Volume 3, Issue 3, March 2011

Introducing an Adaptive Intelligent Method for Dynamic Cluster Formation for Mobile Ad-hoc Networks                                                                                                                                                                                        [ Full-Text ]
Sepideh Adabi, Sahar Adabi and Ali Rezaee

Mobile Ad-hoc Networks (MANET) are multi-hop wireless packet networks in which all the nodes cooperatively maintain the network connectivity without the aid of infrastructure networks. This paper proposes a novel Adaptive Intelligent Method for Dynamic Cluster Formation (AIMDCF) in MANETs. The proposed algorithm considers remaining battery, number of neighbors, number of members, and node stability in order to calculate the node’s score with a fuzzy inference algorithm. After each node calculates its score independently, the neighbors of the node must be notified about it. Each node selects one of its neighbors with the highest score to be its cluster head and, therefore the selection of cluster heads is performed in a distributed manner with the most recent information about current status of neighbor nodes. Through simulations we have compared the performance of the proposed algorithm with weighted clustering algorithm, distributed weighted clustering algorithm, fuzzy cluster mean and linked stability-based clustering algorithm in terms of number of clusters, end-to-end throughput, overhead and lifespan of nodes in the system. The simulation results proved that the proposed algorithm has achieved the goals.

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Analysis of Existing Access Control Models from Web Services Applications’ Perspective           [ Full-Text ]
A. Mohammad, T. Khdour, G. Kanaan, R. Kanaan and S. Bani-Ahmad

In web services environment, new requirements must be obeyed by the access control to preserve a satisfied security level to the applications in this environment, for example the dynamic change of the previously unknown users, the heterogeneity of the large number of users and resources, and the effects of context constraint information on the decision making process, all of these requirements and others should be taken into account when we talk about web service access control. In this paper the authors introduce the clearly defined access control requirements for web services, and then an analysis of the current approaches of web service access control is made in the light of these requirements. The advantages and limitations of the existing access control models in the context of web service environments are investigated. These new requirements are also used as assessment criteria in our comparison study between the predominated access control models. This paper is the first step toward web service access control model, and may be used later as guidelines to design access control solutions for web service environment at the application level.

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Technique to Rectify Displaced Vector Graphics Drawn Over Scalable Raster Drawing                 [ Full-Text ]
Yew Kwang Hooi, Wan Fatimah Wan Ahmad and Leong Siew Yoong

Demarcation circumscribes sections of interest of an image by drawing perimeters known as clouds. The clouds are vector graphics stored as an array of coordinate points drawn on the raster image at runtime. At design time, presence of two or more separate coordinate systems introduces disparity in coordinate scales and origin. Consequently, clouds drawn by are sometimes displaced. This paper proposed a drawing mechanism in Java Graphics2D that contains techniques to prevent graphics displacement problem in systems that combine vector graphics with scalable raster image. Calibration of scale sizes and coordinate origins are simple yet useful techniques that allow vector graphics to be drawn correctly over raster drawing regardless of the magnification ratio.

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Museum: Multidimensional web page segment evaluation model                                                         [ Full-Text ]
K. S. Kuppusamy and G. Aghila

The evaluation of a web page with respect to a query is a vital task in the web information retrieval domain. This paper proposes the evaluation of a web page as a bottom-up process from the segment level to the page level. A model for evaluating the relevancy is proposed incorporating six different dimensions. An algorithm for evaluating the segments of a web page, using the above mentioned six dimensions is proposed. The benefits of fine-granining the evaluation process to the segment level instead of the page level are explored. The proposed model can be incorporated for various tasks like web page personalization, result re-ranking, mobile device page rendering etc.

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Integration of Expert System Technology Into VoiceXML-Based Systems                                    [ Full-Text ]
Oyelami M. Olufemi, Uwadia C. Onuwa and Akinwale A. Taofeek

VoiceXML-based systems are dialogue systems that users interact with using either dual tone multi frequency key input or speech. These systems are generally limited in their level of intelligence, capability and sophistication essentially because the language they are built with is a markup language. However, previous work have successfully integrated intelligent component technologies into these systems so as to enable them generate and understand natural language. This work investigated the viability of building expert systems with VoiceXML. In achieving the objectives of this work, the VoiceXML architecture was augmented with expert system component technology. VoiceObjects Desktop for Eclipse was used to develop a dialogue system for diagnosing diseases, and Java expert system shell was used as the intelligent expert system component technology. The result shows that expert system technology can be seamlessly integrated into VoiceXML-based systems thereby making these systems smarter, more sophisticated and enhancing their capability. This kind of system is useful in Africa where the ratio of doctors to citizens is abysmally low, but where the use of mobile phone is on the rise, as a means of augmenting healthcare delivery.

