Search results for: popular matching

Authors: Hirotaka Watanabe, Takaaki Kondo, Daiki Yoshida, Ariyoshi Nakayama, Taichi Sato, Shuhei Kuriyama, Hiroyuki Kamata

Abstract:

In this paper, we propose a chaotic cipher system consisting of Improved Volterra Filters and the mapping that is created from the actual voice by using Radial Basis Function Network. In order to achieve a practical system, the system supposes to use the digital communication line, such as the Internet, to maintain the parameter matching between the transmitter and receiver sides. Therefore, in order to withstand the attack from outside, it is necessary that complicate the internal state and improve the sensitivity coefficient. In this paper, we validate the robustness of proposed method from three perspectives of "Chaotic properties", "Randomness", "Coefficient sensitivity".

Keywords: Chaos cipher, 16-bit-length fixed point arithmetic, Volterra filter, Seacret communications, RBF Network

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Authors: Jun Luo, Weiguo Zhang., Dabin Qin

Abstract:

It is important to retain customer satisfaction in information technology services. When a service failure occurs, companies need to take service recovery action to recover their customer satisfaction. Although companies cannot avoid all problems and complaints, they should try to make up. Therefore, service failure and service recovery have become an important and challenging issue for companies. In this paper, the literature and the problems in the information technology services were reviewed. An integrated model of profit driven for the service failure and service recovery was established in view of the benefit of customer and enterprise. Moreover, the interaction between service failure and service recovery strategy was studied, the result of which verified the matching principles of the service recovery strategy and the type of service failure. In addition, the relationship between the cost of service recovery and customer-s cumulative value of service after recovery was analyzed with the model. The result attributes to managers in deciding on appropriate resource allocations for recovery strategies.

Keywords: service failure, service recovery, informationtechnology services

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Authors: P. Cermak

Abstract:

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimization of their parameters with using genetic algorithms in development system FUZNET. Finally, extraction Social, Group and Individual Mind from Multiple Agents Rule Bases are provided by Cognitive analysis and Matching criterion.

Keywords: Mind, Multi-agent system, Cognitive analysis, Fuzzy system, Neural network, Genetic algorithm, Rule base.

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Authors: Chia-Jung Tsai, Shin-Shin Kao

Abstract:

The hypercube Qn is one of the most well-known and popular interconnection networks and the k-ary n-cube Qk n is an enlarged family from Qn that keeps many pleasing properties from hypercubes. In this article, we study the panpositionable hamiltonicity of Qk n for k ≥ 3 and n ≥ 2. Let x, y of V (Qk n) be two arbitrary vertices and C be a hamiltonian cycle of Qk n. We use dC(x, y) to denote the distance between x and y on the hamiltonian cycle C. Define l as an integer satisfying d(x, y) ≤ l ≤ 1 2 |V (Qk n)|. We prove the followings: • When k = 3 and n ≥ 2, there exists a hamiltonian cycle C of Qk n such that dC(x, y) = l. • When k ≥ 5 is odd and n ≥ 2, we request that l /∈ S where S is a set of specific integers. Then there exists a hamiltonian cycle C of Qk n such that dC(x, y) = l. • When k ≥ 4 is even and n ≥ 2, we request l-d(x, y) to be even. Then there exists a hamiltonian cycle C of Qk n such that dC(x, y) = l. The result is optimal since the restrictions on l is due to the structure of Qk n by definition.

Keywords: Hamiltonian, panpositionable, bipanpositionable, k-ary n-cube.

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Authors: Rahmatollah Hooshmand, Mahdi Banejad

Abstract:

One of the problems in fault diagnosis of transformer based on dissolved gas, is lack of matching the result of fault diagnosis of different standards with the real world. In this paper, the result of the different standards is analyzed using fuzzy and the result is compared with the empirical test. The comparison between the suggested method and existing methods indicate the capability of the suggested method in on-line fault diagnosis of the transformers. In addition, in some cases the existing standards are not able to diagnose the fault. In theses cases, the presented method has the potential of diagnosing the fault. The information of three transformers is used to the show the capability of the suggested method in diagnosing the fault. The results validate the capability of the presented method in fault diagnosis of the transformer.

Keywords: Fault Diagnosis of Transformer, Dissolved Gas, Fuzzy Logic.

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Authors: Sh. Ladan, A. Yari, H. Khodabandeh

Abstract:

The need for Information Security in organizations, regardless of their type and size, is being addressed by emerging standards and recommended best practices. The various standards and practices which evolved in recent years and are still being developed and constantly revised, address the issue of Information Security from different angles. This paper attempts to provide an overview of Information Security Standards and Practices by briefly discussing some of the most popular ones. Through a comparative study of their similarities and differences, some insight can be obtained on how their combination may lead to an increased level of Information Security.

