Search results for: Plagiarism detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1513

Search results for: Plagiarism detection

583 Object Tracking System Using Camshift, Meanshift and Kalman Filter

Authors: Afef Salhi, Ameni Yengui Jammaoussi

Abstract:

This paper presents a implementation of an object tracking system in a video sequence. This object tracking is an important task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. In a similar vein, most tracking algorithms use pre-specified methods for preprocessing. In our work, we have implemented several object tracking algorithms (Meanshift, Camshift, Kalman filter) with different preprocessing methods. Then, we have evaluated the performance of these algorithms for different video sequences. The obtained results have shown good performances according to the degree of applicability and evaluation criteria.

Keywords: Tracking, meanshift, camshift, Kalman filter, evaluation.

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582 Effect of Different BER Performance Comparison of MAP and ML Detection

Authors: Naveed Ur Rehman, Rehan Jamil, Irfan Jamil

Abstract:

In this paper, we regard as a coded transmission over a frequency-selective channel. We plan to study analytically the convergence of the turbo-detector using a maximum a posteriori (MAP) equalizer and a MAP decoder. We demonstrate that the densities of the maximum likelihood (ML) exchanged during the iterations are e-symmetric and output-symmetric. Under the Gaussian approximation, this property allows to execute a one-dimensional scrutiny of the turbo-detector. By deriving the analytical terminology of the ML distributions under the Gaussian approximation, we confirm that the bit error rate (BER) performance of the turbo-detector converges to the BER performance of the coded additive white Gaussian noise (AWGN) channel at high signal to noise ratio (SNR), for any frequency selective channel.

Keywords: MAP, ML, SNR, Decoder, BER, Coded transmission.

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581 Misleading Node Detection and Response Mechanism in Mobile Ad-Hoc Network

Authors: Earleen Jane Fuentes, Regeene Melarese Lim, Franklin Benjamin Tapia, Alexis Pantola

Abstract:

Mobile Ad-hoc Network (MANET) is an infrastructure-less network of mobile devices, also known as nodes. These nodes heavily rely on each other’s resources such as memory, computing power, and energy. Thus, some nodes may become selective in forwarding packets so as to conserve their resources. These nodes are called misleading nodes. Several reputation-based techniques (e.g. CORE, CONFIDANT, LARS, SORI, OCEAN) and acknowledgment-based techniques (e.g. TWOACK, S-TWOACK, EAACK) have been proposed to detect such nodes. These techniques do not appropriately punish misleading nodes. Hence, this paper addresses the limitations of these techniques using a system called MINDRA.

Keywords: Mobile ad-hoc network, selfish nodes, reputation-based techniques, acknowledgment-based techniques.

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580 Characterization of the Dispersion Phenomenon in an Optical Biosensor

Authors: An-Shik Yang, Chin-Ting Kuo, Yung-Chun Yang, Wen-Hsin Hsieh, Chiang-Ho Cheng

Abstract:

Optical biosensors have become a powerful detection and analysis tool for wide-ranging applications in biomedical research, pharmaceuticals and environmental monitoring. This study carried out the computational fluid dynamics (CFD)-based simulations to explore the dispersion phenomenon in the micro channel of an optical biosensor. The predicted time sequences of concentration contours were utilized to better understand the dispersion development occurred in different geometric shapes of micro channels. The simulation results showed the surface concentrations at the sensing probe (with the best performance of a grating coupler) in respect of time to appraise the dispersion effect and therefore identify the design configurations resulting in minimum dispersion.

Keywords: CFD simulations, dispersion, microfluidic, optical waveguide sensors.

