bluuebunny/crossref_metadata_2025 huggingface dataset:
Confidential Enhancement with Multi-Code Keying Reconfiguration over TS/WH OCDMA Networks
Authors: Chang Yao Tang
Published: March 2013

In order to overcome the vulnerability to eavesdropping on-off-keying based OCDMA scheme, a new multi-code keying reconfiguration is presented to enhance confidentiality over two dimensional time-spreading and wavelength-hopping (2D TS/WH) optical code division multiple access (OCDMA) schemes. The time-shifted carrier-hopping prime codes (CHPCs) are proposed and assigned as signature address code. This proposed scheme provides the integration of electronic and optical layer domain, which inherently comes from the data encryption and spectrum-spreading of the transmitted signals, and then achieves data-confidential enhancement in synchronous networks. Moreover, multi-code keying reconfiguration in a set of distinct codeword is assigned to individual user and random selection by using thin film filter, tunable delay line and optical switch. Here, the probability of interception performance in terms of various multi-code key numbers per user is analyzed. The result shows that the confidentiality is enhanced to combat against eavesdropping while signature address code number per user is increased in proposed multi-code key reconfiguration scheme.
Distributed TXOP Allocation Scheme in IEEE 802.11e Wireless LANs
Authors: Kim Sunmyeng
Published: March 2013

Multimedia traffic is expected to be one of the most important traffic types in wireless LANs. However, multimedia traffic is very sensitive to delay so that the traffic has to be transmitted to receivers within its delay bound. The IEEE 802.11e EDCA (Enhanced Distributed Channel Access) defines a TXOP (Transmission Opportunity) parameter to provide service differentiation and QoS (Quality of Service) of the traffic. A station can continuously transmit multiple packets for the duration of a TXOP. When stations support multimedia applications with different QoS requirements, fairness problem occurs. In order to alleviate the fairness problem, we propose a distributed TXOP allocation scheme based on the delay bound. In the proposed scheme, a station checks the delay bound of each data packet in the queue, and allocates its TXOP value to guarantee the delay bounds of all the packets in the queue. Simulation results show that the proposed scheme outperforms other TXOP allocation schemes.
Dry Machining of T6061 Aluminium Alloy Using Titanium Nitride (TiN) and Titanium Carbonitride (TiCN) Coated Tools
Authors: Ariff Tasnim Firdaus , Paimin Muhamad Fahmie , Hassan Abdirahman
Published: March 2013

Dry machining is a clean machining process and it will be considered as a necessity for manufacturing industries in future. Dry machining is environmental friendly and safe to be performed. Regardless of decreasing tool life due to lack of lubricants, choosing dry machining over wet machining may be a wiser choice since the cost of purchasing and disposing the cutting fluids can contribute to a higher cost. Tool wear intensities of TiN and TiCN coated tools using both dry and traditional wet machining was studied with the aim in finding the optimum cutting speed from three different cutting speeds (318, 394 and 490 m/min) with a feed rate of 0.6 mm/rev and depth of cut of 0.4 mm. Tool tip temperature was also analyzed to see the effect of temperature rise at the tool-chip interface. TiCN coated tool performed better than TiN coated tool since the wear rate for TiCN coated tool is smaller by 40-48 % when compared to TiN coated tool for dry machining for all three cutting speeds. The optimum cutting speed for dry machining of T6061 Aluminium alloy using TiN and TiCN coated tools is 394 m/min. Tool tip temperature for dry machining is also slightly higher than wet machining by 19 and 32 % for TiN and TiCN coated tools respectively at the optimum cutting speed. Dry machining of T6061 Aluminium alloy can be a more suitable eco-friendly machining process particularly at high cutting speed for interrupted cutting operations.
An Improvement to Tree-Structured Vector Quantization
Authors: Chu Chao Ping , Hwang Shaw Hwa , Chang Shun Chieh , Yeh Cheng Yu
Published: March 2013

This study proposes an improvement to tree-structured vector quantization (TSVQ). The selected codeword of TSVQ is employed as the reference codeword. The dynamic triangular inequality elimination (DTIE) is employed to improve the performance of TSVQ. In the DTIE-TSVQ approach, the selected codeword and SNR are identical to that of full-search vector quantization (FSVQ), and the computational saving is better than that of TIE-VQ. The experimental results confirm that DTIE-TSVQ outperforms TIE-VQ, TSVQ.
Hydraulic System Fault Diagnosis Based on EMD and Improved PSO-Elman ANN
Authors: Dong Zeng Shou , Zhang Xiao Yu , Zeng Jian Chao
Published: March 2013

The element parameters of engineering machinery hydraulic system are detected, the fault eigenvector is extracted, and the information is applied to neural network fault diagnosis. Experience mode decomposition (EMD) is used to extract fault characteristic vectors in this paper, combined with the pressure, temperature and flow rate of dominant signal as neural network's inputs. In addition, the paper improves the Elman neural network learning algorithm by PSO algorithm. It can effectively increase network convergence rate and computing power. The particle swarm is used to optimize Elman neural network weights and the threshold value and then applied in the fault diagnosis system by training the network. The results show that the method increases the neural network convergence rate and reduces diagnoses error.
The Dynamic LMS for Line Echo Cancellation
Authors: Ku Ning Yun , Hwang Shaw Hwa , Chang Shun Chieh , Yeh Cheng Yu
Published: March 2013

