Search results for: Instance Recognition Rules

Authors: M. Antonelli, G. Frosini, B. Lazzerini, F. Marcelloni

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In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.

Keywords: computer assisted diagnosis, medical imagesegmentation, shape recognition.

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: Bioassay, machine learning, preprocessing, virtual screen.

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Authors: H. Dornhackl, K. Kadletz, R. Luh, P. Tavolato

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In this paper, we describe the use of formal methods to model malware behaviour. The modelling of harmful behaviour rests upon syntactic structures that represent malicious procedures inside malware. The malicious activities are modelled by a formal grammar, where API calls’ components are the terminals and the set of API calls used in combination to achieve a goal are designated non-terminals. The combination of different non-terminals in various ways and tiers make up the attack vectors that are used by harmful software. Based on these syntactic structures a parser can be generated which takes execution traces as input for pattern recognition.

Keywords: Malware behaviour, modelling, parsing, search, pattern matching.

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Authors: Tadatsugu Kitamoto

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Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: Rough Sets, Rough Neural Networks, Cellular Automata, Image Processing.

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Authors: Ahmed Al-Ani

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Feature selection is an important step in many pattern classification problems. It is applied to select a subset of features, from a much larger set, such that the selected subset is sufficient to perform the classification task. Due to its importance, the problem of feature selection has been investigated by many researchers. In this paper, a novel feature subset search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.

Keywords: Ant Colony Optimization, ant systems, feature selection, pattern recognition.

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Authors: Xun Ge, Jianhua Gong

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ankings for output of Chinese main agricultural commodity in the world for 1978, 1980, 1990, 2000, 2006, 2007 and 2008 have been released in United Nations FAO Database. Unfortunately, where the ranking of output of Chinese cotton lint in the world for 2008 was missed. This paper uses sequential data mining methods with decision rules filling this gap. This new data mining method will be help to give a further improvement for United Nations FAO Database.

Keywords: Ranking, output of the main agricultural commodity, gross domestic product, decision table, information system, data mining, decision rule

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Authors: P. Shunmugapriya, S. Kanmani, P. Jude Fredieric, U. Vignesh, J. Reman Justin, K. Vivek

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Vehicle Routing Problem (VRP) is a complex combinatorial optimization problem and it is quite difficult to find an optimal solution consisting of a set of routes for vehicles whose total cost is minimum. Evolutionary and swarm intelligent (SI) algorithms play a vital role in solving optimization problems. While the SI algorithms perform search, the diversity between the solutions they exploit is very important. This is because of the need to avoid early convergence and to get an appropriate balance between the exploration and exploitation. Therefore, it is important to check how far the solutions are diverse. In this paper, we measure the similarity between solutions, which ABC exploits while optimizing VRP. The similar solutions found are discarded at the end of the iteration and only unique solutions are passed on to the next iteration. The bees of discarded solutions become scouts and they start searching for new solutions. This process is continued and results show that the solution is optimized at lesser number of iterations but with the overhead of computing similarity in all the iterations. The problem instance from Solomon benchmarked dataset has been used for evaluating the presented methodology.

Keywords: ABC algorithm, vehicle routing problem, optimization, Jaccard’s similarity measure.

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Authors: K. A. D. N. K Wimalawarne

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In this paper we introduce a novel kernel classifier based on a iterative shrinkage algorithm developed for compressive sensing. We have adopted Bregman iteration with soft and hard shrinkage functions and generalized hinge loss for solving l1 norm minimization problem for classification. Our experimental results with face recognition and digit classification using SVM as the benchmark have shown that our method has a close error rate compared to SVM but do not perform better than SVM. We have found that the soft shrinkage method give more accuracy and in some situations more sparseness than hard shrinkage methods.

Keywords: Compressive sensing, Bregman iteration, Generalisedhinge loss, sparse, kernels, shrinkage functions

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Authors: Janusz Bobulski, Kamila Pasternak

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Despite many years of effort and research, the problem of waste management is still current. There is a lack of fast and effective algorithms for classifying individual waste fractions. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.

Keywords: Computer vision, environmental protection, image processing, waste management.

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Authors: F. Smach, M. Atri, J. Mitéran, M. Abid

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Face detection and recognition has many applications in a variety of fields such as security system, videoconferencing and identification. Face classification is currently implemented in software. A hardware implementation allows real-time processing, but has higher cost and time to-market. The objective of this work is to implement a classifier based on neural networks MLP (Multi-layer Perceptron) for face detection. The MLP is used to classify face and non-face patterns. The systm is described using C language on a P4 (2.4 Ghz) to extract weight values. Then a Hardware implementation is achieved using VHDL based Methodology. We target Xilinx FPGA as the implementation support.