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579 Calcification Classification in Mammograms Using Decision Trees

Authors: S. Usha, S. Arumugam

Abstract:

Cancer affects people globally with breast cancer being a leading killer. Breast cancer is due to the uncontrollable multiplication of cells resulting in a tumour or neoplasm. Tumours are called ‘benign’ when cancerous cells do not ravage other body tissues and ‘malignant’ if they do so. As mammography is an effective breast cancer detection tool at an early stage which is the most treatable stage it is the primary imaging modality for screening and diagnosis of this cancer type. This paper presents an automatic mammogram classification technique using wavelet and Gabor filter. Correlation feature selection is used to reduce the feature set and selected features are classified using different decision trees.

Keywords: Breast Cancer, Mammogram, Symlet Wavelets, Gabor Filters, Decision Trees

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578 Detecting Rat’s Kidney Inflammation Using Real Time Photoacoustic Tomography

Authors: M. Y. Lee, D. H. Shin, S. H. Park, W.C. Ham, S.K. Ko, C. G. Song

Abstract:

Photoacoustic Tomography (PAT) is a promising medical imaging modality that combines optical imaging contrast with the spatial resolution of ultrasound imaging. It can also distinguish the changes in biological features. But, real-time PAT system should be confirmed due to photoacoustic effect for tissue. Thus, we have developed a real-time PAT system using a custom-developed data acquisition board and ultrasound linear probe. To evaluate performance of our system, phantom test was performed. As a result of those experiments, the system showed satisfactory performance and its usefulness has been confirmed. We monitored the degradation of inflammation which induced on the rat’s kidney using real-time PAT.

Keywords: Photoacoustic tomography, inflammation detection, rat, kidney, contrast agent, ultrasound.

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577 Categories of Botnet: A Survey

Authors: D. Seenivasan, K. Shanthi

Abstract:

Botnets are one of the most serious and widespread cyber threats. Today botnets have been facilitating many cybercrimes, especially financial, top secret thefts. Botnets can be available for lease in the market and are utilized by the cybercriminals to launch massive attacks like DDoS, click fraud, phishing attacks etc., Several large institutions, hospitals, banks, government organizations and many social networks such as twitter, facebook etc., became the target of the botmasters. Recently, noteworthy researches have been carried out to detect bot, C&C channels, botnet and botmasters. Using many sophisticated technologies, botmasters made botnet a titan of the cyber world. Innumerable challenges have been put forth by the botmasters to the researchers in the detection of botnet. In this paper we present a survey of different types of botnet C&C channels and also provide a comparison of various botnet categories. Finally we hope that our survey will create awareness for forthcoming botnet research endeavors.

Keywords: Bot, Botmaster, Botnet, Botnet cloud, Mobile Botnet.

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576 Analysis of Testing and Operational Software Reliability in SRGM based on NHPP

Authors: S. Thirumurugan, D. R. Prince Williams

Abstract:

Software Reliability is one of the key factors in the software development process. Software Reliability is estimated using reliability models based on Non Homogenous Poisson Process. In most of the literature the Software Reliability is predicted only in testing phase. So it leads to wrong decision-making concept. In this paper, two Software Reliability concepts, testing and operational phase are studied in detail. Using S-Shaped Software Reliability Growth Model (SRGM) and Exponential SRGM, the testing and operational reliability values are obtained. Finally two reliability values are compared and optimal release time is investigated.

Keywords: Error Detection Rate, Estimation of Parameters, Instantaneous Failure Rate, Mean Value Function, Non Homogenous Poisson Process (NHPP), Software Reliability.

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575 Intelligent Vision System for Human-Robot Interface

Authors: Al-Amin Bhuiyan, Chang Hong Liu

Abstract:

This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.

Keywords: Fuzzily skewed filter, human-robot interface, rmscontrast, skin color segmentation.

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574 Detection of Coupling Misalignment in a Rotor System Using Wavelet Transforms

Authors: Prabhakar Sathujoda

Abstract:

Vibration analysis of a misaligned rotor coupling bearing system has been carried out while decelerating through its critical speed. The finite element method (FEM) is used to model the rotor system and simulate flexural vibrations. A flexible coupling with a frictionless joint is considered in the present work. The continuous wavelet transform is used to extract the misalignment features from the simulated time response. Subcritical speeds at one-half, one-third, and one-fourth the critical speed have appeared in the wavelet transformed vibration response of a misaligned rotor coupling bearing system. These features are also verified through a parametric study.

