Search results for: Contrast masking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 342

Search results for: Contrast masking

282 Pre-Analysis of Printed Circuit Boards Based On Multispectral Imaging for Vision Based Recognition of Electronics Waste

Authors: Florian Kleber, Martin Kampel

Abstract:

The increasing demand of gallium, indium and rare-earth elements for the production of electronics, e.g. solid state-lighting, photovoltaics, integrated circuits, and liquid crystal displays, will exceed the world-wide supply according to current forecasts. Recycling systems to reclaim these materials are not yet in place, which challenges the sustainability of these technologies. This paper proposes a multispectral imaging system as a basis for a vision based recognition system for valuable components of electronics waste. Multispectral images intend to enhance the contrast of images of printed circuit boards (single components, as well as labels) for further analysis, such as optical character recognition and entire printed circuit board recognition. The results show, that a higher contrast is achieved in the near infrared compared to ultraviolett and visible light.

Keywords: Electronic Waste, Recycling, Multispectral Imaging, Printed Circuit Boards, Rare-Earth Elements.

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281 An Improved Illumination Normalization based on Anisotropic Smoothing for Face Recognition

Authors: Sanghoon Kim, Sun-Tae Chung, Souhwan Jung, Seongwon Cho

Abstract:

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an improved illumination normalization method for face recognition. Illumination normalization algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing-based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing the effect of illumination variations. Due to the result of these improvements, face images preprocessed by the proposed illumination normalization method becomes to have more distinctive feature vectors (Gabor feature vectors) for face recognition. Through experiments of face recognition based on Gabor feature vector similarity, the effectiveness of the proposed illumination normalization method is verified.

Keywords: Illumination Normalization, Face Recognition, Anisotropic smoothing, Gabor feature vector.

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280 Enhancement of m-FISH Images using Spectral Unmixing

Authors: Martin De Biasio, Raimund Leitner, Franz G. Wuertz, Sergey Verzakov, Pierre J. Elbischger

Abstract:

Breast carcinoma is the most common form of cancer in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is a common method for staging breast carcinoma. The interpretation of m-FISH images is complicated due to two effects: (i) Spectral overlap in the emission spectra of fluorochrome marked DNA probes and (ii) tissue autofluorescence. In this paper hyper-spectral images of m-FISH samples are used and spectral unmixing is applied to produce false colour images with higher contrast and better information content than standard RGB images. The spectral unmixing is realised by combinations of: Orthogonal Projection Analysis (OPA), Alterating Least Squares (ALS), Simple-to-use Interactive Self-Modeling Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied on the data to reduce tissue autofluorescence and resolve the spectral overlap in the emission spectra. The results show that spectral unmixing methods reduce the intensity caused by tissue autofluorescence by up to 78% and enhance image contrast by algorithmically reducing the overlap of the emission spectra.

Keywords: breast carcinoma, hyperspectral imaging, m-FISH, spectral unmixing

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279 Performance of Compound Enhancement Algorithms on Dental Radiograph Images

Authors: S.A.Ahmad, M.N.Taib, N.E.A.Khalid, R.Ahmad, H.Taib

Abstract:

The purpose of this research is to compare the original intra-oral digital dental radiograph images with images that are enhanced using a combination of image processing algorithms. Intraoral digital dental radiograph images are often noisy, blur edges and low in contrast. A combination of sharpening and enhancement method are used to overcome these problems. Three types of proposed compound algorithms used are Sharp Adaptive Histogram Equalization (SAHE), Sharp Median Adaptive Histogram Equalization (SMAHE) and Sharp Contrast adaptive histogram equalization (SCLAHE). This paper presents an initial study of the perception of six dentists on the details of abnormal pathologies and improvement of image quality in ten intra-oral radiographs. The research focus on the detection of only three types of pathology which is periapical radiolucency, widen periodontal ligament space and loss of lamina dura. The overall result shows that SCLAHE-s slightly improve the appearance of dental abnormalities- over the original image and also outperform the other two proposed compound algorithms.