Keywords: Classification, Face Detection, FPGA Hardware description, MLP.

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Authors: Arash Azizi Mazreah, Mohammad Reza Sahebi, Mohammad T. Manzuri Shalmani

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To help overcome limits to the density of conventional SRAMs and leakage current of SRAM cell in nanoscaled CMOS technology, we have developed a four-transistor SRAM cell. The newly developed CMOS four-transistor SRAM cell uses one word-line and one bit-line during read/write operation. This cell retains its data with leakage current and positive feedback without refresh cycle. The new cell size is 19% smaller than a conventional six-transistor cell using same design rules. Also the leakage current of new cell is 60% smaller than a conventional sixtransistor SRAM cell. Simulation result in 65nm CMOS technology shows new cell has correct operation during read/write operation and idle mode.

Keywords: SRAM Cell, leakage current, cell area.

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Authors: Wataru Yamazaki, Hironori Hiraishi, Fumio Mizoguchi

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In this paper, we describe a rule-based message passing method to support developing collaborative applications, in which multiple users share resources in distributed environments. Message communications of applications in collaborative environments tend to be very complex because of the necessity to manage context situations such as sharing events, access controlling of users, and network places. In this paper, we propose a message communications method based on unification of artificial intelligence and logic programming for defining rules of such context information in a procedural object-oriented programming language. We also present an implementation of the method as java classes.

Keywords: agent programming, logic programming, multi-media application, collaborative application.

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Authors: Pinaki Pratim Acharjya, Esha Dutta

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In image segmentation contour detection is one of the important pre-processing steps in recent days. Contours characterize boundaries and contour detection is one of the most difficult tasks in image processing. Hence it is a problem of fundamental importance in image processing. Contour detection of an image decreases the volume of data considerably and useless information is removed, but the structural properties of the image remain same. In this research, a robust and effective contour detection technique has been proposed using mathematical morphology. Three different contour detection results are obtained by using morphological dilation and erosion. The comparative analyses of three different results also have been done.

Keywords: Image segmentation, contour detection, mathematical morphology.

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Authors: H. N. Suresh, Dr. V. Udaya Shankara

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A technique proposed for the automatic detection of spikes in electroencephalograms (EEG). A multi-resolution approach and a non-linear energy operator are exploited. The signal on each EEG channel is decomposed into three sub bands using a non-decimated wavelet transform (WT). The WT is a powerful tool for multi-resolution analysis of non-stationary signal as well as for signal compression, recognition and restoration. Each sub band is analyzed by using a non-linear energy operator, in order to detect spikes. A decision rule detects the presence of spikes in the EEG, relying upon the energy of the three sub-bands. The effectiveness of the proposed technique was confirmed by analyzing both test signals and EEG layouts.

Keywords: EEG, Spike, SNEO, Wavelet Transform

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Authors: J. Branstett, V. Gagneux, A. Leleu, B. Levadoux, J. Pascale

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This paper presents the interface ConductHome which controls home automation systems with a Leap Motion using “invariant gesture protocols”. This interface is meant to simplify the interaction of the user with its environment. A hardware part allows the Leap Motion to be carried around the house. A software part interacts with the home automation box and displays the useful information for the user. An objective of this work is the development of a natural/invariant/simple gesture control interface to help elder people/people with disabilities.

Keywords: Automation, ergonomics, gesture recognition, interoperability, leap motion, invariant.

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Authors: Sang-Wan Kim, Hoon Lee, Kyung-Ho Choi, Soon-Young Park

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A talking head system (THS) is presented to animate the face of a speaking 3D avatar in such a way that it realistically pronounces the given Korean text. The proposed system consists of SAPI compliant text-to-speech (TTS) engine and MPEG-4 compliant face animation generator. The input to the THS is a unicode text that is to be spoken with synchronized lip shape. The TTS engine generates a phoneme sequence with their duration and audio data. The TTS applies the coarticulation rules to the phoneme sequence and sends a mouth animation sequence to the face modeler. The proposed THS can make more natural lip sync and facial expression by using the face animation generator than those using the conventional visemes only. The experimental results show that our system has great potential for the implementation of talking head for Korean text.

Keywords: Talking head, Lip sync, TTS, MPEG4.

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Authors: Aicha Baya Goumeidane, Nafaa. Nacereddine

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A welded structure must be inspected to guarantee that the weld quality meets the design requirements to assure safety and reliability. However, X-ray image analyses and defect recognition with the computer vision techniques are very complex. Most difficulties lie in finding the small, irregular defects in poor contrast images which requires pre processing to image, extract, and classify features from strong background noise. This paper addresses the issue of designing methodology to extract defect from noisy background radiograph with image processing. Based on the use of actives contours this methodology seems to give good results

Keywords: Welding, Radiography, Computer vision, Active contour.

