Search results for: Unconstrained vector quantization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 811

Search results for: Unconstrained vector quantization

181 Segmentation and Recognition of Handwritten Numeric Chains

Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

Abstract:

In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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180 An Advanced Time-Frequency Domain Method for PD Extraction with Non-Intrusive Measurement

Authors: Guomin Luo, Daming Zhang, Yong Kwee Koh, Kim Teck Ng, Helmi Kurniawan, Weng Hoe Leong

Abstract:

Partial discharge (PD) detection is an important method to evaluate the insulation condition of metal-clad apparatus. Non-intrusive sensors which are easy to install and have no interruptions on operation are preferred in onsite PD detection. However, it often lacks of accuracy due to the interferences in PD signals. In this paper a novel PD extraction method that uses frequency analysis and entropy based time-frequency (TF) analysis is introduced. The repetitive pulses from convertor are first removed via frequency analysis. Then, the relative entropy and relative peak-frequency of each pulse (i.e. time-indexed vector TF spectrum) are calculated and all pulses with similar parameters are grouped. According to the characteristics of non-intrusive sensor and the frequency distribution of PDs, the pulses of PD and interferences are separated. Finally the PD signal and interferences are recovered via inverse TF transform. The de-noised result of noisy PD data demonstrates that the combination of frequency and time-frequency techniques can discriminate PDs from interferences with various frequency distributions.

Keywords: Entropy, Fourier analysis, non-intrusive measurement, time-frequency analysis, partial discharge

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179 New Drug Delivery System for Cancer Therapy

Authors: Emma R. Arakelova, Stepan G. Grigoryan, Ashot M. Khachatryan, Karapet E. Avjyan, Lilia M. Savchenko, Flora G. Arsenyan

Abstract:

The paper presents a new drugs delivery system, based on the thin film technology. As a model antitumor drug, highly toxic doxorubicin is chosen. The system is based on the technology of obtaining zinc oxide composite of doxorubicin by deposition of nanosize ZnO films on the surface of doxorubicin coating on glass substrate using DC magnetron sputtering of zinc targets in Ar:O2 medium at room temperature. For doxorubicin zinc oxide compositions in the form of coatings and gels with 180-200nm thick ZnO films, higher (by a factor 2) in vivo (ascitic Ehrlich's carcinoma) antitumor activity is observed at low doses of doxorubicin in comparison with that of the initial preparation at therapeutic doses. The vector character of the doxorubicin zinc oxide composite transport to tumor tissues ensures the increase in antitumor activity as well as decrease of toxicity in comparison with the initial drug.

Keywords: Antitumor activity, doxorubicin, DC magnetron sputtering, zinc oxide.

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178 Human Action Recognition Based on Ridgelet Transform and SVM

Authors: A. Ouanane, A. Serir

Abstract:

In this paper, a novel algorithm based on Ridgelet Transform and support vector machine is proposed for human action recognition. The Ridgelet transform is a directional multi-resolution transform and it is more suitable for describing the human action by performing its directional information to form spatial features vectors. The dynamic transition between the spatial features is carried out using both the Principal Component Analysis and clustering algorithm K-means. First, the Principal Component Analysis is used to reduce the dimensionality of the obtained vectors. Then, the kmeans algorithm is then used to perform the obtained vectors to form the spatio-temporal pattern, called set-of-labels, according to given periodicity of human action. Finally, a Support Machine classifier is used to discriminate between the different human actions. Different tests are conducted on popular Datasets, such as Weizmann and KTH. The obtained results show that the proposed method provides more significant accuracy rate and it drives more robustness in very challenging situations such as lighting changes, scaling and dynamic environment

Keywords: Human action, Ridgelet Transform, PCA, K-means, SVM.

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177 An Adaptive Hand-Talking System for the Hearing Impaired

Authors: Zhou Yu, Jiang Feng

Abstract:

An adaptive Chinese hand-talking system is presented in this paper. By analyzing the 3 data collecting strategies for new users, the adaptation framework including supervised and unsupervised adaptation methods is proposed. For supervised adaptation, affinity propagation (AP) is used to extract exemplar subsets, and enhanced maximum a posteriori / vector field smoothing (eMAP/VFS) is proposed to pool the adaptation data among different models. For unsupervised adaptation, polynomial segment models (PSMs) are used to help hidden Markov models (HMMs) to accurately label the unlabeled data, then the "labeled" data together with signerindependent models are inputted to MAP algorithm to generate signer-adapted models. Experimental results show that the proposed framework can execute both supervised adaptation with small amount of labeled data and unsupervised adaptation with large amount of unlabeled data to tailor the original models, and both achieve improvements on the performance of recognition rate.