Keywords: intra-oral dental radiograph, histogram equalization, sharpening, CLAHE.

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278 Enhanced Multi-Intensity Analysis in Multi-Scenery Classification-Based Macro and Micro Elements

Authors: R. Bremananth

Abstract:

Several computationally challenging issues are encountered while classifying complex natural scenes. In this paper, we address the problems that are encountered in rotation invariance with multi-intensity analysis for multi-scene overlapping. In the present literature, various algorithms proposed techniques for multi-intensity analysis, but there are several restrictions in these algorithms while deploying them in multi-scene overlapping classifications. In order to resolve the problem of multi-scenery overlapping classifications, we present a framework that is based on macro and micro basis functions. This algorithm conquers the minimum classification false alarm while pigeonholing multi-scene overlapping. Furthermore, a quadrangle multi-intensity decay is invoked. Several parameters are utilized to analyze invariance for multi-scenery classifications such as rotation, classification, correlation, contrast, homogeneity, and energy. Benchmark datasets were collected for complex natural scenes and experimented for the framework. The results depict that the framework achieves a significant improvement on gray-level matrix of co-occurrence features for overlapping in diverse degree of orientations while pigeonholing multi-scene overlapping.

Keywords: Automatic classification, contrast, homogeneity, invariant analysis, multi-scene analysis, overlapping.

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277 Application of Mutual Information based Least dependent Component Analysis (MILCA) for Removal of Ocular Artifacts from Electroencephalogram

Authors: V Krishnaveni, S Jayaraman, K Ramadoss

Abstract:

The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.

Keywords: Electroencephalogram, Ocular Artifacts (OA), Independent Component Analysis (ICA), Mutual Information (MI), Mutual Information based Least dependent Component Analysis(MILCA)

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276 An Image Enhancement Method Based on Curvelet Transform for CBCT-Images

Authors: Shahriar Farzam, Maryam Rastgarpour

Abstract:

Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: Curvelet transform, image enhancement, CBCT, image denoising.

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275 Design and Fabrication of an Electrostatically Actuated Parallel-Plate Mirror by 3D-Printer

Authors: J. Mizuno, S. Takahashi

Abstract:

In this paper, design and fabrication of an actuated parallel-plate mirror based on a 3D-printer is described. The mirror and electrode layers are fabricated separately and assembled thereafter. The alignment is performed by dowel pin-hole pairs fabricated on the respective layers. The electrodes are formed on the surface of the electrode layer by Au ion sputtering using a suitable mask, which is also fabricated by a 3D-printer.For grounding the mirror layer, except the contact area with the electrode paths, all the surface is Au ion sputtered. 3D-printers are widely used for creating 3D models or mock-ups. The authors have recently proposed that these models can perform electromechanical functions such as actuators by suitably masking them followed by metallization process. Since the smallest possible fabrication size is in the order of sub-millimeters, these electromechanical devices are named by the authors as SMEMS (Sub-Milli Electro-Mechanical Systems) devices. The proposed mirror described in this paper which consists of parallel-plate electrostatic actuators is also one type of SMEMS devices. In addition, SMEMS is totally environment-clean compared to MEMS (Micro Electro-Mechanical Systems) fabrication processes because any hazardous chemicals or gases are utilized.

Keywords: MEMS, parallel-plate mirror, SMEMS, 3D-printer.

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274 A New Image Psychovisual Coding Quality Measurement based Region of Interest

Authors: M. Nahid, A. Bajit, A. Tamtaoui, E. H. Bouyakhf

Abstract:

To model the human visual system (HVS) in the region of interest, we propose a new objective metric evaluation adapted to wavelet foveation-based image compression quality measurement, which exploits a foveation setup filter implementation technique in the DWT domain, based especially on the point and region of fixation of the human eye. This model is then used to predict the visible divergences between an original and compressed image with respect to this region field and yields an adapted and local measure error by removing all peripheral errors. The technique, which we call foveation wavelet visible difference prediction (FWVDP), is demonstrated on a number of noisy images all of which have the same local peak signal to noise ratio (PSNR), but visibly different errors. We show that the FWVDP reliably predicts the fixation areas of interest where error is masked, due to high image contrast, and the areas where the error is visible, due to low image contrast. The paper also suggests ways in which the FWVDP can be used to determine a visually optimal quantization strategy for foveation-based wavelet coefficients and to produce a quantitative local measure of image quality.