Keywords: Information security management, information security standard, BS7799, ISO 17799, COBIT.

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Authors: Sara El Manar El Bouanani, Ismail Kassou

Abstract:

Our objective in this paper is to propose an approach capable of clustering web messages. The clustering is carried out by assigning, with a certain probability, texts written by the same web user to the same cluster based on Stylometric features and using fuzzy clustering algorithms. Focus in the present work is on comparing the most popular algorithms in fuzzy clustering theory namely, Fuzzy C-means, Possibilistic C-means and Fuzzy Possibilistic C-Means.

Keywords: Authorship detection, fuzzy clustering, profiling, stylometric features.

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Authors: Dr. Wendy Wang, Dr. Sigalit Ronen

Abstract:

Telecommuting has become an increasingly popular work arrangement. However, little research has examined the impact of telecommuting on the relationship between employees and the organization. This study aims to shed light on this aspect by comparing the loyalty of telecommuters and non telecommuters as it can be viewed from three angles: organizational loyalty, peer loyalty, and professional loyalty. Furthermore, this paper will explore the dynamics among employee loyalty, productivity, and job satisfaction. Whereas previous studies had looked on employees that are not fully telecommuting, the current study concentrates on employees that are exclusively working from home.

Keywords: loyalty, productivity, satisfaction, telecommuting

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Authors: Yannick Verbelen, Tim Dekegel, Ann Peeters, Klara Stinders, Niek Blondeel, Sam De Winne, An Braeken, Abdellah Touhafi

Abstract:

Matching an embedded electronic application with a cantilever vibration energy harvester remains a difficult endeavour due to the large number of factors influencing the output power. In the presented work, complementary balanced energy harvester parametrization is used as a methodology for simplification of harvester integration in electronic applications. This is achieved by a dual approach consisting of an adaptation of the general parametrization methodology in conjunction with a straight forward harvester benchmarking strategy. For this purpose, the design and implementation of a suitable user friendly cantilever energy harvester benchmarking platform is discussed. Its effectiveness is demonstrated by applying the methodology to a commercially available Mide V21BL vibration energy harvester, with excitation amplitude and frequency as variables.

Keywords: Energy harvesting, vibrations, piezoelectric transducers, embedded systems, harvester parametrization.

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Authors: A. Jalal, S. Kim

Abstract:

Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

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Authors: Brigitte Rafael, Stefan M. Oertl

Abstract:

Music segmentation is a key issue in music information retrieval (MIR) as it provides an insight into the internal structure of a composition. Structural information about a composition can improve several tasks related to MIR such as searching and browsing large music collections, visualizing musical structure, lyric alignment, and music summarization. The authors of this paper present the MTSSM framework, a twolayer framework for the multi-track segmentation of symbolic music. The strength of this framework lies in the combination of existing methods for local track segmentation and the application of global structure information spanning via multiple tracks. The first layer of the MTSSM uses various string matching techniques to detect the best candidate segmentations for each track of a multi-track composition independently. The second layer combines all single track results and determines the best segmentation for each track in respect to the global structure of the composition.

Keywords: Pattern Recognition, Music Information Retrieval, Machine Learning.

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Authors: Yi Zhang, Quan Zhou, Jun Li, Yanlang Hu

Abstract:

Scheduling algorithm is a key technology in satellite switching system with input-buffer. In this paper, a new scheduling algorithm and its realization are proposed. Based on Crossbar switching fabric, the algorithm adopts serial scheduling strategy and adjusts the output port arbitrating strategy for the better equity of every port. Consequently, it increases the matching probability. The algorithm can greatly reduce the scheduling delay and cell loss rate. The analysis and simulation results by OPNET show that the proposed algorithm has the better performance than others in average delay and cell loss rate, and has the equivalent complexity. On the basis of these results, the hardware realization and simulation based on FPGA are completed, which validate the feasibility of the new scheduling algorithm.

Keywords: Scheduling algorithm, input-buffer, serial scheduling, hardware design.

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Authors: Irene Luque Ruiz, Manuel Urbano Cuadrado, Miguel Ángel Gómez-Nieto

Abstract:

In this paper we study different similarity based approaches for the development of QSAR model devoted to the prediction of activity of antiobesity drugs. Classical similarity approaches are compared regarding to dissimilarity models based on the consideration of the calculation of Euclidean distances between the nonisomorphic fragments extracted in the matching process. Combining the classical similarity and dissimilarity approaches into a new similarity measure, the Approximate Similarity was also studied, and better results were obtained. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting of inhibitory activity of drugs. Acceptable results were obtained for the models presented here.

Keywords: Graph similarity, Nonisomorphic dissimilarity, Approximate similarity, Drugs activity prediction.

