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International Review on Computers and Software  Vol. 7 N. 3-- Part A

International Review on Computers and Software  Vol. 7 N. 3-- Part B


go to top   International Review on Computers and Software - May  2012 (Vol. 7 N. 3) - Papers Part A



go to top   International Review on Computers and Software - May  2012 (Vol. 7 N. 3) - Papers Part B








International Review on Computers and Software - Papers- Part A



go to top   Review on ‘Maintainability’ Metrics in Open Source Software
         by  Abubakar Diwani Bakar, Abu Bakar Md. Sultan, Hazura Zulzalil, Jamilah Din

          Vol. 7. n. 3, pp. 903-908


Abstract - A number of individual practitioners and organization adopt Open Source Software (OSS) through try and error approach which leads to the problems of coming across software and then abandoned after realizing lack of important qualities to fit their requirements or facing difficulty in maintaining the software. Several software metrics for measuring object oriented software development process have been proposed but contribution to evaluate readymade OSS is still limited. This paper provides an overview of current available metrics and their applicability in OSS environment.

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Keywords: Open Source Software, Object Oriented Software, Maintainability.



go to top   Programmable High Accuracy Fuzzifier Circuit for Analog Neuro-Fuzzy System
         by Habib Ghasemizadeh, Amir Fathi, Aghil Ahmadi, Sahand Moharami

         Vol. 7. n. 3, pp. 909-914


Abstract - As we know, membership function generating is an important stage around fuzzy controllers. In this work, we propose a Membership function Generator (MFG) circuit in the form of Gaussian and trapezoidal for Neuro-fuzzy applications. Four voltage signals are used to regulate this circuit. Two signals define the knees where output signals begin falling or rising, and others regulate the rising or falling slopes of Gaussian and trapezoidal functions, independently. Therefore we don’t need to change the sizes of transistors or to switch parallel transistors. This is also increases circuit flexibility and the chip area will be decreased. By using two stages, the accuracy of the circuit to generate Gaussian function is improved. Since three generated functions (small, medium and large) are produced by a circuit simultaneously, low power consumption with small occupied area is obtained. Finally, simulation results which were done by HSPICE (level49) in 0.35µm CMOS process are presented and the Layout of the circuit realized less than 1300µm×µm area.

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Keywords: Fuzzifier, Fuzzy Controller, Gaussian Function, MFG, Mixed Signal.



go to top   Determining the Concentration of a Solution by the Experimental Characterization of its Acoustic Parameters
         by S. Soudani, M. Kadri, B. Alshouqaqi, M. Kadri

         Vol. 7. n. 3, pp. 915-918


Abstract - A fluid is an isotropic medium that is to say that all of its physical properties are identical in all aspects. On the contrary, when we consider the acoustic aspect, the parameters which characterize a solution are completely different and depend on the type and the composition of that solution. In this study we show that the acoustic parameters (ultrasonic velocity, compressibility, impedance and attenuation) of saline solution are based on the salt concentration. The results are very clear, very little change in its concentration leads to a variation of these parameters. The database thus constituted can, by propagating an ultrasonic signal in a solution of unknown concentration, determine the exact concentration of salt in that solution. The result can be achieved with any type of solution just by providing its data base of its acoustic aspect.

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Keywords: Concentration, Ultrasonic Velocity, Compressibility, Impedance, Attenuation, Density, On-line Control.



go to top   Non-Destructive Defect Detection on Electrical Equipment Using Thermographic Technology
         by Geoffrey O. Asiegbu, Ahmed M. A. Haidar, Kamarul Hawari

         Vol. 7. n. 3, pp. 919-927


Abstract - Based on the life threatening hazards associated with conventional electrical equipments inspection, this paper thought it wise to automate non-destructive defect detection (NDDD). Quality control and part inspection has done considerably well in the area of manufacturing but not yet gotten to its fully robust image processing technology application. In this paper, thermal imaging technology as one of applied means of electrical defect detection will be utilized. A novel method known as Red, Green and Blue (RGB) Color image and optimal threshold algorithm is proposed for detection of defective parts. Fluke thermal imager is used for infrared thermal (IRT) data acquisition. The input data is taking as thermogram of electrical equipment with different thermal regions in RGB Color space and the output result is in RGB Color space that makes this technique more intuitive. A normalized RGB IRT images are used to estimate a parametric statistical model consisting mixtures of Gaussian Probability Distribution (GPD). Regions of electrical thermogram are segmented through the optimal threshold algorithm ascertained using Receiver Operating Characteristic (ROC) curve and area under convex hull. The classification was done in accordance with international electrical testing standards. Application of this system is quite simple, user friendly, cost-effective yet the result is satisfactory.

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Keywords: Convex Hull, Gaussian Probability, Thermal Image, Threshold Algorithm.



go to top   Investigation of Kinematics for Articulated Robot Arm with SolidDynamics 2004+ and Validation by MATLAB/Simulink
         by  Mahdi Alshamasin, Florin Ionescu, Riad Taha Al-Kasasbeh, Abdullah Alwadie

         Vol. 7. n. 3, pp. 928-936


Abstract – In this paper, a 5-axis articulated robot for a drilling task was designed entirely from scratch with SolidDynamics (SD) software. Kinematics (forward and inverse) of the designed robot was modeled. Using this model, the process of simulation was successfully carried out for the drilling task in the work space of the robot. Results were validated by MATLAB/Simulink software and an agreement between the results obtained by the two softwares was achieved herein, to ensure the trustworthiness of using the quick and easy SD software for performing robot simulation, animation and designing.

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Keywords: Articulated Robot, RRR Motion, Robot Modeling and Simulation, Robot Kinematics (Forward and Inverse), SD Software.



go to top   A Soft Computing Technique for Estimation of Secure Operating Point in Voltage Stability Assessment
         by Kanimozhi.R, Selvi K.

         Vol. 7. n. 3, pp. 937-942


Abstract – This paper proposes a soft computing technique-Personalized Genetic Algorithm (PGA) based method for identifying the secure operating point to endow more information for power system planners and operators. The secure operating point can be identified by the estimation of the maximum loadability point in electric transmission systems. The estimation is done by formulating an objective function which maximizes the reactive power loading at a particular bus. A New Voltage Stability Index (NVSI) is utilized for calculating the fitness of the objective function. The IEEE 14 bus system and a Tamil Nadu Electricity Board (TNEB) 69 bus system, a practical system in India are adopted to illustrate the effectiveness of the proposed technique and also made comparison with existing index.

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Keywords: Maximum Loadability, PGA, Transmission System, Voltage Stability, NVSI.



go to top   HELP Multiplier Based Montgomery Key Generation for Elliptic Curve Cryptography Over GF (2m)
         by  B. MuthuKumar, S. Jeevananthan

         Vol. 7. n. 3, pp. 943-949


Abstract - The Elliptic Curve Cryptography (ECC) widely used in the communication system to provide security with small length key. The projective coordinate paved the way to simplify division and inversion tasks, which are generally most time consuming operations. ECC architecture over GF(2160) is designed with efficient hybrid encoded low power (HELP) multiplier and Montgomery scalar multiplication algorithm, which exhibits low power, less area and works in high frequency. The operation of HELP multiplier greatly depends on the number of 1’s and their positions in the multiplier data. The proposed ECC processor does the 160 bit point scalar multiplication and coordinates conversion with 373mW power consumption, 100MHz frequency and 5193 slices. The architecture is implemented in spartan3E family device XC3S1600E using Modelsim 5.7 and Xilinx 9.2i.
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Keywords: Cryptography, Elliptic Curve, Galois Fields, HELP Multiplier, Montgomery Multiplication Algorithm, Public Key.



go to top   Speed Based EMG Classification Using Fuzzy Logic
         by Shalu George. K, K. S. Sivanandan, K. P. Mohandas

         Vol. 7. n. 3, pp. 950-958


Abstract - Electromyographic signals have become a common tool for rehabilitation purposes, clinical diagnosis, and also as a source for control of prosthetic and assistive devices. It is observed that EMG signals exhibit specific patterns for different activities of the muscle. The correct recognition of the pattern helps in better control of assistive devices for supporting motion. This paper presents the development of a fuzzy logic classifier for classifying the different speeds of movement of a human elbow. Experiments are performed on the biceps brachii muscle of the right hand. Five subjects are asked to perform voluntary contractions with two different speeds with respect to the concerned muscle. From the acquired EMG data, two time domain features are extracted and are applied to the Fuzzy logic classifier. The classifier is found to discriminate the patterns with an average classification accuracy of 99.5%.
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Keywords: Assistive Device, EMG, Fuzzy Logic Classifier, Pattern Classification, Prosthetic Devices.



go to top   Face Detection and Recognition in Real-Time Automated Attendance System
         by Gawed M. Nagi, Rahmita O. K. Rahmat, Fatimah Khalid, Muhamad T. Abdullah

      Vol. 7. n. 3, pp. 959-964


Abstract - Although face detection has achieved high performance in real-time systems, limitations and challenges still remain in face recognition applications where uncontrolled conditions are presented. In this paper, a real-time automated attendance system (AAS) is implemented using face detection and recognition technology. The aim is to address the problems that affect both face detection and recognition and investigate the robustness of recognition in such real-world applications. This work presents the AAS overview and the common scenarios that could possibly selected as well as their strengths and weaknesses. In addition, 2DPCA method has been adopted for face recognition on local dataset and the results have been analyzed to address the problems that may affect and degrade the recognition performance with carrying out the preprocessing phase. The main challenges that have been highlighted are occlusions and facial expressions. However, the effect of head posture and facial scaling variations can be reduced by normalizing images prior to recognition phase.

