Search results for: statistical sampling.

Authors: Lina Fernandes, G. N. Nayak, D. Ilangovan

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Two short sediment cores collected from mangrove areas of Manori and Thane creeks along Mumbai coast were analysed for sediment composition and metals (Fe, Mn, Cu, Pb, Co, Ni, Zn, Cr and V). The statistical analysis of Pearson correlation matrix proved that there is a significant relationship between metal concentration and finer grain size in Manori creek while poor correlation was observed in Thane creek. Based on the enrichment factor, the present metal to background metal ratios clearly reflected maximum enrichment of Cu and Pb in Manori creek and Mn in Thane creek. Geoaccumulation index calculated indicate that the study area is unpolluted with respect to Fe, Mn, Co, Ni, Zn and Cr in both the cores while moderately polluted with Cu and Pb in Manori creek. Based on contamination degree, both the core sediments were found to be considerably contaminated with metals.

Keywords: Creek, Igeo, Mumbai, trace metals

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Authors: B.Tavakoly Sany, A.H .Sulaiman, GH. Monazami, A. Salleh

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Eight heavy metals (Cu, Cr, Zn, Hg, Pb, Cd, Ni and As) were analyzed in sediment samples in the dry and wet seasons from November 2009 to October 2010 in West Port of Peninsular Malaysia. The heavy metal concentrations (mg/kg dry weight) were ranged from 23.4 to 98.3 for Zn, 22.3 to 80 for Pb, 7.4 to 27.6 Cu, 0.244 to 3.53 for Cd, 7.2 to 22.2 for Ni, 20.2 to 162 for As, 0.11 to 0.409 for Hg and 11.5 to 61.5 for Cr. Metals concentrations in dry season were higher than the rainy season except in cupper and chromium. Analysis of variance with Statistical Analysis System (SAS) shows that the mean concentration of metals in the two seasons (α level=0.05) are not significantly different which shows that the metals were held firmly in the matrix of sediment. Also there are significant differences between control point station with other stations. According to the Interim Sediment Quality guidelines (ISQG), the metal concentrations are moderately polluted, except in arsenic which shows the highest level of pollution.

Keywords: Heavy metals, sediment quality guidelines, west port.

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Authors: Jaroslav Polec, Viliam Hirner, Michal Martinovič, Kvetoslava Kotuliaková

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In this paper we present a novel error model for packet loss and subsequent error description. The proposed model simulates the error performance of wireless communication link. The model is designed as two independent Markov chains, where the first one is used for packet generation and the second one generates correctly and incorrectly transmitted bits for received packets from the first chain. The statistical analyses of real communication on the wireless link are used for determination of model-s parameters. Using the obtained parameters and the implementation of the generator, we collected generated traffic. The obtained results generated by proposed model are compared with the real data collection.

Keywords: Wireless channel, error model, Markov chain, Elliot model, Gilbert model, generator, IEEE 802.11.

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Authors: Safak Baykal

Abstract:

The purpose of this study is analyzing the relationship between trust and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: Bonding, homophilous social capital (BoSC), and Bridging, heterophilous social capital (BrSC). These two aspects diverge each other regarding to the social theories. The other concept of the study is Trust (Tr), namely interpersonal trust, willing to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.756 and social capital values (BoSC/BrSC) is not correlated with Tr values of the people.

Keywords: Social capital, interpersonal trust, social network analysis (SNA).

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

Abstract:

Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: Compressed sensing, Lest Support Orthogonal Matching Pursuit, Partial Knowing Support, Restricted isometry property, signal reconstruction.

