Search results for: Spatial Trend Detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2559

Search results for: Spatial Trend Detection

579 Efficient Feature Fusion for Noise Iris in Unconstrained Environment

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: Image fusion, iris recognition, local binary pattern, wavelet.

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578 Experimental Set-Up for Investigation of Fault Diagnosis of a Centrifugal Pump

Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

Abstract:

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: Centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm.

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577 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children

Authors: Norah Alshahrani, Abdulaziz Almaleh

Abstract:

Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD: Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by SVM, achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: Autism Spectrum Disorder, ASD, Machine Learning, ML, Feature Selection, Support Vector Machine, SVM.

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576 GIS-based Non-point Sources of Pollution Simulation in Cameron Highlands, Malaysia

Authors: M. Eisakhani, A. Pauzi, O. Karim, A. Malakahmad, S.R. Mohamed Kutty, M. H. Isa

Abstract:

Cameron Highlands is a mountainous area subjected to torrential tropical showers. It extracts 5.8 million liters of water per day for drinking supply from its rivers at several intake points. The water quality of rivers in Cameron Highlands, however, has deteriorated significantly due to land clearing for agriculture, excessive usage of pesticides and fertilizers as well as construction activities in rapidly developing urban areas. On the other hand, these pollution sources known as non-point pollution sources are diverse and hard to identify and therefore they are difficult to estimate. Hence, Geographical Information Systems (GIS) was used to provide an extensive approach to evaluate landuse and other mapping characteristics to explain the spatial distribution of non-point sources of contamination in Cameron Highlands. The method to assess pollution sources has been developed by using Cameron Highlands Master Plan (2006-2010) for integrating GIS, databases, as well as pollution loads in the area of study. The results show highest annual runoff is created by forest, 3.56 × 108 m3/yr followed by urban development, 1.46 × 108 m3/yr. Furthermore, urban development causes highest BOD load (1.31 × 106 kgBOD/yr) while agricultural activities and forest contribute the highest annual loads for phosphorus (6.91 × 104 kgP/yr) and nitrogen (2.50 × 105 kgN/yr), respectively. Therefore, best management practices (BMPs) are suggested to be applied to reduce pollution level in the area.

Keywords: Cameron Highlands, Land use, Non-point Sources of Pollution

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575 Contrast-Enhanced Multispectal Upconversion Fluorescence Analysis for High-Resolution in-vivo Deep Tissue Imaging

Authors: Lijiang Wang, Wei Wang, Yuhong Xu

Abstract:

Lanthanide-doped upconversion nanoparticles which can convert near-infrared lights to visible lights have attracted growing interest because of their great potentials in fluorescence imaging. Upconversion fluorescence imaging technique with excitation in the near-infrared (NIR) region has been used for imaging of biological cells and tissues. However, improving the detection sensitivity and decreasing the absorption and scattering in biological tissues are as yet unresolved problems. In this present study, a novel NIR-reflected multispectral imaging system was developed for upconversion fluorescent imaging in small animals. Based on this system, we have obtained the high contrast images without the autofluorescence when biocompatible UCPs were injected near the body surface or deeply into the tissue. Furthermore, we have extracted respective spectra of the upconversion fluorescence and relatively quantify the fluorescence intensity with the multispectral analysis. To our knowledge, this is the first time to analyze and quantify the upconversion fluorescence in the small animal imaging.

Keywords: Multispectral imaging, near-infrared, upconversion fluorescence imaging, upconversion nanoparticles.

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574 Precombining Adaptive LMMSE Detection for DS-CDMA Systems in Time Varying Channels: Non Blind and Blind Approaches

Authors: M. D. Kokate, T. R. Sontakke, P. W. Wani

Abstract:

This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.

Keywords: LMMSE, MOE, MUD.

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573 Applications for Additive Manufacturing Technology for Reducing the Weight of Body Parts of Gas Turbine Engines

Authors: Liubov A. Magerramova, Mikhail A. Petrov, Vladimir V. Isakov, Liana A. Shcherbinina, Suren G. Gukasyan, Daniil V. Povalyukhin, Olga G. Klimova-Korsmik, Darya V. Volosevich

Abstract:

Aircraft engines are developing along the path of increasing resource, strength, reliability, and safety. The building of gas turbine engine body parts is a complex design and technological task. Particularly complex in the design and manufacturing are the casings of the input stages of helicopter gearboxes and central drives of aircraft engines. Traditional technologies, such as precision casting or isothermal forging, are characterized by significant limitations in parts production. For parts like housing, additive technologies guarantee spatial freedom and limitless or flexible design. This article presents the results of computational and experimental studies. These investigations justify the applicability of additive technologies (AT) to reduce the weight of aircraft housing gearbox parts by up to 32%. This is possible due to geometrical optimization compared to the classical, less flexible manufacturing methods and as-casted aircraft parts with over-insured values of safety factors. Using an example of the body of the input stage of an aircraft gearbox, visualization of the layer-by-layer manufacturing of a part based on thermal deformation was demonstrated.