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Keywords: Face Detection, Face Recognition, Automated Attendance System (AAS), Recognition Rate, Occlusion, Face Scaling, Head Pose.



go to top   Adaptive Fuzzy Mobility for Delay and Throughput Sensitive Traffic in Ad Hoc Networks
         by Med Amnai, Y. Fakhri, J. Abouchabaka

         Vol. 7. n. 3, pp. 965-971


Abstract - Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure. In this paper we have studied the impact, respectively, of mobility models and the density of nodes on the performances (End-to-End Delay and Throughput) of routing protocol Ad-Hoc On-Demand Distance Vector Routing (AODV). Due to the uncertainty associated with mobility models when estimating the position, speed and pause time of nodes we propose a novel approach based on Fuzzy logic to compute the optimal delay and optimal throughput with respect to the associated, respectively, delay and throughput. The mobility models considered are: Random Way Point, Random Mobgen Steady-State. The experimental results illustrate that the method is prominent and can be used with other mobility models.

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Keywords: Mobility Models, AODV, Fuzzy Logic, MANET.



go to top   Study and Analysis of Various Multiplier Architectures Using Reversible Logic
         by  Amita Nandal, T. Vigneswaran

         Vol. 7. n. 3, pp. 972-976


Abstract – The reversible architecture scheme yields significantly reduced complexity, low power and high speed features. It is a key issue in the interface between computation and physics, and of growing importance as miniaturization progresses towards its physical limits. With the advent of nanotechnology the fault detection and testability is of high interest for accuracy concerns. This research work describes the reversible testable design of various multipliers. There is 82% reduction in number of garbage outputs and constant inputs using proposed logic which is a key parameter for reversible logic. The proposed CSD multiplier circuit shows better performance than others and can be used in the systems requiring very high performance. The proposed approach shows 14% reduced logical complexity. The proposed add and shift multipliers incorporate 40% increased speed and 42% reduced power consumption than existing multiplier designs.

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Keywords: FAdd and Shift Multipliers, Garbage Output, Logical Complexity, Reversible Logic Gates, and Testability.



go to top   Investigating an Advanced Approach to Data Preprocessing in Moodle Platform
         by  Nawal Sael, Abdelaziz Marzak, Hicham Behja

         Vol. 7. n. 3, pp. 977-982


Abstract - Web usage mining is a complex process used to extract knowledge about the characterization of surfers who frequent a Web site and the identification of their navigation patterns. It’s an emerging discipline, notably on e-learning domain, often referred to as educational data mining. In this paper, we propose the use of educational data mining techniques to analyze learners’ behavior and how they exploit the contents of a given course. We are particularly interested in the preprocessing step which is considered the most crucial phase in the whole process. Based on Scorm course content, our work aims to develop an efficient preprocessing tool for e-learning platform using Moodle logs. To be able to get more insights into the course exploitation, we suggest extracting the knowledge describing students’ behavior in each part of this course content.
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Keywords: Web Usage Mining (WUM), Logs, Preprocessing, E-Learning, SCORM.



go to top   Non-Rigid Image Registration Technique for Ultrasound Elastography
         by  Bo Peng, Haiying Li, Dong C. Liu

         Vol. 7. n. 3, pp. 983-990


Abstract - Ultrasound elastography has become a promising imaging method for the diagnosis of tissue abnormalities over the last two decades. It obtains the local relative mechanical properties of tissues by estimating the strains using pre- and post-compression ultrasound echo signals. In this paper, we use non-rigid iamge registration approach to compute the axial and lateral tissue displacements. The proposed approach takes advantage of non-rigid image registration techniques for registering two frames of envelope signals acquired at a position under different levels of compression deformation. The obtained 2-D displacement field is used to calculate the 2-D strain images. A few parameters can be adjusted if the displacement accuracy is lower than a predefined empirical threshold in the whole procedure. To test its performance, this strain estimation method has been validated with simulated motion ultrasound envelope frame pairs. The results show that our method is robust to relatively large strains and capable of generating accurate axial and lateral motion estimation. In phantom experiments, the accuracy of the estimated axial and lateral strain and the ability of the method to overcome large motions also are demonstrated.
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Keywords: Non-Rigid Registration, Ultrasound Elastography, Free Form Deformation.



go to top   Distributed Barrier Synchronization Procedure with the Dynamic Limitation of the Coordinating Signal Propagation Area
         by Ashraf Abdel-Karim Helal Abu-Ein, Igor Valerievich Zotov, Hazem (Moh'd Said) Abdel Majid Hatamleh, Dmitriy Evgenievich Skopin

         Vol. 7. n. 3, pp. 991-995

Abstract - A distributed barrier synchronization procedure for 2D mesh multicomputer featuring the limitation of the coordinating signal propagation area across the communication environment based upon the dynamic construction of a minimal rectangle covering the set of participants of a barrier group is proposed.

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Keywords: C: Synchronization, Multicomputer, Mesh Topology.



go to top   An Evolution Strategy based Service Composition Algorithm in Cloud Computing Systems
         by Peng Xiao, Yanping Zhang

         Vol. 7. n. 3, pp. 996-1003


Abstract - The emergence of Web services has created unprecedented opportunities for organizations to establish more agile and versatile collaborations with other organizations. However, service composition with multiple QoS constraints still remains a challenging issue, since both the QoS performance of services and the QoS requirements of applications might dynamically be changed at runtime. In this paper, a novel service composition algorithm is proposed, which models the service composition problem as a multiple dimension knapsack problem and applies evolution strategy to obtain an approximate solution. In addition, a QoS negation algorithm is proposed to satisfy the dynamical and elastic cloud environments. Experimental results compare our method with other solutions and demonstrate the effectiveness of our approach toward the identification of an optimal solution to the QoS constrained Web service selection problem.

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Keywords: Web Service, Quality of Service, Application Profiling, Optimal Programming.



go to top   Particle Swarm Optimizer for Automatically Clustering High-Dimensional Data
         by  Yanping Lu, Suping Xu, Xing Gao

         Vol. 7. n. 3, pp. 1004-1011


Abstract - In this paper, we present a parameter-free particle swarm optimizer for the problem of clustering high-dimensional data, named autoPSO. As well as identifying clusters, the aim here is to automatically determine the correct number of clusters. The objective function employed is the Davies-Bouldin (DB) index, which makes it possible to directly compare partitions with similar or different numbers of clusters, in the same generation or between adjacent generations. Given the objective function, clustering is formulated as a continuous function optimization problem with bound constraints. In order to encode a variable number of clusters, autoPSO utilizes a real-number matrix and a binary vector representation for a particle. Then, a new crossover matrix learning procedure governed by the associated binary vector, is proposed to maintain the population diversity, making the proposed algorithm immune to the premature convergence problem. Experimental results on both synthetic high-dimensional data sets from a data generator and handcrafted low-dimensional data sets show that it is able to correctly identify clusters of high-dimensional data without needing to rely on a given number of clusters k.
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Keywords: High-Dimensional Data, Particle Swarm Optimizer, Clustering, the Number of Clusters.



go to top   License Plate Identification Algorithms Using Color Analysis and Edge Features
         by Mostafa Ayoubi Mobarhan, Asadollah Shahbahrami, Mojtaba Ayoubi Mobarhan, Atefeh Ahmadnya Khajekini, Shiva Derogar

         Vol. 7. n. 3, pp. 1012-1019

Abstract - License Plate Detection (LPD) plays an important role in an intelligent traffic management system. There are lots of different methods and algorithms in LPD systems. Finding a technique that provides a good accuracy with an excellent response time is difficult. In this paper, two techniques to LPD are presented. First, a technique for LPD using color analysis and edge features is proposed. The proposed technique uses the edge features to find the rows position of the license plate. In order to find the column positions, the small blue color part at the left of the license plates in the determined rows position is found. The experimental results for different image database show that an accuracy of 96.6 percent can be achieved. Also, a technique to improve old Morphology method is presented. We attempted to improve its performance rate by edge detection procedures. In this method, the license plate location rate of success is 97.3 percent. At the end, this method is compared with the previous Morphology (without edge detection) based on two major factors, accuracy and computation time.
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Keywords: LPD, Real Time Methods, Edge Detection, Sobel Filter, Color Analyze System, Morphology Method.



go to top   Information Content Similarity Measure to Assess Stability during Ontology Enrichment
         by K. Kamoun, S. Ben Yahia

         Vol. 7. n. 3, pp. 1020-1027


Abstract - Ontology is often used in dynamic environments. Therefore, they must be adapted to new needs of evolution. Several issues arise from ontology evolution. In this article, we focus on the problem of quality assessment of evolved ontology and more specifically enriched ontology. We propose a new method for ontology enrichment based on the assessment of a new quality aspect which we call ontology stability. We will show the advantages of semantic similarity measures based on the information content and how to use it to compute the stability measure. Finally, we will choose the most appropriate one to be used with different types of ontology structures. This choice is made according to the capacity of the measure to maintain ontology’s stability after its enrichment. The measure Proportion of shared specidicity (PSS) will be the best suited to be integrated into the enrichment process.

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Keywords: Ontology Evolution, Ontology Enrichment, Ontology Quality, Ontology Assessment, Similarity Measure Based On Information Content.



go to top   Evolutionary Game-Based Node’s Incentive Schema for P2P Networks
         by Fang Zuo, Wei Zhang

         Vol. 7. n. 3, pp. 1028-1037

Abstract - Motivated by how to find a mechanism to encourage nodes to share resources and provide services, this paper presents an evolution game model for encouraging node’s service and voiding the betrayal of node in P2P networks with the condition of P2P node’s bounded rationality and the social behaviors of nodes in P2P networks. Paper takes into account diversity of nodes types, complexity of node strategies, asymmetry of node information and uses replicate dynamics model to simulate node’s learning and strategic adjustment process in P2P application. In this model, node’s behaviors are divided into three types. The corresponding strategies adopted by each type of nodes at each stage in P2P application can be defined as mixed strategies of nodes. Based on such strategies, paper analyzes payoff matrix of the evolution game among various node strategies, the game’s evolutionary stability and also shows the transfer conditions for reaching P2P evolution strategy. Finally, simulations based on the evolutionary results with P2P network environment are carried out. Moreover, simulation gives us interesting insight into the overall nature of nodes’ interactions and how system efficiency can be improved.

