Search results for: Automatic loom

Authors: Yue Wang, Jixin Ma, Brian Knight

Abstract:

This paper presents a visualized computer aided case tool for non-expert, called Visual Time, for representing and reasoning about incomplete and uncertain temporal information. It is both expressive and versatile, allowing logical conjunctions and disjunctions of both absolute and relative temporal relations, such as “Before”, “Meets”, “Overlaps”, “Starts”, “During”, and “Finishes”, etc. In terms of a visualized framework, Visual Time provides a user-friendly environment for describing scenarios with rich temporal structure in natural language, which can be formatted as structured temporal phrases and modeled in terms of Temporal Relationship Diagrams (TRD). A TRD can be automatically and visually transformed into a corresponding Time Graph, supported by automatic consistency checker that derives a verdict to confirm if a given scenario is temporally consistent or inconsistent.

Keywords: Time Visualization, Uncertainty, Incompleteness, Consistency Checking.

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Authors: Jung-Eun Park, Kyung-Whan Oh

Abstract:

Intelligent systems are required in order to quickly and accurately analyze enormous quantities of data in the Internet environment. In intelligent systems, information extracting processes can be divided into supervised learning and unsupervised learning. This paper investigates intelligent clustering by unsupervised learning. Intelligent clustering is the clustering system which determines the clustering model for data analysis and evaluates results by itself. This system can make a clustering model more rapidly, objectively and accurately than an analyzer. The methodology for the automatic clustering intelligent system is a multi-agent system that comprises a clustering agent and a cluster performance evaluation agent. An agent exchanges information about clusters with another agent and the system determines the optimal cluster number through this information. Experiments using data sets in the UCI Machine Repository are performed in order to prove the validity of the system.

Keywords: Intelligent Clustering, Multi-Agent System, PCA, SOM, VC(Variance Criterion)

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Authors: Shuo-Li Hsu, Peng-Wei Gau, I-Lin Wu, Jyh-Horng Jeng

Abstract:

For most image fusion algorithms separate relationship by pixels in the image and treat them more or less independently. In addition, they have to be adjusted different parameters in different time or weather. In this paper, we propose a region–based image fusion which combines aspects of feature and pixel-level fusion method to replace only by pixel. The basic idea is to segment far infrared image only and to add information of each region from segmented image to visual image respectively. Then we determine different fused parameters according different region. At last, we adopt artificial neural network to deal with the problems of different time or weather, because the relationship between fused parameters and image features are nonlinear. It render the fused parameters can be produce automatically according different states. The experimental results present the method we proposed indeed have good adaptive capacity with automatic determined fused parameters. And the architecture can be used for lots of applications.

Keywords: Image fusion, Region-based fusion, Segmentation, Neural network, Multi-sensor.

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Authors: Ali Serhan Koyuncugil, Nermin Ozgulbas

Abstract:

In this paper, a data mining model to SMEs for detecting financial and operational risk indicators by data mining is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. In addition, this paper is based on a project which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK).

Keywords: Risk Management, Financial Risk, Operational Risk, Financial Early Warning System, Data Mining, CHAID Decision Tree Algorithm, SMEs.

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Authors: Hae-Yeoun Lee

Abstract:

Mosaic refers to a technique that makes image by gathering lots of small materials in various colors. This paper presents an automatic algorithm that makes the photo-mosaic image using photos. The algorithm is composed of 4 steps: partition and feature extraction, block matching, redundancy removal and color adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.

Keywords: Photo-mosaic, Euclidean distance, Block matching, Intensity adjustment.

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Authors: A. Pashayev, D. Askerov, R. Sadiqov, A. Samedov, C. Ardil

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi-stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Gas turbine, cooled blade, nozzle blade, temperature field.

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

Abstract:

Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: Edge detection, medical MR images, multi-agent systems, vector field convolution.