Keywords: Additive technologies, gas turbine engines, geometric optimization, weight reduction.

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572 Sub-Lethal Effects of Thiamethoxam and Pirimicarb on Life-Table Parameters of Diaeretiella rapae (Hymenoptera: Braconidae), Parasitoid of Lipaphis erysimi (Hemiptera: Aphididae)

Authors: Nastaran Rezaei, Mohammad Saeed Mossadegh, Farhan Kocheyli, Khalil Talebi Jahromi, Aurang Kavousi

Abstract:

Integrated Pest Management (IPM) aims to combine biological and chemical strategies and measures, hence highlighting the study of acute toxicity and sub-lethal effects of pesticides comprehensively. The present research focused on the side effects of thiamethoxam and pirimicarb sub-lethal concentrations on demographic parameters of Diaeretiella rapae (McIntosh Laboratory) (Hymenoptera: Braconidae). Adult parasitoids were exposed to LC25 of insecticides as well as distilled water as the control. The results showed that thiamethoxam adversely affected population parameters (r, λ, R0, T), adults' longevity, females' oviposition period and mean fecundity, and a similar trend was obtained for pirimicarb with the exception of generation time (T), the latter did not significantly change compared to the control. The intrinsic rate of increase (r) in the control and those treated with pirimicarb and thiamethoxam were 0.2801, 0.2064, 0.1525 days-1, respectively, and the sex ratio was biased toward females in all treatments. Furthermore, none of the insecticides influenced total pre-oviposition period (TPOP) and offspring emergence rate. In general, these results indicated that both insecticides potentially distort the demographic parameters of the parasitoid even at sub-lethal concentrations, and then they should not be considered for IPM program in the presence of D. rapae.

Keywords: Diaeretiella rapae, Lipaphis erysimi, life-table study, pirimicarb, thiamethoxam.

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571 Electrical Characteristics of Biomodified Electrodes using Nonfaradaic Electrochemical Impedance Spectroscopy

Authors: Yusmeeraz Yusof, Yoshiyuki Yanagimoto, Shigeyasu Uno, Kazuo Nakazato

Abstract:

We demonstrate a nonfaradaic electrochemical impedance spectroscopy measurement of biochemically modified gold plated electrodes using a two-electrode system. The absence of any redox indicator in the impedance measurements provide more precise and accurate characterization of the measured bioanalyte at molecular resolution. An equivalent electrical circuit of the electrodeelectrolyte interface was deduced from the observed impedance data of saline solution at low and high concentrations. The detection of biomolecular interactions was fundamentally correlated to electrical double-layer variation at modified interface. The investigations were done using 20mer deoxyribonucleic acid (DNA) strands without any label. Surface modification was performed by creating mixed monolayer of the thiol-modified single-stranded DNA and a spacer thiol (mercaptohexanol) by a two-step self-assembly method. The results clearly distinguish between the noncomplementary and complementary hybridization of DNA, at low frequency region below several hundreds Hertz.

Keywords: Biosensor, electrical double-layer, impedance spectroscopy, label free DNA.

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570 An Adaptive Dimensionality Reduction Approach for Hyperspectral Imagery Semantic Interpretation

Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

Abstract:

With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: Band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation.

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569 Energy Efficient Construction and the Seismic Resistance of Passive Houses

Authors: Vojko Kilar, Boris Azinović, David Koren

Abstract:

Recently, an increasing trend of passive and low-energy buildings transferring form non earthquake-prone to earthquake-prone regions has thrown out the question about the seismic safety of such buildings. The paper describes the most commonly used thermal insulating materials and the special details, which could be critical from the point of view of earthquake resistance. The most critical appeared to be the cases of buildings founded on the RC foundation slab lying on a thermal insulation (TI) layer made of extruded polystyrene (XPS). It was pointed out that in such cases the seismic response of such buildings might differ to response of their fixed based counterparts. The main parameters that need special designers’ attention are: the building’s lateral top displacement, the ductility demand of the superstructure, the foundation friction coefficient demand, the maximum compressive stress in the TI layer and the percentage of the uplifted foundation. The analyses have shown that the potentially negative influences of inserting the TI under the foundation slab could be expected only for slender high-rise buildings subjected to severe earthquakes. Oppositely it was demonstrated for the foundation friction coefficient demand which could exceed the capacity value yet in the case of low-rise buildings subjected to moderate earthquakes. Some suggestions to prevent the horizontal shifts are also given.