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Enhancing Capacity of IEEE 802.16j Mobile Multi-hop Networks by two-player Game Theory Model                                                                                                                                                                                                  [ Full-Text ]
Venus Marza and Hamidreza Navidi

Primary goal of game theoretical approach is making accurate predictions in strategic situations. IEEE 802.16j Mobile Multi-hop Networks can be formed as tree structures which contains subscriber stations (SS), relay stations (RS), and base stations (BS). In this paper, we propose a 2 player game theory model to maximize upward capacity links. Here, (Mobile/Fixed) Relay Stations (RS) or Subscriber Stations (SS) simulated as players in game and they try to send their message to BS as way that uplink capacity is improved. So players should cooperate with each other and track the Nash equilibrium in each state of tree structure game model.

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Automatic construction of ontology by exploiting web using Google API and JSON                 [ Full-Text ]
Kalyan Netti

Much of the data available on the web is unstructured and constructing ontology from an unexplored domain is a difficult task. Automatic generation of ontology from the unstructured data is a very important part in semantic web. In this paper we present a methodology to automatically contruct an ontology from the information extracted from the web for a given keyword. This ontology represents taxonomy of classes for the specified keyword’s domain and facilitates user to choose most significant sites that he can find on the Web. The automatic construction of ontology that is being suggested, discharges generation and renewal of ontology automatically whenever searching is completed. A key resource in our work is Google Ajax Search API for extracting information and JSON is used to parse the output for the construction of ontology.The obtained classification in hierarchial structured list of the most representative web sites for each ontology class is a great help for finding and accessing the desired web resources.

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A CDMA Based MAC Protocol for Ad Hoc Networks with Directional Antennas                             [ Full-Text ]
Vahid Pourgolzari and Seyed Ali Ghorashi

IEEE 802.11 DCF (Distributed Coordination Function) is one of the basic MAC protocols used in wireless ad hoc networks. The DCF allows nodes to access the medium without any centralized unit and primarily assumes that omni-directional antennas are used for packet transmission at nodes. One of the main challenges in DCF is silent area which yields to channel spatial reuse reduction. This problem can be compensated by utilization of directional antennas. However, using directional antennas itself leads to other problems such as new hidden terminal and deafness problems. In this paper, we propose a new MAC protocol based on CDMA technique in which directional antennas are used. In our proposed multichannel protocol, channels are specified by CDMA codes. One of the channels which is common in the network and called control channel is used for RTS/CTS handshaking and other channels are used for data transmission. In the proposed protocol fewer codes are used compaired to other CDMA based protocols and simulation results in different network topologies show that network throughput is improved and spatial reuse of wireless channel is higher compaired to 802.11 DCF, DMAC (basic Directional MAC) and conventional CDMA based MAC protocols based on IEEE 802.11 DCF.

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Improved Nelder Mead’s Simplex Method and Applications                                                                    [ Full-Text ]
Nam Pham and Bogdan M. Wilamowski

Nelder Mead’s simplex method is known as a fast and widely used algorithm in local minimum optimization. However, this algorithm by itself does not have enough capability to optimize large scale problems or train neural networks. This paper will present a solution to improve this deficiency of Nelder Mead’s simplex algorithm by incorporating with a quasi gradient method. This method approximates gradients of a function in the vicinity of a simplex by using numerical methods without calculating derivatives and it is much simpler than analytical gradient methods in mathematic perspectives. With this solution, the improved algorithm can converge much faster with higher success rate and still maintain the simplicity of simplex method. Testing results with several benchmark optimization problems of this improved algorithm will be compared with Nelder Mead’s simplex method. Then this algorithm will be applied in synthesizing lossy ladder filters and training neural networks to control robot arm kinematics. These typical applications are used to show the ability of the improved algorithm to solve the varieties of engineering problems.

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Optimal Weight Selection of ANN to Predict the Price of the General Index for Amman Stock Exchange                                                                                                                                                                                         [ Full-Text ]
K. Eghnam, A. Sheta and S. Bani-Ahmad

Artificial neural networks (ANNs) have been successfully used to solve variety of problem in prediction, recognition, pattern classification, modeling and simulation of dynamic systems. Unfortunately, it was reported that the optimization of the ANN weights represents a challenge. The reason is traditional ANN learning algorithms such as the back propagation algorithm can stuck by local minimum. There is no guarantee that the produced weights are the optimal set to solve the problem under study. Genetic Algorithms (GAs) were able to provide solutions for diversity of parameter optimization problems. In this study, we encoded the ANN weights as parameters (i.e. chromosome) for GAs to optimize. This simple idea significantly helps in solving a challenge problem in stock exchange. A financial data set for Banks Participation, Insurance Participation, Service Participation, and Industry Participation for the period 1992-2005 was collected from Amman Stock Exchange (ASE). This data set was used as a training data set for the proposed ANNs-GAs model. The developed results show that the proposed model out-performs the traditional Multiple Linear Regression model (MLR) with 4.95%. The experimental results are promising.