Keywords: Human Visual System, Image Quality, ImageCompression, foveation wavelet, region of interest ROI.

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273 Monitoring the Effect of Doxorubicin Liposomal in VX2 Tumor Using Magnetic Resonance Imaging

Authors: Ren-Jy Ben, Jo-Chi Jao, Chiu-Ya Liao, Ya-Ru Tsai, Lain-Chyr Hwang, Po-Chou Chen

Abstract:

Cancer is still one of the serious diseases threatening the lives of human beings. How to have an early diagnosis and effective treatment for tumors is a very important issue. The animal carcinoma model can provide a simulation tool for the studies of pathogenesis, biological characteristics, and therapeutic effects. Recently, drug delivery systems have been rapidly developed to effectively improve the therapeutic effects. Liposome plays an increasingly important role in clinical diagnosis and therapy for delivering a pharmaceutic or contrast agent to the targeted sites. Liposome can be absorbed and excreted by the human body, and is well known that no harm to the human body. This study aimed to compare the therapeutic effects between encapsulated (doxorubicin liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox) anti-tumor drugs using magnetic resonance imaging (MRI). Twenty-four New Zealand rabbits implanted with VX2 carcinoma at left thighs were classified into three groups: control group (untreated), Dox-treated group, and LipoDox-treated group, 8 rabbits for each group. MRI scans were performed three days after tumor implantation. A 1.5T GE Signa HDxt whole body MRI scanner with a high resolution knee coil was used in this study. After a 3-plane localizer scan was performed, three-dimensional (3D) fast spin echo (FSE) T2-weighted Images (T2WI) was used for tumor volumetric quantification. Afterwards, two-dimensional (2D) spoiled gradient recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was used for tumor perfusion evaluation. DCE-MRI was designed to acquire four baseline images, followed by contrast agent Gd-DOTA injection through the ear vein of rabbit. A series of 32 images were acquired to observe the signals change over time in the tumor and muscle. The MRI scanning was scheduled on a weekly basis for a period of four weeks to observe the tumor progression longitudinally. The Dox and LipoDox treatments were prescribed 3 times in the first week immediately after the first MRI scan; i.e. 3 days after VX2 tumor implantation. ImageJ was used to quantitate tumor volume and time course signal enhancement on DCE images. The changes of tumor size showed that the growth of VX2 tumors was effectively inhibited for both LipoDox-treated and Dox-treated groups. Furthermore, the tumor volume of LipoDox-treated group was significantly lower than that of Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is significantly lower than that of the other two groups, which implies that targeted therapeutic drug remained in the tumor tissue. This study provides a radiation-free and non-invasive MRI method for therapeutic monitoring of targeted liposome on an animal tumor model.

Keywords: Doxorubicin, dynamic contrast-enhanced MRI, lipodox, magnetic resonance imaging, VX2 tumor model.

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272 Accelerating Quantum Chemistry Calculations: Machine Learning for Efficient Evaluation of Electron-Repulsion Integrals

Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

Abstract:

A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient, but not the magnitude. A neural network with two hidden layers was then used to learn the coefficient magnitudes, along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: Quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction.

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271 Iris Recognition Based On the Low Order Norms of Gradient Components

Authors: Iman A. Saad, Loay E. George

Abstract:

Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: Iris recognition, contrast stretching, gradient features, texture features, Euclidean metric.