Keywords: Earthquake Response, Extruded Polystyrene (XPS), Low-Energy Buildings, Foundations on Thermal Insulation Layer.

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568 Kinetic Spectrophotometric Determination of Ramipril in Commercial Dosage Forms

Authors: Nafisur Rahman, Habibur Rahman, Syed Najmul Hejaz Azmi

Abstract:

This paper presents a simple and sensitive kinetic spectrophotometric method for the determination of ramipril in commercial dosage forms. The method is based on the reaction of the drug with 1-chloro-2,4-dinitrobenzene (CDNB) in dimethylsulfoxide (DMSO) at 100 ± 1ºC. The reaction is followed spectrophotometrically by measuring the rate of change of the absorbance at 420 nm. Fixed-time (ΔA) and equilibrium methods are adopted for constructing the calibration curves. Both the calibration curves were found to be linear over the concentration ranges 20 - 220 μg/ml. The regression analysis of calibration data yielded the linear equations: Δ A = 6.30 × 10-4 + 1.54 × 10-3 C and A = 3.62 × 10-4 + 6.35 × 10-3 C for fixed time (Δ A) and equilibrium methods, respectively. The limits of detection (LOD) for fixed time and equilibrium methods are 1.47 and 1.05 μg/ml, respectively. The method has been successfully applied to the determination of ramipril in commercial dosage forms. Statistical comparison of the results shows that there is no significant difference between the proposed methods and Abdellatef-s spectrophotometric method.

Keywords: Equilibrium method, Fixed-time (ΔA) method, Ramipril, Spectrophotometry.

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567 Effect of Fat Percentage and Prebiotic Composition on Proteolysis, ACE-Inhibitory and Antioxidant Activity of Probiotic Yogurt

Authors: Mohammad B. HabibiNajafi, Saeideh Sadat Fatemizadeh, Maryam Tavakoli

Abstract:

In recent years, the consumption of functional foods, including foods containing probiotic bacteria, has come to notice. Milk proteins have been identified as a source of angiotensin-I-converting enzyme )ACE( inhibitory peptides and are currently the best-known class of bioactive peptides. In this study, the effects of adding prebiotic ingredients (inulin and wheat fiber) and fat percentage (0%, 2% and 3.5%) in yogurt containing probiotic Lactobacillus casei on physicochemical properties, degree of proteolysis, antioxidant and ACE-inhibitory activity within 21 days of storage at 5 ± 1 °C were evaluated. The results of statistical analysis showed that the application of prebiotic compounds led to a significant increase in water holding capacity, proteolysis and ACE-inhibitory of samples. The degree of proteolysis in yogurt increases as storage time elapses (P < 0.05) but when proteolysis exceeds a certain threshold, this trend begins to decline. Also, during storage time, water holding capacity reduced initially but increased thereafter. Moreover, based on our findings, the survival of Lactobacillus casei in samples treated with inulin and wheat fiber increased significantly in comparison to the control sample (P < 0.05) whereas the effect of fat percentage on the survival of probiotic bacteria was not significant (P = 0.095). Furthermore, the effect of prebiotic ingredients and the presence of probiotic cultures on the antioxidant activity of samples was significant (P < 0.05).

Keywords: Yogurt, proteolysis, ACE-inhibitory, antioxidant activity.

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566 Optimal Convolutive Filters for Real-Time Detection and Arrival Time Estimation of Transient Signals

Authors: Michal Natora, Felix Franke, Klaus Obermayer

Abstract:

Linear convolutive filters are fast in calculation and in application, and thus, often used for real-time processing of continuous data streams. In the case of transient signals, a filter has not only to detect the presence of a specific waveform, but to estimate its arrival time as well. In this study, a measure is presented which indicates the performance of detectors in achieving both of these tasks simultaneously. Furthermore, a new sub-class of linear filters within the class of filters which minimize the quadratic response is proposed. The proposed filters are more flexible than the existing ones, like the adaptive matched filter or the minimum power distortionless response beamformer, and prove to be superior with respect to that measure in certain settings. Simulations of a real-time scenario confirm the advantage of these filters as well as the usefulness of the performance measure.

