Search results for: Discrete Fourier Transform (DFT)

Authors: Iman Elyasi, Sadegh Zarmehi

Abstract:

Due to some reasons, observed images are degraded which are mainly caused by noise. Recently image denoising using the wavelet transform has been attracting much attention. Waveletbased approach provides a particularly useful method for image denoising when the preservation of edges in the scene is of importance because the local adaptivity is based explicitly on the values of the wavelet detail coefficients. In this paper, we propose several methods of noise removal from degraded images with Gaussian noise by using adaptive wavelet threshold (Bayes Shrink, Modified Bayes Shrink and Normal Shrink). The proposed thresholds are simple and adaptive to each subband because the parameters required for estimating the threshold depend on subband data. Experimental results show that the proposed thresholds remove noise significantly and preserve the edges in the scene.

Keywords: Image denoising, Bayes Shrink, Modified Bayes Shrink, Normal Shrink.

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Authors: Amrita Tripathi, Neeru Adlakha

Abstract:

Calcium [Ca2+] dynamics is studied as a potential form of neuron excitability that can control many irregular processes like metabolism, secretion etc. Ca2+ ion enters presynaptic terminal and increases the synaptic strength and thus triggers the neurotransmitter release. The modeling and analysis of calcium dynamics in neuron cell becomes necessary for deeper understanding of the processes involved. A mathematical model has been developed for cylindrical shaped neuron cell by incorporating physiological parameters like buffer, diffusion coefficient, and association rate. Appropriate initial and boundary conditions have been framed. The closed form solution has been developed in terms of modified Bessel function. A computer program has been developed in MATLAB 7.11 for the whole approach.

Keywords: Laplace Transform, Modified Bessel function, reaction diffusion equation, diffusion coefficient, excess buffer, calcium influx

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

Abstract:

One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: ATR, HRRP, motion compensation, SFW, TMP.

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Authors: M. Sari Yilmaz, N. Karamahmut Mermer

Abstract:

Coal fly ash is formed as a solid waste product from the combustion of coal in coal fired power stations. Huge amounts of fly ash are produced globally every year and are predicted to increase. Nowadays, less than half of the fly ash is used as a raw material for cement manufacturing, construction and the rest of it is disposed as a waste causing yet another environmental concern. For this reason, the recycling of this kind of slurries into useful materials is quite important in terms of economical and environmental aspects. The purpose of this study is to evaluate the Orhaneli and Tuncbilek coal fly ashes for utilization in some industrial applications. Therefore the mineralogical and chemical compositions of these fly ashes were analyzed by X-ray fluorescence spectroscopy, ourier-transform infrared spectrometer, and X-ray diffraction. The silicon (Si) and aluminum (Al) in the fly ashes were activated by alkali fusion technique with sodium hydroxide. The obtained extracts were analyzed for Si and Al content by inductively coupled plasma optical emission spectrometry.

Keywords: Extraction, Fly ash, Fusion, XRD.

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Authors: Khaldon Lweesy, Luay Fraiwan, Christoph Maier, Hartmut Dickhaus

Abstract:

This paper describes a new method for extracting the fetal heart rate (fHR) and the fetal heart rate variability (fHRV) signal non-invasively using abdominal maternal electrocardiogram (mECG) recordings. The extraction is based on the fundamental frequency (Fourier-s) theorem. The fundamental frequency of the mother-s electrocardiogram signal (fo-m) is calculated directly from the abdominal signal. The heart rate of the fetus is usually higher than that of the mother; as a result, the fundamental frequency of the fetal-s electrocardiogram signal (fo-f) is higher than that of the mother-s (fo-f > fo-m). Notch filters to suppress mother-s higher harmonics were designed; then a bandpass filter to target fo-f and reject fo-m is implemented. Although the bandpass filter will pass some other frequencies (harmonics), we have shown in this study that those harmonics are actually carried on fo-f, and thus have no impact on the evaluation of the beat-to-beat changes (RR intervals). The oscillations of the time-domain extracted signal represent the RR intervals. We have also shown in this study that zero-to-zero evaluation of the periods is more accurate than the peak-to-peak evaluation. This method is evaluated both on simulated signals and on different abdominal recordings obtained at different gestational ages.

Keywords: Aabdominal ECG, fetal heart rate variability, frequency harmonics, fundamental frequency.

