Search results for: three-dimensional Digital Image Correlation (DIC).

Authors: Lenka Ševelová, Aleš Florian

Abstract:

To improve the efficiency of parametric studies or tests planning the method is proposed, that takes into account all input parameters, but only a few simulation runs are performed to assess the relative importance of each input parameter. For K input parameters with N input values the total number of possible combinations of input values equals NK. To limit the number of runs, only some (totally N) of possible combinations are taken into account. The sampling procedure Updated Latin Hypercube Sampling is used to choose the optimal combinations. To measure the relative importance of each input parameter, the Spearman rank correlation coefficient is proposed. The sensitivity and the influence of all parameters are analyzed within one procedure and the key parameters with the largest influence are immediately identified.

Keywords: Concrete, pavement, simulation, reliability, Latin Hypercube Sampling, parametric studies.

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Authors: Luis Gracia, Carlos Perez-Vidal, Carlos Gracia

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This paper presents the theoretical background and the real implementation of an automated computer system to introduce machine vision in flower, fruit and vegetable processing for recollection, cutting, packaging, classification, or fumigation tasks. The considerations and implementation issues presented in this work can be applied to a wide range of varieties of flowers, fruits and vegetables, although some of them are especially relevant due to the great amount of units that are manipulated and processed each year over the world. The computer vision algorithms developed in this work are shown in detail, and can be easily extended to other applications. A special attention is given to the electromagnetic compatibility in order to avoid noisy images. Furthermore, real experimentation has been carried out in order to validate the developed application. In particular, the tests show that the method has good robustness and high success percentage in the object characterization.

Keywords: Image processing, Vision system, Automation

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: Edge detection, medical MR images, multi-agent systems, vector field convolution.

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Authors: Ferreira F. C. L., Souza D. N., Rodrigues T. M. A., Cunha C. J., Dullius M. A., Andrade J. E., Sousa A. H., Vieira J. P. C., Carvalho Júnior A. B., Santos L. P. B., Passos R. O.

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The objective this study was to characterize and develop anthropomorphic liver phantoms in tomography hepatic procedures for quality control and improvement professionals in nuclear medicine. For the conformation of the anthropomorphic phantom was used in plaster and acrylic. We constructed three phantoms representing processes with liver cirrhosis. The phantoms were filled with 99mTc diluted with water to obtain the scintigraphic images. Tomography images were analyzed anterior and posterior phantom representing a body with a greater degree cirrhotic. It was noted that the phantoms allow the acquisition of images similar to real liver with cirrhosis. Simulations of hemangiomas may contribute to continued professional education of nuclear medicine, on the question of image acquisition, allowing of the study parameters such of the matrix, energy window and count statistics.

Keywords: Nuclear medicine, liver phantom, control quality

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Authors: Payal Abichandani, Rishi Prakash, Paras Nath Barwal, B. K. Murthy

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Information generated from various computerization processes is a potential rich source of knowledge for its designated community. To pass this information from generation to generation without modifying the meaning is a challenging activity. To preserve and archive the data for future generations it’s very essential to prove the authenticity of the data. It can be achieved by extracting the metadata from the data which can prove the authenticity and create trust on the archived data. Subsequent challenge is the technology obsolescence. Metadata extraction and standardization can be effectively used to resolve and tackle this problem. Metadata can be categorized at two levels i.e. Technical and Domain level broadly. Technical metadata will provide the information that can be used to understand and interpret the data record, but only this level of metadata isn’t sufficient to create trustworthiness. We have developed a tool which will extract and standardize the technical as well as domain level metadata. This paper is about the different features of the tool and how we have developed this.  

Keywords: Digital Preservation, Metadata, OAIS, PDI, XML.

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Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

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Fabric textures are very common in our daily life. However, the representation of fabric textures has never been explored from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. We choose 140 types of fabrics to get the classical fabric textures as materials. Experiment results indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: Fabric Texture, Receptive Filed, Simple Cell, Spare Coding.

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Authors: Khalid M. Aamir, Mohammad A. Maud

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Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. In this paper, recursive version of the Wiener-Khintchine theorem has been derived by using the sliding DFT approach meant for computation of STFT. The computational complexity of the proposed recursive Wiener-Khintchine algorithm, for a window size of N, is O(N).

Keywords: Power Spectral Density (PSD), Wiener-KhintchineTheorem, Periodogram, Short Time Fourier Transform (STFT), TheSliding DFT.