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Authors: Yoonsoo Kim

Abstract:

This paper introduces an open-source software package SCILAB [1], an alternative of MATLAB [2], which can be used for robust control design and analysis of a typical mass-spring-damper (MSD) system. Using the previously published ideas in [3,4], this popular mechanical system is considered to provide another example of usefulness of SCILAB for advanced control design.

Keywords: Robust Control, SCILAB, Mass-Spring-Damper(MSD).

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Authors: O. Abusaeeda, J. P. O Evans, D. Downes

Abstract:

We demonstrate the synthesis of intermediary views within a sequence of color encoded, materials discriminating, X-ray images that exhibit animated depth in a visual display. During the image acquisition process, the requirement for a linear X-ray detector array is replaced by synthetic image. Scale Invariant Feature Transform, SIFT, in combination with material segmented morphing is employed to produce synthetic imagery. A quantitative analysis of the feature matching performance of the SIFT is presented along with a comparative study of the synthetic imagery. We show that the total number of matches produced by SIFT reduces as the angular separation between the generating views increases. This effect is accompanied by an increase in the total number of synthetic pixel errors. The trends observed are obtained from 15 different luggage items. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, view synthesis, KDE

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Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

Abstract:

Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN.

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Authors: M. Habchi, S. M. Mesli, M. Kotbi

Abstract:

A structural study of an aqueous electrolyte whose experimental results are available. It is a solution of LiCl-6H2O type at glassy state (120K) contrasted with pure water at room temperature by means of Partial Distribution Functions (PDF) issue from neutron scattering technique. Based on these partial functions, the Reverse Monte Carlo method (RMC) computes radial and angular correlation functions which allow exploring a number of structural features of the system. The obtained curves include some artifacts. To remedy this, we propose to introduce a screened potential as an additional constraint. Obtained results show a good matching between experimental and computed functions and a significant improvement in PDFs curves with potential constraint. It suggests an efficient fit of pair distribution functions curves.

Keywords: RMC simulation; Screened potential; partial and pair distribution functions; glassy and liquid state

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Authors: Y.Chakrapani, K.Soundera Rajan

Abstract:

In this paper a hybrid technique of Genetic Algorithm and Simulated Annealing (HGASA) is applied for Fractal Image Compression (FIC). With the help of this hybrid evolutionary algorithm effort is made to reduce the search complexity of matching between range block and domain block. The concept of Simulated Annealing (SA) is incorporated into Genetic Algorithm (GA) in order to avoid pre-mature convergence of the strings. One of the image compression techniques in the spatial domain is Fractal Image Compression but the main drawback of FIC is that it involves more computational time due to global search. In order to improve the computational time along with acceptable quality of the decoded image, HGASA technique has been proposed. Experimental results show that the proposed HGASA is a better method than GA in terms of PSNR for Fractal image Compression.

Keywords: Fractal Image Compression, Genetic Algorithm, HGASA, Simulated Annealing.

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Authors: G. Poonkuzhali, K.Thiagarajan, K.Sarukesi, G.V.Uma

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The emergence of the Internet has brewed the revolution of information storage and retrieval. As most of the data in the web is unstructured, and contains a mix of text, video, audio etc, there is a need to mine information to cater to the specific needs of the users without loss of important hidden information. Thus developing user friendly and automated tools for providing relevant information quickly becomes a major challenge in web mining research. Most of the existing web mining algorithms have concentrated on finding frequent patterns while neglecting the less frequent ones that are likely to contain outlying data such as noise, irrelevant and redundant data. This paper mainly focuses on Signed approach and full word matching on the organized domain dictionary for mining web content outliers. This Signed approach gives the relevant web documents as well as outlying web documents. As the dictionary is organized based on the number of characters in a word, searching and retrieval of documents takes less time and less space.

Keywords: Outliers, Relevant document, , Signed Approach, Web content mining, Web documents..

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Authors: Manasi Pathade, Prachi Kadam, Renuka Kulkarni, Tejas Teredesai

Abstract:

In this paper, we propose a novel concept of relative distance measurement using Stereo Vision Technology and discuss its implementation on a FPGA based real-time image processor. We capture two images using two CCD cameras and compare them. Disparity is calculated for each pixel using a real time dense disparity calculation algorithm. This algorithm is based on the concept of indexed histogram for matching. Disparity being inversely proportional to distance (Proved Later), we can thus get the relative distances of objects in front of the camera. The output is displayed on a TV screen in the form of a depth image (optionally using pseudo colors). This system works in real time on a full PAL frame rate (720 x 576 active pixels @ 25 fps).

Keywords: Stereo Vision, Relative Distance Measurement, Indexed Histogram, Real time FPGA Image Processor

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Authors: Sotiris B. Kotsiantis

Abstract:

Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.

Keywords: Regressors, statistical learning.