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Authors: Päivi Aarreniemi-Jokipelto, Merja Alanko-Turunen

Abstract:

The possibilities of mobile technology generate new demands for vocational teacher trainers to transform their approach to work and to incorporate its usage into their ordinary educational practice. This paper presents findings of a focus discussion group (FDG) session on the usage of iPads within a school of vocational teacher education (SoVTE). It aims to clarify how the teacher trainers are using iPads and what has changed in their work during the usage of iPads. The analytical framework bases on content analysis and expansive learning cycle. It was not only found what kind of a role iPads played in their daily practices but it brought also into attention how a cultural change regarding the usage of social media and mobile technology was desperately needed in the whole work community. Thus, the FGD was abducted for developing the knowledge practices of the community of the SoVTE.

Keywords: iPad, mobile learning, vocational teacher education.

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Authors: Ingy A. El-Khouly, Khaled S. El-Kilany, Aziz E. El-Sayed

Abstract:

The process of wafer fabrication is arguably the most technologically complex and capital intensive stage in semiconductor manufacturing. This large-scale discrete-event process is highly reentrant, and involves hundreds of machines, restrictions, and processing steps. Therefore, production control of wafer fabrication facilities (fab), specifically scheduling, is one of the most challenging problems that this industry faces. Dispatching rules have been extensively applied to the scheduling problems in semiconductor manufacturing. Moreover, lot release policies are commonly used in this manufacturing setting to further improve the performance of such systems and reduce its inherent variability. In this work, simulation is used in the scheduling of re-entrant flow shop manufacturing systems with an application in semiconductor wafer fabrication; where, a simulation model has been developed for the Intel Five-Machine Six Step Mini-Fab using the ExtendTM simulation environment. The Mini-Fab has been selected as it captures the challenges involved in scheduling the highly re-entrant semiconductor manufacturing lines. A number of scenarios have been developed and have been used to evaluate the effect of different dispatching rules and lot release policies on the selected performance measures. Results of simulation showed that the performance of the Mini-Fab can be drastically improved using a combination of dispatching rules and lot release policy.

Keywords: Dispatching rules, lot release policy, re-entrant flowshop, semiconductor manufacturing.

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Authors: Aussadavut Dumrongsiri

Abstract:

Web-based technologies have created numerous opportunities for electronic word-of-mouth (eWOM) communication. There are many factors that affect customer adoption and decisionmaking process. However, only a few researches focus on some factors such as the membership time of forum and propensity to trust. Using a discrete-time event simulation to simulate a diffusion model along with a consumer decision model, the study shows the effect of each factor on adoption of opinions on on-line discussion forum. The purpose of this study is to examine the effect of factor affecting information adoption and decision making process. The model is constructed to test quantitative aspects of each factor. The simulation study shows the membership time and the propensity to trust has an effect on information adoption and purchasing decision. The result of simulation shows that the longer the membership time in the communities and the higher propensity to trust could lead to the higher demand rates because consumers find it easier and faster to trust the person in the community and then adopt the eWOM. Other implications for both researchers and practitioners are provided.

Keywords: word of mouth, simulation, consumer behavior, ebusiness, marketing, diffusion process.

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Authors: Abdulkarim Mohammed Iliyasu, Mahmud Abba Tahir

Abstract:

Freezing and thawing are considered to be one of the major causes of concrete deterioration in the cold regions. This study aimed at assessing the freezing and thawing of concrete within the cover zone by monitoring the formation of ice and melting at different temperatures using electrical measurement technique. A multi-electrode array system was used to obtain the resistivity of ice formation and melting at discrete depths within the cover zone of the concrete. A total number of four concrete specimens (250 mm x 250 mm x 150 mm) made of ordinary Portland cement concrete and ordinary Portland cement replaced by 65% ground granulated blast furnace slag (GGBS) is investigated. Water/binder ratios of 0.35 and 0.65 were produced and ponded with water to ensure full saturation and then subjected to freezing and thawing process in a refrigerator within a temperature range of -30 ⁰C and 20 ⁰C over a period of time 24 hours. The data were collected and analysed. The obtained results show that the addition of GGBS changed the pore structure of the concrete which resulted in the decrease in conductance. It was recommended among others that, the surface of the concrete structure should be protected as this will help to prevent the instantaneous propagation of ice trough the rebar and to avoid corrosion and subsequent damage.