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Authors: Wang Xue, Liu Dan, Liu Ying, Wang Molin, Qian Zhihong

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A low-complexity, high-accurate frequency offset estimation for multi-band orthogonal frequency division multiplexing (MB-OFDM) based ultra-wide band systems is presented regarding different carrier frequency offsets, different channel frequency responses, different preamble patterns in different bands. Utilizing a half-cycle Constant Amplitude Zero Auto Correlation (CAZAC) sequence as the preamble sequence, the estimator with a semi-cross contrast scheme between two successive OFDM symbols is proposed. The CRLB and complexity of the proposed algorithm are derived. Compared to the reference estimators, the proposed method achieves significantly less complexity (about 50%) for all preamble patterns of the MB-OFDM systems. The CRLBs turn out to be of well performance.

Keywords: CAZAC, Frequency Offset, Semi-cross Contrast, MB-OFDM, UWB

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Authors: S. Zouari, H. Daoud, M. Loulou, P. Loumeau, N. Masmoudi

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A wideband 2-1-1 cascaded ΣΔ modulator with a single-bit quantizer in the two first stages and a 4-bit quantizer in the final stage is developed. To reduce sensitivity of digital-to-analog converter (DAC) nonlinearities in the feedback of the last stage, dynamic element matching (DEM) is introduced. This paper presents two modelling approaches: The first is MATLAB description and the second is VHDL-AMS modelling of the proposed architecture and exposes some high-level-simulation results allowing a behavioural study. The detail of both ideal and non-ideal behaviour modelling are presented. Then, the study of the effect of building blocks nonidealities is presented; especially the influences of nonlinearity, finite operational amplifier gain, amplifier slew rate limitation and capacitor mismatch. A VHDL-AMS description presents a good solution to predict system-s performances and can provide sensitivity curves giving the impact of nonidealities on the system performance.

Keywords: behavioural study, DAC nonlinearity, DEM, ΣΔ modulator, VHDL-AMS modelling.

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Authors: Mina Alibeigi, Sattar Hashemi, Ali Hamzeh

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Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. In this paper, we propose a new unsupervised feature selection method which will remove redundant features from the original feature space by the use of probability density functions of various features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several datasets derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both classification accuracy and the number of selected features.

Keywords: Feature, Feature Selection, Filter, Probability Density Function

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Authors: Majid Forghani, Michael Khachay

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In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: Antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition.

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Authors: E. Bene

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Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Centre for Agricultural Sciences of University of Debrecen, in 2012-2014. The paper contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences the leaf area index and the activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying the effects of each other, develop average yields.

Keywords: Sowing date, hybrid, leaf area index, photosynthetic capacity.

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Authors: Thanawit Buafai, Siyathorn Khunon

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This paper aims to explore the satisfaction levels of tourism product components on the island of Samui by studying the cultural dimension relationships of Hofsted’s classic theory. Both the six Hofsted cultural dimensions and tourism production satisfaction measures have been of interest worldwide. Therefore, the challenge of this study is to re-confirm previous research results in the ever-changing current contexts of the modern globalized business era. Self-rated questionnaires were employed to collect data from six nationalities of tourists in Samui, totaling 386 samples. The reliability of this research methodology was 0.967. Correlation was applied to analyze the relationships. The results indicate that Masculinity is significantly related to tourism destination satisfaction for every factor, while the other five cultural dimensions are related to some factors of tourism satisfaction. Surprisingly, tourist satisfaction toward the bar/restaurant factor is significantly correlated with all six cultural dimensions.

Keywords: Cultural dimensions, tourism products, Samui, Thailand.

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Authors: R. Rishma Rodrigo, R. Radhika, M. Vanitha Lakshmi

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Numerous signal processing based speech enhancement systems have been proposed to improve intelligibility in the presence of noise. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A method is presented for recording high-frequency speech components into a low-frequency region, to increase audibility for hearing loss listeners. The purpose of the paper is to enhance the formant of the speech based on the Kaiser window. The pitch and formant of the signal is based on the auto correlation, zero crossing and magnitude difference function. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain. A MATLAB software’s are used for the implementation of the system with low complexity is developed.

Keywords: Formant estimation, formant enhancement, pitch detection, speech analysis.