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Authors: Maohai Li, Bingrong Hong, Zesu Cai, Ronghua Luo

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This paper presents the novel Rao-Blackwellised particle filter (RBPF) for mobile robot simultaneous localization and mapping (SLAM) using monocular vision. The particle filter is combined with unscented Kalman filter (UKF) to extending the path posterior by sampling new poses that integrate the current observation which drastically reduces the uncertainty about the robot pose. The landmark position estimation and update is also implemented through UKF. Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem, and introducing the evolution strategies (ES) for avoiding particle impoverishment. The 3D natural point landmarks are structured with matching Scale Invariant Feature Transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-Tree in the time cost of O(log2 N). Experiment results on real robot in our indoor environment show the advantages of our methods over previous approaches.

Keywords: Mobile robot, simultaneous localization and mapping, Rao-Blackwellised particle filter, evolution strategies, scale invariant feature transform.

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Authors: L.Tahmooresnejad, M.A.Shafia, R.Salami

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Technology transfer is a common method for companies to acquire new technology and presents both challenges and substantial benefits. In some cases especially in developing countries, the mere possession of technology does not guarantee a competitive advantage if the appropriate infrastructure is not in place. In this paper, we identify the localization factors needed to provide a better understanding of the conditions necessary for localization in order to benefit from future technology developments. Our theoretical and empirical analyses allow us to identify several factors in the technology transfer process that affect localization and provide leverage in enhancing capabilities and absorptive capacity.The impact factors are categorized within different groups of government, firms, institutes and market, and are verified through the empirical survey of a technology transfer experience. Moreover, statistical analysis has allowed a deeper understanding of the importance of each factor and has enabled each group to prioritize their organizational policies to effectively localize their technology.

Keywords: Absorption Capacity, Adaptation, Technology Transfer, Technology Localization

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Authors: Alireza Ghasemizad

Abstract:

In Both developed and developing countries, governments play a basic role in making policies, programs and instruments which support the development of micro, small and medium enterprises. One of the mechanisms employed to nurture small firms for more than two decades is business incubation. One of the mechanisms employed to nurture small firms for more than two decades is technology business incubation. The main aim of this research was to establish influencing factors in Technology Business Incubator's effectiveness and their explanatory model. Therefore, among 56 Technology Business Incubators in Iran, 32 active incubators were selected and by stratified random sampling, 528 start-ups were chosen. The validity of research questionnaires was determines by expert consensus, item analysis and factor analysis; and their reliability calculated by Cronbach-s alpha. Data analysis was then made through SPSS and LISREL soft wares. Both organizational procedures and entrepreneurial behaviors were the meaningful mediators. Organizational procedures with (P < .01, β =0.45) was stronger mediator for the improvement of Technology Business Incubator's effectiveness comparing to entrepreneurial behavior with (P < .01, β =0.36).

Keywords: Technology, Incubators, Effectiveness, Explanatorymodel.

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Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of Decode and Forward (DF) multihop Free Space Optical ( FSO) scheme deploying Multiple Input Multiple Output (MIMO) configuration under Gamma-Gamma (GG) statistical distribution, that adopts M-ary Pulse Position Modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of Symbol-Error Rates (SERs) respectively. A closed form formula related to the Probability Density Function (PDF) is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: FSO, MIMO, MIMO, multihop, DF, SER, GG channel.

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Authors: Mohamad Mahdavi, Mojtaba Mahdavi

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This paper tries to represent a new method for computing the reliability of a system which is arranged in series or parallel model. In this method we estimate life distribution function of whole structure using the asymptotic Extreme Value (EV) distribution of Type I, or Gumbel theory. We use EV distribution in minimal mode, for estimate the life distribution function of series structure and maximal mode for parallel system. All parameters also are estimated by Moments method. Reliability function and failure (hazard) rate and p-th percentile point of each function are determined. Other important indexes such as Mean Time to Failure (MTTF), Mean Time to repair (MTTR), for non-repairable and renewal systems in both of series and parallel structure will be computed.