To the best of our knowledge, this study represents the proposal using the dynamic least mean square (DLMS) algorithm to reduce the computation load of LMS. Moreover, three regions of impulse response of line echo path are also proposed to analyze the redundant coefficients. Using the DLMS method, redundant coefficients can be detected and grouped, thereby automatically reducing computation. We employed line echo cancellation (LEC) to evaluate the performance of DLMS. The pure-delay and overlong regions of impulse response of line echo path are grouped and the associated computation load is reduced. The experimental results confirm the excellent performance of DLMS achieving a 35% savings in computation. Moreover, the quality echo return loss enhancement (ERLE) of DLMS also maintains at a level nearly equal to LMS.
3D Angle Searching System with PSO for Face Recognition
Authors: Hsieh Ching Tang , Hu Chia Shing , Shih Meng Shian
Published: March 2013

Conventional 2D face recognition methods often struggle when a subject's head is turned even slightly to the side. In this study, a face recognition system based on 3D head modeling that is able to tolerate facial rotation angles was constructed by leveraging the Open source graphic library (OpenGL) framework. To minimize the extensive angle searching time that often occurs in conventional 3D modeling, Particle Swarm Optimization (PSO) was used to determine the correct facial angle in 3D. This reduced the angle computation time to 6 seconds, which is significantly faster than other methods. Experimental results showed that successful ID recognition can be achieved with a high recognition rate of 90%.
A Multi-Criteria Image Quality Evaluation Scheme
Authors: Chang Yen Ching , Chang Chun Ming , Chen Liang Hwa , Chan Tung Jung
Published: March 2013

It is difficult to objectively and quantitatively judge image quality by a single criterion, such as contrast. In general, excessive contrast enhancement easily leads to a loss of image quality. Thus, it easily gives a wrong evaluation to rank image quality according to contrast values. In order to achieve a consistent result with human vision perception, balancing multi-criteria will be a feasible approach. Therefore, we propose a multi-criteria image quality evaluation scheme for ranking seven existing contrast enhancement methods. The scheme applies four criteria to a newly proposed way of computing a grey relational grade (GRGd), called the consistent grey relational grade (CGRGd). Experimental results show that our proposed CGRGd do provides a very effective mechanism to choose the best method for a specific purpose.
A New Algorithm Based Orthogonal Arrays for Design of Experiment on Nonlinear Functions
Authors: Kuo Hsin Chuan , Lee Chao Tsung , Lin Ching Hai
Published: March 2013

A new algorithm based orthogonal arrays was developed to determine the optimal solution amid all the optional settings for a new initiated device. The proposed algorithm begins with several successive orthogonal arrays and ends with a full factorial array. After each orthogonal array is accomplished, the algorithm employs variance analyses to screen the dominating variable from among all the current variables and then determines the best level of the dominating variable. Here, after successive orthogonal arrays were completed, the number of unfixed variables was gradually reduced to a number that was small enough to feasibly conduct a full factorial array, resulting in the final selection of the problem’s optimum setting. We verified the proposed algorithm by first applying it to the Rosenbrock function.To distinguish the superior performance of the proposed algorithm in comparison with other design of experiments approaches, we experimented with three different problems with non-interactive or interactive variables. The results show that the proposed method not only provides a final solution that is identical to the problem’s exact solution but also that the computation time in comparison with that required by a full factorial array drops drastically as the number of variables increases.
A New Evolution Algorithm: Cultural Evolution Algorithm for Global Optimizations
Authors: Kuo Hsin Chuan , Lin Ching Hai
Published: March 2013

The course of socio-cultural transition is not a phenomenon of aimless, arbitrary development, but towards a clear goal. Such process of moving towards higher-level soul experience and mental state is a common goal of social species' evolution. In this paper, the model of cultural development is imitated to be the system thinking frame for developing an evolution algorithm, namely cultural evolution algorithm. It consists of several search methods with similar thinking and then proposes four strategies of the cultural evolution algorithm. Seven benchmark functions are utilized to validate the search performance of the proposed algorithm. The results show that all of the four strategies of cultural evolution algorithm have better performance when compared with relevant literatures.
Novel 3-D Image Encryption Using Computational Integral Imaging and Linear-Complemented MLCA
Authors: Li Xiao Wei , Kim Dong Hwan , Cho Sung Jin , Kim Seok Tae
Published: March 2013

Three dimensional (3-D) images encryption schemes can provide feasible and secure for images encryption due to the 3-D properties of images. In this paper, we present a novel 3-D images encryption algorithm by combining use of integral imaging (II) and maximum-length cellular automata (MLCA) as the secret key ciphering for 3D image encryption technique. In this proposed algorithm, a lenslet array first decomposes the 3-D object into 2-D elemental images (EIs) via the pick-up process of II. We encrypt the 2-D EIs with an encryption method based on linear and complemented MLCA. Decryption process is the opposite of operation encryption process: The 2-D EIs is recovered by the MLCA key, 3-D object is reconstructed by the recovered EIs via computational integral imaging (CII) reconstruction. To verify the usefulness of the proposed algorithm, we carry out the computational experiments and present the experimental results for various attacks. Experimental results show that the proposed algorithm can improve the performance of encryption against various attacks due to large key space in MLCA and 3-D characteristic of data redundancy.
A Novel Region-Based Approach for Automatic Road Extraction from High Resolution Satellite Images
Authors: Byun Young Gi
Published: March 2013