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Keywords: Traitor Behavior, Incentives, P2P Networks, Replicators Dynamic Model, P2P Evolutionary Stable Strategy.



go to top   A New Clustering Algorithm for Uncertain Data Stream Based on the Existence Probability of Tuple
   by Ju Chunhua, Zhang Pengkun

           Vol. 7. n. 3, pp. 1038-1044

Abstract - In this paper, we proposed a new clustering algorithm called UDSC for uncertain data stream. According to the existence probability of cluster, clusters are divided into three levels: strong, transitional and weak. An effective strategy for choosing candidate cluster is developed based on four factors: distance, cluster compactness, existence probability of cluster and existence strength of cluster, which used to find optimal accepted cluster for each continuously arriving data. Then we proposed several rules to describe drifts and shifts in clusters, which used to help users known the changes clearly in clusters and help users make new decisions accurately. Experiment results shows that UDSC clustering algorithm outperforms the existing methods in efficiency and effectiveness.

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Keywords: Clustering, Uncertain Data Stream, Existence Strength.



go to top   A Cloud Manufacturing Resource Model for Service-Manufacturing System
         by  Juan Yang, Gang Guo

         Vol. 7. n. 3, pp. 1045-1052


Abstract - With the development of the globalization of manufacturing services, service influence or integrate into the manufacturing called service-manufacturing. When cloud computing is a kind of methodology that can be applied in service-manufacturing, which names cloud manufacturing that can achieve integration of distributed manufacturing resources and highly collaborative of their core competitiveness. In this background, efficient cloud manufacturing resource management is a core. Although there are numerous studies on cloud manufacturing resource, there are still some problems have not been satisfactorily resolved. In this paper, based on the analysis of the features of cloud manufacturing resource for the cloud manufacturing, then cloud manufacturing resource model is proposed for resource description, resource matching and resource optimization. The cloud manufacturing resource is classified by ontology method, then use semantic and vector distance algorithm for intelligent search. Finally, this model and realize technology is verified through a study case.

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Keywords: Service-Manufacturing System, Cloud Manufacturing, Cloud Manufacturing Resource, Cloud Manufacturing User, Cloud Manufacturing Supplier.



go to top   An Improved Approach based on Fuzzy Clustering and Back-Propagation Neural Networks with Adaptive Learning Rate for Sales Forecasting
         by  Attariuas Hicham, Bouhorma Mohamed, El Fallahi Abdellah

         Vol. 7. n. 3, pp. 1053-1061


Abstract - This paper describes new hybrid sales forecasting system based on fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learning rate (FCBPN).The proposed approach is composed of three stages: (1) Winter’s Exponential Smoothing method will be utilized to take the trend effect into consideration; (2) utilizing Fuzzy C-Means clustering method (Used in an clusters memberships fuzzy system (CMFS)), the clusters membership levels of each normalized data records will be extracted; (3) Each cluster will be fed into parallel BP networks with a learning rate adapted as the level of cluster membership of training data records. Compared to many researches which use Hard clustering, we employ fuzzy clustering which permits each data record to belong to each cluster to a certain degree, which allows the clusters to be larger which consequently increases the accuracy of the proposed forecasting system . Printed Circuit Board (PCB) will be used as a case study to evaluate the precision of our proposed architecture. Experimental results show that the proposed model outperforms the previous and traditional approaches. Therefore, it is a very promising solution for industrial forecasting.

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Keywords: Sales Forecasting, Fuzzy Clustering, Fuzzy System, Printed Circuit Boards, Back Propagation Network, Hybrid Intelligence Approach.



go to top   Cancer Detection Based on Experimental Sampling by Genetic-Fuzzy Classification System
         by  Hamid Tabatabaee -Y, Maryam Mehrnejad, S. Kazem Shekofteh

         Vol. 7. n. 3, pp. 1062-1069


Abstract - Today the automatic diagnostic of cancer is an important and real world medical problem. Some cancers like breath cancer are more important and need to early detection with too much effort. Also, rule extraction from limited training dataset in uncertain environments like medical diagnosis classification system is a significant area in knowledge discovery. Unfortunately lack of expert, long time and expensive diagnosis process and tech gibberish problem makes such systems more complicated. This paper presents a new fuzzy genetic approach for rule extraction in Wisconsin breast cancer Dataset. We code a fuzzy classifier as a chromosome in the proposed genetic approach. Then the accuracy rate of classification for each solution is taken account as the most important factor in fitness function. Several mechanisms are applied to improve the results containing; elitism, dynamic mutation rate and etc. The results show that the proposed method produces a high classification performance which is also human interpretable.

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Keywords: Genetic Algorithm, Fuzzy Logic, Genetic-Fuzzy System, Classification, Disease Diagnosis, Breast Cancer.



go to top   Hybrid eABC-LSSVM for Correlated Metal Price Prediction
         by  Zuriani Mustaffa, Yuhanis Yusof

         Vol. 7. n. 3, pp. 1070-1077


Abstract - This paper proposes a financial time series prediction model, namely enhanced Artificial Bee Colony-Least Squares Support Vector Machines (eABC-LSSVM). As the performance of LSSVM highly depends on its hyper parameters, namely regularization parameter, γ and kernel parameter, σ2, a great deal of attention was paid in determining the parameters of interest. The mutation strategy is applied in improving standard ABC which also acts as a prevention of premature convergence. To see the effectiveness of the proposed model, it was compared with standard ABC and Cross-Validation (CV). The models were demonstrated using three correlated metals price time series, which are gold, silver and palladium. By using time series from 2008-2011, the prediction performance was evaluated using mean Absolute Percentage Error (MAPE). Analysis of the experimental results revealed that LSSVM model achieves better prediction performance when hybrid with eABC. The encouraging results showed that eABC-LSSVM could be applied as an effective prediction tool in the context study.

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Keywords: Artificial Bee Colony, Least Squares Support Vector Machines, Correlated Metal Price, Prediction.



go to top   Interpreting Web Usage Patterns Generated Using a Hybrid SOM-Based Clustering Technique
         by  Ammar M. Huneiti

         Vol. 7. n. 3, pp. 1078-1088


Abstract - The rapid and huge growth of the web has emphasized the need to monitor the behavior of web users and to identify their interest, knowledge, preferences, goals, etc. This paper introduces a methodology for classifying users and pages of an educational online hypermedia using a hybrid clustering technique based on Self Organizing Map (SOM) neural networks. This paper also introduces an analytical cluster validation and interpretation approach to verify and explain the generated clusters of users and pages. The implemented cluster validation process utilizes a silhouette-based quantitative measure, while a combined data visualization and statistical cluster interpretation technique is proposed. Several experiments have been carried out using real data collected through special lab sessions of real students navigating an online tutorial. Experimental results indicated that the proposed methodology was able to prototype users and to recognize the association between pages based on their usage. Moreover, the topic of interest and the users interested in these topics were also identified.

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Keywords: Web Usage Mining, SOM, Cluster Validation and Interpretation, User Modelling, Adaptive Hypermedia.



go to top   Custom Design and Implementation of National Innovation Capability Database
         by  Andrew Obok Opok, Sajid M. Sheikh

      Vol. 7. n. 3, pp. 1089-1099


Abstract - The paper presents the custom design and implementation of a database for National Innovation System (NIS) for Botswana. This was a customer driven design and achieved through sustained consultation with the client to define the framework for the national innovation capability system, the data requirements, and the set of indicators it was required to produce upon commissioning. A top-down design methodology was applied involving moving from technology-independent level to technology-dependent level in the system development process, taking into account the data and processing requirement of the system. My SQL (Structured Query Language) software platform was selected as the most suitable after comparative analysis with competing solutions. The design was limited to a standalone system though it could easily be upgraded for web-based operation. The capability of the database produced was comprehensive and capable of producing all National Innovation Systems Indicators required. The paper demonstrates how to overcome practical challenges of designing a custom non-conventional database, it highlights how to adapt and apply generic database design to custom databases; it offers a practical experience on database design and implementation in new areas of application such the National Innovation System, in contrast to business oriented databases; and offers lessons learned in the design of the database.

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Keywords: Database Design, National Innovation System, Indicators.



go to top   Medical X-ray Image Clustering Using a New Gabor Function-Based Image Representation
         by  Nooshin Jafari Fesharaki, Hossein Pourghassem

         Vol. 7. n. 3, pp. 1100-1106


Abstract - Nowadays, by generating a numerous number of medical images as well as their wide-spread usage in many different medicine applications, the need for more powerful searching and retrieving engines is ever-increasing. As a result, clustering plays meanwhile an important role in organizing medical images. In this paper, we try to develop a new image clustering framework by using Gabor function based on image representation which reduces the complexities in extracting the utilized features. The features in global and pixel levels are then extracted from these new image representations. Finally, a one-against-one multi-class Support Vector Machine (SVM) classifier is applied to cluster medical images. In this task, a dataset consisting of different medical X-ray images is used to evaluate the proposed clustering scheme and its effectiveness is shown according to the presented experimental results.