Keywords: Concrete, conductance, deterioration, freezing and thawing, ordinary Portland cement.

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Authors: Yan Su, Jane H. Davidson, F. A. Kulacki

Abstract:

The RANS method with Saffman-s turbulence model was employed to solve the time-dependent turbulent Navier-Stokes and energy equations for oscillating pipe flows. The method of partial sums of the Fourier series is used to analyze the harmonic velocity and temperature results. The complete structures of the oscillating pipe flows and the averaged Nusselt numbers on the tube wall are provided by numerical simulation over wide ranges of ReA and ReR. Present numerical code is validated by comparing the laminar flow results to analytic solutions and turbulence flow results to published experimental data at lower and higher Reynolds numbers respectively. The effects of ReA and ReR on the velocity, temperature and Nusselt number distributions have been di scussed. The enhancement of the heat transfer due to oscillating flows has also been presented. By the way of analyzing the overall Nusselt number over wide ranges of the Reynolds number Re and Keulegan- Carpenter number KC, the optimal ratio of the tube diameter over the oscillation amplitude is obtained based on the existence of a nearly constant optimal KC number. The potential application of the present results in sea water cooling has also been discussed.

Keywords: Keulegan-Carpenter number, Nusselt number, Oscillating pipe flows, Reynolds number

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Authors: Mohammad S. Laghari, Gulzar A. Khuwaja

Abstract:

Many problems in computer vision and image processing present potential for parallel implementations through one of the three major paradigms of geometric parallelism, algorithmic parallelism and processor farming. Static process scheduling techniques are used successfully to exploit geometric and algorithmic parallelism, while dynamic process scheduling is better suited to dealing with the independent processes inherent in the process farming paradigm. This paper considers the application of parallel or multi-computers to a class of problems exhibiting spatial data characteristic of the geometric paradigm. However, by using processor farming paradigm, a dynamic scheduling technique is developed to suit the MIMD structure of the multi-computers. A hybrid scheme of scheduling is also developed and compared with the other schemes. The specific problem chosen for the investigation is the Hough transform for line detection.

Keywords: Hough transforms, parallel computer, parallel paradigms, scheduling.

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Authors: Sonia Regina Lyra

Abstract:

The desire for unequivocal clarity is understandable, but this can make one forget that things of the soul are experiential processes, or transformations, which should never be designated unilaterally if it is not wanted to transform something that moves, a living thing, into something static. Among the so-called ‘things of the soul’ there are especially spontaneous fantasies, that emerge during the processes, as a result from the use of the active imagination technique, for when fantasy is not forced, violated, or subjugated by an illegitimate, intellectually preconceived idea, then it is a legitimate and authentic product of the unconscious mind. This is how one can gain access to unadulterated information about everything that transcends the conscious mind. However, it is vital to discern between ego and non-ego, because this principle will result in a release of energy and a renewal of life, which will come to have meaning. This study will deal with the active imagination as a knowledge that depends on the individual experience of the therapist because the patient will be taken just to reach where the unconscious of the therapist was assimilated to his own conscience. In this way, the therapist becomes the method itself, being his personality, a fundamental part of an effective factor.

Keywords: Active imagination, effective factor, symptom, transformation.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, ParetoOptimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Homayoon Zarshenas, Mahdi Bamdad, Hadi Grailu, Akbar A. Shakoori

Abstract:

In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Keywords: BCI, EEG, Classifier, Fuzzy operator, OWA.

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Authors: O. Abusaeeda, J. P. O Evans, D. Downes

Abstract:

We demonstrate the synthesis of intermediary views within a sequence of color encoded, materials discriminating, X-ray images that exhibit animated depth in a visual display. During the image acquisition process, the requirement for a linear X-ray detector array is replaced by synthetic image. Scale Invariant Feature Transform, SIFT, in combination with material segmented morphing is employed to produce synthetic imagery. A quantitative analysis of the feature matching performance of the SIFT is presented along with a comparative study of the synthetic imagery. We show that the total number of matches produced by SIFT reduces as the angular separation between the generating views increases. This effect is accompanied by an increase in the total number of synthetic pixel errors. The trends observed are obtained from 15 different luggage items. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, view synthesis, KDE

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Authors: Suet Leng Khoo, Tiun Ling Ta, Lay Wah Lee

Abstract:

