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Emerging Technologies, 2008. ICET 2008. 4th International Conference on

Date 18-19 Oct. 2008

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Displaying Results 1 - 25 of 71
  • [Front cover]

    Page(s): c1
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  • [Back cover]

    Page(s): c4
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  • 4th IEEE International conference on emerging technologies 2008

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  • [Title page]

    Page(s): i
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  • [Copyright notice]

    Page(s): ii
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  • Organizing Committee (ICET 2008)

    Page(s): iii
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  • Foreword

    Page(s): iv
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  • Table of contents

    Page(s): v - x
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  • Author index

    Page(s): xi - xiii
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  • Reciprocal anaphora resolution in Pashto discourse

    Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (860 KB)  

    It is very important for an effective machine translation system to transform the multi-sentential discourses, of a source language, into simple and cohesion free discourses. Anaphora resolution is the predicament in computational linguistics that is responsible for the alleged problem. This paper is about the lexical (reciprocal) anaphora resolution in Pashto language and presents an algorithm that is based on the rules to resolve the reciprocal pronouns (RecipPro) of Pashto language. The algorithm has been tested on real world text taken from Pashto stories, novels, newspapers, Web-pages and showed an accuracy of 94.45%. View full abstract»

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  • Genetic Algorithms and its application to image fusion

    Page(s): 6 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1436 KB) |  | HTML iconHTML  

    Image fusion is the process of combining images taken from different sources, to obtain better situational awareness. In fusing source images, the objective is to combine the most relevant information from source images into a composite image. There are many Image Fusion techniques based on signal, pixel, feature and symbol level fusion. Genetic Algorithms (GA's) are used for solving optimization problems. GA can be employed to image fusion where some kind of parameter optimization is required. In this paper, an existing and three novel image fusion algorithms which use GA's are presented. The experimental results have shown that GA based image fusion algorithms outperform the existing image fusion algorithms. GA based image fusion methods are time consuming, so they cannot be adopted in real time applications, however they can be very helpful in static image fusion applications (e.g. concealed weapon detection, medical imaging, remote sensing, weather forecasting etc). View full abstract»

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  • Theoretical foundations of automated synthesis using Bond-Graphs and genetic programming

    Page(s): 11 - 16
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3961 KB) |  | HTML iconHTML  

    Automated synthesis refers to design of physical systems using any of the models proposed for machine intelligence like evolutionary computation, neural networks and fuzzy logic. Mechatronic systems are mixed or hybrid systems as they combine elements from different energy domains. These dynamic systems are inherently complex and capturing underlying energy behavior among interacting sub-systems is difficult owing to the variety in the composition of the mechatronic systems and also due to the limitation imposed by conventional modeling techniques unable to handle more than one energy domain. Bond-graph modeling and simulation is an advanced domain independent, object oriented and polymorphic graphical description of physical systems. The universal modeling paradigm offered by bond-graphs is well suited for mechatronic systems as it can represent their multi energy domain character using a unified notation scheme. Genetic programming is one of the most promising evolutionary computation techniques. The genetic programming paradigm is modeled on Darwinian concepts of evolution and natural selection. Genetic programming starts from a high level statement of a problem's requirements along with a fitness criterion and attempts to produce a computer program that provides a solution to the problem. Combining unified modeling and analysis tools offered by bond-graphs with topologically open ended synthesis and search capability of genetic programming, a novel automated design methodology has been developed for generating mechatronic systems designs using an integrated synthesis, analysis and feedback scheme which comes close to the definition of a true automated invention machine. This research paper develops a theoretical foundation for automated synthesis and design of mechatronic systems using bond-graphs and genetic programming. View full abstract»

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  • A bi-level hierarchical fuzzy object based approach to natural scene classification

    Page(s): 17 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1973 KB) |  | HTML iconHTML  

    A fuzzy logic based approach for modeling various categories of natural scenes in images is presented. Different local objects occurring in a natural scene are represented as fuzzy semantic objects having various color and texture attributes. The entire scene is viewed as a two-level abstraction hierarchy. At the top level, the scene is considered to be comprised of three separate regions defined across its vertical dimension. At the lower level, each region is viewed as a collection of several local fuzzy objects. The frequency of occurrence of fuzzy objects in various vertical regions is used to determine the scene class. The system has been tested on a standard dataset and shows good results. View full abstract»

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  • Hepatic lesions classification by ensemble of SVMs using statistical features based on co-occurrence matrix

    Page(s): 21 - 26
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1069 KB) |  | HTML iconHTML  

    Liver diseases are among the leading causes of death worldwide. The most useful approach for controlling the growth of diseases to reach at severe condition is to treat these diseases at the early stages. Early treatment requires early diagnosis, which needs an accurate and reliable diagnostic procedure. The aim of this study is to develop a computer-aided diagnostic system to achieve aforementioned objective. Computed tomography is one of the most common and robust imaging techniques for the detection of liver lesions. Although in recent years the quality of CT images has been significantly improved, however in some cases image interpretation by human beings is often limited. We developed an automated system to detect and classify liver anomalies using CT images. Region of interest from CT images is segmented using active contours (snakes) algorithm and segmented image is used to extract statistical features based on co-occurrence matrix. To facilitate the classification of hepatic lesions, support vector machine is used. The results show that it is possible to automatically identify patients with liver lesions like hemangioma, hepatoma or cirrhosis based on texture features and that the machine performance is satisfactory and can assist human experts. View full abstract»