With the constantly increasing public availability of high resolution satellite imagery, interest in automatic road extraction from this imagery has recently increased. Road extraction from high resolution satellite imagery refers to reliable road surface extraction instead of road line extraction because roads in the imagery mostly correspond to an elongated region with a locally constant spectral signature rather than traditional thin lines. This paper proposes a novel automatic road extraction approach that is based on a combination of image segmentation and one-class classification and consists of two main steps. First, the image is segmented using a modified previous segmentation algorithm to achieve more reliable segmentation for road extraction. The key road objects are then automatically extracted from the segmented image to obtain road training samples. Then one-class classification, based on a support vector data description classifier, is carried out to extract the road surface area from the image. The experimental results from a pan-sharpened KOMPSAT-2 satellite image demonstrate the correctness and efficiency of the proposed method for its application to road extraction from high resolution satellite image.
Effect of Bi2O3 Addition on the Microstructure and Electrical Properties of Lead-Free (Na0.5K0.5)NbO3-Ba(Sn0.02Ti0.98)O3 Ceramics
Authors: Wang Chun Huy
Published: March 2013

PbZrO3-PbTiO3 (PZT)-based ceramics are playing a dominant role in piezoelectric materials, their evaporation of harmful lead oxide during the sintering process causes a crucial environment problem. It is necessary to search for lead-free piezoelectric materials that have such excellent properties as those found in the PZT-based ceramics. Therefore (Na0.5K0.5)NbO3-based solid solutions were studied to improve piezoelectric properties. In the present study, various quantities of Bi2O3 were added into 0.98(Na0.5K0.5)NbO3-0.02Ba(Sn0.02Ti0.98)O3 (0.98NKN-0.02BST) ceramics. It was found that 0.98NKN-0.02BST with the addition of 0~4.0 wt.% Bi2O3 exhibit relatively good piezoelectric properties. For 0.98NKN-0.02BST ceramic with the addition of 1.0 wt.% Bi2O3, the electromechanical coupling coefficients of the planar mode kp and the thickness mode kt reach 0.21 and 0.46, respectively, at the sintering of 1100oC for 3 h. The ratio of thickness coupling coefficient to planar coupling coefficient is 2.2. It is obvious that 0.98NKN-0.02BST solid solution ceramic by adding low quantities of Bi2O3 is one of the promising lead-free ceramics for high frequency electromechanical transducer applications.
An Algorithm of the Misconception Order
Authors: Sheu Tian Wei , Tsai Ching Pin , Tzeng Jian Wei , Chen Tzu Liang , Nagai Masatake
Published: March 2013

In recent years, the grey system theory is widely applied in academic community, and it has obtained very good results. This study proposes GSP chart (Grey Student-Problem chart) which combines S-P chart (Student-Problem chart) with GRA (Grey Relational Analysis). This paper selects the students whose Gamma value is near 0.5 from the GSP chart. Those students are defined as the Misconception-Students. Then we analyze those students’ answers and select the right and wrong answers created by those Misconception Students at the different time. It is said that the misconception questions are defined as the Misconception-Problem Chart. Through the Problem-Concept Chart conducted by teachers, we can define the Misconception Rate and the Misconception Order by comparing the Misconception-Concept Chart. This method can not only accurately predict where students’ misconception is, but also apply to the remedial instruction.
An Efficient Neural Network Model with Taylor Series-Based Data Pre-Processing for Stock Price Forecast
Authors: Li Jung Bin , Wu Chien Ho
Published: March 2013

This study adopts popular back-propagation neural network to make one-period-ahead prediction of the stock price. A model based on Taylor series by using both fundamental and technical indicators EPS and MACD as input data is built for an empirical study. Leading Taiwanese companies in non-hi-tech industry such as Formosa Plastics, Yieh Phui Steel, Evergreen Marine, and Chang Hwa Bank are picked as targets to analyze their reasonable prices and moving trends. The performance of this model shows remarkable return and high accuracy in making long/short strategies.
An EigenMLLR-Like Eigen-FLS Approach for Speech Pattern Recognition
Authors: Ding Ing Jr , Yen Chih Ta
Published: March 2013