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Authors: D. Beziakina, E. Bulgakova

Abstract:

The paper deals with cross-gender and cross-linguistic comparison of pitch characteristics for Tuvinian with two other Turkic languages - Uzbek and Azerbaijani, based on the results of statistical analysis of pitch parameter values and intonation patterns used by male and female speakers.

The main goal of our work is to obtain the ranges of pitch parameter values typical for Tuvinian speakers for the purpose of automatic language identification. We also propose a cross-gender analysis of declarative intonation in the poorly studied Tuvinian language.

The ranges of pitch parameter values were obtained by means of specially developed software that deals with the distribution of pitch values and allows us to obtain statistical language-specific pitch intervals.

Keywords: Speech analysis, Statistical analysis, Speaker recognition, Identification of person.

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Authors: Badr Hssina, Belaid Bouikhalene, Abdelkrim Merbouha

Abstract:

This article presents our prototype MASET (Multi Agents System for E-Tutoring Learners engaged in online collaborative work). MASET that we propose is a system which basically aims to help tutors in monitoring the collaborative work of students and their various interactions. The evaluation of such interactions by the tutor is based on the results provided by the automatic analysis of the interaction indicators. This system is predicated upon the middleware JADE (Java Agent Development Framework) and e-learning Moodle platform. The MASET environment is modeled by AUML which allows structuring the different interactions between agents for the fulfillment and performance of online collaborative work. This multi-agent system has been the subject of a practical experimentation based on the interactions data between Master Computer Engineering and System students.

Keywords: AUML, Collaborative work, E-learning, E-tutoring, JADE, Moodle, SMA, Web Agent.

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Authors: E. B. Jo, J. H. Lee, J. Y. Park, S. M. Kim

Abstract:

In this study, we present an advanced detection technique for mass type breast cancer based on texture information of organs. The proposed method detects the cancer areas in three stages. In the first stage, the midpoints of mass area are determined based on AHE (Adaptive Histogram Equalization). In the second stage, we set the threshold coefficient of homogeneity by using MLE (Maximum Likelihood Estimation) to compute the uniformity of texture. Finally, mass type cancer tissues are extracted from the original image. As a result, it was observed that the proposed method shows an improved detection performance on dense breast tissues of Korean women compared with the existing methods. It is expected that the proposed method may provide additional diagnostic information for detection of mass-type breast cancer.

Keywords: Mass Type Breast Cancer, Mammography, Maximum Likelihood Estimation (MLE), Ranklets, SVM

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Authors: Yen-Ting Wang, Kenny Wen-Chyuan Chen, I-Tsun Chiang, Lung-Ching Liang, Alex J.Y. Lee

Abstract:

The aim of this study was to establish the feasibility of a minute incremental exercise testing protocol in young asthma children. Twenty-two children with clinically diagnosed mild to moderate asthma volunteered to participate. The maximum incremental exercise test was performed using a cycle ergometer with an electromagnetic braking. A warm-up unloaded for 2 minutes then the workload was started at 40 watts for 2 minutes, and then stepwise increments of 8 watts per 2 minutes were applied. The pedaling frequency was set at 50 rpm. Ventilation and gas exchange were measured with a breath-by-breath automatic metabolic measurement system. Results showed that this test was well tolerated by all asthmatic children. Most of the children reached the VO2 plateau and satisfied the criteria for maximal respiratory exchange ratio of ≥ 1. This Study demonstrated that this testing protocol was suitable for young asthmatic children.

Keywords: Asthma, Child, Exercise, Pediatrics.

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Authors: S. Abdollahi Pour, M. Saneei

Abstract:

This paper propose a new circuit design which monitor total leakage current during standby mode and generates the optimal reverse body bias voltage, by using the adaptive body bias (ABB) technique to compensate die-to-die parameter variations. Design details of power monitor are examined using simulation framework in 65nm and 32nm BTPM model CMOS process. Experimental results show the overhead of proposed circuit in terms of its power consumption is about 10 μW for 32nm technology and about 12 μW for 65nm technology at the same power supply voltage as the core power supply. Moreover the results show that our proposed circuit design is not far sensitive to the temperature variations and also process variations. Besides, uses the simple blocks which offer good sensitivity, high speed, the continuously feedback loop.