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Authors: Hossein Pazhoumand-Dar, Amir Mohsen Toliyat Abolhassani, Ehsan Saeedi

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Speed estimation is one of the important and practical tasks in machine vision, Robotic and Mechatronic. the availability of high quality and inexpensive video cameras, and the increasing need for automated video analysis has generated a great deal of interest in machine vision algorithms. Numerous approaches for speed estimation have been proposed. So classification and survey of the proposed methods can be very useful. The goal of this paper is first to review and verify these methods. Then we will propose a novel algorithm to estimate the speed of moving object by using fuzzy concept. There is a direct relation between motion blur parameters and object speed. In our new approach we will use Radon transform to find direction of blurred image, and Fuzzy sets to estimate motion blur length. The most benefit of this algorithm is its robustness and precision in noisy images. Our method was tested on many images with different range of SNR and is satisfiable.

Keywords: Blur Analysis, Fuzzy sets, Speed estimation.

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Authors: Morteza Moazami-Goudarzi, Ali Taheri, Mohammad Pooyan, Reza Mahboobi

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In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.

Keywords: ECG compression, Prefiltering, Cardinal Balanced Multiwavelet.

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Authors: Ka-Yan Yim, Chi-Wai Kan

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This paper conducts a comparison study using KES-FB and PhabrOmeter to measure 58 selected warp knitted fabric hand properties. Fabric samples were selected and measured by both KES-FB and PhabrOmeter. Results show differences between these two measurement methods. Smoothness and stiffness values obtained by KES-FB were found significant correlated (p value = 0.003 and 0.022) to the PhabrOmeter results while softness values between two measurement methods did not show significant correlation (p value = 0.828). Disagreements among these two measurement methods imply limitations on different mechanism principles when facing warp knitted fabrics. Subjective measurement methods and further studies are suggested in order to ascertain deeper investigation on the mechanisms of fabric hand perceptions.

Keywords: Fabric hand, fabric objective measurement, KES-FB, PhabrOmeter.

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Authors: P. Latha, L. Ganesan, N. Ramaraj, P. V. Hari Venkatesh

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Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.

Keywords: Frame separation, Correlation Network, Neural network training, Radial Basis Function, object tracking, Motion Detection.

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Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: Artificial neural networks, cellular automata, decision support system, pattern recognition.

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe V. Lakshminarayanan, K. Raahemifar

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Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: Diabetic retinopathy, fundus images, STARE, Gabor filter, SVM.

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Authors: Anna Veres

Abstract:

People’s ability to adapt to a constantly changing environment is essential. Career adaptability is central to Career Construction Theory, where proper adaptation to new situations, changing environments, and jobs require adequate career development. Based on current career theories and the possibilities offered by digital technology, the primary goal of this study is to develop career adaptability through an online tool. Its secondary goal is to apply for an online career intervention program and explore its developmental possibilities. A total of 132 university students from the bachelor program took part in the study, from which 65 students received a four-week online career intervention, while 67 participants formed the control group. Based on the results, it can state that career adaptability can be developed, and there is a great demand and interest from university students to use career-related programs on online platforms. Career interventions should be performed online as well if there is suitable software and a well-constructed program. Limitations and further implications are discussed.

Keywords: career adaptability, career development, online career intervention, university student

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Authors: O. O. Olawusi-Peters, O. E. Aguda, F. O. Okoye

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Investigations on the accumulation of heavy metals in water and sediments of river Ogbese were carried out between December 2010 and February 2011 using Atomic Absorption Spectrophotometer. Etheria elliptica a sessile organism was also used to determine the concentration of heavy metal in the aquatic environmental. In water, Cu had the highest concentration (0.55 – 0.13 mg/l ±0.1) while in sediments, the highest value obtained was in Fe (1.46-3.89mg/l±0.27). The minimum concentrations recorded were in Pb; which was below detectable level. The result also revealed that the shell accumulate more heavy metals than the flesh of the mussel with Cu in the shell exhibiting a negative correlation with all the metals in the flesh. However, the condition factor (K) value is 6.44, an indication of good health. The length-weight relationship is expressed as W = -0.48 x L 1.94 (r2 = 0.29) showing the growth pattern to be negatively allometric.

Keywords: Condition factor, Etheria elliptica, heavy metals, River Ogbese.

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Authors: Yue Zhao, Chao Li

Abstract:

Camera calibration is an important step in 3D reconstruction. Camera calibration may be classified into two major types: traditional calibration and self-calibration. However, a calibration method in using a checkerboard is intermediate between traditional calibration and self-calibration. A self is proposed based on a square in this paper. Only a square in the planar template, the camera self-calibration can be completed through the single view. The proposed algorithm is that the virtual circle and straight line are established by a square on planar template, and circular points, vanishing points in straight lines and the relation between them are be used, in order to obtain the image of the absolute conic (IAC) and establish the camera intrinsic parameters. To make the calibration template is simpler, as compared with the Zhang Zhengyou-s method. Through real experiments and experiments, the experimental results show that this algorithm is feasible and available, and has a certain precision and robustness.