Keywords: Reliability, extreme value, parallel, series, lifedistribution

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Authors: Sara A.Yones, Ahmed S. Moussa

Abstract:

Quantitative measurements of tumor in general and tumor volume in particular, become more realistic with the use of Magnetic Resonance imaging, especially when the tumor morphological changes become irregular and difficult to assess by clinical examination. However, tumor volume estimation strongly depends on the image segmentation, which is fuzzy by nature. In this paper a fuzzy approach is presented for tumor volume segmentation based on the fuzzy connectedness algorithm. The fuzzy affinity matrix resulting from segmentation is then used to estimate a fuzzy volume based on a certainty parameter, an Alpha Cut, defined by the user. The proposed method was shown to highly affect treatment decisions. A statistical analysis was performed in this study to validate the results based on a manual method for volume estimation and the importance of using the Alpha Cut is further explained.

Keywords: Alpha Cut, Fuzzy Connectedness, Magnetic Resonance Imaging, Tumor volume estimation.

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Authors: Zh.Mingaleva, K.Balkova

Abstract:

Innovations and innovative activity get the increasing value for successful financial and economic activity of the countries and regions. The level of innovative sphere development determines place of a country or a region in world economy and forms a basis of steady economic growth. This article is devoted to different aspects of organization of the national economic safety in the conditions of innovative development, its problems, risks and threats. Economy can be considered as aspiring for transition to innovative way only with finding of economic safety: financial independence, power stability and technological progress. There are statistical indicators, defining the level of economic security and factors, threatening economic safety of the state. The research is based on the analysis of factors and indicators in conditions of innovative development. The paper is illustrated by the examples of possible estimated system of the economic safety level.

Keywords: Economic safety, innovative activity, innovative development, innovative economy

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Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: Complementary and alternative medicine, Iridology, iris, feature extraction, classification, disease prediction.

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Authors: Yoonsuh Jung

Abstract:

As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an ‘optimal’ value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: Cross Validation, Parameter Averaging, Parameter Selection, Regularization Parameter Search.

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Authors: Jann-Eike Saathoff, Kirill Alexander Schmoor, Martin Achmus, Mauricio Terceros

Abstract:

By using partial factors of safety, uncertainties due to the inherent variability of the soil properties and loads are taken into account in the geotechnical design process. According to the reliability index concept in Eurocode-0 in conjunction with Eurocode-7 a minimum safety level of β = 3.8 for reliability class RC2 shall be established. The reliability of the system depends heavily on the choice of the prespecified safety factor and the choice of the characteristic soil properties. The safety factors stated in the standards are mainly based on experience. However, no general accepted method for the calculation of a characteristic value within the current design practice exists. In this study, a laterally loaded monopile is investigated and the influence of the chosen quantile values of the deterministic system, calculated with p-y springs, will be presented. Monopiles are the most common foundation concepts for offshore wind energy converters. Based on the calculations for non-cohesive soils, a recommendation for an appropriate quantile value for the necessary safety level according to the standards for a deterministic design is given.

Keywords: Asymptotic sampling, characteristic value, monopile foundation, probabilistic design, quantile values.

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Authors: Lebari B. Gboeloh

Abstract:

The occurrence of adult Taenia saginata in major abattoirs in Port Harcourt metropolis was investigated. Out of 514 cattle investigated, an overall prevalence of 35(6.8%) was recorded. Infected male and female cattle represented 1.2% (6/514) and 5.6% (29/514) of the overall prevalence respectively. There was a statistical significant difference (P< 0.05) in prevalence of adult Taenaia saginata between male and female cattle examined in the study area. Old cattle have a significant (P< 0.05) infestation rate than young ones. Adult Taenia saginata exists in cattle and still remains a public health concern in the study area. Deliberate effort is needed from stake-holders and the Government to design and implement programs that will lead to the prevention and possible eradication of the parasite.

Keywords: Taenia saginata, Adult, Cattle, Occurrence, Port Harcourt.