Keywords: Adaptive matched filter, minimum variance distortionless response, beam forming, Capon beam former, linear filters, performance measure.

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565 Fault Tolerant (n, k)-Star Power Network Topology for Multi-Agent Communication in Automated Power Distribution Systems

Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj Biswas, Frank Ferrese

Abstract:

This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star Topology, Fault Tolerance, Conditional Diagnosability, Multi-Agent System, Automated Power System.

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564 Conducting Flow Measurement Laboratory Test Work

Authors: M. B. Kime

Abstract:

Mass flow measurement is the basis of most technoeconomic formulations in the chemical industry. This calls for reliable and accurate detection of mass flow. Flow measurement laboratory experiments were conducted using various instruments. These consisted of orifice plates, various sized rotameters, wet gas meter and soap bubble meter. This work was aimed at evaluating appropriate operating conditions and accuracy of the aforementioned devices. The experimental data collected were compared to theoretical predictions from Bernoulli’s equation and calibration curves supplied by the instrument’s manufacturers. The results obtained showed that rotameters were more reliable for measuring high and low flow rates; while soap-bubble meters and wet-gas meters were found to be suitable for measuring low flow rates. The laboratory procedures and findings of the actual work can assist engineering students and professionals in conducting their flow measurement laboratory test work.

Keywords: Flow measurement, orifice plates, rotameters, wet gas meter, soap bubble meter.

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563 Data Quality Enhancement with String Length Distribution

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

Abstract:

Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: Data quality, feature selection, probability distribution, string classification, string length.

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562 Semi-automatic Background Detection in Microscopic Images

Authors: Alessandro Bevilacqua, Alessandro Gherardi, Ludovico Carozza, Filippo Piccinini

Abstract:

The last years have seen an increasing use of image analysis techniques in the field of biomedical imaging, in particular in microscopic imaging. The basic step for most of the image analysis techniques relies on a background image free of objects of interest, whether they are cells or histological samples, to perform further analysis, such as segmentation or mosaicing. Commonly, this image consists of an empty field acquired in advance. However, many times achieving an empty field could not be feasible. Or else, this could be different from the background region of the sample really being studied, because of the interaction with the organic matter. At last, it could be expensive, for instance in case of live cell analyses. We propose a non parametric and general purpose approach where the background is built automatically stemming from a sequence of images containing even objects of interest. The amount of area, in each image, free of objects just affects the overall speed to obtain the background. Experiments with different kinds of microscopic images prove the effectiveness of our approach.

Keywords: Microscopy, flat field correction, background estimation, image segmentation.

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561 Microscopic Analysis of Welded Dental Alloys

Authors: S. Porojan, L. Sandu, F. Topalâ

Abstract:

Microplasma welding is a less expensive alternative to laser welding in dental technology. The aim of the study was to highlight discontinuities present in the microplasma welded joints of dental base metal alloys by visual analysis. Five base metal alloys designated for fixed prostheses manufacture were selected for the experiments. Using these plates, preliminary tests were conducted by microplasma welding in butt joint configuration, without filler material, bilaterally and with filler material, proper for each base metal. Macroscopic visual inspection was performed to assess carefully the irregularities in the welds. Electron microscopy allowed detection of discontinuities that are not visible to the eye and revealing details regarding location, trajectory, morphology and size of discontinuities. Supplementing visual control with microscopic analysis allows to detect small discontinuities, which escapes the macroscopic control and to make a detailed study of the weld.

Keywords: base metal alloys, fixed prosthodontics, microplasmawelding, visual inspection

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560 Medical Image Segmentation Using Deformable Model and Local Fitting Binary: Thoracic Aorta

Authors: B. Bagheri Nakhjavanlo, T. S. Ellis, P.Raoofi, Sh.ziari

Abstract:

This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the level set formulation aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets, and are shown to be more effective than other approaches in coping with intensity inhomogeneities. We have applied the Courant Friedrichs Levy (CFL) condition as stability criterion for our algorithm.

Keywords: Image segmentation, Level-sets, Local fitting binary, Thoracic aorta.

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559 Efficient and Extensible Data Processing Framework in Ubiquitious Sensor Networks

Authors: Junghoon Lee, Gyung-Leen Park, Ho-Young Kwak, Cheol Min Kim

Abstract:

This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.