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Keywords: Image Clustering, Gabor Function-Based Image Representation, Feature Extraction, One-Against-One Multi-Class SVM Classifier.



go to top   Probabilistic-Based Meta-Scheduling Framework for Deadline Sensitive Task in Heterogeneous Systems
         by  Peng Xiao, Peixin Qu, Ning Han

         Vol. 7. n. 3, pp. 1107-1113


Abstract - In heterogeneous distributed systems, task scheduling with deadline constraint is a challenging issue as the heterogeneity and distribution features of resources. In this paper, we propose a probabilistic-based meta-scheduling framework, which uses stochastic service model to evaluate the deadline-guarantee of given scheduling schemes and selects the one with optimal deadline-guarantee as final scheduling scheme. The proposed scheduling framework combines the merits of various scheduling policies, and overcomes the shortcomings of them. Extensive experiments are conducted to verify the effectiveness and the performance of the proposed framework in terms of deadline-miss rate. Experimental results show that it can provide scheduling scheme with improved deadline-guarantee and lower down the deadline-miss rate for real-time tasks in large-scale heterogeneous systems.

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Keywords: Heterogeneous Systems, Real-Time Task, Stochastic Service Model, Meta-Scheduling.



go to top   Vehicle Detection Based on Template Matching in Traffic Surveillance System
         by  Fatemeh Mazrouei Sebdani, Hossein Pourghassem

         Vol. 7. n. 3, pp. 1114-1121


Abstract - The road traffic monitoring is one of important problem in computer vision for intelligent transportation systems (ITS). Computer vision-based traffic monitoring requires detection of moving vehicles from traffic scenes in real time. In this paper, a robust algorithm for vehicle detection is proposed. Our algorithm conclude two main phase: 1) segmentation of moving vehicle based on background subtraction techniques. In this phase, we use adaptive gaussian mixture models for background extraction. Then, morphology operator and shadow removing are used to enhance extracted blob corresponding to moving object. 2) Detection of vehicle based on template matching. In this phase, we use two criteria Normalized Cross-Correlation (NCC) and Mutual Information (MI) for template matching. The post-processing stage is applied to improve the performance of our vehicle detection. The proposed system was performed well for three traffic video sequences acquired under different weather, illumination, and traffic conditions. Experimental results demonstrate effectiveness of the proposed algorithm.

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Keywords: Intelligent Transportation Systems (ITS), Normalized Cross-Correlation (NCC), Template Matching, Vehicle Detection.



go to top   A Novel Automatic Synthetic Segmentation Algorithm Based on Mean Shift Clustering and Canny Edge Detector for Aerial and Satellite Images
         by  Mohammad Javad Ebrahim, Hossein Pourghassem

         Vol. 7. n. 3, pp. 1122-1129


Abstract - In practice, the most of the aerial and satellite images are crowded or semi-crowded. As a result the segmentation task will be complicated. Although current segmentation algorithms are useful to find the segments, it seems that these algorithms are not acceptable enough the find the segments in the images. In this paper, we present a new automatic segmentation algorithm based on combination of Canny edge detector and mean shift clustering in crowded and semi-crowded aerial or satellite images. In this algorithm, a primary plan is determined based on edge detection algorithm and after that different segments in the image are labeled and finally, the final segmented image is determined automatically based on mean shift clustering algorithm. This algorithm works well in any type of image. The experimental results show that this algorithm gives a more accurate segmentation than current algorithms.

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Keywords: Mean Shift, Edge detection, Closing, Labeling.



go to top   Teeth Contour Extraction Using Modified Active Contour without Edges
         by  Azam Amini Harandi, Hossein Pourghassem

         Vol. 7. n. 3, pp. 1130-1141


Abstract - Segmentation of dental X-ray images and teeth contour extraction are important parts of automatic dental identification system (ADIS). The first step in extracting the contour of teeth is segmentation the image. In this paper, the horizontal and vertical integral projections with active contour are applied to segment the teeth. This method uses 7 different morphological filters and two models of active contour without edges to extract the contour of teeth .In addition to improve the segmentation results, adaptive histogram equalization is employed. The proposed segmentation algorithm is evaluated on a perfect set of dental X-ray images. The obtained results show efficiency and effectiveness of our algorithm in the real and operational conditions.

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Keywords: Teeth Contour Extraction, Morphological Filter and Active Contour Without Edges.



International Review on Computers and Software - Papers- Part B



go to top   A Semi-distributed Packet Scheduling Scheme for Two-hop OFDMA Relay-enhanced Cellular Systems
         by  Gaoyong Huang, Xuming Fang

         Vol. 7. n. 3, pp. 1142-1148


Abstract – In this paper, we propose a semi-distributed packet scheduling algorithm (SPS) for two-hop orthogonal frequency division multiple access (OFDMA) relay-enhanced cellular system. The objective is to provide an adaptive scheduling algorithm with limited feedback to support the mixed traffics with diverse quality of service (QoS) requirements, and keep the trade-off between the system throughput and the users’ QoS requirements. Furthermore, an adaptive slot reallocation scheme (ASR) is proposed to reduce the feedback information from the relay stations (RSs) and relay users. Simulation results show that the proposed scheme achieves good performances in terms of system throughput, users’ QoS requirements, and the savings of system overhead. Our proposed scheme also reduces the average handover packet drop ratio.
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Keywords: OFDMA, Relay-enhanced Cellular System, Semi-distributed Scheduling Algorithm, QoS Requirement, Packet Drop Ratio.



go to top   Complexity Analysis with Function-call Graph on Windows Software
         by  Yang Guo, Zhengxu Zhao, Yiqi Zhou

         Vol. 7. n. 3, pp. 1149-1153


Abstract – Complex network is being considered as an important interdisciplinary approach to representing complex systems. Power-law distributions occur in many situations of natural and man-made systems. There is evidence that power laws appear in software systems at the class or function level. In previous studies researchers mainly focus on the systems running on Linux systems and those findings have certain limitations to some extent. In this paper, we elaborate a function-call graph reconstruction algorithm based on Windows systems and present a complex network approach to the study of software engineering. We have examined function-call graphs contained within two open-source visual simulation platforms, and found them to reveal small-world, scale-free features similar to those identified in other sociological, biological, and technological systems.
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Keywords: Object-oriented Programming, Power-law Distributions, Scale-free Network, Function-call graph, Connected Component.



go to top   Effects of Relationship Bonding Strategy on Customer Loyalty Under B2C E-Commerce Environment
         by  Zhaohui Li

         Vol. 7. n. 3, pp. 1154-1160


Abstract – In recent years, many scholars have engaged in the research on relationship marketing. However, empirical researches on the relationship bonding strategy are still few, and researches on this aspect under B2C (business to consumer) e-commerce environment are less. This paper studies the effects of relationship bonding strategy on the customer loyalty, verifies the intermediary role of the trust and emotional attachment through empirical data collection and analysis under e-commerce environment. The paper finds out that social and structural bonding strategies both affect customer trust, financial and social bonding also influence to emotional attachment, customer trust and emotional attachment both affect attitudinal loyalty and behavioral loyalty.
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Keywords: Relationship Bonding Strategy, Customer Loyalty, Customer Trust, Emotional Attachment.



go to top   A Decision Support System Architecture for Automobile Industry Chain
         by  Weizhi Liao, Linfu Sun

         Vol. 7. n. 3, pp. 1161-1166


Abstract – This paper firstly analyzes the features of software as a service (SaaS) based collaboration platform for automobile industry chain. Then, a decision support system architecture for automobile industry, which consists of platform support layer, resource support layer, decision support layer and the hierarchical relationships, is proposed. A Union -Decision-Resource application supporting relationships, which consists of manufacturing-company-oriented decision support functions, collaborating-company-oriented decision support functions and the platform-based decision support functions are established based on the collaboration platform. On the basis of the above studies, the collaboration platform oriented decision support system is designed and it can provide good support of SaaS-based decision analysis for all kinds of enterprises in automobile industry chain.
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Keywords: Automobile Industry Chain, Software as a Service, Decision Support System.



go to top   Space-time Model of Information Diffusion from Network Perspective
         by  Yirui Deng, Xiaofeng Xu

         Vol. 7. n. 3, pp. 1167-1173


Abstract – In nowadays, the network space and the realistic space both exist in our life, and the development of network especially Internet has provided a function prepared platform about open information diffusion and resource sharing for information diffusion. The superiority dimension-forces which network has make the source information reach any destinations in broad spatial scope fast and synchronously, and accumulate information instantaneously to surmount the threshold value of information destination, then realize the diffusion distance willfully far, the quantity of information destination willfully more, the diffusion effect obviously strengthens. Information diffusion Model is mainly on movement forms of information diffusion, which is very important for the further understanding of information diffusion. On the basis of the definition of the related concepts and the diffusion space and time, using for reference from the core idea of the network dimension-force theory and the Markov drift chain theory, this paper establishes the space-time model of information diffusion, which describes the space-time expansion mode and the characteristic of diffusion. This space-time model attempts to describe the motion state of information diffusion from the macro level systematically and semantically, and is mainly applied to predict the trend of information space-time diffusion.
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Keywords: Information Diffusion, Network Dimension-force, Space-time Model.



go to top   On Price and Service Competition with Complementary Goods
         by  Bin Wang, Jing Wang

         Vol. 7. n. 3, pp. 1174-1181


Abstract – This research studies a case that two enterprises produce two different but complementary goods. The consumer demand depends on two factors: prices and service levels of the product and complementary product. This article is based on two scenarios: Nash Equilibrium and Enterprise Alliance. Game-theoretic framework is applied to find the optimal solutions for every participant. This research has conclusions as follow. Firstly, as market base of one product increases, it can benefit for both of them. Second, when one product has some economic advantage in providing service, it will have benefit from it, and the complementary goods also earn profit. Third, enterprises will provide more services, set high prices, and gain more profit in Enterprise Alliance than in Nash Equilibrium.
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Keywords: Complementary Goods, Pricing Strategy, Service Level.