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270 The Impact of Hospital Intensive Care Unit Window Design on Daylighting and Energy Performance in Desert Climate

Authors: A. Sherif, H. Sabry, A. Elzafarany, M. Gadelhak, R. Arafa, M. Aly

Abstract:

This paper addresses the design of hospital Intensive Care Unit windows for the achievement of visual comfort and energy savings. The aim was to identify the window size and shading system configurations that could fulfill daylighting adequacy, avoid glare and reduce energy consumption. The study focused on addressing the effect of utilizing different shading systems in association with a range of Window-to-Wall Ratios (WWR) in different orientations under the desert clear-sky of Cairo, Egypt. The results of this study demonstrated that solar penetration is a critical concern affecting the design of ICU windows in desert locations, as in Cairo, Egypt. Use of shading systems was found to be essential in providing acceptable daylight performance and energy saving. Careful positioning of the ICU window towards a proper orientation can dramatically improve performance. It was observed that ICU windows facing the north direction enjoyed the widest range of successful window configuration possibilities at different WWRs. ICU windows facing south enjoyed a reasonable number of configuration options as well. By contrast, the ICU windows facing the east orientation had a very limited number of options that provide acceptable performance. These require additional local shading measures at certain times due to glare incidence. Moreover, use of horizontal sun breakers and solar screens to protect the ICU windows proved to be more successful than the other alternatives in a wide range of Window to Wall Ratios. By contrast, the use of light shelves and vertical shading devices seemed questionable.

Keywords: Daylighting, Desert, Energy Efficiency, Shading.

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269 Development of Effective Cooling Schemes of Gas Turbine Blades Based on Computer Simulation

Authors: Pasayev, A., C. Askerov, R. Sadiqov, C. Ardil

Abstract:

In contrast to existing of calculation of temperature field of a profile part a blade with convective cooling which are not taking into account multi connective in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM AND FDM) numerical methods from the point of view of a realization on the PC. The theoretical substantiation of these methods is proved by the appropriate theorems.

Keywords: multi coherent systems, method of the boundary integrated equations, singular operators, gas turbines

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268 Oxygen-Interstitials and Group-V Element Doping for p-Type ZnO

Authors: A. M. Gsiea, J. P. Goss, P. R. Briddon, K. M. Etmimi

Abstract:

In realizing devices using ZnO, a key challenge is the production of p-type material. Substitution of oxygen by a group-V impurity is thought to result in deep acceptor levels, but a candidate made up from a complex of a group-V impurity (P, As, Sb) on a Zn site coupled with two vacant Zn sites is widely viewed as a candidate. We show using density-functional simulations that in contrast to such a view, complexes involving oxygen interstitials are energetically more favorable, resulting in group-V impurities coordinated with four, five or six oxygen atoms.

Keywords: DFT, Oxygen, p-Type, ZnO.

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267 Toward Indoor and Outdoor Surveillance Using an Improved Fast Background Subtraction Algorithm

Authors: A. El Harraj, N. Raissouni

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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266 Making Computer Learn Color

Authors: Rinaldo Christian Tanumara, Ming Xie

Abstract:

Color categorization is shared among members in a society. This allows communication of color, especially when using natural language such as English. Hence sociable robot, to live coexist with human in human society, must also have the shared color categorization. To achieve this, many works have been done relying on modeling of human color perception and mathematical complexities. In contrast, in this work, the computer as brain of the robot learns color categorization through interaction with humans without much mathematical complexities.

Keywords: Color categorization, color learning, machinelearning.

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265 Thermoelectric Generators as Alternative Source for Electric Power

Authors: L. C. Ding, Bradley. G. Orr, K. Rahaoui, S. Truza, A. Date, A. Akbarzadeh

Abstract:

The research on thermoelectric has been a blooming field of research for the latest decade, owing to large amount of heat source available to be harvested, being eco-friendly and static in operation. This paper provides the performance of thermoelectric generator (TEG) with bulk material of bismuth telluride, Bi2Te3. Later, the performance of the TEGs is evaluated by considering attaching the TEGs on a plastic (polyethylene sheet) in contrast to the common method of attaching the TEGs on the metal surface.

Keywords: Electric power, heat transfer, renewable energy, thermoelectric generator.