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The Evolution of Synchronous Sequential Circuits Based on Description of gate levels                [ Full-Text ]
P. Soleimani, S. Mirzakuchaki and R. Sabbaghi-Nadooshan

Evolvable hardware (EHW) is a new concept for automatic design of electronic systems instead of manual design that has been used by electronic engineering. Final purpose of EHW is to build the electronic circuit. Conventional method, specify that the design and the implementation of the electronic circuit how does, but evolutionary design method only denotes the implementation of the circuit. This paper, proposes a method to design and optimize the synchronous sequential circuits. Evolutionary strategy has been used as evolutionary algorithm. In this approach, to increase the speed of evolution, each combinational parts of sequential circuit have been evolved separately. Finally, the sequential circuit has been assembled. The results show our method can reduce the number of generations and the time of evoluation for designing and decreasing the number of logic gates which have been used in combinational parts of sequential circuit.

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Secure and Priority Based Routing Mechan-ism in MANET through Mobile Agent                            [ Full-Text ]
Puneet Kumar and A. K. Vatsa

The wide availability of mobile devices equipped with infrastructure-free wireless communication capabilities together with the technical possibility to form Mobile ad-hoc networks (MANET) paved the path for building highly dynamic communities of mobile users. Mobile agent is a program segment which is self-controlling. The mobile agents have no security mechanism and authentication scheme is used to permit mobile agents to perform computations. Due to lacks of security aspects when applied to MANET where nodes cannot be classified as they are malicious or not, hence for the cases where the security of data or reliability of agent became must we need some method to insure the things. Thus, In this paper, we propose a Admission Control Mechanism on hierarchical model architecture of MANET maintained by Mobile agent using secure and priority based routing algorithm with effective security authentication technique. Our technique has three phases, In Initial phase, Admission Control method - where we provide admission of mobile nodes in hierarchical model. In the next phase, we discuss the priority based routing mechanism using BFS technique for routing. In the last phase, we provide security over mobile agents with effective authentication methods.

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Design of novel optimized reversible multiplier                                                                                            [ Full-Text ]
S B Rashmi and H K Shreedhar

Reversible logic has emerged as one of the most important approaches for power optimization, which finds  applications in low power CMOS design, quantum computing, optical information processing, DNA computing, bioinformatics and nanotechnology. Multipliers are very essential for the construction of various computational units of a quantum computer. Quantum cost of a reversible multiplier circuit can be minimized by reducing the number of reversible logic gates and garbage outputs. This paper proposes an improved design of a 4 X 4 multiplier using reversible logic gates. It is faster and has lower hardware complexity compared to the existing designs. In addition, the proposed reversible multiplier is better than the existing counterparts in terms of number of gates, number of garbage outputs, number of constant inputs and quantum cost.

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Code Signed ZIP Validation Using Native OS Calls                                                                                    [ Full-Text ]
Milind Wanjari and Susmita Gupta

A mechanism to validate signed ZIP files without JRE dependence is significant, particularly in the case of software developed for native OS. This paper provides an overview of the validation process of code signed ZIP file using native OS calls. The most commonly used method of code signing and validating ZIP files is by using Sun’s JARSigner utility. This utility comes along with the Java Runtime Environment (JRE). Any application on any OS with JRE installed can use this utility to validate code signed ZIP files. But this also means that there is a dependency on JRE. To remove this dependency, applications must have their own mechanism to validate code signed ZIP files. ZIP validation using native Windows OS calls is one such area which has been worked on and detailed in this paper.