go to top   A Novel Scheme for Improving QoS in Optical Burst Switching Networks
         by  Yinghui Qiu

         Vol. 7. n. 3, pp. 1182-1186


Abstract – With the explosive growing of Internet traffic and emerging applications, such as video conferencing, multimedia delivery and Grid computing, long-haul transport networks must provide more bandwidth capacity and reliable delivery. Optical burst switching (OBS) is such a promising bufferless WDM switching technology. In order to offer better services for diverse Internet applications, the development of quality of service (QoS) mechanisms becomes an important issue in OBS networks. In this paper, a novel scheme for improving QoS in OBS networks is proposed and is compared with conventional scheduling algorithm in OBS through simulation. Simulation results show that the proposed scheme can guarantee QoS requirements in the OBS networks and can get a low burst blocking probability.
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Keywords: Optical Burst Switching, Quality-of-Service, Contention Resolution, Deflection Routing.



go to top   Knowledge Acquisition Approach for Incomplete System Based on Decision Entropy and Divide-and-conquer Method
         by  Feng Hu, Liang Xiang, Hang Li, JingQi Zhou

         Vol. 7. n. 3, pp. 1187-1192


Abstract – Knowledge acquisition is one of the most important contributions of rough set theory for machine learning, pattern recognition and data mining. The generalization of decision rule of incomplete information system is a difficult issue due to the missing of attribute values. In order to improve the generalization of rough set theory, it is urgent to study the novel approaches for knowledge acquisition with high precision. Decision entropy is an effective tool to obtain decision rule with high precision through confidence degree and coverage degree. In this paper, we present the basic notions for incomplete information system and propose the principle of knowledge acquisition based on decision entropy. After that, we employ divide-and-conquer method to develop an algorithm for computing the tolerance classes. Based on the proposed algorithm, we propose a knowledge acquisition approach for incomplete information system. Simulation evaluation on uci data sets shows that the proposed approach is more effective with higher recognition rate and less running time than the existed approaches.
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Keywords: Rough Sets, Knowledge Acquisition, Decision Entropy, Divide-and-conquer, Incomplete System.



go to top   Intelligibility of Native and Non-Native Chinese Speech
         by  Huaying Chen, Yi Yang, Anniwar Rozy

         Vol. 7. n. 3, pp. 1193-1198


Abstract – The intelligibility of speech is known to be lower if the speaker is non-native instead of native for the given language. This study aims at quantifying the degradation due to limitations of non-native speakers of Standard Chinese, specifically of Chinese-speaking Uyghurs who are bilinguals of Uyghur and Chinese, living in Xinjiang, China. The experiment focuses on Standard Chinese vowel intelligibility. It is found that the main contribution to the degradation of speech intelligibility by introducing non-native speakers and listeners is the confusion of vowels. Vowels that are difficult for second-language speakers to produce are also difficult for second-language listeners to classify; such vowels attract false recognition, reducing the overall recognition rate for all vowels.
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Keywords: Intelligibility, Non-Nativeness, Standard Chinese, Uyghur.



go to top   An Effective Min-Attribute Generalization Algorithm to Protect Private Data Based Cloud Environment
         by  Jian Wang

         Vol. 7. n. 3, pp. 1199-1203


Abstract – With the development of the cloud computing technology, more and more companies are willing to apply this technology. When our private data are out-sourced in cloud computing, we should guarantee the confidentiality and searchability of the sensitive data. However, nowadays privacy preserving issues in the cloud have not been carefully explored at current stage. To relieve individuals’ concerns of their data privacy, this paper explores an effective algorithm based on privacy protocol and min-attribute generalization to avoid the disclosure of private information in the cloud environment. This paper also provides security analysis and experimental evaluation for the proposed algorithm.
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Keywords: Private Data, Privacy Protocol, Attribute Generalization, Cloud Computing.



go to top   Buyer-Seller Watermarking Protocol: Problems and Solutions
         by  Dangui Chen, Xiliang Zeng

         Vol. 7. n. 3, pp. 1204-1208


Abstract – Digital watermarking is an emerging technology for combating copyright piracy. In a forensic watermarking architecture, the transaction between a buyer and a seller is done through a specific watermarking protocol. A buyer-seller watermarking protocol can enable the seller to identify a traitor from pirated copies, while preventing the seller from framing an innocent buyer. Buyer-seller watermarking protocol design has been a hot research topic and a lot of watermarking protocols have been proposed in recent years. In this paper, we point out the major problems with buyer-seller watermarking protocol and summarize the current state-of-the-art of the solutions to these major problems.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Digital Watermarking, Buyer-Seller Protocol, Digital Copyright Protection.



go to top   Weighted-Cooperative Spectrum Sensing Scheme Using Clustering
         by  Huiheng Liu, Wei Chen

         Vol. 7. n. 3, pp. 1209-1214


Abstract – Cognitive radio technology is proposed for using the unused spectrum band efficiently because of the spectrum scarcity problem. Efficient and reliable spectrum sensing plays a critical role in cognitive radio. This paper proposes a weighted-cooperative spectrum sensing scheme using clustering for cognitive radio system. We firstly classify the secondary users into a few clusters according to several existent methods, and then use cluster-head to collect the observation results coming from different secondary users in the same cluster and make a cluster-decision. Considering the different distances between the clusters and the fusion center, different weightings are used to weight the cluster-decisions before combining. The simulation results show that our proposed method improves the probability of detection and reduces the probability of error.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Cognitive Radio, Weighted-Cooperative Spectrum Sensing, Energy Detection, Clustering, Fusion Center.



go to top   Contact Dynamics Analysis of Helical Gear Based on Precise Tooth Surface Model
         by  Xueyi Li, Chaochao Li, Sanshuai Li, Shoubo Jiang

         Vol. 7. n. 3, pp. 1215-1220


Abstract – A method to develop a precise spiral surface for involute helical gear based on bicubic B-spline interpolated surface is proposed in this paper. The contact finite element model of helical gear pair with precise tooth surfaces is established, and the boundary conditions are derived based on the gear meshing theory and the multi-constraint technology. The tooth contact status and bending stresses of gear pair during the whole meshing cycle are calculated by transient contact dynamics analysis. Correspondingly, the maximum tooth contact stress and the maximum bending stress of both gears can be defined. The study reveals that the contact dynamics simulation of helical gear based on precise bicubic B-spline surface model can reflect the real dynamic performance in the meshing process, and provides reliable assurance for calculating strength and fatigue life of gear.
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Keywords: Helical Gear, Bicubic B-spline Surface, Contact Dynamics, Finite Element Analysis.



go to top   A PSO-based Creative Design Approach to Improve Aesthetic-Oriented Product Interface
         by  Jiang Xu, Xi Zhao

         Vol. 7. n. 3, pp. 1221-1227


Abstract – In order to enhance the aesthetic-oriented satisfaction of the product interface, the formal description on aesthetic measurement (AM) evaluation is proposed to improve the interface design. The factors of AM mainly consist of Balance, Equilibrium, Symmetry and Continuity. Considering the problem space for the design is huge, the method of the optimized design is advanced based on the particle swarm optimization (PSO) algorithm, in which the fitness function of AM is built and the mix coding manner combining the real with the integer is developed specially. Finally, a case study of the cabinet for machine was conducted to evaluate the practicability of this method. The method can also be applied to the related fields such as media design and other visual interface design.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Particle Swarm Optimization, Product Interface, Aesthetics Measurement.



go to top   Application of Similarity Flooding Algorithm in the Calculation of Concept Similarity
         by  Guoyan Xu, Yong Yang,Li Yang

         Vol. 7. n. 3, pp. 1228-1232


Abstract – With the widespread application of ontology in the fields of information retrieval, artificial intelligence etc., the calculation of concept similarity of domain ontology has become the focus research field. However, the amount of mapping pairs with similar semantics can't be computed accurately by traditional computation of concept similarity based on semantic distance. Hence, the algorithm of Similarity Flooding is introduced to calculate concept similarity in this paper. The algorithm of Similarity Flooding is compared with WordNet-based algorithm and string-edit-distance-based algorithm. As it shows, in a certain extent, the algorithm of Similarity Flooding improves the precision of the calculation of concept similarity.
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Keywords: Domain Ontology, Concept Similarity Calculation, Similarity Flooding Algorithm.



go to top   Optimal Vibration Control and Algorithm Design for Offshore Platform
         by  Yanjun Liang, Tao Guo, Aimin Wan

         Vol. 7. n. 3, pp. 1233-1238


Abstract – The optimal vibration control of the offshore jacket platform is studied. The wave load to the platform systems is expressed as disturbances produced by the exosystems. In order to designing the vibration control for the platform systems, an average performance index with exponential decay rate is chosen. A new optimal vibration controller is designed for the offshore jacket platform control systems. An algorithm of the new control scheme is presented. Numerical simulations illustrate the effectiveness of the proposed controller.
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Keywords: Optimal Control, Vibration Control, Offshore Platform.



go to top   Vulnerability Assessment of Regional Agricultural Drought Disaster Based on Fuzzy Set Pair Analysis
         by  Junfei Chen, Xiaolan Zhou

         Vol. 7. n. 3, pp. 1239-1244


Abstract – With the global climate change, regional agriculture drought disasters occur frequently and caused huge economic losses. Vulnerability assessment of regional agricultural drought disaster is an important content for drought disaster risk management and planning of regional agricultural. In this paper, the vulnerability evaluation index system of regional agricultural drought disaster which includes eight evaluation indices is established. The fuzzy set pair analysis (SPA) model on vulnerability assessment of regional agricultural drought disaster is proposed and applied to evaluate the vulnerability of regional agriculture drought. The vulnerability degree of each region is computed and the ranks of each region are obtained. The results show that the proposed method is effective for assessing the vulnerability of regional agricultural drought disaster and can provide important guiding for drought relief of regional agricultural system.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Agricultural Drought Disaster, Fuzzy System, Set Pair Analysis (SPA), Vulnerability Assessment.