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264 An Implementation of Stipple Operations

Authors: Nakhoon Baek

Abstract:

Stipples are desired for pattern fillings and transparency effects. In contrast, some graphics standards, including OpenGL ES 1.1 and 2.0, omitted this feature. We represent details of providing line stipples and polygon stipples, through combining texture mapping and alpha blending functions. We start from the OpenGL-specified stipple-related API functions. The details of mathematical transformations are explained to get the correct texture coordinates. Then, the overall algorithm is represented, and its implementation results are followed. We accomplished both of line and polygon stipples, and verified its result with conformance test routines.

Keywords: Stipple operation, OpenGL ES, Implementation.

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263 On the Construction of Lightweight Circulant Maximum Distance Separable Matrices

Authors: Qinyi Mei, Li-Ping Wang

Abstract:

MDS matrices are of great significance in the design of block ciphers and hash functions. In the present paper, we investigate the problem of constructing MDS matrices which are both lightweight and low-latency. We propose a new method of constructing lightweight MDS matrices using circulant matrices which can be implemented efficiently in hardware. Furthermore, we provide circulant MDS matrices with as few bit XOR operations as possible for the classical dimensions 4 × 4, 8 × 8 over the space of linear transformations over finite field F42 . In contrast to previous constructions of MDS matrices, our constructions have achieved fewer XORs.

Keywords: Linear diffusion layer, circulant matrix, lightweight, MDS matrix.

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262 Measuring E-Learning Effectiveness Using a Three-Way Comparison

Authors: Matthew Montebello

Abstract:

The way e-learning effectiveness has been notoriously measured within an academic setting is by comparing the e-learning medium to the traditional face-to-face teaching methodology. In this paper, a simple yet innovative comparison methodology is introduced, whereby the effectiveness of next generation e-learning systems are assessed in contrast not only to the face-to-face mode, but also to the classical e-learning modality. Ethical and logistical issues are also discussed, as this three-way approach to compare teaching methodologies was applied and documented in a real empirical study within a higher education institution.

Keywords: E-learning effectiveness, higher education, teaching modality comparison.

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261 Bleeding Detection Algorithm for Capsule Endoscopy

Authors: Yong-Gyu Lee, Gilwon Yoon

Abstract:

Automatic detection of bleeding is of practical importance since capsule endoscopy produces an extremely large number of images. Algorithm development of bleeding detection in the digestive tract is difficult due to different contrasts among the images, food dregs, secretion and others. In this study, were assigned weighting factors derived from the independent features of the contrast and brightness between bleeding and normality. Spectral analysis based on weighting factors was fast and accurate. Results were a sensitivity of 87% and a specificity of 90% when the accuracy was determined for each pixel out of 42 endoscope images.

Keywords: bleeding, capsule endoscopy, image analysis, weighted spectrum

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260 Grid Artifacts Suppression in Computed Radiographic Images

Authors: Igor Belykh

Abstract:

Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when digital image is resized on a diagnostic monitor. In this paper we propose an automated grid artifactsdetection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: Computed radiography, grid artifacts, image filtering.

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259 Chemical Analysis of PM2.5 during Dry Deforestation Season in Southeast Asia

Authors: Bahareh Khezri, Richard D. Webster

Abstract:

In Southeast Asia, during the dry season (August to October) forest fires in Indonesia emit pollutants into the atmosphere. For two years during this period, a total of 67 samples of 2.5 μm particulate matters were collected and analyzed for total mass and elemental composition with ICP - MS after microwave digestion. A study of 60 elements measured during these periods suggest that the concentration of most of elements, even those usually related to crustal source, are extremely high and unpredictable during the haze period. In By contrast, trace element concentration in non - haze months is more stable and covers a lower range. Other unexpected events and their effects on the findings are discussed.

Keywords: Haze, ICP - MS, Particulate Patter, Transboundary Air Pollution.