Keywords: Absolute conic, camera calibration, circle point, vanishing point.

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Authors: Mounir Sayadi, Farhat Fnaiech

Abstract:

In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.

Keywords: Texture analysis, statistical features, adaptive filters, Chandrasekhar algorithm.

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Authors: Chen-Chien Hsu, Guo-Tang Dai

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This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

Keywords: multiple object tracking, particle swarm optimization, gray-level histogram, image

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Authors: Dinesh Kumar, Y. S. Brar, V. K. Banga

Abstract:

Multicast Network Technology has pervaded our lives-a few examples of the Networking Techniques and also for the improvement of various routing devices we use. As we know the Multicast Data is a technology offers many applications to the user such as high speed voice, high speed data services, which is presently dominated by the Normal networking and the cable system and digital subscriber line (DSL) technologies. Advantages of Multi cast Broadcast such as over other routing techniques. Usually QoS (Quality of Service) Guarantees are required in most of Multicast applications. The bandwidth-delay constrained optimization and we use a multi objective model and routing approach based on genetic algorithm that optimizes multiple QoS parameters simultaneously. The proposed approach is non-dominated routes and the performance with high efficiency of GA. Its betterment and high optimization has been verified. We have also introduced and correlate the result of multicast GA with the Broadband wireless to minimize the delay in the path.

Keywords: GA (genetic Algorithms), Quality of Service, MOGA, Steiner Tree.

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Authors: Abbas Hani

Abstract:

The concentrations of As, Hg, Co, Cr and Cd were tested for each soil sample, and their spatial patterns were analyzed by the semivariogram approach of geostatistics and geographical information system technology. Multivariate statistic approaches (principal component analysis and cluster analysis) were used to identify heavy metal sources and their spatial pattern. Principal component analysis coupled with correlation between heavy metals showed that primary inputs of As, Hg and Cd were due to anthropogenic while, Co, and Cr were associated with pedogenic factors. Ordinary kriging was carried out to map the spatial patters of heavy metals. The high pollution sources evaluated was related with usage of urban and industrial wastewater. The results of this study helpful for risk assessment of environmental pollution for decision making for industrial adjustment and remedy soil pollution.

Keywords: Geographic Information system, Geostatistics, Kaveh, Multivariate Statistical Analysis.

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Authors: L. Rozumová, J. Seidlerová

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The aim of this paper was to study the sorption properties of a blast furnace sludge used as the sorbent. The sorbent was utilized for reduction of content of lead and zinc ions. Sorbent utilized in this work was obtained from metallurgical industry from process of wet gas treatment in iron production. The blast furnace sludge was characterized by X-Ray diffraction, scanning electron microscopy, and XRFS spectroscopy. Sorption experiments were conducted in batch mode. The sorption of metal ions in the sludge was determined by correlation of adsorption isotherm models. The adsorption of lead and zinc ions was best fitted with Langmuir adsorption isotherms. The adsorption capacity of lead and zinc ions was 53.8 mg.g^-1 and 10.7 mg.g^-1, respectively. The results indicated that blast furnace sludge could be effectively used as secondary material and could be also employed as a low-cost alternative for the removal of heavy metals ions from wastewater.

Keywords: Blast furnace sludge, lead, zinc, sorption.

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Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung

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This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.

Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.

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Authors: Fu E. Tang

Abstract:

The increase in energy demand has raised concerns over adverse impacts on the environment from energy generation. It is important to understand the status of energy consumption for institutions such as Curtin Sarawak to ensure the sustainability of energy usage, and also to reduce its costs. In this study, a preliminary audit framework was developed and was conducted around the Malaysian campus to obtain information such as the number and specifications of electrical appliances, built-up area and ambient temperature to understand the relationship of these factors with energy consumption. It was found that the number and types of electrical appliances, population and activities in the campus impacted the energy consumption of Curtin Sarawak directly. However, the built-up area and ambient temperature showed no clear correlation with energy consumption. An investigation of the diurnal and seasonal energy consumption of the campus was also carried out. From the data, recommendations were made to improve the energy efficiency of the campus.

Keywords: Energy audit, energy consumption, energy efficiency

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