go to top   An Image Restoration Algorithm based on Image Fusion
         by  Weihua Liu

         Vol. 7. n. 3, pp. 1245-1249


Abstract – An image restoration algorithm based on two-step iterative shrinkage (TwIST) and multiply filter banks is proposed, which combines the multi-scale, multi-resolution, multi-direction, spatial anisotropy of contourlet transform, and the multi-scale, multi-resolution and spatial isotropy of wavelet transform. First, the blurred image is separately deblurred by various wavelet basis and contourlet basis based on TwIST, so as to select the better deblurred images. Second, these deblurred images are fused into one clean image based on the fused measure. The weighted average method is applied to the fused measure. The power is decided by the residual between the blurred image and the deblurred image. The deviations of the local variances of the residual image are exploited to evaluate the local quality of the deblurred image in pixel domain. The experimental results show that the proposed algorithm achieves improvement on improved signal-noise ratio (ISNR).
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Image Restoration, Image Fusion, Two-Step Iterative Thresholding Method, Weighted Average.



go to top   A Logic Based Analysis on Trust Negotiation Policies
         by  Dongmei Xia, Guosun Zeng

         Vol. 7. n. 3, pp. 1250-1256


Abstract – In the virtual computing environment, the securing co-operation is based on the trust between the strangers, automated trust negotiation provides a mean to establish trust between strangers in distributed situation. However, the current negotiation takes it for granted that the access control policy of negotiation is correct, which will probably cause many problems to lead negotiation to fail. This paper emphasizes on analyzing the characters of negotiation policy. Firstly, aiming at the inconsistency problems such as inconsistent policy and trivial policy, this paper establishes a logic proving method based on label binary tree in order to test policy consistency, so as to prove the soundness and completeness of this method; Secondly, this paper gains the minimal credential set by predigesting the policy tree, then successful negotiation is achieved through one-off discovering the minimal credential set, which will avoid the policy circle and improve the efficiency and the probability of negotiation.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Automated Trust Negotiation, Access Control Policy, Policy Circle.



go to top   Electrovalence Fluctuation based on Second and Third Moments Characteristics
         by  Hongfu Wang, Hui Ma

         Vol. 7. n. 3, pp. 1257-1261


Abstract – With comprehensive analysis of the changing rules in electricity market spot price, a multicycle GARCH-M model based on Gram-Charlier series expansion of the normal density function is proposed, in which the second moment, third moment and multicycle of electricity price series are described by time-varying variance, time-varying skewness and sine function. This model can fully take into account the changing trend, volatility of second and third moments, multicycle and the relationship among load and spot price. There exist second moment volatility clustering and weekly, semi-monthly, monthly, bimonthly, quarterly and semi-annual periods, and the second and third moments of electricity price series manifest the clear synchronous time-varying characteristics. Through the analysis of historical data of the PJM power market show that the system load square and time-varying variance has a significant impact on the mean electricity prices.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: GARCH-M Model, Time-varying Variance, Third Moment, Electricity Price Series.



go to top   Intelligent Control of Coke Oven Air-fuel Ratio
         by  Gongfa Li, Yuesheng Gu, Jianyi Kong,Guozhang Jiang, Liangxi Xie

         Vol. 7. n. 3, pp. 1262-1267


Abstract – The constant proportion of the combustion air-fuel ratio control results in low combustion efficiency and fault-prone, it’s difficult to adapt to changes in complex working conditions. Intelligent air-fuel ratio control method is proposed using case-based reasoning intelligent technology. Based on current trends in working conditions and combustion process fault case, the typical faults are predicted the combustion process. On this basis, the real-time air-fuel ratio revision is realized through case-based reasoning algorithm. The appropriate flue gas flow and flue suction are obtained based on fuzzy-PID temperature cascade control, the stability and optimal control of the combustion process is achieved. Intelligent control of air-fuel ratio is realized. Temperature fluctuation is reduced, so the method is effective.
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Keywords: Intelligent control, Coke Oven, Air-fuel ratio, Case-based Reasoning.



go to top   Fluctuation Analysis of Stock Market Using Empirical Mode Decomposition
         by  Bin Miao

         Vol. 7. n. 3, pp. 1268-1272


Abstract – The volatility research of the stock market is of great significance for improving China's securities market management mechanism and helping investors get better returns. In this paper, the empirical mode decomposition method is introduced to analyze the fluctuations of stock prices. Through Matlab simulation, the closing price data of the Shanghai Composite Index from 2006 to 2010 are decomposed with the EMD method into natural modal function of different scales, based on which the characteristics of each IMF component are analyzed and the appropriate trend component is found. The results show that, the change trend of the trend component is much the same with that of the original signal, and the long-term change trend of stock prices can be judged better for the short-term micro-wave interference of the stock price has been excluded, which provides evidence for long-term investors make correct investment decisions.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: EMD Decomposition, Stock Market, Frequency Decomposition, Fluctuation Characteristics, Matlab Simulation.



go to top   Integrated Optimization of Production Planning and Scheduling for Flexible Jobshop
         by  Qiaoying Dong, Jiansha Lu, Yuankun Gui

         Vol. 7. n. 3, pp. 1273-1282


Abstract – The production planning and scheduling of flexible jobshop is more difficult than Jobshop for its multiple selection of processing route and multiple equipments for single process. In the traditional serial production planning and scheduling in flexible jobshop, the plan can not respond to the changes in scheduling and the changes can not be feedback in time. So the integrated optimization complete model of production planning and scheduling for flexible jobshop based on multiple objectives and constraints was constructed. For the difficulty in solving the integrated optimization complete model, an improved discrete particle swarm optimization (IDPSO) was presented to solve the model in discrete space. The segmented encoding method suited for discrete code was proposed to avoid the unfeasible solution and improve the efficiency. A dynamic parameter methods and self-adaptive escapes and variation scheme were proposed to enhance the diversity of particles. For the production planning and scheduling of a metal processing shop on 5 products in 4 cycles, the experiments validate the presented model and algorithm can realize the simultaneously optimization of production planning and scheduling in flexible jobshop and contribute to the performance improvement and the application scope extension of the particle swarm optimization algorithm.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Production Planning, Flexible Jobshop, Integrated Optimization Complete Model, Segmented Encoding, Discrete Particle Swarm Optimization.



go to top   Three-Dimensional Computer Numerical Simulation for Micro-hole Abrasive Flow Machining Feature
         by  Wanjiang Zheng, Junye Li, Guo Hao

         Vol. 7. n. 3, pp. 1283-1287


Abstract – The explanation of abrasive flow ultra-precision machining mechanism offers feasible solution to the improvement of abrasive flow ultra-precision machining ability. The application of modern design technology and means, together with appropriate usage of numerical calculation, will effectively help understand and reveal the experiment. Through the process, the procedures of manufacturing technology are instructed, and the comprehensive properties of the products will be improved. In order to discuss the processing properties of abrasive flow machining special passages, numerical analysis software is employed to perform the three-dimensional simulation. By discussing the way to calculate hydromechanics model and its boundary and initial conditions in solid-liquid two-phase flow field, the mechanical properties and flowing features of turbulent flow during abrasive flow machining can be analyzed and micro-cutting mechanism of abrasive flow machining can be revealed. The simulating results have important theoretical significance for the explanation of abrasive flow ultra-precision machining mechanism
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Keywords: Numerical Calculation, Micro-Hole, Abrasive Flow Machining, Numerical Analysis.



go to top   Data Gathering of Wireless Sensor Networks via Sparsifying Bernoulli Measurement Matrices
         by Xiaoxia Song, Yong Li

         Vol. 7. n. 3, pp. 1288-1292


Abstract – Due to the fact that sensor nodes are usually powered by batteries which are difficult to replace or recharge in most cases, the limited energy supply of sensor node is a main challenge in wide applications of wireless sensor networks (WSNs). Fortunately, the data gathering methods based on compressed sensing (CS) provide a new clue to save and balance the energy of sensor nodes since it can use fewer measurements to perfectly reconstruct the signal by considering the sparsity prior of the signal. This paper proposes a method to collect the data of sensor nodes via sparsifying Bernoulli measurement matrices to further save the energy consumption of sensor nodes. In the proposed method, three schemes are provided to sparsify the Bernoulli measurement matrices. This sparsifying operation may reduce the redundancy among compressive measurements and further save the energy of sensor nodes. Experimental results show that the proposed schemes can save the energy of sensor nodes without reducing reconstruction performances of the signals for the measurements without and with the noise, compared with the Bernoulli measurement scheme.
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Keywords: Wireless Sensor Networks, Data Gathering, Compressed Sensing, Bernoulli Measurement Matrix.



go to top   Supplier Performance Evaluation Based on Entropy for Intuitionistic Fuzzy Sets Method
         by  Mei Li, Chong Wu, Lina You

         Vol. 7. n. 3, pp. 1293-1297


Abstract – The purpose of this article is to provide a method on supplier performance evaluation. By using of entropy for intuitionistic fuzzy sets, this paper analyzes how to evaluate supplier performance. After introducing the relevant definitions and algorithms, the entropy for intuitionistic fuzzy sets model is built and applied in a numerical example.This simple method, combining the advantages of the entropy and intuitionistic fuzzy sets, with high information utilization, can be widely applied in various evaluations.
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Keywords: Supplier Performance Evaluation, Entropy for Intuitionistic Fuzzy Sets.



go to top   Simulation of Delivery Behavior of Mass Customized Supply Chain
         by  Yunxing Xiong, Kepeng Qi, Guohua Xiao