Keywords: Continuous wavelet transform, flexible coupling, rotor system, sub critical speed.

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573 Image Segment Matching Using Affine- Invariant Regions

Authors: Ibrahim El rube'

Abstract:

In this paper, a method for matching image segments using triangle-based (geometrical) regions is proposed. Triangular regions are formed from triples of vertex points obtained from a keypoint detector (SIFT). However, triangle regions are subject to noise and distortion around the edges and vertices (especially acute angles). Therefore, these triangles are expanded into parallelogramshaped regions. The extracted image segments inherit an important triangle property; the invariance to affine distortion. Given two images, matching corresponding regions is conducted by computing the relative affine matrix, rectifying one of the regions w.r.t. the other one, then calculating the similarity between the reference and rectified region. The experimental tests show the efficiency and robustness of the proposed algorithm against geometrical distortion.

Keywords: Image matching, key point detection, affine invariant, triangle-shaped segments.

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572 A Four Method Framework for Fighting Software Architecture Erosion

Authors: Sundus Ayyaz, Saad Rehman, Usman Qamar

Abstract:

Software Architecture is the basic structure of software that states the development and advancement of a software system. Software architecture is also considered as a significant tool for the construction of high quality software systems. A clean design leads to the control, value and beauty of software resulting in its longer life while a bad design is the cause of architectural erosion where a software evolution completely fails. This paper discusses the occurrence of software architecture erosion and presents a set of methods for the detection, declaration and prevention of architecture erosion. The causes and symptoms of architecture erosion are observed with the examples of prescriptive and descriptive architectures and the practices used to stop this erosion are also discussed by considering different types of software erosion and their affects. Consequently finding and devising the most suitable approach for fighting software architecture erosion and in some way reducing its affect is evaluated and tested on different scenarios.

Keywords: Software Architecture, Architecture Erosion, Prescriptive Architecture, Descriptive Architecture.

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571 Torque Based Selection of ANN for Fault Diagnosis of Wound Rotor Asynchronous Motor-Converter Association

Authors: Djalal Eddine Khodja, Boukhemis Chetate

Abstract:

In this paper, an automatic system of diagnosis was developed to detect and locate in real time the defects of the wound rotor asynchronous machine associated to electronic converter. For this purpose, we have treated the signals of the measured parameters (current and speed) to use them firstly, as indicating variables of the machine defects under study and, secondly, as inputs to the Artificial Neuron Network (ANN) for their classification in order to detect the defect type in progress. Once a defect is detected, the interpretation system of information will give the type of the defect and its place of appearance.

Keywords: Artificial Neuron Networks (ANN), Effective Value (RMS), Experimental results, Failure detection Indicating values, Motor-converter unit.

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570 Microfluidic Plasmonic Bio-Sensing of Exosomes by Using a Gold Nano-Island Platform

Authors: Srinivas Bathini, Duraichelvan Raju, Simona Badilescu, Muthukumaran Packirisamy

Abstract:

A bio-sensing method, based on the plasmonic property of gold nano-islands, has been developed for detection of exosomes in a clinical setting. The position of the gold plasmon band in the UV-Visible spectrum depends on the size and shape of gold nanoparticles as well as on the surrounding environment. By adsorbing various chemical entities, or binding them, the gold plasmon band will shift toward longer wavelengths and the shift is proportional to the concentration. Exosomes transport cargoes of molecules and genetic materials to proximal and distal cells. Presently, the standard method for their isolation and quantification from body fluids is by ultracentrifugation, not a practical method to be implemented in a clinical setting. Thus, a versatile and cutting-edge platform is required to selectively detect and isolate exosomes for further analysis at clinical level. The new sensing protocol, instead of antibodies, makes use of a specially synthesized polypeptide (Vn96), to capture and quantify the exosomes from different media, by binding the heat shock proteins from exosomes. The protocol has been established and optimized by using a glass substrate, in order to facilitate the next stage, namely the transfer of the protocol to a microfluidic environment. After each step of the protocol, the UV-Vis spectrum was recorded and the position of gold Localized Surface Plasmon Resonance (LSPR) band was measured. The sensing process was modelled, taking into account the characteristics of the nano-island structure, prepared by thermal convection and annealing. The optimal molar ratios of the most important chemical entities, involved in the detection of exosomes were calculated as well. Indeed, it was found that the results of the sensing process depend on the two major steps: the molar ratios of streptavidin to biotin-PEG-Vn96 and, the final step, the capture of exosomes by the biotin-PEG-Vn96 complex. The microfluidic device designed for sensing of exosomes consists of a glass substrate, sealed by a PDMS layer that contains the channel and a collecting chamber. In the device, the solutions of linker, cross-linker, etc., are pumped over the gold nano-islands and an Ocean Optics spectrometer is used to measure the position of the Au plasmon band at each step of the sensing. The experiments have shown that the shift of the Au LSPR band is proportional to the concentration of exosomes and, thereby, exosomes can be accurately quantified. An important advantage of the method is the ability to discriminate between exosomes having different origins.

Keywords: Exosomes, gold nano-islands, microfluidics, plasmonic biosensing.

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569 Nonstationarity Modeling of Economic and Financial Time Series

Authors: C. Slim

Abstract:

Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: Stationarity, unit root tests, economic time series.

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568 Modeling HIV/AIDS Prevention by Defense

Authors: Farai Nyabadza

Abstract:

The functional response of an infective is the relationship between an infected individual-s infection rate and the abundance of the number of susceptibles that one can potentially be infected. In this paper, we consider defensive attitudes for HIV prevention (primary prevention) while at the same time emphasizing on offensive attitudes that reduce infection for those infected (secondary prevention). We look at how defenses can protect an uninfected individual in the case where high risk groups such as commercial sex workers and those who deliberately go out to look for partners. We propose an infection cycle that begins with a search, then an encounter, a proposal and contact. The infection cycle illustrates the various steps an infected individual goes through to successfully infect a susceptible. For heterogeneous transmission of HIV, there will be no infection unless there is contact. The ability to avoid an encounter, detection, proposal and contact constitute defense.

Keywords: Functional response, Infection cycle, Prevention, Defences, SSS equation.

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567 Development of Autonomous Line-Following Soccer Robots

Authors: A. A. Shafie, M. F. Alias, M. H. Ali

Abstract:

The main objective of this project is to build an autonomous microcontroller-based mobile robot for a local robot soccer competition. The black competition field is equipped with white lines to serve as the guidance path for competing robots. Two prototypes of soccer robot embedded with the Basic Stamp II microcontroller have been developed. Two servo motors are used as the drive train for the first prototype whereas the second prototype uses two DC motors as its drive train. To sense the lines, lightdependent resistors (LDRs) supply the analog inputs for the microcontroller. The performances of both prototypes are evaluated. The DC motor-driven robot has produced better trajectory control over the one using servo motors and has brought the team into the final round.

Keywords: Soccer robot, Obstacle detection, Differential drive, Line following.

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566 Wavelet-Based Spectrum Sensing for Cognitive Radios using Hilbert Transform

Authors: Shiann-Shiun Jeng, Jia-Ming Chen, Hong-Zong Lin, Chen-Wan Tsung

Abstract:

For cognitive radio networks, there is a major spectrum sensing problem, i.e. dynamic spectrum management. It is an important issue to sense and identify the spectrum holes in cognitive radio networks. The first-order derivative scheme is usually used to detect the edge of the spectrum. In this paper, a novel spectrum sensing technique for cognitive radio is presented. The proposed algorithm offers efficient edge detection. Then, simulation results show the performance of the first-order derivative scheme and the proposed scheme and depict that the proposed scheme obtains better performance than does the first-order derivative scheme.

