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Malaysia is one of the classic examples of a multi-ethnic society. The country is proud of its multiracial culture which makes it a model for other countries. The ubiquitous community hall in the Malaysian landscape, as it stands now, has long passed its time of usefulness. These halls are labelled with names like dewan serbaguna, dewan orang ramai or even balai raya. But as it stands today, the community hall in our midst is nothing more than a large empty space used for games like badminton or ping pong and the occa-sional event. The changing modern Malaysian society demands more of this simple out-dated facility; there must be a place for the various ethnic groups to meet and fulfil modern needs such as family days, health checks, child’s play, music lessons and many more important uses This paper strives to identify and analyse some of the architectural problems in current community centres in Malaysia with the focus on the spatial aspects and space usage. It is expected that this paper can give a clear picture of the problems faced by Malaysian community centres with some considerations and a framework to develop a new scheme for community centre development in the future.

In this paper, we present a ground robotic system which is developed to deal with rough outdoor conditions. The platform is to be used as an environmental monitoring robot for 2 main application areas: - Humanitarian demining: The vehicle is equipped with a specialized multi-channel metal detector array. An unmanned aerial system supports it for locating suspected locations of mines, which can then be confirmed by the ground vehicle. - Search and rescue: The vehicle is equipped with human victim detection sensors and a 3D camera enabling it to assess the traversability of the terrain in front of the robot in order to be able to navigate autonomously. The paper discusses both the mechanical design of these platforms as the autonomous perception capabilities on board of these vehicles.

The theory of linguistic dynamic system (LDS) focuses on modeling, analysis, control and evaluation of complex systems at a linguistic level through computing with words. The concepts, frameworks and methods in conventional dynamic systems (CDS) are adopted in research of LDS. This paper is concerned about linguistic controller design of LDS upon cell mapping concept. In view of the studies of controller design for type-I and type-II LDS and optimal fuzzy controller design and tuning methods based on cell-to-cell mapping, two approaches to construct optimal linguistic controller for LDS using cell-to-cell mapping techniques are outlined in this paper.

Automatic seal imprint identification system is highly demanded in oriental countries. Even though several seal identification techniques have been proposed, it is seldom to find the papers on the recovery of lost seal imprint strokes caused by superimposition. In this paper, a new seal verification for Chinese color seal is proposed. This approach segments the seal imprint from the input image in terms of the adaptive thresholds. The lost seal imprint strokes are recovered based on the text stroke width that can be detected automatically. In addition, the moment-based seal verification is to compare the reference seal imprint and the recovered one. Experimental results show that the proposed method is able to correctly and efficiently verify the genuine and forgery seal imprint.

The challenging for buyers around the globe to identify good quality of Durian. For several kinds of Durian, it may be difficult for buyers to determine the Durian quality by appearance. The ability to select only good quality Durian without cutting or cleaving is useful because buyers will not waste money ordering undesirable Durian.This paper proposes a nondestructive technique to determine the stages of maturity of durian fruits. The presented methodology utilizes the concept of pattern matching. We used the local knocking equipment to knock the durian for knocked-sound. After that the knocked-sound was analyzed and generated to Mel-frequency cepstral coefficients (MFCCs) that is used to train data for the classifier. Feed-Forward Neural Network was used for the classifier and can effectively classification the stages of maturity of durian fruits with accuracy rate more than 82%.

Finger clubbing, also known as drumstick finger, is the medical symptom that is indicated by the development of the sponginess or swelling in the nail beds of nails and toes. The higher grade of clubbing on the patients can be easily identified with the presence of drumstick finger. The existing available measurement device to identify the early stage of clubbing required much time which is impractical for a busy clinic practice. This paper explains the determination of the finger clubbing by using the Digital Index (DI) measurement, which was deployed by implementing and developing the Portable Finger Clubbing Meter hardware and the Microsoft Visual Basic (VB) Graphical User Interface (GUI). Finger circumference values of nail-fold (NF) and distal interphalangeal joint (DIP) of twenty participants were measured using the developed hardware. Data analysis was then performed using the GUI for DI computation, and the presence of finger clubbing could be determined.

Application of Fast Fourier Transform (FFT) in machinery faults detection is known to be only effective if fault is of repetitive in nature and considering severe. While minor and transient faults are usually remain undetected based on vibration spectrum analysis. Wavelet analysis is relatively new technique which is still suffered from inadequately in its time-frequency resolution. In this paper, ahmedrabak_time wavelet is proposed based on the wavelet reassignment technique for Morlet mother wavelet. The proposed wavelet analysis is compared to the conventional wavelet analysis for machinery faults detection based on simulated signal. The results showed that the proposed wavelet has a better resolution than conventional wavelet analysis which could clearly indicate the presence and the location of the fault.

In agriculture industry, natural produce classification is used in sorting, grading, measuring, and pricing. Currently, a lot of methods have been developed using computer vision to replace human expert in natural produce classification. However, some of the method used long features descriptor and complex classifier to obtain high classification rate. This paper proposes natural produce classification method using computer vision based on simple statistical color features and derivative of radius function. The k-nearest neighbors (k-NN) and artificial neural network (ANN) were used to classify the produce based on the extracted features. Preliminary experiment results show that the proposed method achieved best result with average classification accuracy of 99.875% using ANN classifier with nine nodes in hidden layer.

Machines are the heart of most industries. By ensuring the health of machines, one could easily increase the company revenue and eliminates any safety threat related to machinery catastrophic failures. In condition monitoring (CM), questions often arise during decision making time whether the machine is still safe to run or not? Traditional CM approach depends heavily on human interpretation of results whereby decision is made solely based on the individual experience and knowledge about the machines. The advent of artificial intelligence (AI) and automated ways for decision making in CM provides a more objective and unbiased approach for CM industry and has become a topic of interest in the recent years. This paper reviews the techniques used for automated decision making in CM with emphasis given on Dempster-Shafer (D-S) evident theory and other basic probability assignment (BPA) techniques such as support vector machine (SVM) and etc.