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Authors: I. Severin, M. Caramihai, R. El Abdi, M. Poulain, A. Avadanii

Abstract:

In order to assess optical fiber reliability in different environmental and stress conditions series of testing are performed simulating overlapping of chemical and mechanical controlled varying factors. Each series of testing may be compared using statistical processing: i.e. Weibull plots. Due to the numerous data to treat, a software application has appeared useful to interpret selected series of experiments in function of envisaged factors. The current paper presents a software application used in the storage, modelling and interpretation of experimental data gathered from optical fibre testing. The present paper strictly deals with the software part of the project (regarding the modelling, storage and processing of user supplied data).

Keywords: Optical fibres, computer aided analysis, data models, data processing, graphical user interfaces.

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Authors: Wardah, T., Kamil, A.A., Sahol Hamid, A.B., Maisarah, W.W.I

Abstract:

Quantitative precipitation forecast (QPF) from atmospheric model as input to hydrological model in an integrated hydro-meteorological flood forecasting system has been operational in many countries worldwide. High-resolution numerical weather prediction (NWP) models with grid cell sizes between 2 and 14 km have great potential in contributing towards reasonably accurate QPF. In this study the potential of two NWP models to forecast precipitation for a flood-prone area in a tropical region is examined. The precipitation forecasts produced from the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) models are statistically verified with the observed rain in Kelantan River Basin, Malaysia. The statistical verification indicates that the models have performed quite satisfactorily for low and moderate rainfall but not very satisfactory for heavy rainfall.

Keywords: MM5, Numerical weather prediction (NWP), quantitative precipitation forecast (QPF), WRF

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Authors: Hamid Reza Boveiri

Abstract:

Classification of Persian printed numeral characters has been considered and a proposed system has been introduced. In representation stage, for the first time in Persian optical character recognition, extended moment invariants has been utilized as characters image descriptor. In classification stage, four different classifiers namely minimum mean distance, nearest neighbor rule, multi layer perceptron, and fuzzy min-max neural network has been used, which first and second are traditional nonparametric statistical classifier. Third is a well-known neural network and forth is a kind of fuzzy neural network that is based on utilizing hyperbox fuzzy sets. Set of different experiments has been done and variety of results has been presented. The results showed that extended moment invariants are qualified as features to classify Persian printed numeral characters.

Keywords: Extended moment invariants, optical characterrecognition, Persian numerals classification.

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Authors: L. Tizzi

Abstract:

The aim of this contribution is to present the experience of the U.S. secondary school Social Justice High School (SoJo), part of the larger Campus of Little Village Lawndale High School (LVLHS) located in Chicago, Illinois (USA). This experience can be considered a concrete application of the principles of the educational perspective known, in the United States, as Social Justice Education, aimed at ensuring quality education and educational success for students from disadvantaged groups, particularly those characterized by “biculturalism”, i.e. students with a dual cultural and linguistic background. The contribution will retrace the historical and social events that led to the birth of the SoJo, explaining the principles and methods used by the school to achieve its objectives and giving also some statistical data.

Keywords: Biculturalism, educational success, social justice education, social justice high school.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

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An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: Sumita Chowhan

Abstract:

Abilities are important for academic success. Yet, abilities cannot be the whole story. Styles might be one source of unexplained variation. A style is a preferred way of using ones abilities. Students are thought to be incompetent not because they are lacking in abilities, but because their styles do not match the academic course chosen. The purpose of the study was to determine the role of abilities and learning styles in prediction of academic performance and their adjustment. Participants were 272 engineering students. The tools used are Myers Briggs Type Indicator, Culture Fair Intelligence Test and Student Problem Checklist. The statistical procedures employed were t-test, correlations and stepwise regressions. The analyses of the data indicated that although abilities are better predictors of academic performance, learning styles also shown a significant relationship. The study also indicates that if students learning styles matches to their chosen academic course, they tend to show better performance and less adjustment problems.

Keywords: Abilities, Academic Performance, Adjustment, Learning Styles.