Keywords: sign language recognition, signer adaptation, eMAP/VFS, polynomial segment model.

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176 Performance Comparison of AODV and Soft AODV Routing Protocol

Authors: Abhishek, Seema Devi, Jyoti Ohri

Abstract:

A mobile ad hoc network (MANET) represents a system of wireless mobile nodes that can self-organize freely and dynamically into arbitrary and temporary network topology. Unlike a wired network, wireless network interface has limited transmission range. Routing is the task of forwarding data packets from source to a given destination. Ad-hoc On Demand Distance Vector (AODV) routing protocol creates a path for a destination only when it required. This paper describes the implementation of AODV routing protocol using MATLAB-based Truetime simulator. In MANET's node movements are not fixed while they are random in nature. Hence intelligent techniques i.e. fuzzy and ANFIS are used to optimize the transmission range. In this paper, we compared the transmission range of AODV, fuzzy AODV and ANFIS AODV. For soft computing AODV, we have taken transmitted power and received threshold as input and transmission range as output. ANFIS gives better results as compared to fuzzy AODV.

Keywords: ANFIS, AODV, fuzzy, MANET, reactive routing protocol, routing protocol, Truetime.

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175 Construction of cDNALibrary and EST Analysis of Tenebriomolitorlarvae

Authors: JiEun Jeong, Se-Won Kang, Hee-Ju Hwang, Sung-Hwa Chae, Sang-Haeng Choi, Hong-SeogPark, YeonSoo Han, Bok-Reul Lee, Dae-Hyun Seog, Yong Seok Lee

Abstract:

Tofurther advance research on immune-related genes from T. molitor, we constructed acDNA library and analyzed expressed sequence taq (EST) sequences from 1,056 clones. After removing vector sequence and quality checkingthrough thePhred program (trim_alt 0.05 (P-score>20), 1039 sequences were generated. The average length of insert was 792 bp. In addition, we identified 162 clusters, 167 contigs and 391 contigs after clustering and assembling process using a TGICL package. EST sequences were searchedagainst NCBI nr database by local BLAST (blastx, EKeywords: EST, Innate immunity, Tenebriomolitor

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174 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

Abstract:

The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.

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173 A Comparative Study of SVM Classifiers and Artificial Neural Networks Application for Rolling Element Bearing Fault Diagnosis using Wavelet Transform Preprocessing

Authors: Commander Sunil Tyagi

Abstract:

Effectiveness of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) classifiers for fault diagnosis of rolling element bearings are presented in this paper. The characteristic features of vibration signals of rotating driveline that was run in its normal condition and with faults introduced were used as input to ANN and SVM classifiers. Simple statistical features such as standard deviation, skewness, kurtosis etc. of the time-domain vibration signal segments along with peaks of the signal and peak of power spectral density (PSD) are used as features to input the ANN and SVM classifier. The effect of preprocessing of the vibration signal by Discreet Wavelet Transform (DWT) prior to feature extraction is also studied. It is shown from the experimental results that the performance of SVM classifier in identification of bearing condition is better then ANN and pre-processing of vibration signal by DWT enhances the effectiveness of both ANN and SVM classifier

Keywords: ANN, Artificial Intelligence, Fault Diagnosis, Pattern Recognition, Rolling Element Bearing, SVM. Wavelet Transform

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172 Neural Network Based Icing Identification and Fault Tolerant Control of a 340 Aircraft

Authors: F. Caliskan

Abstract:

This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.

Keywords: Aircraft Icing, Stability Derivatives, Neural NetworkIdentification, Reconfiguration.