This paper presents experimental results of object handling motions to evaluate tactile slippage sensation in a multi fingered robot arm with optical three-axis tactile sensors installed on its two hands. The optical three-axis tactile sensor is a type of tactile sensor capable of defining normal and shear forces simultaneously. Shear force distribution is used to define slippage sensation in the robot hand system. Based on tactile slippage analysis, a new control algorithm was proposed. To improve performance during object handling motions, analysis of slippage direction is conducted. The control algorithm is classified into two phases: grasp-move-release and grasp-twist motions. Detailed explanations of the control algorithm based on the existing robot arm control system are presented. The experiment is conducted using a bottle cap, and the results reveal good performance of the proposed control algorithm to accomplish the proposed object handling motions.

[EN] Soccer robots have been frequently used to validate models of multi-agent systems, involving collaboration among the agents. For this purpose, many researchers in robotics have been developing robotic soccer teams which compete in events such as RoboCup. This paper presents a strategy model for multi-robot coordination in robotic soccer teams involving ball position, team member position and opponent position for the selection of a team tactic and the player roles. This assignation is dynamical and achieved by a virtual coach. This strategy model was validated in a RoboCup Small Size League environment using Webots robot simulator, This project is partially funded by the Ministry of Higher Education Malaysia under the grant number 600-RMI/ERGS 5/3 (23/2011)

The Internet accelerates the communication and understandings between people, which make information unprecedented important. Furthermore, it changes the way that people book rooms, which makes rooms-booking diversified, convenient, and individualized. Out of the demand of modern hotels and based on the B/S model, this paper analyzes and designs the hotel booking operation, and achieves the functions of register, login-in, reservation, customer management, and reservation management, and etc., in order to improve the efficiency of hotel reservation. 1 Grants: This study is financially support by the following foundations: Young Talents in Colleges of Anhui Province under Grant No. 2011SQRW107, National Natural Science Foundation of China under Grant No.70871032, and Humanity and Social Science Foundation of Ministry of Education of China under Grant No. 09YJA630029. About the authors: Hu Ping (1979-), female, born in Jiujiang, Jiangxi Province, master, lecturer, her current areas of research interest includes E-Government, information system and managerial innovation. Contact: 13365609125 (0551-62158118), huping@hfuu.edu.cn, Department of Management at Hefei University, 373 Fairview Avenue, Hefei 230022, P.R. CHINBA

In the security monitoring system, in order to realize the multi-angle and different positions of the camera monitoring the camera monitoring, a pan tilt zoom (PTZ) module is used. This paper describes the PELCO-D protocol of PTZ and serial communication firstly. Then it achieves control the of PTZ and lens work based on Windows VC++. Finally, It discusses the main function of the system structure and coding.

This paper presents a novel Dempster-Shafer evidence construction approach for aircraft aim recognition. The prior-probability of the properties of aircraft was used for establishing a probabilistic argumentation system. Dempster-Shafer evidence was constructed by assumption-based reasoning. Therefore, additional information could be provided to the classification of the data fusion system. Experiments on artificial and real data demonstrated that the proposed method could improve the classification results.

Distributed optical fiber sensor can acquire the information of physical field along time and spatial continuous distribution. It plays an important role in long-distance oil and electricity transmission and security. In this paper, the author introduced the universal steps in triggering pattern recognition, which includes signal characteristics extracting by accurate endpoint detecting, templates establishing by training, and pattern matching. By training the samples acquired in the laboratory, three templates are established. And pattern matching had been done between templates and all the samples. The results show that, 87.5 percent of the samples are matched correctly with the triggering patterns they are belonging to.

In order to improve the fault diagnosis precision of electron system, a method based on wavelet packet transform and SVM was proposed. Fault diagnosis method based on SVM was researched on in this paper because of the complexity of electron system, difficulty of fault diagnosis method and special advantages of SVM. Wavelet packet transform is used to extract fault features from the signal of the circuit output voltage. The specific feature extraction method is introduced. Improved QPSO algorithm was proposed to improve the training speed and class precision of SVM. At last the method mentioned above was applied to a circuit. The result showed that this method was very good.

This paper aims to present a first part of research carried out on pneumatic muscles. The first applications of these actuators were in the innovative research areas as: rehabilitation medical equipments, prosthesis, robotics and exoskeletons. Despite of a large number of applications, theoretical and experimental research in this area are not many, due to there complex structure in which are used new materials, a combination synthetic rubber membrane and polymers fibers. In this article will be presented the experimental results of a specific pneumatic muscle based on which it will be realized a mathematical model to describe its behavior and to determine the parameters that influence largely static and dynamic feature.

This paper describes hybrid multivariate methods: Fisher’s Discriminant Analysis and Principal Component Analysis improved by Genetic Algorithm. These methods are good techniques that have been used to detect faults during the operation of industrial processes. In this study, score and residual space of modified PCA and modified FDA are applied to the Tennessee Eastman Process simulator and show that modified PCA and modified FDA are more proficient than PCA and FDA for detecting faults.

RETRACTED PAPER: A method of tool wear intelligence measure based on Discrete Hidden Markov Models (DHMM) is proposed to monitor tool wear and to predict tool failure. FFT features are first extracted from the vibration signal and cutting force in cutting process, and then FFT vectors are presorted and converted into integers by SOM. Finally, these codes are introduced to DHMM for machine learning and 3 models for different tool wear stage are built up. Pattern of HMM is recognised by calculating probability. The results of tool wear intelligence measure and pattern recognition of tool wear experiments show that the method is effective.