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Authors: Chen-Chien Hsu, Guo-Tang Dai

Abstract:

This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

Keywords: multiple object tracking, particle swarm optimization, gray-level histogram, image

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Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

Abstract:

The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: Group formation, group commerce, mobile commerce, So-Lo-Mo, social influence.

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Authors: M. M. Mortula

Abstract:

Bottle water is getting very popular all through the world; especially in the gulf countries as the main source of drinking water. However, concerns over leaching of toxic chemicals are increasing. In this study, a health risk assessment was conducted in accordance with the guidelines indicated by United States Environmental Protection Agency (USEPA). It is conducted based on leaching of Diethyl Phthalate (DEP) from Polyethylene terephthalate (PET). The toxicity and exposure assessment of diethyl phthalate was conducted to characterize its risk on human health. Risk management is also discussed.

Keywords: Toxicity, diethyl phthalate, PET, risk Assessment.

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Authors: Marzieh. Savoj, S. Amirhassan. Monadjemi

Abstract:

Iris localization is a very important approach in biometric identification systems. Identification process usually is implemented in three levels: iris localization, feature extraction, and pattern matching finally. Accuracy of iris localization as the first step affects all other levels and this shows the importance of iris localization in an iris based biometric system. In this paper, we consider Daugman iris localization method as a standard method, propose a new method in this field and then analyze and compare the results of them on a standard set of iris images. The proposed method is based on the detection of circular edge of iris, and improved by fuzzy circles and surface energy difference contexts. Implementation of this method is so easy and compared to the other methods, have a rather high accuracy and speed. Test results show that the accuracy of our proposed method is about Daugman method and computation speed of it is 10 times faster.

Keywords: Convolution, Edge detector filter, Fuzzy circle, Identification

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Authors: S. Balaji, M. Rajaram, Y. Harold Robinson, E. Golden Julie

Abstract:

Delay Tolerant Networks (DTN) which have sufficient state information include trajectory and contact information, to protect routing efficiency. However, state information is dynamic and hard to obtain without a global and/or long-term collection process. To deal with these problems, the internal social features of each node are introduced in the network to perform the routing process. This type of application is motivated from several human contact networks where people contact each other more frequently if they have more social features in common. Two unique processes were developed for this process; social feature extraction and multipath routing. The routing method then becomes a hypercube–based feature matching process. Furthermore, the effectiveness of multipath routing is evaluated and compared to that of single-path routing.

Keywords: Delay tolerant networks, entropy, human contact networks, hyper cubes, multipath Routing, social features.

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Authors: Liheng Ying, Guangjiong Sun

Abstract:

The intent of this essay is to evaluate the effectiveness of surge suppressor aimed at power supply used for automation devices in power distribution system which is consist of MOV and T type low-pass filter. Books, journal articles and e-sources related to surge protection of power supply used for automation devices in power distribution system were consulted, and the useful information was organized, analyzed and developed into five parts: characteristics of surge wave, protection against surge wave, impedance characteristics of target, using Matlab to simulate circuit response after 5kV,1.2/50s surge wave and suggestions for surge protection. The results indicate that various types of load situation have great impact on the effectiveness of surge protective device. Therefore, type and parameters of surge protective device need to be carefully selected, and load matching is also vital to be concerned.

Keywords: automation devices in power distribution system, MOV, surge, T type low-pass filter.

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Authors: Mourad Moussa, Ali Douik, Hassani Messaoud

Abstract:

In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.

Keywords: Image segmentation, objects tracking, Parzen window, singular value decomposition, target recognition.

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Authors: Pradeep Singh, Sukhwinder Singh, Gurjinder Kaur

Abstract:

In recent years, rapid advances in software and hardware in the field of information technology along with a digital imaging revolution in the medical domain facilitate the generation and storage of large collections of images by hospitals and clinics. To search these large image collections effectively and efficiently poses significant technical challenges, and it raises the necessity of constructing intelligent retrieval systems. Content-based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images[5]. Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes.

Keywords: Classification, clustering, content-based image retrieval (CBIR), relevance feedback (RF), statistical similarity matching, support vector machine (SVM).

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Authors: Sahilu Wendeson, Wan Fatimah Bt. Wan Ahmad, Nazleeni Samiha Bt. Haron

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Mobile learning (M-learning) is the current technology that is becoming more popular. It uses the current mobile and wireless computing technology to complement the effectiveness of traditional learning process. The objective of this paper is presents a survey from 90 undergraduate students of Universiti Teknologi PETRONAS (UTP), to identify the students- perception on Mlearning. From the results, the students are willing to use M-learning. The acceptance level of the students is high, and the results obtained revealed that the respondents almost accept M-learning as one method of teaching and learning process and also able to improve the educational efficiency by complementing traditional learning in UTP.

Keywords: M-learning, Traditional learning, WirelessTechnology.

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