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171 Automatic Lip Contour Tracking and Visual Character Recognition for Computerized Lip Reading

Authors: Harshit Mehrotra, Gaurav Agrawal, M.C. Srivastava

Abstract:

Computerized lip reading has been one of the most actively researched areas of computer vision in recent past because of its crime fighting potential and invariance to acoustic environment. However, several factors like fast speech, bad pronunciation, poor illumination, movement of face, moustaches and beards make lip reading difficult. In present work, we propose a solution for automatic lip contour tracking and recognizing letters of English language spoken by speakers using the information available from lip movements. Level set method is used for tracking lip contour using a contour velocity model and a feature vector of lip movements is then obtained. Character recognition is performed using modified k nearest neighbor algorithm which assigns more weight to nearer neighbors. The proposed system has been found to have accuracy of 73.3% for character recognition with speaker lip movements as the only input and without using any speech recognition system in parallel. The approach used in this work is found to significantly solve the purpose of lip reading when size of database is small.

Keywords: Contour Velocity Model, Lip Contour Tracking, LipReading, Visual Character Recognition.

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170 A Mahalanobis Distance-based Diversification and Nelder-Mead Simplex Intensification Search Scheme for Continuous Ant Colony Optimization

Authors: Sasadhar Bera, Indrajit Mukherjee

Abstract:

Ant colony optimization (ACO) and its variants are applied extensively to resolve various continuous optimization problems. As per the various diversification and intensification schemes of ACO for continuous function optimization, researchers generally consider components of multidimensional state space to generate the new search point(s). However, diversifying to a new search space by updating only components of the multidimensional vector may not ensure that the new point is at a significant distance from the current solution. If a minimum distance is not ensured during diversification, then there is always a possibility that the search will end up with reaching only local optimum. Therefore, to overcome such situations, a Mahalanobis distance-based diversification with Nelder-Mead simplex-based search scheme for each ant is proposed for the ACO strategy. A comparative computational run results, based on nine nonlinear standard test problems, confirms that the performance of ACO is improved significantly with the integration of the proposed schemes in the ACO.

Keywords: Ant Colony Optimization, Diversification Scheme, Intensification, Mahalanobis Distance, Nelder-Mead Simplex.

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169 Leadership´s Controlling via Complexity Investigation in Crisis Scenarios

Authors: Jiří Barta, Oldřich Svoboda, Jiří. F. Urbánek

Abstract:

In this paper will be discussed two coin´s sides of crisis scenarios dynamics. On the one's side is negative role of subsidiary scenario branches in its compactness weakening by means unduly chaotic atomizing, having many interactive feedbacks cases, increasing a value of a complexity here. This negative role reflects the complexity of use cases, weakening leader compliancy, which brings something as a ´readiness for controlling capabilities provision´. Leader´s dissatisfaction has zero compliancy, but factual it is a ´crossbar´ (interface in fact) between planning and executing use cases. On the other side of this coin, an advantage of rich scenarios embranchment is possible to see in a support of response awareness, readiness, preparedness, adaptability, creativity and flexibility. Here rich scenarios embranchment contributes to the steadiness and resistance of scenario mission actors. These all will be presented in live power-points ´Blazons´, modelled via DYVELOP (Dynamic Vector Logistics of Processes) on the Conference.

Keywords: Leadership, Controlling, Complexity, DYVELOP, Scenarios.

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168 Comparative Analysis of DTC Based Switched Reluctance Motor Drive Using Torque Equation and FEA Models

Authors: P. Srinivas, P. V. N. Prasad

Abstract:

Since torque ripple is the main cause of noise and vibrations, the performance of Switched Reluctance Motor (SRM) can be improved by minimizing its torque ripple using a novel control technique called Direct Torque Control (DTC). In DTC technique, torque is controlled directly through control of magnitude of the flux and change in speed of the stator flux vector. The flux and torque are maintained within set hysteresis bands.

The DTC of SRM is analyzed by two methods. In one method, the actual torque is computed by conducting Finite Element Analysis (FEA) on the design specifications of the motor. In the other method, the torque is computed by Simplified Torque Equation. The variation of peak current, average current, torque ripple and speed settling time with Simplified Torque Equation model is compared with FEA based model.

Keywords: Direct Toque Control, Simplified Torque Equation, Finite Element Analysis, Torque Ripple.

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167 Performences of Type-2 Fuzzy Logic Control and Neuro-Fuzzy Control Based on DPC for Grid Connected DFIG with Fixed Switching Frequency

Authors: Fayssal Amrane, Azeddine Chaiba

Abstract:

In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications.

Keywords: Doubly fed induction generetor, direct power control, space vector modulation, type-2 fuzzy logic control, neuro-fuzzy control, maximum power point tracking.