Keywords: leakage current, leakage power monitor, body biasing, low power

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Authors: Mona A. Fouad, Fatma M. Bayoumi, Hoda M. Onsi, Mohamed G. Darwish

Abstract:

Digital libraries become more and more necessary in order to support users with powerful and easy-to-use tools for searching, browsing and retrieving media information. The starting point for these tasks is the segmentation of video content into shots. To segment MPEG video streams into shots, a fully automatic procedure to detect both abrupt and gradual transitions (dissolve and fade-groups) with minimal decoding in real time is developed in this study. Each was explored through two phases: macro-block type's analysis in B-frames, and on-demand intensity information analysis. The experimental results show remarkable performance in detecting gradual transitions of some kinds of input data and comparable results of the rest of the examined video streams. Almost all abrupt transitions could be detected with very few false positive alarms.

Keywords: Adaptive threshold, abrupt transitions, gradual transitions, MPEG video streams.

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Authors: Pei-Jeng Kuo, Terumasa Aoki, Hiroshi Yasuda

Abstract:

PARIS (Personal Archiving and Retrieving Image System) is an experiment personal photograph library, which includes more than 80,000 of consumer photographs accumulated within a duration of approximately five years, metadata based on our proposed MPEG-7 annotation architecture, Dozen Dimensional Digital Content (DDDC), and a relational database structure. The DDDC architecture is specially designed for facilitating the managing, browsing and retrieving of personal digital photograph collections. In annotating process, we also utilize a proposed Spatial and Temporal Ontology (STO) designed based on the general characteristic of personal photograph collections. This paper explains PRAIS system.

Keywords: Ontology, Databases and Information Retrieval, MPEG-7, Spatial-Temporal, Digital Library Designs l, metadata, Semantic Web, semi-automatic annotation

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Authors: Jaqueline M. R. Vieira

Abstract:

Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge dataset configurations.

Keywords: Brazil, classifiers, data-mining, Image Segmentation, oil well visualization, classifiers.

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Authors: Biswajit Biswas

Abstract:

Demand of energy is increasing faster than the generation. It leads shortage of power in all sectors of society. At peak hours this shortage is higher. Unless we utilize energy efficient technology, it is very difficult to minimize the shortage of energy. So energy efficiency program and energy conservation has an important role. Energy efficient technologies are cost intensive hence it is always not possible to implement in country like India. In the recent study, an educational building with operating hours from 10:00 a.m. to 05:00 p.m. has been selected to quantify the possibility of lighting energy conservation. As the operating hour is in daytime, integration of daylight with artificial lighting system will definitely reduce the lighting energy consumption. Moreover the initial investment has been given priority and hence the existing lighting installation was unaltered. An automatic controller has been designed which will be operated as a function of daylight through windows and the lighting system of the room will function accordingly. The result of the study of integrating daylight gave quite satisfactory for visual comfort as well as energy conservation.

Keywords: Lighting energy, energy efficiency, daylight, illumination, energy conservation.

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Authors: А. Pashayev, C. Ardil, D. Askerov, R. Sadiqov, A. Samedov

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Mathematical Modeling, Gas Turbine Blade Cooling, Neural Networks, BIEM and FDM.

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Authors: Yuki. Akiyama, Hiroaki. Sengoku, Ryosuke. Shibasaki

Abstract:

In this study, the locations and areas of commercial accumulations were detected by using digital yellow page data. An original buffering method that can accurately create polygons of commercial accumulations is proposed in this paper.; by using this method, distribution of commercial accumulations can be easily created and monitored over a wide area. The locations, areas, and time-series changes of commercial accumulations in the South Kanto region can be monitored by integrating polygons of commercial accumulations with the time-series data of digital yellow page data. The circumstances of commercial accumulations were shown to vary according to areas, that is, highly- urbanized regions such as the city center of Tokyo and prefectural capitals, suburban areas near large cities, and suburban and rural areas.