         Vol. 7. n. 3, pp. 1298-1302


Abstract – Studying delivery behavior of mass customized supply chain (abbreviated as MCSC) is a complex and significant work. To simulate the delivery behavior of MCSC, it’s necessary to have a comparative study between TSC (that is traditional supply chain) and MCSC. After analyzing the operating mechanisms of TSC and MCSC, their dynamics models are established by the principle and method of system dynamics to analyze quantificationally their delivery behavior. Then the simulation of delivery stability analysis under the circumstance of the same parameters, ordering cycle and target inventory’s influence to behavior of MCSC and TSC was run. Simulation results indicate that: a) MCSC has greater advantages in meeting its delivery to the last customers; b)For MCSC, its delivery ratio can be increased only through adjusting order cycle time, not through changing target inventory.
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Keywords: Delivery Behavior, Mass Customized Supply Chain, Computer Simulation.



go to top   A Text Classification Algorithm based on Community Discovery
         by  Xiaoqiang Jia

         Vol. 7. n. 3, pp. 1303-1307


Abstract – In order to overcome text classification algorithm based on the SVM ignoring the context of semantic information, construct complex network graph model, On the basis, use community discovery theory to make text classification, introduce the concept of contribution and overlapping coefficient overcome one boundary point can only belong to a community of view, and propose feature selection algorithm based on community discovery. Experiments show the performance of the algorithm, which shows that the algorithm can remain the text in the context of semantic information, and have more reasonable to divide the boundary points into the community. Then in the Bayesian classifier validate the algorithm performance in the recall, precision and F1 values. The results show that the algorithm performance is superior to MIDF and has a good flexibility in text classification.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Complex Network, Text Classification, Community Discover, Contribution Degree, Overlap Coefficient.



go to top   An Improved Single-Image Super-Resolution Algorithm Through Neighbor Embedding and Fusion of Image Patch
         by  Weichu Xiao, Baolong Guo

         Vol. 7. n. 3, pp. 1308-1315


Abstract – Neighbor embedding algorithm has been widely used in single-image super-resolution (SR) reconstruction, which makes the assumption that neighbor patches embedded are contained in a single manifold. However, this is not true for SR because of “one-to-many” mappings between low-resolution (LR) and high-resolution (HR) patches. To overcome the problem, we believe that textures may be contained in multiple manifolds. Under this assumption, by considering that the middle-frequency information of LR images has greater correlation with high resolution image than low frequency. We propose an improved single-image super-resolution algorithm. First, the low-resolution test and train image is decomposed into its middle-frequency and low-frequency components by applying the Gaussian low-pass filter. Then, we use locally linear embedding (LLE) to estimate HR patches for middle-frequency and low-frequency components of the low-resolution test image, respectively. Finally, two HR patches are fused into one by using fusion rules and all HR patches are merged to obtain the final HR image. The experimental results show that the proposed method performs better in both quantitative and qualitative evaluation compare with several NE-related SR approaches and the bi-cubic interpolation.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Super Resolution, Neighbor Embedding, Image Fusion, Locally Linear Embedding.



go to top   Urban Traffic Flow Prediction Based on FNN and Improved GA Optimization
         by  Yuesheng Gu, Peixin Qu, Zhengyong Feng

         Vol. 7. n. 3, pp. 1316-1319


Abstract – Precise prediction of short time traffic flow is the key point to realize reasonable traffic control and induce. The intelligent artificial neural network (ANN) can provide effective forecasting performance. However, inadequate design of the ANN prediction model may lead to a low prediction rate. Hence, a new hybrid intelligent forecasting approach base on the integration of improved genetic algorithm (GA) optimization and fuzzy neural network (FNN) is proposed for the short time traffic flow prediction in this paper. The proposed improved GA-FNN method offers optimized FNN model to avoid the influence of the improper FNN structure. By doing so, the forecasting rate can be improved much higher than traditional ways. 360 samples of the practical traffic flow data are collected to validate the proposed prediction model. The analysis results show that the proposed method can extract the underlying rules of the testing data and decrease the prediction error by 0.58% or better when compared with only FNN approach. Thus, the new improved GA-FNN traffic flow prediction model can provide practical use.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Traffic Flow, Prediction, Genetic Algorithm, Fuzzy Neural Network.



go to top   An Optimization Algorithm for Particle Swarm with Self-Adapted Inertia Weighting Adjustment
         by Zhuang Wu

         Vol. 7. n. 3, pp. 1320-1326


Abstract – According to the standard particle swarm algorithm, when the search space is very complex, it is very easy to fall into the local optimum problem. So the algorithm of particle swarm with dynamically changing inertia weighting adjustment is proposed. First define the best fitness value of rate of change of parameters and the inertia weight of the mathematical expectation will change with the best fitness value of the rate of change of the parameters to have more flexible adjustment of the global search and local search capabilities. The algorithm randomly selects the inertia weight, which makes the impact that the particles have on the former and current speed is random so that they can maintain diversity of population. At last, perform the simulation on the three classical test functions and the results show that the algorithm has been improved both in the average optimal value and success rate, especially in the effect of multi-peak function.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Particle Swarm Optimization, Inertia Weighting, Self-adapted, Diversity of Population.



go to top   A Multimedia Copyright Protection Scheme Using Encryption and Digital Fingerprinting
         by Bentian Jiang, Long Zhang, Kai Xing

         Vol. 7. n. 3, pp. 1327-1330


Abstract – This paper proposes a secure multimedia distribution scheme, which combines encryption and digital fingerprinting technique seamlessly. In the proposed scheme, encryption is used to prevent the copyrighted multimedia content from unauthorized accessing, and the digital fingerprinting technique is used to prove the ownership and uniquely identify the source of pirated copies. Before distributing to customers, the multimedia content copy is encrypted with a partial encryption algorithm to reduce the computational complexity and improves the encryption speed. Each authorized or paid customer can get a different decryption key that is generated from the encryption key and a uniquely assigned serial number called digital fingerprint. At the client end, when different customers use their decryption keys to decrypt the same encrypted copy, they will get slightly different decrypted copies, the difference of the decrypted copies can be used to distinguish and track the corresponding customers.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Secure Multimedia Distribution, Copyright Protection, Encryption, Information Hiding, Digital Fingerprinting.



go to top   Semantic Role Induction Based on Multi-Features
         by Dong Yuan, Jianliang Xu, Jing Xiong, Shuyuan Liu, Feng Liu

      Vol. 7. n. 3, pp. 1331-1336


Abstract – This paper describes a novel approach for inducing the semantic roles of verbal predicate directly from flat text. This approach divides the arguments into two groups according to their complexity of the syntactic structure and classifies each group with different syntactic features. Then an optimized hierarchical algorithm is used to merge clusters from these two groups into finial results. Each cluster in the clustering results represents a specific semantic role. Evaluation on the CoNLL2008 benchmark dataset demonstrated that this approach illustrates how the features work and outperforms competitive unsupervised approaches by a wide margin.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Semantic Role Induction, Multi-Feature, Hierarchical Algorithm.



go to top   Review on Pose of Measurement Sensors and Measurement Methods
         by Qingxuan Jia, Liu Meng

         Vol. 7. n. 3, pp. 1337-1346


Abstract – The pose measurement sensors are popular for autonomous robots and us in recent years. The combination of the pose measurement sensors and measurement methods are helpful to introduce this field more detailed and comprehensive. The use of various sensors to detect the targets may use many kinds of different methods which are adequate for. We use the integration methods to classify the pose measurement sensors into five basic categories such as: mechanical field, magnetic field , ultrasound field, optics and inertial field, then we discuss and analyze the five kinds of sensors .Last we make the analyze for the major measurement methods.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Sensors, Pose Measurement, Autonomous Robot.



go to top   Separation and Extraction of Moving Vehicles in Traffic Images Based on Horizontal Roof Edges
         by Honghui Fan, Hongjin Zhu

         Vol. 7. n. 3, pp. 1347-1351


Abstract – The necessity of traffic monitoring or surveillance is growing. For the purpose of detection moving vehicles in traffic video, Horizontal Roof Edges (HE) method is presented in this paper. Horizontal Roof Edges can strengthen characteristic strength of horizontal direction, so the detection rate of extracting and tracking moving vehicles with horizontal edge can be raised. And the shape of the vehicle is essentially symmetrical, top feature and bottom feature of vehicle can be strengthened by Local AutoCorrelation (LAC), which is converted to LAC images for vehicle detection based on Horizontal Roof Edges method. We verified the system using a variety of weather (in fog, car shadow existence, evening) traffic video, experimental results showed that the high detection rate of moving vehicles be obtained by the proposed method.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Moving Vehicle, Horizontal Roof Edges, Local AutoCorrelation.



go to top   Pest Suicide of Solar Insecticidal Device Based on Buck-Boost Two-Way Converter
         by Zhikun Wang

         Vol. 7. n. 3, pp. 1352-1358


Abstract – This paper designs a double switch Buck-Boost bi-directional converter. First, the STC12C5412AD MCU hardware is used to design the dynamic time domain model of the Buck-Boost converter. Second, the Matlab7.0/VC++ 6.0 converter is utilized to design and analyze the buck-Boost converter. The dynamic time domain model is used to improve simulation speed of the bi-directional converter. The simulation results show that the simplified dynamic phasor model has a high accuracy in calculation. The designed intelligent solar pest control device has a unique advantages and good prospects in application.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Solar Pest Killer Zapper, Bi-Directional Converter, Green Agriculture Production.



go to top   Arc Fault Detection Algorithm for Electrical Fire
         by Qiongfang Yu, Zhina Shi, Dezhong Zheng,Yi Yang, Aihua Dong