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  • Nature inspired optimization techniques for Camera calibration

    Page(s): 27 - 31
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1955 KB) |  | HTML iconHTML  

    Nature inspired optimization algorithm are techniques which imitate some natural phenomenon to find an optimum solution of a problem. We have explored the potential of three nature inspired continuous optimization techniques simulated annealing, genetic algorithms and particle swarm optimization in solving the camera calibration problem in computer vision. Our experiment setup has demonstrated the calibration accuracy achieved with these algorithms with respect to noise levels, variable bounds and number of control points. Results are compared with Tsai , Zhang and Heikkil calibration accuracy. Stochastic nature of these algorithms yields different results for same experiment settings. In order to gain reliable results we have quantitatively determined the probability of achieving accurate results by applying statistical tolerance interval on fitness values computed by each algorithm for various trials. The statistical evaluation shows that in terms of solution accuracy the PSO surpasses SA and GA and produces better results than their non natural competitors Tsai , Zhang and Heikkil , whereas the probability of achieving a correct solution with a desired fitness value range is high with GA. Our work can serve as a guideline for comparative evaluation of natural optimization algorithms with respect to solution quality, reliability and efficiency. View full abstract»

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  • Extracting semantic annotations and their correlation with document components

    Page(s): 32 - 37
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5407 KB) |  | HTML iconHTML  

    Digital repositories can preserve terabytes of information in the form of digital documents. Searching these digital documents requires time and computing resources. Techniques are required to efficiently process these digital repositories. Metadata and semantic annotations can augment the overall search process and provide a foundation to build intelligent applications by using the documents in the repository. In this paper, we are proposing an approach for generation of context aware metadata to enhance search for the scientific publications and also prove the impact of compound words on semantic metadata. Major contribution of our work is to correlate the extracted semantic annotations with the document components. This allows, for example, searching a document centered around a scientific claim by differentiating between author's claims and statements about related systems mentioned in different document components. The approach utilizes the syntactic and semantic measures to increase the quality of the extracted semantic annotations and to bring improvements in precision of search results. View full abstract»

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  • Distributive anaphora resolution in Urdu discourse

    Page(s): 38 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1140 KB)  

    For a human being it is easy to understand and resolve the anaphora in natural languages. For a computer it is a relatively complex task to handle it. This paper is about the resolution of distributive anaphoric devices in Urdu language. The algorithm presented in this paper is tested on real world text taken from e.g. newspapers and novels. The algorithm successfully searches the antecedents to distributive anaphoric devices and resolves the distributive anaphoric links in the text. View full abstract»

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  • Modeling and designing of RF MEMS switch using ANSYS

    Page(s): 44 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1085 KB) |  | HTML iconHTML  

    This paper presents the design optimization and simulation of low-voltage series and capacitive radio frequency (RF) Micro-electromechanical (MEMS) switches using ANSYS Multiphysics. First, a series switch is simulated using shape memory alloy (SMA) which shows that the use of SMA beam to actuate switching, allows the excitation voltage to be relatively much lower (5 V) compared to that needed for electrostatic actuation (30 V). Secondly, in the capacitive switch structure both contact plates of the switch are designed as displaceable membranes with similar dimensions and conditions, differing on only membrane materials. The obtained results (5 V) indicate about 30% reductions in actuation voltage from the conventional single beam (15 V). The stress on the beam due to the actuation voltage is also reduced increasing the switching life time. View full abstract»

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  • Autonomous control for a Kadet MKII RC airplane

    Page(s): 50 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (12052 KB) |  | HTML iconHTML  

    In this paper we present a complete autonomous control system for a Kadet MKII aircraft. This control system comprises a mathematical model of the aircraft, a localization and navigation module, and a set of controller for tracking state trajectories. When coupled together we show the system controls the aircraft with a positioning error ranging from 2-3 m and an orientation error ranging between 3-4deg. View full abstract»

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  • Extended Kalman filter design for multiple satellites formation flying

    Page(s): 56 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2909 KB) |  | HTML iconHTML  

    First of all, mathematically detailed non-linear and linear relative dynamic models for satellites in formation flying in low earth orbit (LEO) are derived and next state estimation based on Kalman filter is emphasized. The Extended Kalman filter (EKF) and linear Kalman filter (LKF) for nonlinear and linear relative models respectively are compared in this paper. By increasing relative distance between satellites in formation, EKF based on nonlinear model outperforms the LKF which is based on linear model. A comparison of the centralized EKF and the centralized LKF has been made to show that centralized EKF exhibits better performance for large formations in terms of absolute estimation error. View full abstract»