Keywords: cognitive radio, Spectrum Sensing, wavelet, edgedetection

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565 Video Coding Algorithm for Video Sequences with Abrupt Luminance Change

Authors: Sang Hyun Kim

Abstract:

In this paper, a fast motion compensation algorithm is proposed that improves coding efficiency for video sequences with brightness variations. We also propose a cross entropy measure between histograms of two frames to detect brightness variations. The framewise brightness variation parameters, a multiplier and an offset field for image intensity, are estimated and compensated. Simulation results show that the proposed method yields a higher peak signal to noise ratio (PSNR) compared with the conventional method, with a greatly reduced computational load, when the video scene contains illumination changes.

Keywords: Motion estimation, Fast motion compensation, Brightness variation compensation, Brightness change detection, Cross entropy.

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564 Effects of Reversible Watermarking on Iris Recognition Performance

Authors: Andrew Lock, Alastair Allen

Abstract:

Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance ofinvestigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: Biometrics, iris recognition, reversible watermarking.

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563 Gesture Recognition by Data Fusion of Time-of-Flight and Color Cameras

Authors: Piercarlo Dondi, Luca Lombardi, Marco Porta

Abstract:

In the last years numerous applications of Human- Computer Interaction have exploited the capabilities of Time-of- Flight cameras for achieving more and more comfortable and precise interactions. In particular, gesture recognition is one of the most active fields. This work presents a new method for interacting with a virtual object in a 3D space. Our approach is based on the fusion of depth data, supplied by a ToF camera, with color information, supplied by a HD webcam. The hand detection procedure does not require any learning phase and is able to concurrently manage gestures of two hands. The system is robust to the presence in the scene of other objects or people, thanks to the use of the Kalman filter for maintaining the tracking of the hands.

Keywords: Gesture recognition, human-computer interaction, Time-of-Flight camera.

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562 A Proposal for U-City (Smart City) Service Method Using Real-Time Digital Map

Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo

Abstract:

Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Keywords: RDM, multi-source data, big data, U-City.

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561 A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images

Authors: Firas Gerges, Frank Y. Shih

Abstract:

Malignant Melanoma, known simply as Melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient death. When detected early, Melanoma is curable. In this paper we propose a deep learning model (Convolutional Neural Networks) in order to automatically classify skin lesion images as Malignant or Benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: Deep learning, skin cancer, image processing, melanoma.

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560 An Automatic Gridding and Contour Based Segmentation Approach Applied to DNA Microarray Image Analysis

Authors: Alexandra Oliveros, Miguel Sotaquirá

Abstract:

DNA microarray technology is widely used by geneticists to diagnose or treat diseases through gene expression. This technology is based on the hybridization of a tissue-s DNA sequence into a substrate and the further analysis of the image formed by the thousands of genes in the DNA as green, red or yellow spots. The process of DNA microarray image analysis involves finding the location of the spots and the quantification of the expression level of these. In this paper, a tool to perform DNA microarray image analysis is presented, including a spot addressing method based on the image projections, the spot segmentation through contour based segmentation and the extraction of relevant information due to gene expression.

Keywords: Contour segmentation, DNA microarrays, edge detection, image processing, segmentation, spot addressing.