The Eigen-FLS using an eigenspace-based scheme to build up fuzzy logic system (FLS) fast for speech pattern recognition applications has been developed in the author’s previous works. However, speech pattern recognition by Eigen-FLS will still encounter a dissatisfactory recognition performance when the collected data for eigen value calculations of the FLS eigenspace, i.e. the eigen-decomposition process, is scarce. To regulate the influence of Eigen-FLS when data from a test speaker for eigen-decomposition is improper, this paper proposes an EigenMLLR-like Eigen-FLS approach. The developed EigenMLLR-like Eigen-FLS integrates the kernel idea of EigenMLLR speaker adaptation for properly adjusting the target speaker’s Eigen-FLS model in the eigenspace of FLS. EigenMLLR-like Eigen-FLS developed in this paper will be more robust than conventional Eigen-FLS in a speech pattern recognition application with an adverse condition of insufficient data from the speaker.
Chinese Semantic Word-Formation Analysis Using FKP-MCO Classifier Based on Layered and Weighted GED
Authors: Gao Guang Xia , Zhang Zhi Wang , Kang Shi Yong
Published: March 2013

For Chinese information processing, automatic classification based on a large-scale database for different patterns of semantic word-formation can remarkably improve the identification for the unregistered word, automatic lexicography, semantic analysis, and other applications. However, owing to noise, anomalies, nonlinear characteristics, class-imbalance, and other uncertainties in word-formation data, the predictive performance of multi-criteria optimization classifier (MCOC) and other traditional data mining approaches will rapidly degenerate. In this paper we put forward an novel MCOC with fuzzification, kernel, and penalty factors (FKP-MCOC) based on layered and weighted graph edit distance (GED): firstly the layered and weighted GEDs between each semantic word-formation graph and prototype graphs are calculated and used for the dissimilarity measure, then the normalized GEDs are embedded into a new feature vector space, and FKP-MCO classifier based on the feature vector space is built for predicting the patterns of semantic word-formation. Our experimental results of Chinese word-formation analysis and comparison with support vector machine (SVM) show that our proposed approach can increase the separation of different patterns, the predictive performance of semantic pattern of a new compound word.
Effects of SiO2 and TiO2 Nanofillers on Conductivity Level of LLDPE-NR Nanocomposite HV Insulator
Authors: Akmal Mohd Jamail Nor , Afendi Mohamed Piah Mohamed , Nor Asiah Muhamad , Addawiyah Zainir Rubiatul , Nur Faizal Kasri
Published: March 2013

Polymeric nanocomposites have gained importance in the material properties to provide enhanced performances such as electrical and mechanical properties. One of the targets in this field is to obtain new materials with improved dielectric properties for High Voltage (HV) insulation application. In general, the good insulator must have low conductivity level. This paper presents the outcome of an experimental study to find the conductivity level of LLDPE-Natural Rubber (NR) compound filled with different amount of nanoparticles of SiO2 and TiO2 by using Polarization and Depolarization Current (PDC) measurement technique. PDC measurement is an efficient and effective insulator diagnostic technique based on time domain measurement to monitor the dielectric behaviour. The experiment was conducted to find PDC pattern and conductivity variations of each new sample. The results show that the addition of SiO2 filler exhibited in less conductivity compared to TiO2 filler with certain percentage. LLDPE-NR/ SiO2 can be a good insulator compared with LLDPE-NR/ TiO2.
Combined Probabilistic and Possibilistic Used to a Build Type-2 Fuzzy Clustering Algorithm Model
Authors: Yao Leehter , Weng Kuei Sung
Published: March 2013

In a noise environment probabilistic fuzzy clustering will force the noise into one or more clusters, seriously influencing the main dataset structure. We extend Type-1 membership values to Type-2 by assigning a possibilistic-membership function to each Type-1 membership value. The idea in building the Type-2 fuzzy sets is based simply on the fact that, for the same Type-1 membership value, the secondary membership function should make the larger possibility value greater than the smaller possibility value. This paper presents an efficient combined probabilistic and possibilistic method for building Type-2 fuzzy sets. Utilizing this concept we present a Type-2 FCM (T2FCM) that is an extension of the conventional FCM. The experimental results show that the T2FCM is less susceptible to noise than the Type-1 FCM. The T2FCM can ignore the inlier and outlier interrupt. The clustering results show the robustness of the proposed T2FCM because a reasonable amount of noise data does not affect its clustering performance.
Data Mining Based Intelligent System for Voting Behavior Analysis
Authors: Chen Duen Kai
Published: March 2013

In this study, we report a voting behavior analysis intelligent system based on data mining technology. From previous literature, we have witnessed increasing number of studies applied information technology to facilitate voting behavior analysis. In this study, we built a likely voter identification model through the use of data mining technology, the classification algorithm used here constructs decision tree model to identify voters and non voters. This model is evaluated by its accuracy and number of attributes used to correctly identify likely voter. Our goal is to try to use just a small number of survey questions while maintaining the accuracy rates of other similar models. This model was built and tested on Taiwan’s Election and Democratization Study (TEDS) data sets. According to the experimental results, the proposed model can improve likely voter identification rate and this finding is consistent with previous studies based on American National Election Studies.
Detection of Content-Aware Image Resizing Using Seam Properties
Authors: Ryu Seung Jin , Lee Hae Yeoun , Lee Heung Kyu
Published: March 2013