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  • Analysis of optimal Adaptive Optics system for Hybrid RF-wireless optical communication for maximum efficiency and reliability

    Page(s): 62 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (9855 KB) |  | HTML iconHTML  

    Free space optics (FSO) has become a viable, high-bandwidth wireless alternative to fiber optic cabling. A more practical solution to extending the high availability range is to back-up the FSO link with a lower data rate radio frequency (RF) link. This hybrid FSO/RF system would extend the 99.999% link range to longer distances and open up a much larger metro/access market to the carriers. However, the atmospheric turbulence is the major limiting factor in these types of systems. The use of the optimal adaptive optics (AO) systems is investigated for mitigation of turbulence effects in the Hybrid RF-FSO systems. We develop the efficient analysis and simulation tools for modeling the highly random, turbulence degraded optical channel. Kolmogorov phase screen models are used to generate realistic aperture plane distributions and calculations and prediction of laser beam parameters. Optical adaptive optics system is used at the receiver end. It is shown that the use of adaptive optics greatly improves the performance of the hybrid receiver by reducing the scintillations induced errors. View full abstract»

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  • Optimal design of measurement-type current transformer using particle swarm optimization

    Page(s): 68 - 73
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2128 KB) |  | HTML iconHTML  

    In this paper a new approach based on particle swarm optimization (PSO) for measurement-type current transformer design has been proposed. This algorithm presents design parameters of current transformer in order to minimize ratio and phase displacement errors to 1.2 times of rated current and also construction cost. It has better performance in comparison with common methods of CT designing that are mainly based on trial and error. In this research, effects of burden change have been taken into consideration and finally, the rated burden of transformer to reach the expected measuring accuracy has been obtained. At the end, several current transformers with different rated values are designed using this method. Results show that the proposed approach can be used for optimal design of current transformer perfectly. View full abstract»

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  • A point target reference spectrum based on Loffeld's bistatic formula (LBF) for hybrid configurations

    Page(s): 74 - 77
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1205 KB) |  | HTML iconHTML  

    This paper concentrates on the focusing for hybrid bistatic SAR configurations, consisting of a space borne/airborne carrier configuration with considerable differences in velocities and altitudes of transmitter and receiver. Therefore the direct implementation of a bistatic SAR focusing algorithm based on Loffeld's bistatic formulae (LBF) cannot be readily applied. An extension of the bistatic point target reference spectrum, based on LBF is derived. Simulated focusing results verify the proposed approach. View full abstract»

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  • Bidirectional Radio-over-Fiber architecture based on frequency up- and down-conversion with lightsource and LO-source free BS

    Page(s): 78 - 82
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (6120 KB) |  | HTML iconHTML  

    Radio-over-Fiber (RoF) is a promising technology to fulfill future broadband access requirements with reliability, transparency and flexibility. We propose bi-directional RoF system with high RF carrier support. Downlink scheme utilizes optical frequency up-conversion while uplink scheme is based on electrical frequency down-conversion. For downlink, an un-modulated micro-wave band signal, fLO electrically combined with DPSK encoded digital data stream sub-carrier modulated at intermediate frequency (IF) is intensity modulated at an optical carrier, fIF in control station. An un-modulated high frequency carrier, local oscillator (LO) is also modulated over separate wavelength, fLO at CS. At remote node (RN), semiconductor optical amplifier Mach-Zehnder interferometer (SOA-MZI) is used for photonic mm-wave mixing (between fIF and fLO) and frequency up-conversion. After photo-detection at BS of optical channel modulated with up-converted RF signal, fRF up-converted downlink data signal at high RF (fRF) is extracted, down-converted to IF, de-modulated and tested for BER. During mixing process at RN, fLO also gets up-converted and modulated over wavelength fRF. For uplink, data at high RF is down-converted to IF at BS by extracting and using up-converted fLO from downlink electrical signal. Further wavelength re-use concept was employed for uplink where down-converted uplink signal is modulated over extracted optical carrier (from downlink signal) and transmitted to CS. Hence, it does not require sending separate optical LO, fLO to each BS. Cost-effective bi-directional solution is proposed with acceptable performance measures by employing wavelength reuse and remote LO delivery concepts. View full abstract»

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  • A stand alone induction generator model producing a constant voltage constant frequency output

    Page(s): 83 - 86
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    Mathematical modelling, design and development of ldquoa variable speed constant frequency self-excited induction generator (IG)rdquo using field-oriented techniques for its voltage and frequency control is described. A space-phasor model for the generator is developed to implement Indirect Field Oriented Control. To study the generator dynamic response the machine was driven by a separately-excited DC motor simulated as a variable speed turbine and a 2.2kW wound rotor IM as an IG. The excitation current for the wound rotor induction generator (variable frequency, 3-phase sinusoidal current) was provided by a current-controlled voltage-source inverter (CCVSI). The generator closed-loop control performance has been studied under varying load and wind speed conditions. Simulated results are compared with experimental data to validate the proposed control system. View full abstract»

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