In this era of globalization, the role of the State in all aspects of development is widely debated. Some scholars contend the 'demise' and diminishing role of the State whilst others claim that the State is still “de facto developmental". Clearly, it is vital to ascertain which of these two contentions are reflective of the role of the State as nations ascend their development trajectories. Based on the findings of this paper, the perception that the Malaysian State plays an active and committed role towards distributing equitable educational opportunities and enhancing employability of Malaysian PWDs is actually a myth and not reality. Thus, in order to fulfill the promise of Vision 2020 to transform Malaysia into a caring and socially-inclusive society; this paper calls for a more interventionist and committed role by the Malaysian State to translate the universal rights of education and employment opportunities for PWDs from mere policy rhetoric into inclusive realities.

Keywords: People with Disabilities, Malaysia, role of State, equal employment opportunities

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Authors: F. Rotaru, S. Bejinariu, C. D. Niţâ, R. Luca, I. Pâvâloi, C. Lazâr

Abstract:

The paper presents a technique suitable in robot vision applications where it is not possible to establish the object position from one view. Usually, one view pose calculation methods are based on the correspondence of image features established at a training step and exactly the same image features extracted at the execution step, for a different object pose. When such a correspondence is not feasible because of the lack of specific features a new method is proposed. In the first step the method computes from two views the 3D pose of feature points. Subsequently, using a registration algorithm, the set of 3D feature points extracted at the execution phase is aligned with the set of 3D feature points extracted at the training phase. The result is a Euclidean transform which have to be used by robot head for reorientation at execution step.

Keywords: features correspondence, registration algorithm, robot vision, triangulation method.

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Authors: Hamza Nejib, Okba Taouali

Abstract:

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: KLMS, online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS.

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Authors: Abbas Siefi, Mohammad Javad Karimifar

Abstract:

We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.

Keywords: Spatial design of experiments, maximum entropy sampling, computer experiments, genetic algorithm.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, Pareto Optimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Raquel Ramos López, Anissa El-Khattabi, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

Abstract:

An increasing number of mobile devices with integrated cameras has meant that most digital video comes from these devices. These digital videos can be made anytime, anywhere and for different purposes. They can also be shared on the Internet in a short period of time and may sometimes contain recordings of illegal acts. The need to reliably trace the origin becomes evident when these videos are used for forensic purposes. This work proposes an algorithm to identify the brand and model of mobile device which generated the video. Its procedure is as follows: after obtaining the relevant video information, a classification algorithm based on sensor noise and Wavelet Transform performs the aforementioned identification process. We also present experimental results that support the validity of the techniques used and show promising results.

Keywords: Digital video, forensics analysis, key frame, mobile device, PRNU, sensor noise, source identification.

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Authors: S. Sabbour, H. Lasi, P. von Tessin

Abstract:

The purpose of this study is two-fold. First, it attempts to explore potential opportunities for utilizing visual interactive simulations along with Business Intelligence (BI) as a decision support tool for strategic decision making. Second, it tries to figure out the essential top-level managerial requirements that would transform strategic decision simulation into an integral component of BI systems. The domain of particular interest was the application of visual interactive simulation capabilities in the field of supply chains. A qualitative exploratory method was applied, through the use of interviews with two leading companies. The collected data was then analysed to demonstrate the difference between the literature perspective and the practical managerial perspective on the issue. The results of the study suggest that although the use of simulation particularly in managing supply chains is very evident in literature, yet, in practice such utilization is still in its infancy, particularly regarding strategic decisions. Based on the insights a prototype of a simulation based BI-solution-extension was developed and evaluated.

Keywords: Business Intelligence, decision support, strategic decisions, simulation, SCM.

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Authors: M. Rychlik, R. Roszak, M. Morzynski, M. Nowak, H. Hausa, K. Kotecki

Abstract:

Article presents the geometry and structure reconstruction procedure of the aircraft model for flatter research (based on the I22-IRYDA aircraft). For reconstruction the Reverse Engineering techniques and advanced surface modeling CAD tools are used. Authors discuss all stages of data acquisition process, computation and analysis of measured data. For acquisition the three dimensional structured light scanner was used. In the further sections, details of reconstruction process are present. Geometry reconstruction procedure transform measured input data (points cloud) into the three dimensional parametric computer model (NURBS solid model) which is compatible with CAD systems. Parallel to the geometry of the aircraft, the internal structure (structural model) are extracted and modeled. In last chapter the evaluation of obtained models are discussed.