Visually convincing content-aware image resizing, which preserves semantically important image content, has been actively researched in recent years. This paper proposes a resizing detector that reveals the trace of seam carving and seam insertion. To unveil the evidence of seam carving, we exploit energy bias of seam carved images. In addition, the correlation between adjacent pixels is analyzed to estimate the inserted seams. Empirical evidence from a large database of test images demonstrates the superior performance of the proposed detector under a variety of settings.
Exploring the Factor Effect of Learning Vector Quantization in Artificial Neural Networks
Authors: Shih Yih Shan , Tsai Liang Ting , Yang Chih Chien
Published: March 2013

The goal of this study is to explore the factor effect of learning vector quantization. The manipulated factors are training pattern, learning rate, types of mixed data, and hidden node. The results showed that the average accuracy for severe overlap data was significantly lower than for those of slight and moderate overlap data. The worst classification accuracy was found for mixed data with learning rate equals to 0.1; whereas the best classification accuracy was found when the number of hidden nodes and output categories are equal. As a result, the classification accuracy increased as the number of training patterns increased. Conclusions and discussions are provided for practical guidelines.
Anti-Corrosion Properties of the Reactive Anode and Cathode Inhibitor by Electrochemical Treatment in Aqueous
Authors: Lee Han Seung , Ryu Hwa Sung
Published: March 2013

The durability of a concrete structure is most significantly influenced by the corrosion of reinforcing bars, rather than by the deterioration of concrete itself. The corrosion of reinforcement bars due to chloride serves as a main deterioration factor at the interface between the bars and the concrete in the concrete structure. Accordingly, the corrosion inhibitors are widely used to improve the resistance to chloride penetration into reinforced concrete. Corrosion inhibitors are generally divided into the anode-type inorganic inhibitors and anode-cathode-type organic inhibitors, in terms of the reaction type. It is known that when the Cl-:OH- concentration ratio exceeds 0.6%, film on passive state metal on the bar-concrete interface is damaged and local corrosion starts regardless of the chloride ion content. In this study, the performance of the corrosion inhibitor was examined using a potentiostat, with chloride ion contents of 1.2kg/m3 (as reference), 2.4kg/m3, and 4.8kg/m3. The variables were the inhibitor type, Cl-:OH- molar ratio according to the addition of anode-type inorganic corrosion inhibitor (four ratios: 0.0%, 0.3%, 0.6% and 1.2%), and ratio compared to the standard anode-cathode-type organic corrosion inhibitor liquid (four ratios: 0.0, norm 1/2, norm, norm 2 times). As a result, with the anode-type inorganic nitrite corrosion inhibitor, the corrosion inhibition performance was verified with a corrosion potential of -0.30V at a molar ratio of 0.3% or higher when the chloride ion content was 1.2kg/m3, and at a molar ratio of 0.6% or higher when the chloride ion content was 2.4kg/m3 or 4.8kg/m3. With the anode-cathode-type organic corrosion inhibitor, the corrosion inhibition performance was very good at half the standard quantity (0.42kg/m3) regardless of the chloride ion content. From the added corrosion inhibitor quantities, the anode-cathode-type organic corrosion inhibitor had a better corrosion inhibition performance than the anode-type inorganic nitrite corrosion inhibitor.
Flame Synthesis of Carbon Nanotubes and Nano-Onions in a Rotating Opposed-Jets Flow
Authors: Hou Shuhn Shyurng , Huang Wei Cheng
Published: March 2013

The influence of flow rotation on the synthesis of carbon nano-structures using rotating opposed flow ethylene diffusion flames and a catalytic Ni substrate was investigated. In the experiments, the flame parameter was kept constant with fuel and oxidizer compositions of 20%C2H2+80%N2 and 40%O2+60%N2 in the upper and lower burners, respectively, whereas the strain rate was varied by adjusting the rotation speed. Stain rate affects carbon nano-structures synthesis either through the residence time of the flow or carbon sources available for the growth of carbon nanotubes (CNTs) and onions. A diffusion flame at low strain rate is stronger than a weak flame at high strain rate and produces more carbon sources because of the longer residence time of the flow. At a higher strain rate, curved and entangled tubular multi-walled CNTs were harvested, however, at a lower strain rate carbon nano-onions (CNOs) were synthesized. It is verified that flow rotation associated with residence time plays an important role in the synthesis of carbon nanostructures.
Fast Depth Generating Algorithm From Binocular Images
Authors: Cheng Fang Hsuan , Kuo Tzu Hao
Published: March 2013

This paper proposes a line segment method to estimate the depth information from a pair of rectified images. The proposed method can achieve fast and high quality stereo-matching. This method first uses a simple edge detection to find out the line segments in the reference image and then calculates the color difference of each line segment from binocular images. The last step is to find out the minimum difference of each line segment as the corresponding points. From the experimental results, it is proved that the proposed method can fast and accurately generate the depth information from binocular images.
Unsupervised Mining of Visually and Temporally Consistent Shots for Sports Video Summarization
Authors: Dong Yuan , Zhang Ji Wei , Zhao Jian , Liu Wei , Tao Kun
Published: March 2013