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166 Convective Heat Transfer Enhancement in an Enclosure with Fin Utilizing Nano Fluids

Authors: S. H. Anilkumar, Ghulam Jilani

Abstract:

The objective of the present work is to conduct investigations leading to a more complete explanation of single phase natural convective heat transfer in an enclosure with fin utilizing nano fluids. The nano fluid used, which is composed of Aluminum oxide nano particles in suspension of Ethylene glycol, is provided at various volume fractions. The study is carried out numerically for a range of Rayleigh numbers, fin heights and aspect ratio. The flow and temperature distributions are taken to be two-dimensional. Regions with the same velocity and temperature distributions are identified as symmetry of sections. One half of such a rectangular region is chosen as the computational domain taking into account the symmetry about the fin. Transport equations are modeled by a stream functionvorticity formulation and are solved numerically by finite-difference schemes. Comparisons with previously published works on the basis of special cases are done. Results are presented in the form of streamline, vector and isotherm plots as well as the variation of local Nusselt number along the fin under different conditions.

Keywords: Fin height, Nano fluid, natural convection, Rayleigh number.

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165 Classification of Political Affiliations by Reduced Number of Features

Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the “Decision Tree”, “Rule Induction” and “M5 Rule” classifiers when used with “SVM” and “IGR” feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “Function”, as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.

Keywords: Politics, machine learning, feature selection, LIWC.

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164 Direct Power Control Strategies for Multilevel Inverter Based Custom Power Devices

Authors: S. Venkateshwarlu, B. P. Muni, A. D. Rajkumar, J. Praveen

Abstract:

Custom power is a technology driven product and service solution which embraces a family devices such as Dynamic Voltage Restorer (DVR), Distributed Shunt Compensator (DSTATCOM), Solid State Breaker (SSB) etc which will provide power quality functions at distribution voltages. The rapid response of these devices enables them to operate in real time, providing continuous and dynamic control of the supply including voltage and reactive power regulation, harmonic reduction and elimination of voltage dips. This paper presents the benefits of multilevel inverters when they are used for DPC based custom power devices. Power flow control mechanism, salient features, advantages and disadvantages of direct power control (DPC) using lookup table, SVM, predictive voltage vector and hybrid DPC strategies are discussed in this paper. Simulation results of three level inverter based STATCOM, harmonic analysis of multi level inverters are presented at the end.

Keywords: DPC, DPC-SVM, Dynamic voltage restorer, DSTATCOM, Multilevel inverter, PWM Converter, PDPC, VF-DPC.

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163 Damage Localization of Deterministic-Stochastic Systems

Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

Abstract:

A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: Damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification.

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162 Massive Lesions Classification using Features based on Morphological Lesion Differences

Authors: U. Bottigli, D.Cascio, F. Fauci, B. Golosio, R. Magro, G.L. Masala, P. Oliva, G. Raso, S.Stumbo

Abstract:

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensitivity (percentage of pathological ROIs correctly classified) and specificity (percentage of non-pathological ROIs correctly classified) will be presented through the Receive Operating Characteristic curve (ROC). In particular the best performances are 88% ± 1 of area under ROC curve obtained with the Feed Forward Neural Network.

Keywords: Neural Networks, K-Nearest Neighbours, SupportVector Machine, Computer Aided Diagnosis.

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161 Stator-Flux-Oriented Based Encoderless Direct Torque Control for Synchronous Reluctance Machines Using Sliding Mode Approach

Authors: J. Soltani, H. Abootorabi Zarchi, Gh. R. Arab Markadeh

Abstract:

In this paper a sliding-mode torque and flux control is designed for encoderless synchronous reluctance motor drive. The sliding-mode plus PI controllers are designed in the stator-flux field oriented reference frame which is able to track the mentioned reference signals with a minimum pulsations in the state condition. In addition, with these controllers a fast dynamic response is also achieved for the drive system. The proposed control scheme is robust subject to parameters variation except to stator resistance. To solve this problem a simple estimator is used for on-line detecting of this parameter. Moreover, the rotor position and speed are estimated by on-line obtaining of the stator-flux-space vector. The effectiveness and capability of the proposed control approach is verified by both the simulation and experimental results.

Keywords: Synchronous Reluctance Motor, Direct Torque and Flux Control, Sliding Mode, Field-Oriented Frame, Encoderless.

