaptive Rate Control (ARC) is introduced and deployed on High-Definition (HD) contents transmitting on Paralleled Digital Subscriber Lines and compare with classical mechanism to provide more ...
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    Performance Evaluation of Dynamic Cell Zooming Algorithms in Omni-directional and Sector-based Cells 

    Tun, Khin Cho; Kunagorn Kunavut (2014)

    This paper evaluates and highlights the performance of three dynamic cell zooming algorithms applied in both omni-directional and sector-based networks. A possible framework compatible with dynamic cell zooming algorithms for user’s location detection is presented. The performance of each cell zooming algorithm is simulated in terms of power saving and possible outage in a full-day operation. According to simulated results, there is no significant difference between the performance of each algorithm and others at low traffic hours, but ...