Video summarization aims at providing compact representation containing enough information for users to understand the entire content or important events, which serves as the fundamental process in content-based video analysis. This paper presents a novel sport video summarization algorithm by mining consistent field-of-views applied visual and temporal information in a totally unsurprised manner. After videos are broken into shots, a content-based similarity measure is proposed in the shot level to structurally analysis the visually matching cost of original videos. Then modified agglomerative hierarchical clustering is performed with an energy-based function to match the statistical distribution of various views in game videos and a refined distance metric is proposed as similarity measure of two shots. Extended temporal prior is introduced to meet the fact that temporally neighbored shots with similar duration are more likely to be in the same clusters. Experiments on a database of 6 sport genres with over 10251 minutes of videos from different sources achieved an average accuracy of 91.5% and quantitative results are presented to justify each choice made in the design of our algorithm. Our proposed algorithm is applied for the non-linear browsing service of Orangesports by France Telecomm and an android based app has been implemented for smart mobile devices.
Investigation of Hybridization Efficiency of a Sequence-Orientated Coaxial DNA Probe Microarryed on Biochips Using Atomic Force Microscope
Authors: Wu Jui Chuang , Yang Dan Kai , Lin Yane Shu , Chen Jun Yi
Published: March 2013

Two sequence-inversed probes were microarrayed on glass slides to study the hybridization efficiency with their DNA targets. A fluorescence laser scanner and an atomic force microscope (AFM) were utilized to investigate the efficiency in different hybridization cases and their corresponding depth changes on the chips. The sequences of two targets were designed to be fully complementary to their shared DNA probe in a coaxial stacking configuration. In other words, after the first DNA target is hybridized (pre-hybridizing) onto the probe, the second one is stacked onto the non-hybridized region of the same probe. The pre-hybridizing and the second DNA targets were distinguished by two distinct fluorescent dyes. The enhancement of the hybridization efficiency was investigated through the comparison between the stacking and individual hybridization configurations. AFM was used to measure the depths of two probes at different steps of hybridization. The results indicated that the depths increased as the hybridization proceeded. Probe#1, pre-hybridizing close to the chip surface, obtained a thicker depth than the other probe pre-hybridizing away from the chip surface, Probe#2. A hypothesis was proposed to explain how the depth variation was associated with the observed hybridization efficiency.
Significant Features Selection Resistant to Temporal Distortions
Authors: Lu Ta-Te
Published: March 2013

Most patterns in continuous video sequences are similar. Temporal distortion, e.g. frames dropping, insertions, transposition, is a challenging issue for video reconstruction to find the actual missing positions in video sequences. The aim of this paper is to raise the detection accuracy and synchronize video frames back to original positions following temporal synchronization distortions. The successive video frames have similar statistics but the statistics in some local regions may differ from one another. Therefore, the block partition is partitioned into non-overlapping blocks by each frame, and then the local variance is calculated and taken as the block feature in each block. For most of the video frames, the pixels within the frame blocks are correlated and the maximum eigenvalue will be far from other eigenvalues. In this case, the maximum eigenvalue is set as the dominated block feature. For less correlated blocks, the values of the eigenvalues will be a little closer. In this case, the mean value of the eigenvalues represents the dominated block feature. Then, the sum of variance is regarded as the frame feature to calculate from these selective dominated blocks. Simulation results show the proposed methods are robust in evaluating the missing positions against temporal distortions.
Robust Image Process of Corresponding Lines Using Moving-Window Method
Authors: Tsai Zhi Ren , Hwang Jiing Dong
Published: March 2013

This paper introduces a kind of image process, moving-window method, for enhancing the consistency in searching for corresponding structured lines on images captured from different views. Effectiveness of the approach is demonstrated by a comparison of correctness with three of the most popular algorithms, the Multiple-line, the Scale Invariant Feature Transform (SIFT), and the Phase-Only Correlation method (POC).
Pareto Ensembles for Evolutionary Synthesis of Neurocontrollers in a 2D Maze-Based Video Game
Authors: Tan Tse Guan , Teo Jason , Chin Kim On , Anthony Patricia
Published: March 2013

In this paper, we present a study of evolving artificial neural network controllers for autonomously playing maze-based video game. A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network (PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. The experiments are designed to address two research aims investigating: (1) evolving weights (including biases) of the connections between the neurons and structure of the network through multi-objective evolutionary algorithm in order to reduce its runtime operation and complexity, (2) improving the generalization ability of the networks by using neural network ensemble model. A comparative analysis between the single network model as the baseline system and the model built based on the neural ensemble are presented. The evidence from this study suggests that Pareto multi-objective paradigm and neural network ensembles can be effective for creating and controlling the behaviors of video game characters.
Palmprint Verification for Images Captured in Peg-Less Scenarios
Authors: Lu Chun Wei , Lin Chih Lung , Fan Kuo Chin , Cheng Hsu Yung , Juan Chang Jung
Published: March 2013

This paper presents a reliable and robust palmprint verification approach using palmprint feature point number (FPN). The feature verified by support vector machine (SVM). It has the advantages of capturing palm images in peg-less scenarios and by a low cost and low-resolution (100dpi) digital scanner. The low-resolution images lead a less database size. There are 4800 palmprint images were collected from 160 persons to verify the validity of the proposed approach and the results are satisfactory with 98.30% classification correct rate (CCR). Experimental results demonstrate that the proposed approach is feasible and effective in palmprint verification. Our findings will help to extend palmprint verification technologies to security access control systems.
Non-Uniform SURF Feature Point Detection and Matching
Authors: Huang Yea Shuan , Ou Zhi Hong , Yu Hung Hsiu , Hsieh Hsiang Wen
Published: March 2013