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559 Heavy Metals in Marine Sediments of Gulf of Izmir

Authors: E. Kam, Z. U. Yümün, D. Kurt

Abstract:

In this study, sediment samples were collected from four sampling sites located on the shores of the Gulf of İzmir. In the samples, Cd, Co, Cr, Cu, Mn, Ni, Pb and Zn concentrations were determined using inductively coupled, plasma-optical emission spectrometry (ICP-OES). The average heavy metal concentrations were: Cd < LOD (limit of detection); Co 14.145 ± 0.13 μg g−1; Cr 112.868 ± 0.89 μg g−1; Cu 34.045 ± 0.53 μg g−1; Mn 481.43 ± 7.65 μg g−1; Ni 76.538 ± 3.81 μg g−1; Pb 11.059 ± 0.53 μg g−1 and Zn 140.133 ± 1.37 μg g−1, respectively. The results were compared with the average abundances of these elements in the Earth’s crust. The measured heavy metal concentrations can serve as reference values for further studies carried out on the shores of the Aegean Sea.

Keywords: Heavy metal, Aegean Sea, ICP-OES, sediment.

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558 Curvelet Features with Mouth and Face Edge Ratios for Facial Expression Identification

Authors: S. Kherchaoui, A. Houacine

Abstract:

This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: Facial expression identification, curvelet coefficients, support vector machine (SVM).

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557 Educational Plan and Program of the Subject Maintenance of Electric Power Equipment

Authors: Rade Ciric, Sasa Mandic

Abstract:

Students of Higher Education Technical School of Professional Studies in Novi Sad follow the subject ‘Maintenance of Electric Power Equipment’ at the Electrotechnical Department. This paper presents educational plan and program of the subject Maintenance of Electric Power Equipment. The course deals with the problems of preventive and investing maintenance of transformer stations (TS), performing and maintenance of grounding of TS and pillars, as well as tracing and detection the location of the cables failure. There is a special elaborated subject concerning the safe work conditions for the electrician during network maintenance, as well as the basics of making and keeping technical documentation of the equipment.

Keywords: Educational plan and program, electric power equipment, maintenance, technical documentation, safe work.

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556 Determination of Cyclic Citrullinated Peptide Antibodies on Quartz Crystal Microbalance Based Nanosensors

Authors: Y. Saylan, F. Yılmaz, A. Denizli

Abstract:

In this study, we have focused our attention on combining of molecular imprinting into nanofilms and QCM nanosensor approaches and producing QCM nanosensor for anti- CCP, chosen as model protein, using anti-CCP imprinted nanofilms. The nonimprinted nanosensor was also prepared to evaluate the selectivity of the imprinted nanosensor. Anti-CCP imprinted QCM nanosensor was tested for real time detection of anti-CCP from aqueous solution. The kinetic and affinity studies were determined by using anti-CCP solutions with different concentrations. The responses related with mass shifts (%m) and frequency shifts (%f) were used to evaluate adsorption properties. To show the selectivity of the anti-CCP imprinted QCM nanosensor, competitive adsorption of anti-CCP and IgM was investigated. The results indicate that anti- CCP imprinted QCM nanosensor has higher adsorption capabilities for anti-CCP than for IgM, due to selective cavities in the polymer structure.

Keywords: Anti-CCP, molecular imprinting, QCM nanosensor, rheumatoid arthritis.

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555 Risk Classification of SMEs by Early Warning Model Based on Data Mining

Authors: Nermin Ozgulbas, Ali Serhan Koyuncugil

Abstract:

One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.

Keywords: Early Warning Systems, Data Mining, Financial Risk, SMEs.

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554 Adaptive Multi-Camera Shooting System Based on Dynamic Workflow in a Compact Studio

Authors: Norihiro Nishio, Yuki Deguchi, Takahiro Sugiyama, Yoichi Takebayashi

Abstract:

We developed a multi-camera control system that a (one) cameraman can operate several cameras at a compact studio. we analyzed a workflow of a cameraman of some program shootings with two cameras and clarified their heavy tasks. The system based on a dynamic workflow which adapts a program progressing and recommends of cameraman. we perform the automation of multicamera controls by modeling of studio environment and perform automatic camera adjustment for suitable angle of view with face detection. Our experiment at a real program shooting showed that one cameraman can carry out the task of shooting sufficiently.

Keywords: Camera work, compact studio, dynamic workflow, shooting support.

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