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Intelligent Diagnostic System for the diagnosis and prognosis of Breast Cancer using ANN        [ Full-Text ]
R. R. Janghel, Anuj Mehra, Anupam Shukla and Ritu Tiwari

Breast cancer occurs mostly in women and figures states that almost one out of eight women suffers from this disease. Breast cancer is second only to lung cancer that causes the majority of deaths among women and is difficult to identify accurately and treat. Diagnostic computational tools can be used effectively, with high degree of accuracy, which may help in improving the specificity and sensitivity of diagnoses. There are two known types of breast cancer namely benign and malignant which are cured mostly by mammography, FNA (Fine Needle Aspirate) and surgical biopsy. In this research work, our main objective is to develop and compare a diagnostic system for diagnosis; prognosis and prediction of breast cancer with the usage of the computational intelligence namely Back Propagation (BPA), Learning vector Quantization (LVQ), Support vector machine (SVM) and Adaptive Neuro-fuzzy Inference System (ANFIS). These modeling tools can highlight the important features that play pivotal roles in the classification and aid physicians to diagnose and prognosticate breast cancer. The database used in developing the above discussed model in this research work is adopted from the University of Wisconsin (UCI) Machine Learning Repository. Experimental result shows that different models give optimal performance for the data set. However, all the models are able to solve the problem up to a greater extent but a maximum accuracy of 96.50% is being achieved on the usage of LVQ which outdo all the other models.

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Forecasting Gold prices using Fuzzy C means                                                                                        [ Full-Text ]
Pushpa Rani Suri and Neetu Sardana

Gold is a precious metal since past and consequently its price forecast has been a subject of interest among people. The demand for this commodity is on the rise. Due to increase in its demand, it is necessary to develop a model that reflects the structure and pattern of gold market and forecast movement of gold price. For this reason, we make an attempt to develop a forecasting model for predicting gold prices. We use Fuzzy C Mean (FCM) based on the Takagi-Sugeno Model, to forecast gold price. The results obtained are satisfactory.

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RBF Kernel Support Vector Regression based Controller for a Robot gripper                                    [ Full-Text ]
D. V. Pushpalatha and K. R. Sudha

Robotic grippers are commonly required to grasp and manipulate loads under a wide range of operating conditions, without the load slipping from the end-effector and avoiding damage to the load. The increasing demand on robotic gripper performance leads to the use of advanced control strategies. In the present paper, a novel approach for on-line adaptive tuning of Support Vector Regression (SVR) based controller for a two finger robot gripper using RBF kernel is presented. The efficacy of the controller is tested on Robot gripper and compared with unsymmetrical triangular input fuzzy logic controller. It is observed that the proposed controller results to a better response than the unsymmetrical fuzzy sets.

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Design of generalized regression model based neural network controller to improve transient stability of power system                                                                                                                                                      [ Full-Text ]
K. R. Sudha and K. Harinadha Reddy

This paper presents the design of neural network controller for Unified Power Flow Controller to reduce the oscillations of power system network. The generalised neural network is used to minimize error signal at signified level. A generalised regression neural network controller has been developed for conventional power system stabiliser using error signal derived from power system network. The Power system stabilizer has been tested for different operating conditions with 250ms fault duration and carried simulations using a single machine-infinite bus model.

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A  study using covering to attribute reduction in information systems                                                [ Full-Text ]
A. S. Salama

Attribute reduction is considered as an important preprocessing step for pattern recognition, machine learing, and data mining. This paper provides a topological study on attribute reduction with covering rough sets. We study covering-based rough sets from the topological  point of view. We explore the topological properties of this type of rough sets, study the interdependency between the lower and the upper approximation operations, and establish the conditions under which two coverings generate the same lower approximation and the same upper approximation operation. We define a covering information system, a consistent covering decision system, and a covering decision system and their attribute reductions. Furthermore, we present an algorthim to reduce  any covering. Also, we present a discernability matrix  and a discernability function associated with attribute reduction; based on them, we can compute all the reducts and the core of any covering information system.

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Data Mining Based on Extreme Learning Machines for the Classification of Premium and Regular Gasoline in Arson and Fuel Spill Investigation                                                                                                            [ Full-Text ]
S. O. Olatunji, Imran A. Adeleke and Alaba Akingbesote

In this work, we developed a data mining approach based on extreme learning machines (ELM) for identifying gasoline types. Detection and correct identification of gasoline types during Arson and Fuel Spill Investigation are very important in forensic science.  As the number of arson and spillage becomes a common place, it becomes more important to have an accurate means of detecting and classifying gasoline found at such sites of incidence. However, currently only a very few number of classification models have been explored in this germane field of forensic science, particularly as relates to gasoline identification. The proposed model was constructed using gas chromatography–mass spectrometry (GC–MS) spectral data obtained from gasoline sold in Canada over one calendar year. Prediction accuracy of the model was evaluated and compared with earlier used methods on the same datasets. Empirical results from simulation showed that the proposed ELM based approach achieved better performance compared to other earlier implemented techniques.

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