Keywords: Commercial accumulations, Spatio-temporal analysis, Urban monitoring, Yellow page data

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

Abstract:

In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: Evolving learning, knowledge extraction, knowledge graph, text mining.

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Authors: Prashanth C.M., K. Chandrashekar Shet

Abstract:

In recent past, the Unified Modeling Language (UML) has become the de facto industry standard for object-oriented modeling of the software systems. The syntax and semantics rich UML has encouraged industry to develop several supporting tools including those capable of generating deployable product (code) from the UML models. As a consequence, ensuring the correctness of the model/design has become challenging and extremely important task. In this paper, we present an approach for automatic verification of protocol model/design. As a case study, Session Initiation Protocol (SIP) design is verified for the property, “the CALLER will not converse with the CALLEE before the connection is established between them ". The SIP is modeled using UML statechart diagrams and the desired properties are expressed in temporal logic. Our prototype verifier “UML-SMV" is used to carry out the verification. We subjected an erroneous SIP model to the UML-SMV, the verifier could successfully detect the error (in 76.26ms) and generate the error trace.

Keywords: Unified Modeling Language, Statechart, Verification, Protocol Design, Model Checking.

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Authors: Dongho Kim, Sung Choi, Kyowoong Pee, Youngsik Cho, Seungwoo Jeong, Soo-Ho Kim

Abstract:

This study is about the orbital TIG welding robot system which travels on the guide rail installed on the pipe, and welds and tracks the pipe seam using the LVS (Laser Vision Sensor) joint profile data. The orbital welding robot system consists of the robot, welder, controller, and LVS. Moreover we can define the relationship between welding travel speed and wire feed speed, and we can make the linear equation using the maximum and minimum amount of weld metal. Using the linear equation we can determine the welding travel speed and the wire feed speed accurately corresponding to the area of weld captured by LVS. We applied this orbital TIG welding robot system to the stainless steel or duplex pipe on DSME (Daewoo Shipbuilding and Marine Engineering Co. Ltd.,) shipyard and the result of radiographic test is almost perfect. (Defect rate: 0.033%).

Keywords: Adaptive welding, automatic welding, Pipe welding, Orbital welding, Laser vision sensor, LVS, welding D/B.

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Authors: Abdulrahman S. Alturki, John S. Loomis

Abstract:

This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: Camera Calibration, Corner Detector, Saddle Points, X-Corners.

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Authors: A. Tellaeche, R. Arana, I.Maurtua

Abstract:

The exhaustive quality control is becoming more and more important when commercializing competitive products in the world's globalized market. Taken this affirmation as an undeniable truth, it becomes critical in certain sector markets that need to offer the highest restrictions in quality terms. One of these examples is the percussion cap mass production, a critical element assembled in firearm ammunition. These elements, built in great quantities at a very high speed, must achieve a minimum tolerance deviation in their fabrication, due to their vital importance in firing the piece of ammunition where they are built in. This paper outlines a machine vision development for the 100% inspection of percussion caps obtaining data from 2D and 3D simultaneous images. The acquisition speed and precision of these images from a metallic reflective piece as a percussion cap, the accuracy of the measures taken from these images and the multiple fabrication errors detected make the main findings of this work.

Keywords: critical tolerance, high speed decision makingsimultaneous 2D/3D machine vision.

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Authors: A. Pashayev, D. Askerov, R.Sadiqov, A. Samedov, C. Ardil

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade

Keywords: multiconnected systems, method of the boundary integrated equations, splines, neural networks.