Keywords: computer modeling, numerical simulation, Reverse Engineering, structural model

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Authors: Madihah Mohd Saudi, Zul Hilmi Abdullah

Abstract:

This research paper presents a framework on how to build up malware dataset.Many researchers took longer time to clean the dataset from any noise or to transform the dataset into a format that can be used straight away for testing. Therefore, this research is proposing a framework to help researchers to speed up the malware dataset cleaningprocesses which later can be used for testing. It is believed, an efficient malware dataset cleaning processes, can improved the quality of the data, thus help to improve the accuracy and the efficiency of the subsequent analysis. Apart from that, an in-depth understanding of the malware taxonomy is also important prior and during the dataset cleaning processes. A new Trojan classification has been proposed to complement this framework.This experiment has been conducted in a controlled lab environment and using the dataset from VxHeavens dataset. This framework is built based on the integration of static and dynamic analyses, incident response method and knowledge database discovery (KDD) processes.This framework can be used as the basis guideline for malware researchers in building malware dataset.

Keywords: Dataset, knowledge database discovery (KDD), malware, static and dynamic analyses.

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

Abstract:

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

Abstract:

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: Nükhet Konuk, N. Gamze Turan, Yüksel Ardalı

Abstract:

Cities play a vital role in the social fabric of countries and in national and regional economic growth worldwide; however, the environmental effects of such growth need to be assessed and managed better. The critical and most immediate problems faced by cities of developing countries are the health impacts of urban pollution that derive from inadequate water, sanitation, drainage and solid waste services, poor urban and industrial waste management, and air pollution. As globalization continues, earth's natural processes transform local problems into international issues. The aim of this study is to provide a broad overview of the pollution from urban wastes and emissions in Turkey which is a developing country. It is aimed to underline the significance of reorganizing the institutional tools in a worldwide perspective in order to generate coherent solutions to urban problems, and to enhance urban quality.

Keywords: Environmental pollution, developing countries, environmental degradation, urban environmental problems.

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Authors: Hui Fang Huang Su, Jia Borror

Abstract:

This study compared two different interventions for math instruction among preschoolers with autism spectrum disorder (ASD). The first intervention, a combination of discrete trial teaching and Strategies for Teaching Based on Autism Research (STAR), was the regular math curriculum utilized at the preschool. The second activity-based, naturalistic intervention was Project Mind, also known as Math is Not Difficult. The curricular interventions were randomly assigned to four preschool classrooms with ASD students and implemented over three months for Project MIND. Measurements gained during the same three months for the STAR intervention were used. A quasi-experimental, pre-test/post-test design was selected to compare which intervention was the most effective in increasing mathematical knowledge and skills among preschoolers with ASD. Standardized pre and post-test instruments included the Bracken Basic Concept Scale-3 Receptive, the Applied Problems and Calculation subtests of the Woodcock-Johnson IV Tests of Achievement, and the TEMA 3: Test of Early Mathematics Ability – Third Edition. The STAR assessment is typically administered to all preschoolers at the study site three times per year, and those results were used in this study. We anticipated that the implementation of these two approaches would lead to improvement in the mathematical knowledge and skills of children with ASD. Still, it is essential to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: Autism, mathematics, preschool, special education.

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Authors: Essam Al Daoud

Abstract:

Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: Ant colony algorithm, Edit distance, Genome breakpoint, Genome rearrangement, Reversal sort.

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Authors: Basak Oguz Yolcular

Abstract:

A large amount of valuable information is available in plain text clinical reports. New techniques and technologies are applied to extract information from these reports. In this study, we developed a domain based software system to transform 600 Otorhinolaryngology discharge notes to a structured form for extracting clinical data from the discharge notes. In order to decrease the system process time discharge notes were transformed into a data table after preprocessing. Several word lists were constituted to identify common section in the discharge notes, including patient history, age, problems, and diagnosis etc. N-gram method was used for discovering terms co-Occurrences within each section. Using this method a dataset of concept candidates has been generated for the validation step, and then Predictive Apriori algorithm for Association Rule Mining (ARM) was applied to validate candidate concepts.

Keywords: association rule mining, otorhinolaryngology, predictive apriori, text mining

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