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Authors: M. Y. Misro, A. Ramli, J. M. Ali

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Bezier curves have useful properties for path generation problem, for instance, it can generate the reference trajectory for vehicles to satisfy the path constraints. Both algorithms join cubic Bezier curve segment smoothly to generate the path. Some of the useful properties of Bezier are curvature. In mathematics, curvature is the amount by which a geometric object deviates from being flat, or straight in the case of a line. Another extrinsic example of curvature is a circle, where the curvature is equal to the reciprocal of its radius at any point on the circle. The smaller the radius, the higher the curvature thus the vehicle needs to bend sharply. In this study, we use Bezier curve to fit highway-like curve. We use different approach to find the best approximation for the curve so that it will resembles highway-like curve. We compute curvature value by analytical differentiation of the Bezier Curve. We will then compute the maximum speed for driving using the curvature information obtained. Our research works on some assumptions; first, the Bezier curve estimates the real shape of the curve which can be verified visually. Even though, fitting process of Bezier curve does not interpolate exactly on the curve of interest, we believe that the estimation of speed are acceptable. We verified our result with the manual calculation of the curvature from the map.

Keywords: Speed estimation, path constraints, reference trajectory, Bezier curve.

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Authors: Chang-Hung Hsu, Chun-Yao Lee, Guan-Lin Liao, Yung-Tsan Jou, Jin-Maun Ho, Yu-Hua Hsieh, Yi-Xing Shen

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This article simulates the wind generator set which has two fault bearing collar rail destruction and the gear box oil leak fault. The electric current signal which produced by the generator, We use Empirical Mode Decomposition (EMD) as well as Fast Fourier Transform (FFT) obtains the frequency range-s signal figure and characteristic value. The last step is use a kind of Artificial Neural Network (ANN) classifies which determination fault signal's type and reason. The ANN purpose of the automatic identification wind generator set fault..

Keywords: Wind-driven generator, Fast Fourier Transform, Neural network

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Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: Automatic design, learning, fuzzy rules, hybrid, swarm optimization.

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Authors: Alan C. Lin, Dean K. Sheu

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This paper aims to study the methodology of building the knowledge of planning adequate punches in order to complete the task of strip layout for shearing processes, using progressive dies. The proposed methodology uses die design rules and characteristics of different types of punches to classify them into five groups: prior use (the punches must be used first), posterior use (must be used last), compatible use (may be used together), sequential use (certain punches must precede some others) and simultaneous use (must be used together). With these five groups of punches, the searching space of feasible designs will be greatly reduced, and superimposition becomes a more effective method of punch layout. The superimposition scheme will generate many feasible solutions, an evaluation function based on number of stages, moment balancing and strip stability is developed for helping designers to find better solutions.

Keywords: Manufacturing systems, advances in metal forming, computer-aided design, progressive die.

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Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.

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Authors: D. I. De Souza, D. R. Fonseca, R. Rocha

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In this paper we will develop further the sequential life test approach presented in a previous article by [1] using an underlying two parameter Weibull sampling distribution. The minimum life will be considered equal to zero. We will again provide rules for making one of the three possible decisions as each observation becomes available; that is: accept the null hypothesis H0; reject the null hypothesis H0; or obtain additional information by making another observation. The product being analyzed is a new type of a low alloy-high strength steel product. To estimate the shape and the scale parameters of the underlying Weibull model we will use a maximum likelihood approach for censored failure data. A new example will further develop the proposed sequential life testing approach.

Keywords: Sequential Life Testing, Underlying Weibull Model, Maximum Likelihood Approach, Hypothesis Testing.

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Authors: Ö. Şenyiğit, A. Çolak

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It is of great importance for an architectural student to know the parameters through which he/she can conduct his/her design and makes his/her design effective in architectural education. Therefore; an empirical application study was carried out through the designing activity using the emulation model to support the design and design approaches of architectural students. During the investigation period, studies were done on the basic design elements and principles of the fall semester, and the emulation model, one of the designing methods that constitute the subject of the study, was fictionalized as three phased “recognition-interpretation-application”. As a result of the study, it was observed that when students were given a key method during the design process, their awareness increased and their aspects improved as well.

Keywords: Basic design, design education, design methods, emulation.

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Authors: M. J. Nassiri, A. Vafaei, A. Monadjemi

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Random and natural textures classification is still one of the biggest challenges in the field of image processing and pattern recognition. In this paper, texture feature extraction using Slant Hadamard Transform was studied and compared to other signal processing-based texture classification schemes. A parametric SHT was also introduced and employed for natural textures feature extraction. We showed that a subtly modified parametric SHT can outperform ordinary Walsh-Hadamard transform and discrete cosine transform. Experiments were carried out on a subset of Vistex random natural texture images using a kNN classifier.