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Authors: A. Pashayev, D. Askerov, C. Ardil, R. Sadiqov

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi-stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Multiconnected systems, method of the boundary integrated equations, splines, neural networks.

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Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai

Abstract:

Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.

Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.

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Authors: Sarra Roubi, Mohammed Erramdani, Samir Mbarki

Abstract:

This paper presents an approach for the model-driven generating of Rich Internet Application (RIA) focusing on the graphical aspect. We used well known Model-Driven Engineering (MDE) frameworks and technologies, such as Eclipse Modeling Framework (EMF), Graphical Modeling Framework (GMF), Query View Transformation (QVTo) and Acceleo to enable the design and the code automatic generation of the RIA. During the development of the approach, we focused on the graphical aspect of the application in terms of interfaces while opting for the Model View Presenter pattern that is designed for graphics interfaces. The paper describes the process followed to define the approach, the supporting tool and presents the results from a case study.

Keywords: Code generation, Design Pattern, metamodel, Model Driven Engineering, MVP, Rich Internet Application, transformation, User Interface.

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Authors: Bremananth R, Nithya B, Saipriya R

Abstract:

The proposed system identifies the species of the wood using the textural features present in its barks. Each species of a wood has its own unique patterns in its bark, which enabled the proposed system to identify it accurately. Automatic wood recognition system has not yet been well established mainly due to lack of research in this area and the difficulty in obtaining the wood database. In our work, a wood recognition system has been designed based on pre-processing techniques, feature extraction and by correlating the features of those wood species for their classification. Texture classification is a problem that has been studied and tested using different methods due to its valuable usage in various pattern recognition problems, such as wood recognition, rock classification. The most popular technique used for the textural classification is Gray-level Co-occurrence Matrices (GLCM). The features from the enhanced images are thus extracted using the GLCM is correlated, which determines the classification between the various wood species. The result thus obtained shows a high rate of recognition accuracy proving that the techniques used in suitable to be implemented for commercial purposes.

Keywords: Correlation, Grey Level Co-Occurrence Matrix, ProbabilityDensity Function, Wood Recognition.

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Authors: S. Cherif, S. Marcos, M. Jaidane

Abstract:

In this paper the behavior of the decision feedback equalizers (DFEs) adapted by the decision-directed or the constant modulus blind algorithms is presented. An analysis of the error surface of the corresponding criterion cost functions is first developed. With the intention of avoiding the ill-convergence of the algorithm, the paper proposes to modify the shape of the cost function error surface by using a soft decision instead of the hard one. This was shown to reduce the influence of false decisions and to smooth the undesirable minima. Modified algorithms using the soft decision during a pseudo-training phase with an automatic switch to the properly tracking phase are then derived. Computer simulations show that these modified algorithms present better ability to avoid local minima than conventional ones.

Keywords: Blind DFEs, decision-directed algorithm, constant modulus algorithm, cost function analysis, convergence analysis, soft decision.

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Authors: Arash Habibi Lashkari, Azizah Abdul Manaf, Maslin Masrom

Abstract:

In today's day and age, one of the important topics in information security is authentication. There are several alternatives to text-based authentication of which includes Graphical Password (GP) or Graphical User Authentication (GUA). These methods stems from the fact that humans recognized and remembers images better than alphanumerical text characters. This paper will focus on the security aspect of GP algorithms and what most researchers have been working on trying to define these security features and attributes. The goal of this study is to develop a fuzzy decision model that allows automatic selection of available GP algorithms by taking into considerations the subjective judgments of the decision makers who are more than 50 postgraduate students of computer science. The approach that is being proposed is based on the Fuzzy Analytic Hierarchy Process (FAHP) which determines the criteria weight as a linear formula.

Keywords: Graphical Password, Authentication Security, Attack Patterns, Brute force attack, Dictionary attack, Guessing Attack, Spyware attack, Shoulder surfing attack, Social engineering Attack, Password Entropy, Password Space.

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