Keywords: sensor network, intelligent farm, middleware, event detection

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558 A Parametric Study of an Inverse Electrostatics Problem (IESP) Using Simulated Annealing, Hooke & Jeeves and Sequential Quadratic Programming in Conjunction with Finite Element and Boundary Element Methods

Authors: Ioannis N. Koukoulis, Clio G. Vossou, Christopher G. Provatidis

Abstract:

The aim of the current work is to present a comparison among three popular optimization methods in the inverse elastostatics problem (IESP) of flaw detection within a solid. In more details, the performance of a simulated annealing, a Hooke & Jeeves and a sequential quadratic programming algorithm was studied in the test case of one circular flaw in a plate solved by both the boundary element (BEM) and the finite element method (FEM). The proposed optimization methods use a cost function that utilizes the displacements of the static response. The methods were ranked according to the required number of iterations to converge and to their ability to locate the global optimum. Hence, a clear impression regarding the performance of the aforementioned algorithms in flaw identification problems was obtained. Furthermore, the coupling of BEM or FEM with these optimization methods was investigated in order to track differences in their performance.

Keywords: Elastostatic, inverse problem, optimization.

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557 Automated Detection of Alzheimer Disease Using Region Growing technique and Artificial Neural Network

Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman

Abstract:

Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.

Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.

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556 Player Number Localization and Recognition in Soccer Video using HSV Color Space and Internal Contours

Authors: Matko Šaric, Hrvoje Dujmic, Vladan Papic, Nikola Rožic

Abstract:

Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.

Keywords: player number, soccer video, HSV color space

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555 Inter-Phase Magnetic Coupling Effects on Sensorless SR Motor Control

Authors: N. H. Mvungi

Abstract:

Control of commutation of switched reluctance (SR) motor has been an area of interest for researchers for sometime now with mixed successes in addressing the inherent challenges. New technologies, processing schemes and methods have been adopted to make sensorless SR drive a reality. There are a number of conceptual, offline, analytical and online solutions in literature that have varying complexities and achieved equally varying degree of robustness and accuracies depending on the method used to address the challenges and the SR drive application. Magnetic coupling is one such challenge when using active probing techniques to determine rotor position of a SR motor from stator winding. This paper studies the effect of back-of-core saturation on the detected rotor position and presents results on measurement made on a 4- phase SR motor. The results shows that even for a four phase motor which is excited one phase at a time and using the electrically opposite phase for active position probing, the back-of-core saturation effects should not be ignored.

Keywords: Sensorless, SR motor, saturation effects, detection.

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554 An Efficient Backward Semi-Lagrangian Scheme for Nonlinear Advection-Diffusion Equation

Authors: Soyoon Bak, Sunyoung Bu, Philsu Kim

Abstract:

In this paper, a backward semi-Lagrangian scheme combined with the second-order backward difference formula is designed to calculate the numerical solutions of nonlinear advection-diffusion equations. The primary aims of this paper are to remove any iteration process and to get an efficient algorithm with the convergence order of accuracy 2 in time. In order to achieve these objects, we use the second-order central finite difference and the B-spline approximations of degree 2 and 3 in order to approximate the diffusion term and the spatial discretization, respectively. For the temporal discretization, the second order backward difference formula is applied. To calculate the numerical solution of the starting point of the characteristic curves, we use the error correction methodology developed by the authors recently. The proposed algorithm turns out to be completely iteration free, which resolves the main weakness of the conventional backward semi-Lagrangian method. Also, the adaptability of the proposed method is indicated by numerical simulations for Burgers’ equations. Throughout these numerical simulations, it is shown that the numerical results is in good agreement with the analytic solution and the present scheme offer better accuracy in comparison with other existing numerical schemes.

Keywords: Semi-Lagrangian method, Iteration free method, Nonlinear advection-diffusion equation.

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553 Antioxidant and Aِntimicrobial Properties of Peptides as Bioactive Components in Beef Burger

Authors: F. M. Abu-Salem, M. H. Mahmoud, M. H. El-Kalyoubi, A. Y. Gibriel, A. A. Abou-Arab Arab

Abstract:

Dried soy protein hydrolysate powder was added to the burger in order to enhance the oxidative stability as well as decreases the microbial spoilage. The soybean bioactive compounds (soy protein hydrolysate) as antioxidant and antimicrobial were added at level of 1, 2 and 3 %.Chemical analysis and physical properties were affected by protein hydrolysate addition. The TBA values were significantly affected (P < 0.05) by the storage period and the level of soy protein hydrolysate. All the tested soybean protein hydrolysate additives showed strong antioxidant properties. Samples of soybean protein hydrolysate showed the lowest (P < 0.05) TBA values at each time of storage. The counts of all determined microbiological indicators were significantly (P < 0.05) affected by the addition of the soybean protein hydrolysate. Decreasing trends of different extent were also observed in samples of the treatments for total viable counts, Coliform, Staphylococcus aureus, yeast and molds. Storage period was being significantly (P < 0.05) affected on microbial counts in all samples Staphylococcus aureus were the most sensitive microbe followed by Coliform group of the sample containing protein hydrolysate, while molds and yeast count showed a decreasing trend but not significant (P < 0.05) until the end of the storage period compared with control sample. Sensory attributes were also performed, added protein hydrolysate exhibits beany flavor which was clear about samples of 3% protein hydrolysate.

Keywords: Antioxidant, antimicrobial, isoflavones, bioactive peptide, antioxidant peptides, soybean protein hydrolysate.

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552 Estimation of Skew Angle in Binary Document Images Using Hough Transform

Authors: Nandini N., Srikanta Murthy K., G. Hemantha Kumar

Abstract:

This paper includes two novel techniques for skew estimation of binary document images. These algorithms are based on connected component analysis and Hough transform. Both these methods focus on reducing the amount of input data provided to Hough transform. In the first method, referred as word centroid approach, the centroids of selected words are used for skew detection. In the second method, referred as dilate & thin approach, the selected characters are blocked and dilated to get word blocks and later thinning is applied. The final image fed to Hough transform has the thinned coordinates of word blocks in the image. The methods have been successful in reducing the computational complexity of Hough transform based skew estimation algorithms. Promising experimental results are also provided to prove the effectiveness of the proposed methods.

Keywords: Dilation, Document processing, Hough transform, Optical Character Recognition, Skew estimation, and Thinning.

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551 Authenticity Issues of Social Media: Credibility, Quality and Reality

Authors: Shahrinaz Ismail, Roslina Abdul Latif

Abstract:

Social media has led to paradigm shifts in ways people work and do business, interact and socialize, learn and obtain knowledge. So much so that social media has established itself as an important spatial extension of this nation-s historicity and challenges. Regardless of the enabling reputation and recommendation features through social networks embedded in the social media system, the overflow of broadcasted and publicized media contents turns the table around from engendering trust to doubting the trust system. When the trust is at doubt, the effects include deactivation of accounts and creation of multiple profiles, which lead to the overflow of 'ghost' contents (i.e. “the abundance of abandoned ships"). In most literature, the study of trust can be related to culture; hence the difference between Western-s “openness" and Eastern-s “blue-chip" concepts in networking and relationships. From a survey on issues and challenges among Malaysian social media users, 'authenticity' emerges as one of the main factors that causes and is caused by other factors. The other issue that has surfaced is credibility either in terms of message/content and source. Another is the quality of the knowledge that is shared. This paper explores the terrains of this critical space which in recent years has been dominated increasingly by, arguably, social networks embedded in the social media system, the overflow of broadcasted and publicized media content.

Keywords: Authenticity, credibility, knowledge quality and social media.

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550 Numerical Investigation of Delamination in Carbon-Epoxy Composite using Arcan Specimen

Authors: M. Nikbakht, N. Choupani

Abstract:

In this paper delamination phenomenon in Carbon-Epoxy laminated composite material is investigated numerically. Arcan apparatus and specimen is modeled in ABAQUS finite element software for different loading conditions and crack geometries. The influence of variation of crack geometry on interlaminar fracture stress intensity factor and energy release rate for various mixed mode ratios and pure mode I and II was studied. Also, correction factors for this specimen for different crack length ratios were calculated. The finite element results indicate that for loading angles close to pure mode-II loading, a high ratio of mode-II to mode-I fracture is dominant and there is an opposite trend for loading angles close to pure mode-I loading. It confirms that by varying the loading angle of Arcan specimen pure mode-I, pure mode-II and a wide range of mixed-mode loading conditions can be created and tested. Also, numerical results confirm that the increase of the mode- II loading contribution leads to an increase of fracture resistance in the CF/PEI composite (i.e., a reduction in the total strain energy release rate) and the increase of the crack length leads to a reduction of interlaminar fracture resistance in the CF/PEI composite (i.e., an increase in the total interlaminar strain energy release rate).

Keywords: Fracture Mechanics, Mixed Mode, Arcan Specimen, Finite Element.

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