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258 Observer Design for Chaos Synchronization of Time-delayed Power Systems

Authors: Jui-Sheng Lin, Yi-Sung Yang, Meei-Ling Hung, Teh-Lu Liao, Jun-Juh Yan

Abstract:

The global chaos synchronization for a class of time-delayed power systems is investigated via observer-based approach. By employing the concepts of quadratic stability theory and generalized system model, a new sufficient criterion for constructing an observer is deduced. In contrast to the previous works, this paper proposes a theoretical and systematic design procedure to realize chaos synchronization for master-slave power systems. Finally, an illustrative example is given to show the applicability of the obtained scheme.

Keywords: Chaos, Synchronization, Quadratic stability theory, Observer

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257 Mixing Behaviors of Wet Granular Materials in Gas Fluidized Beds

Authors: Eldin Wee Chuan Lim

Abstract:

The mixing behaviors of dry and wet granular materials in gas fluidized bed systems were investigated computationally using the combined Computational Fluid Dynamics and Discrete Element Method (CFD-DEM). Dry particles were observed to mix fairly rapidly during the fluidization process due to vigorous relative motions between particles induced by the flow of gas. In contrast, due to the presence of strong cohesive forces arising from capillary liquid bridges between wet particles, the mixing efficiencies of wet granular materials under similar operating conditions were observed to be reduced significantly.

Keywords: Computational Fluid Dynamics, Discrete Element Method, Gas Fluidization, Mixing, Wet particles

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256 Forces Association-Based Active Contour

Authors: Aicha Baya Goumeidane, Nafaa. Nacereddine

Abstract:

A welded structure must be inspected to guarantee that the weld quality meets the design requirements to assure safety and reliability. However, X-ray image analyses and defect recognition with the computer vision techniques are very complex. Most difficulties lie in finding the small, irregular defects in poor contrast images which requires pre processing to image, extract, and classify features from strong background noise. This paper addresses the issue of designing methodology to extract defect from noisy background radiograph with image processing. Based on the use of actives contours this methodology seems to give good results

Keywords: Welding, Radiography, Computer vision, Active contour.

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255 Efficient Design of Distribution Logistics by Using a Model-Based Decision Support System

Authors: J. Becker, R. Arnold

Abstract:

The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structures. Combined with qualitative measures the decision support system will contribute to a more efficient design of distribution logistics.

Keywords: Decision support system distribution logistics, potential analyses, supply chain management.

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254 In Search of the Meaning of Entrepreneurship

Authors: H. Fabian Weber, Betina Szkudlarek

Abstract:

The following study aims to outline, whether the perceptions of entrepreneurs about their entrepreneurial activities and the underlying meanings of their activities are universal or whether they vary systematically across cultures. In contrast to previous studies, the phenomenographical approach and the resulting findings of this study provide new insights into what constitutes entrepreneurship by drawing an inference from the perceptions of entrepreneurs in the United States and in Germany. Culture is shown to have an important impact on entrepreneurship, since the underlying meanings of entrepreneurship vary significantly among the two sample groups. Furthermore, the study sheds more light on the culturally contingent 'why' of entrepreneurship by looking at the internal motivations of individuals instead of exclusively focusing on character traits or external influences of the respective economic environments.

Keywords: Cross-Cultural Management, Entrepreneurship, Phenomenography, Qualitative Research.

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253 How to Modernise the European Competition Network (ECN)

Authors: Dorota Galeza

Abstract:

This paper argues that networks, such as the ECN and the American network, are affected by certain small events which are inherent to path dependence and preclude the full evolution towards efficiency. It is advocated that the American network is superior to the ECN in many respects due to its greater flexibility and longer history. This stems in particular from the creation of the American network, which was based on a small number of cases. Such a structure encourages further changes and modifications which are not necessarily radical. The ECN, by contrast, was established by legislative action, which explains its rigid structure and resistance to change. This paper is an attempt to transpose the superiority of the American network on to the ECN. It looks at concepts such as judicial cooperation, harmonisation of procedure, peer review and regulatory impact assessments (RIAs), and dispute resolution procedures.

Keywords: Antitrust, Competition, Networks, Path Dependence.

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