         Vol. 7. n. 3, pp. 1359-1362


Abstract –The frequent occurrence of electrical fire is harmful to human’s lives and property. Arc fault is an important reason for the cause of electric fire, comprehensive and effective detection of fault arc is the content of this paper. In the comparisons, the current signal is used for the detection physical parameter and the wavelet transform is used to study the arc fault detection. First constructed the wavelet function, then carried out the arc fault’s wavelet singularity detection, finally analyzed the current signal by the method of wavelet approximation.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Electrical Fire, Arc Fault, Wavelet Transform.



go to top   Agriculture Products Price Forecasting Based on Grey Method and Neural Network
         by Quanyin Zhu, Jiajun Zong, Yonghua Yin

         Vol. 7. n. 3, pp. 1363-1369


Abstract –In order to get the excellent accuracy for price forecast in the agriculture products market, the Grey Prediction method, the RBF Neural Network (NN) and BP NN are utilized to forecast the price of the agriculture products in this paper. Ten agriculture products, which extracted from Agricultural Bank of China from January 2011 to December 2011, are selected to forecast the price about four weeks and compare the Mean Absolute Percentage Errors (MAPE) by Grey Method (GM), RBF NN and BP NN respectively. Experiments demonstrate that the GM(1,1) is not good for forecasting which is only can get 96.5 percent average accuracy, and it is not stable as well. The RBF NN is the better one which can get 98.7 percent average accuracy. While the BP NN is always has high accuracy which is can get 99.6 percent average accuracy. Experiment results prove that this verdict is meaningful and useful to analyze and to research the price forecast in the agriculture products market.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Price Forecast, Agriculture Products, Mean Absolute Percentage Errors(MAPE), Grey Prediction, Neural Network.



go to top   Numerical Simulation of the Netting Panel Rigged with Ropes Based on R Language
         by Yuwei Li, Xinfeng Zhang, Xiaorong Zou, Min Zhang, Yingqi Zhou

         Vol. 7. n. 3, pp. 1370-1374


Abstract – The netting panel rigged with ropes (NPRR) is commonly used and the basic component in fishing gears. The modeling of NPRR is generally constructed as many lumped mass points interconnected with springs without mass. The lumped mass method is successfully used to simulate the dynamical behavior of the netting panel rigged with ropes. And the implicit method is applied to solve the stiff equations. The tension forces of the netting are estimated by the model and the results show that tension loads are mainly concentrated on each rope line.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Netting Panel, Implicit Algorithm, Lumped Mass Method.



go to top   LDPC Code-Aided Frame Synchronization Algorithms Based on LLR Value from Decoder
         by Zhixiong Chen

         Vol. 7. n. 3, pp. 1375-1379


LDPC code-aided frame synchronization algorithms based on Maximum-Likelihood rule are studied. For soft information vectors with different frame offsets, the likelihood ratio value presenting the probability ratio of satisfaction of all check restrictions and dissatisfaction of all check restrictions are computed respectively, and then the point corresponding to the maximum value or larger than a threshold is chosen as the final frame synchronization bounder. Both frame synchronization error ratios of new algorithms are derived. New frame synchronization algorithms can be implemented by parts of LDPC decoder resource. Compared to other code-aided frame synchronization algorithms, simulation results show favorable performance of new code-aided frame synchronization algorithms based on soft information.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: LDPC Codes, Code-Aided, Frame Synchronization, LLR Value.



go to top   An Evolutionary Based Routing Protocol for Clustered Wireless Sensor Networks
         by Shunyuan Sun, Qiu Zhang, Minfang Chen , Baoguo Xu

         Vol. 7. n. 3, pp. 1380-1385


Since sensor nodes have limited energy, energy efficient routing is very important for wireless sensor network (WSN). LEACH and PEGASIS wireless sensor networks are two classic clustering routing protocols among those protocols developed for WSN. In this paper, a new evolutionary based routing protocol for clustered WSN based on LEACH and PEGASIS is proposed, in which the residual energy and link quality are chosen as the criteria of cluster head selecting. The new algorithm utilizes a link quality evaluation model in Gauss distribution, in which the real-time link information is recorded by a dynamic window. In the process of cluster formation, cluster head with low residual energy and poor link quality will be replaced with a high energy and excellent link quality node in order to balance the energy and avoid the premature death of nodes, a chain like PEGASIS among the cluster heads is formed to achieve data integration and multi-hop transmission. To compensate the shortcoming of link routing, a reliable transform scheme is also proposed. Theoretical analysis and simulation data demonstrate that the proposed protocol, compared with LEACH, is more efficient to balance and reduce energy consumption and hence prolongs the network lifetime.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Routing Protocols, Residual Energy, Link Quality, Network Lifetime.



go to top   A Cloud Storage Optimization Approach Based on Genetic Algorithm
         by Xiangbing Zhou, Fang Miao, Hongjiang Ma

         Vol. 7. n. 3, pp. 1386-1391


According to the retractable requirements of the cloud storage about data storage efficiency and space utilization, a cloud storage optimization approach based on genetic algorithm is proposed in this paper. This method is to divide information diffusion through the data at the cloud storage interface, and use genetic algorithm to realize the attributes (buttons) of cloud storage—value optimization storage. Therefore, establish system structure of cloud storage optimization and characteristics of cloud storage in the first place; and then realize information diffusion division through cloud storage interface data based on this, optimize and store the division results by using genetic algorithm; finally, verify by designing an example on SimpleDB, which could effectively improve the efficiency of cloud storage and save storage space.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Cloud Storage, Spread Division, Genetic Algorithm.



go to top   A Probabilistic Fuzzy Set for Uncertainties-Based Integration Inference
         by Wenjing Huang, Yihua Li

         Vol. 7. n. 3, pp. 1392-1397


The probabilistic fuzzy set and the related probabilistic fuzzy logic system is designed for handling the uncertainties with both stochastic and fuzzy features. However, the probabilistic fuzzy set established is just to consider the Gaussian traditional fuzzy set. In fact, based on people’s different perception, triangle is also a popular shape used for membership function in practical application. In this paper, considering the random variation from center in the triangular membership function, a novel probabilistic fuzzy set is proposed. Furthermore, based on the proposed triangular probabilistic fuzzy set, a function approximation is conducted by triangle-based probabilistic fuzzy logic system. It shows the better performance than the ordinary fuzzy logic system in noise circumstance.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Probability Fuzzy Set, Triangular Fuzzy Membership Function, Triangle-Based Probabilistic Fuzzy Logic System.



go to top   General Two-Stage Programming Model of Partial Postponed Production
         by Yanhong Qin

         Vol. 7. n. 3, pp. 1398-1404


The postponement strategy can lessen the mismatch between the forecast-driven production and the actual demand, reduce the effect of bullwhip in the supply chain and improve customer satisfaction obviously. This paper described the concept model of the non postponed production, full postponed production and partial postponed production. And then, I model the general two-stage programming model of partial postponed production, and I proved that when the second stage problem is optimal, the sale quantity will equal the market demand, and the optimal sale price of final product is always positive. Finally, the numerical analysis is applied to analyze the influence of variance, correlation of market size and the substitution coefficient of demand on the quantity and profit, where postponed production and pricing can benefit the manufacturer from the greater demand volatility, and the higher correlation of market sizes will lead to the lower revenue and market risk.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Non Postponed Production, Full Postponed Production, Partial Postponed Production.



go to top   An Image Filtering Method Based on Improved Particle Swarm Optimization Algorithm
         by Zhuang Wu

         Vol. 7. n. 3, pp. 1405-1411


An image filtering algorithm based on improved Particle Swarm Optimization (PSO) -Random Inertia Weight (RIW) algorithm is proposed in this work. Image denoising is an important task in computer vision and image processing, as images acquired through image sensors are usually contaminated by noise. Image denoising algorithms can be directly used for image restoration and other higher-level tasks as a pre-processing step. The main goal of image denoising is to suppress noise images while preserving their features, such as meaningful edges or texture details, as much as possible. PSO algorithms have gained increasing interest for dealing with continuous optimization problems in recent years. PSO algorithm is an optimization tool based on population, which starts from random solution, finds an optimal value via iteration and has the characteristics of simplicity, efficiency, high precision and quick convergence. This paper proposes to adopt a improved PSO-RIW method to seek the optimal parameter of a fuzzy membership function, then perform fuzzy median filtering on the noise image and recover the gray value of the noise stained pixel point. Experimental results show the proposed algorithm gets better PSNR than other methods mentioned, observably. In terms of visual quality, the proposed algorithm can get the images with more details, smooth profiles and aliasing is restricted.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Particle Swarm Optimization, Image Filtering, Self-Adapted Inertia Weighting Adjustment, Median Filtering.



go to top   An Unsupervised Image Segmentation Algorithm Based on Multiresolution Pixon-Represnetation
         by Guoying Liu, Changqing Zhang

         Vol. 7. n. 3, pp. 1412-1418


Pixon only describes the variation of pixels according to the information embedded in the image on a single resolution, which limits its complete feature extraction and counts against the exact label assignation. In order to overcome this problem, this paper presents a multiresolution pixon-based unsupervised image segmentation algorithm, which employs the wavelet transform and the meanshift transform algorithm to produce the multiresolution pixon-representation of the observed image. On each scale, pixons are defined as a region adjacency graph (RAG) and modeled by the Markov random field models (MRFs), and the segmentation result is obtained in the Bayesian framework. The optimization on each resolution scale starts from the initial segmentation obtained from the next coarser resolution scales, and further refines this initial result according to pixon features on this scale. The segmentation result on the primary resolution scale is the final segmentation result of our proposed method. Experiments show that our method is more robust than the pixon-based method on a single resolution scale.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved


Keywords: Image Segmentation, Pixon-Representation, Multiresolution, Markov Random Field.



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