Keywords: Texture Analysis, Slant Transform, Hadamard, DCT.

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Authors: Dewi Nasien, Habibollah Haron, Siti SophiayatiYuhaniz

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This paper presents a comparison of metaheuristic algorithms, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), in producing freeman chain code (FCC). The main problem in representing characters using FCC is the length of the FCC depends on the starting points. Isolated characters, especially the upper-case characters, usually have branches that make the traversing process difficult. The study in FCC construction using one continuous route has not been widely explored. This is our motivation to use the population-based metaheuristics. The experimental result shows that the route length using GA is better than ACO, however, ACO is better in computation time than GA.

Keywords: Handwriting Recognition, Feature Extraction, Freeman Chain Code, Genetic Algorithm and Ant ColonyOptimization.

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Authors: Vahid Rostami, Omid sojodishijani , Saeed Ebrahimijam, Ali MohsenizanjaniNejad

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This paper is described one of the intelligent control method in Autonomous systems, which is called fuzzy control to correct the three wheel omnidirectional robot movement while it make mistake to catch the target. Fuzzy logic is especially advantageous for problems that can not be easily represented by mathematical modeling because data is either unavailable, incomplete or the process is too complex. Such systems can be easily up grated by adding new rules to improve performance or add new features. In many cases , fuzzy control can be used to improve existing traditional controller systems by adding an extra layer of intelligence to the current control method. The fuzzy controller designed here is more accurate and flexible than the traditional controllers. The project is done at MRL middle size soccer robot team.

Keywords: Robocup , omnidirectional , fuzzy control, soccer robot , intelligent control.

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Authors: Erik Vassøy Olsen, Hirpa G. Lemu

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Inspired by the Formula-1 competition, IMechE (Institute of Mechanical Engineers) and Formula SAE (Society of Mechanical Engineers) organize annual competitions for University and College students worldwide to compete with a single-seat racecar they have designed and built. Design of the chassis or the frame is a key component of the competition because the weight and stiffness properties are directly related with the performance of the car and the safety of the driver. In addition, a reduced weight of the chassis has direct influence on the design of other components in the car. Among others, it improves the power to weight ratio and the aerodynamic performance. As the power output of the engine or the battery installed in the car is limited to 80 kW, increasing the power to weight ratio demands reduction of the weight of the chassis, which represents the major part of the weight of the car. In order to reduce the weight of the car, ION Racing team from University of Stavanger, Norway, opted for a monocoque design. To ensure fulfilment of the competition requirements of the chassis, the monocoque design should provide sufficient torsional stiffness and absorb the impact energy in case of possible collision. The study reported in this article is based on the requirements for Formula Student competition. As part of this study, diverse mechanical tests were conducted to determine the mechanical properties and performances of the monocoque design. Upon a comprehensive theoretical study of the mechanical properties of sandwich composite materials and the requirements of monocoque design in the competition rules, diverse tests were conducted including 3-point bending test, perimeter shear test and test for absorbed energy. The test panels were homemade and prepared with equivalent size of the side impact zone of the monocoque, i.e. 275 mm x 500 mm, so that the obtained results from the tests can be representative. Different layups of the test panels with identical core material and the same number of layers of carbon fibre were tested and compared. Influence of the core material thickness was also studied. Furthermore, analytical calculations and numerical analysis were conducted to check compliance to the stated rules for Structural Equivalency with steel grade SAE/AISI 1010. The test results were also compared with calculated results with respect to bending and torsional stiffness, energy absorption, buckling, etc. The obtained results demonstrate that the material composition and strength of the composite material selected for the monocoque design has equivalent structural properties as a welded frame and thus comply with the competition requirements. The developed analytical calculation algorithms and relations will be useful for future monocoque designs with different lay-ups and compositions.

Keywords: Composite material, formula student, ion racing, monocoque design, structural equivalence.

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Authors: Sobia T. Javed, Sarmad Hussain, Ameera Maqbool, Samia Asloob, Sehrish Jamil, Huma Moin

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The electronically available Urdu data is in image form which is very difficult to process. Printed Urdu data is the root cause of problem. So for the rapid progress of Urdu language we need an OCR systems, which can help us to make Urdu data available for the common person. Research has been carried out for years to automata Arabic and Urdu script. But the biggest hurdle in the development of Urdu OCR is the challenge to recognize Nastalique Script which is taken as standard for writing Urdu language. Nastalique script is written diagonally with no fixed baseline which makes the script somewhat complex. Overlap is present not only in characters but in the ligatures as well. This paper proposes a method which allows successful recognition of Nastalique Script.

Keywords: HMM, Image processing, Optical CharacterRecognition, Urdu OCR.

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