This paper presents a method for detecting feature points from an image and locating their matching correspondence points across images. The proposed method leverages a novel rapid LBP feature point detection to filter out texture-less SURF feature points. The detected feature points, also known as Non-Uniform SURF feature points, are used to match corresponding feature points from other frame images to reliably locate positions of moving objects. The proposed method consists of two processing modules: Feature Point Extraction (FPE) and Feature Point Mapping (FPM). First, FPE extracts salient feature points with Feature Transform and Feature Point Detection. FPM is then applied to generate motion vectors of each feature point with Feature Descriptor and Feature Point Matching. Experiments are conducted on both artificial template patterns and real scenes captured from moving camera at different speed settings. Experimental results show that the proposed method outperforms the commonly-used SURF feature point detection and matching approach.
Moments and Parametrizing Construction for 3-Band Biorthogonal Scaling Coefficients
Authors: Cui Li Hong , Zhou Yan , Huang Bin , Sun Jian Jun
Published: March 2013

Regensburger and Scherzer described a symbolic computation method for moments and filter coefficients of scaling functions and obtained parametrizing compactly supported orthonormal wavelets. Following the idea, we are devoted to a study moments and parameterization construction for 3-band biorthogonal scaling coefficients with several vanishing moments. Firstly, we investigate the relations between filter lengths and symmetry. Then, we prove the relationship between dual continuous moments of 3-band biorthogonal scaling functions in theorem 2. This theorem reveals that the sum of continuous moments of dual scaling functions and is completely determined by the lower discrete moments. And we show the fact that the odd-indexed discrete moments are determined by the smaller even-indexed discrete moments. Finally, a family 3-band biorthogonal scaling coefficients with discrete moments as parameters are explicitly expressed based on computer algebra.
Lane Detection and Predicting Algorithm Based on Randomized Hough Transform
Authors: Zhou Zhi Heng , Zhang Wenting
Published: March 2013

Lane detection is the key technology of the intelligent vehicle based on machine vision. In order to improve the detection of real-time, a lane detection and prediction algorithm based on Randomized Hough Transform is developed in this paper. The algorithm includes lane detection algorithm and prediction algorithm. First of all at identification stages, scan the pretreated image in order to search lanes candidate points, and combine with the lanes angle range of constraints, fit the candidate boundary points by Randomized Hough Transform for the improvement of real-time and robustness. The driveway line prediction algorithm is also proposed. With the dynamic searching window, weights of prediction are adaptive and they can make the line prediction more accurate. Test results show that algorithm has good real-time and robust performance.
The Humidity Property of the AR Texture with SiO2 Nanospheres by Spin Coating Method
Authors: Hsu Cheng Chih , Lan Wen Lin , Fu Wei En
Published: March 2013

In this study, we proposed an anti-reflection (AR) texture constructed with nano-scale silicon dioxide particle dispersed in Accuglass® T-11 solution to form the structure on the glass by two-steps spin coating technique. We demonstrated the transmittance of the glass with AR texture will be enhanced about 2 % under optimal manufactured conditions. And we have proposed the simulated out-door endurance testing of AR texture which can provide the acceptable transmittance at different relative humidity levels. Based on these findings, we believe that the AR texture with SiO2 nanospheres on the cover glass can be useful in the applications of solar cell, thermal collector, and display device under appropriate environmental conditions.
LemK_MSA: A Multiple Sequence Alignment Method with Sequence Vectorization Based on Lempel-Ziv
Authors: Ji Guo Li , Yao Jing Ci , Yang Zi Jiang , Ye Cong Ting
Published: March 2013

In this paper, we propose a method for multiple sequence alignment, LemK_MSA, which integrates Lempel-Ziv based sequence vectorization and k-means clustering analysis. LemK_MSA converts multiple sequence alignment into corresponding 10-dimensional vector alignment by 10 types of copy modes. Then it uses k-means algorithm and NJ algorithm to divide the sequences into several groups and calculate guide tree of each part with the vectors of the sequences. A complete guide tree for multiple sequence alignment could be constructed by merging guide tree of every group. Thus, the time efficiency of processing multiple sequence alignment, especially for large-scale sequences, can be improved. The high-throughput mouse antibody sequences are used to validate the proposed method. Compared to ClustalW, MAFFT and Mbed, LemK_MSA is more than ten times efficient while ensuring the alignment accuracy at the same time. LemK_MSA also provides an effective method to analyze the evolutionary relationship and structural features among high-throughput sequences.
An Efficient Control System for Combating Cybersickness in the Elderly within a Virtual Store
Authors: Liu Cheng Li , Uang Shiaw Tsyr
Published: March 2013