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160 Motion Area Estimated Motion Estimation with Triplet Search Patterns for H.264/AVC

Authors: T. Song, T. Shimamoto

Abstract:

In this paper a fast motion estimation method for H.264/AVC named Triplet Search Motion Estimation (TS-ME) is proposed. Similar to some of the traditional fast motion estimation methods and their improved proposals which restrict the search points only to some selected candidates to decrease the computation complexity, proposed algorithm separate the motion search process to several steps but with some new features. First, proposed algorithm try to search the real motion area using proposed triplet patterns instead of some selected search points to avoid dropping into the local minimum. Then, in the localized motion area a novel 3-step motion search algorithm is performed. Proposed search patterns are categorized into three rings on the basis of the distance from the search center. These three rings are adaptively selected by referencing the surrounding motion vectors to early terminate the motion search process. On the other hand, computation reduction for sub pixel motion search is also discussed considering the appearance probability of the sub pixel motion vector. From the simulation results, motion estimation speed improved by a factor of up to 38 when using proposed algorithm than that of the reference software of H.264/AVC with ignorable picture quality loss.

Keywords: Motion estimation, VLSI, image processing, search patterns

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159 An Energy Reverse AODV Routing Protocol in Ad Hoc Mobile Networks

Authors: Said Khelifa, Zoulikha Mekkakia Maaza

Abstract:

In this paper we present a full performance analysis of an energy conserving routing protocol in mobile ad hoc network, named ER-AODV (Energy Reverse Ad-hoc On-demand Distance Vector routing). ER-AODV is a reactive routing protocol based on a policy which combines two mechanisms used in the basic AODV protocol. AODV and most of the on demand ad hoc routing protocols use single route reply along reverse path. Rapid change of topology causes that the route reply could not arrive to the source node, i.e. after a source node sends several route request messages, the node obtains a reply message, and this increases in power consumption. To avoid these problems, we propose a mechanism which tries multiple route replies. The second mechanism proposes a new adaptive approach which seeks to incorporate the metric "residual energy " in the process route selection, Indeed the residual energy of mobile nodes were considered when making routing decisions. The results of simulation show that protocol ER-AODV answers a better energy conservation.

Keywords: Ad hoc mobile networks, Energy AODV, Energy consumption, ER-AODV, Reverse AODV.

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158 A Universal Model for Content-Based Image Retrieval

Authors: S. Nandagopalan, Dr. B. S. Adiga, N. Deepak

Abstract:

In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

Keywords: Content Based Image Retrieval (CBIR), Cooccurrencematrix, Feature vector, Edge Histogram Descriptor(EHD), Greedy strategy.

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157 Jacobi-Based Methods in Solving Fuzzy Linear Systems

Authors: Lazim Abdullah, Nurhakimah Ab. Rahman

Abstract:

Linear systems are widely used in many fields of science and engineering. In many applications, at least some of the parameters of the system are represented by fuzzy rather than crisp numbers. Therefore it is important to perform numerical algorithms or procedures that would treat general fuzzy linear systems and solve them using iterative methods. This paper aims are to solve fuzzy linear systems using four types of Jacobi based iterative methods. Four iterative methods based on Jacobi are used for solving a general n × n fuzzy system of linear equations of the form Ax = b , where A is a crisp matrix and b an arbitrary fuzzy vector. The Jacobi, Jacobi Over-Relaxation, Refinement of Jacobi and Refinement of Jacobi Over-Relaxation methods was tested to a five by five fuzzy linear system. It is found that all the tested methods were iterated differently. Due to the effect of extrapolation parameters and the refinement, the Refinement of Jacobi Over-Relaxation method was outperformed the other three methods.

Keywords: Fuzzy linear systems, Jacobi, Jacobi Over- Relaxation, Refinement of Jacobi, Refinement of Jacobi Over- Relaxation.

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156 View-Point Insensitive Human Pose Recognition using Neural Network and CUDA

Authors: Sanghyeok Oh, Keechul Jung

Abstract:

Although lots of research work has been done for human pose recognition, the view-point of cameras is still critical problem of overall recognition system. In this paper, view-point insensitive human pose recognition is proposed. The aims of the proposed system are view-point insensitivity and real-time processing. Recognition system consists of feature extraction module, neural network and real-time feed forward calculation. First, histogram-based method is used to extract feature from silhouette image and it is suitable for represent the shape of human pose. To reduce the dimension of feature vector, Principle Component Analysis(PCA) is used. Second, real-time processing is implemented by using Compute Unified Device Architecture(CUDA) and this architecture improves the speed of feed-forward calculation of neural network. We demonstrate the effectiveness of our approach with experiments on real environment.

Keywords: computer vision, neural network, pose recognition, view-point insensitive, PCA, CUDA.

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155 Adaptive Educational Hypermedia System for High School Students Based on Learning Styles

Authors: Stephen Akuma, Timothy Ndera

Abstract:

Information seekers get “lost in hyperspace” due to the voluminous documents updated daily on the internet. Adaptive Hypermedia Systems (AHS) are used to direct learners to their target goals. One of the most common AHS designed to help information seekers to overcome the problem of information overload is the Adaptive Education Hypermedia System (AEHS). However, this paper focuses on AEHS that adopts the learning preference of high school students and deliver learning content according to this preference throughout their learning experience. The research developed a prototype system for predicting students’ learning preference from the Visual, Aural, Read-Write and Kinesthetic (VARK) learning style model and adopting the learning content suitable to their preference. The predicting strength of several classifiers was compared and we found Support Vector Machine (SVM) to be more accurate in predicting learning style based on users’ preferences.

Keywords: Hypermedia, adaptive education, learning style, lesson content, user profile, prediction, feedback, adaptive hypermedia, learning style.

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154 An Enhanced AODV Routing Protocol for Wireless Sensor and Actuator Networks

Authors: Apidet Booranawong, Wiklom Teerapabkajorndet

Abstract:

An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.

Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio.

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153 Interfacing Photovoltaic Systems to the Utility Grid: A Comparative Simulation Study to Mitigate the Impact of Unbalanced Voltage Dips

Authors: Badr M. Alshammari, A. Rabeh, A. K. Mohamed

Abstract:

This paper presents the modeling and the control of a grid-connected photovoltaic system (PVS). Firstly, the MPPT control of the PVS and its associated DC/DC converter has been analyzed in order to extract the maximum of available power. Secondly, the control system of the grid side converter (GSC) which is a three-phase voltage source inverter (VSI) has been presented. A special attention has been paid to the control algorithms of the GSC converter during grid voltages imbalances. Especially, three different control objectives are to achieve; the mitigation of the grid imbalance adverse effects, at the point of common coupling (PCC), on the injected currents, the elimination of double frequency oscillations in active power flow, and the elimination of double frequency oscillations in reactive power flow. Simulation results of two control strategies have been performed via MATLAB software in order to demonstrate the particularities of each control strategy according to power quality standards.

Keywords: Renewable energies, photovoltaic systems, DC link, voltage source inverter, space vector SVPWM, unbalanced voltage dips, symmetrical components.

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152 Cloning and Expression of D-Threonine Aldolase from Ensifer arboris NBRC100383

Authors: Sang-Ho Baik

Abstract:

D-erythro-cyclohexylserine (D chiral unnatural β-hydroxy amino acid expected for the synthesis of drug for AIDS treatment. To develop a continuous bioconversion system with whole cell biocatalyst of D-threonine aldolase (D genes for the D-erythro-CHS production, D-threonine aldolase gene was amplified from Ensifer arboris 100383 by direct PCR amplication using two degenerated oligonucleotide primers designed based on genomic sequence of Shinorhizobium meliloti Sequence analysis of the cloned DNA fragment revealed one open-reading frame of 1059 bp and 386 amino acids. This putative D-TA gene was cloned into NdeI and EcoRI (pEnsi His-tag sequence or BamHI (pEnsi-DTA[2]) sequence of the pET21(a) vector. The expression level of the cloned gene was extremely overexpressed by E. coli BL21(DE3) transformed with pEnsi-DTA[1] compared to E. coli BL21(DE3) transformed with pEnsi-DTA[2]. When the cells expressing the wild used for D-TA enzyme activity, 12 mM glycine was successfully detected in HPLC analysis. Moreover, the whole cells harbouring the recombinant D-TA was able to synthesize D-erythro of 0.6 mg/ml in a batch reaction.

Keywords: About four key words or phrases in alphabetical order, separated by commas.

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