3D virtual store with an internet connection used at home can provide the elderly a new channel to buy something which they need. However, most virtual environments (VEs) more often lack subdued response to pleasantness. A further confounding factor is that some users exhibit symptoms that parallel those of classical motion sickness, called cybersickness, both during and after the VE experience. The study investigated the factors that contribute to cybersickness among the elderly when immersed into a 3D virtual store. The results of the first experiment showed that the rate of simulator sickness questionnaire (SSQ) scores increases significantly with navigational rotating speed and duration of exposure. In applying these findings, a warning system with fuzzy control for combating cybersickness was developed. The results of the second experiment showed that the proposed system can efficiently determine the level of cybersickness based on the associated subjective sickness estimates and combat cybersickness induced within a 3D virtual store.
Hardware/Software Co-Design of 2D-to-3D Video Conversion on FPGA
Authors: Schumann Thomas , Krauß Herbert , Lai Yeong Kang , Lai Yu Fan
Published: March 2013

With advances in technology, 3D video technology becomes possible and attractive. However, there are still many pre-recorded 2D videos/images which need to get transferred to 3D. Hence this paper presents a high quality view synthesis algorithm and architecture for 2D-to-3D video conversion. During the process of view synthesis, the monocular depth information together with the intermediate view is synthesized to the left-eye and right-eye view. The proposed view synthesis algorithm consists of two parts: 3D image warping and inpainting (hole filling). 3D image warping transforms a 2D camera image plane to a 3D coordinate plane. However the integer grid points of the reference are warped to irregularly spaced points in the virtual view, resulting in occlusion problems. Thus inpainting is needed to fix the virtual images. The proposed algorithm shows an improved PSNR gain of 0.2~1.5dB. We adopt hardware/software co-design to accomplish the proposed view synthesis algorithm. For this we implemented the image inpainting on a FPGA device and the remaining algorithm in software.
A Design of Smart Dressing System
Authors: Kao Yang Ta
Published: March 2013

In traditional clothing store, it’s necessary to try clothes before purchasing. But in many situations, people do not like to try it, which were caused in wearing on and off is considered as an inconvenient action. Besides, females’ make-up may stain the clothes while fitting. The proposed method provides a smart dressing system which can enhance the willingness to try dressing but also avoid staining the clothes when wears on and off. This system is composed with three stages: contour initialization, attaching the control points, and field morphing. The experimental results compare to those existing systems show that our system provides a convenient dressing system which can be widely adoptable by apparel stores.
A New Front-End Anonymity and Back-End Real-Name Mechanism in e-Commerce
Authors: Chiu Ying Ching , Horng Wen Bing
Published: March 2013

In this paper, we propose a new approach using both the Citizen Digital Certificate and anonymous identification to fulfill the back-end real-name and front-end anonymous verification requirements in an online transaction. Anonymous identification is a simple design to establish the link between the real name and the pseudonym (account ID) selected by the user during the registration, in which the reverse-lookup is not allowed so that the anonymous verification is achieved. The back-end real-name mechanism in this model plays an important role which requires total fairness and trust. Thus, we use the government MOICA as the trust back-end platform, which issues the Citizen Digital Certificate and thus will have the user’s real-name. The main purpose of the front-end anonymity mechanism is that, the online shopping store does not know the real identities of its customers but pseudonyms. The customer is able to conduct a transaction anonymously in a normal circumstance, in which his/her privacy is preserved. The back-end real-name mechanism will be activated only when crime events occur. In such cases, anonymity will be removed through legal means to trace the real identity.
A Novel Optimal Routing Strategy for Internet of Things’ Machine-to-Machine Network under Time Constraint
Authors: Chou Yu Cheng
Published: March 2013

In this paper, an optimal routing strategy called TM3NORA for the Internet of Things’ Machine-to-Machine network is proposed. In the Internet of Things, devices or nodes are clustered to create a Machine-to-Machine network, which can be considered as a small-world network. The network model concerned is a Time-constrained Multi-packet Multi-state Machine-to-machine network (TM3N). A TM3N has four characteristics: (1) each arc employs two attributes, capacity and lead time; (2) the arc capacity is stochastic; (3) different packets consume the arc capacity differently; (4) the delivery has to be completed within the promised time window. Essentially, the TM3NORA generates a small-world route map, reduces the route map, obtains the optimal route set that can be used to deliver all types of packets from the source node to the sink node within the desired time window, and evaluates the small-world route map’s overall reliability that all types of packets can arrive at the sink node within the time constraint. The efficiency and accuracy of the TM3NORA are validated through a numerical example of a six-node small-world route map.
A Preliminary Study on Non-Intrusive User Authentication Method Using Smartphone Sensors
Authors: Lin Chien Cheng , Chang Chin Chun , Liang De Ron , Yang Ching Han
Published: March 2013

This paper proposes a non-intrusive authentication method based on two sensitive apparatus of smartphones, namely, the orientation sensor and the touchscreen. We have found that these two sensors are capable of capturing behavioral biometrics of a user while the user is engaged in relatively stationary activities. The experimental results with respect to two types of flick operating have an equal error rate of about 3.5% and 5%, respectively. To the best of our knowledge, this work is the first publicly reported study that simultaneously adopts the orientation sensor and the touchscreen to build an authentication model for smartphone users. Finally, we show that the proposed approach can be used together with existing intrusive mechanisms, such as password and/or fingerprints, to build a more robust authentication framework for smartphone users.