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Authors: Hyunjin Rho, Bongjin Shin, Okbok Lee, Yu-Hyun Choi, Jiyoung Lee, Jaerang Rho

Abstract:

The increasing usage of antibiotics in the animal farming industry is an emerging worldwide problem contributing to the development of antibiotic resistance. The purpose of this work was to investigate the prevalence and antibiotic resistance profile of bacterial isolates collected from aquatic environments and meats in a peri-urban community in Daejeon, Korea. In an antibacterial susceptibility test, the bacterial isolates showed a high incidence of resistance (~ 26.04 %) to cefazolin, tetracycline, gentamycin, norfloxacin, erythromycin and vancomycin. The results from a test for multiple antibiotic resistance indicated that the isolates were displaying an approximately 5-fold increase in the incidence of multiple antibiotic resistance to combinations of two different antibiotics compared to combinations of three or more antibiotics. Most of the isolates showed multi-antibiotic resistance, and the resistance patterns were similar among the sampling groups. Sequencing data analysis of 16S rRNA showed that most of the resistant isolates appeared to be dominated by the classes Betaproteobacteria and Gammaproteobacteria in the phylum Proteobacteria.

Keywords: Antibiotics, Antibiotic resistance, Antimicrobial resistance, Multi-resistance

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Authors: Xin Zhao, Yin-fan Zhu, Wei-ping Wang, Qun Li

Abstract:

The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the inter- influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.

Keywords: Time-sliced influence diagrams, discrete event systems, dynamic-stochastic influence diagrams, modeling formalism, simulation algorithm.

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Authors: Mounira Rouaïnia, Mohamed Salah Medjram, Noureddine Doghmane

Abstract:

In Multiple Sclerosis, pathological changes in the brain results in deviations in signal intensity on Magnetic Resonance Images (MRI). Quantitative analysis of these changes and their correlation with clinical finding provides important information for diagnosis. This constitutes the objective of our work. A new approach is developed. After the enhancement of images contrast and the brain extraction by mathematical morphology algorithm, we proceed to the brain segmentation. Our approach is based on building statistical model from data itself, for normal brain MRI and including clustering tissue type. Then we detect signal abnormalities (MS lesions) as a rejection class containing voxels that are not explained by the built model. We validate the method on MR images of Multiple Sclerosis patients by comparing its results with those of human expert segmentation.

Keywords: EM algorithm, Magnetic Resonance Imaging, Mathematical morphology, Markov random model.

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Authors: Autcha Araveeporn

Abstract:

This paper is to compare the parameter estimation of the mean in normal distribution by Maximum Likelihood (ML), Bayes, and Markov Chain Monte Carlo (MCMC) methods. The ML estimator is estimated by the average of data, the Bayes method is considered from the prior distribution to estimate Bayes estimator, and MCMC estimator is approximated by Gibbs sampling from posterior distribution. These methods are also to estimate a parameter then the hypothesis testing is used to check a robustness of the estimators. Data are simulated from normal distribution with the true parameter of mean 2, and variance 4, 9, and 16 when the sample sizes is set as 10, 20, 30, and 50. From the results, it can be seen that the estimation of MLE, and MCMC are perceivably different from the true parameter when the sample size is 10 and 20 with variance 16. Furthermore, the Bayes estimator is estimated from the prior distribution when mean is 1, and variance is 12 which showed the significant difference in mean with variance 9 at the sample size 10 and 20.

Keywords: Bayes method, Markov Chain Monte Carlo method, Maximum Likelihood method, normal distribution.

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Authors: Mustafa M. Donma, Orkide Donma, Savas Guzel

Abstract:

Iron is physiologically essential. However, it also participates in the catalysis of free radical formation reactions. Its deficiency is associated with amplified health risks. This trace element establishes some links with another physiological process related to cell death, apoptosis. Both iron deficiency and iron overload are closely associated with apoptosis. Soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) has the ability to trigger apoptosis and plays a dual role in the physiological versus pathological inflammatory responses of tissues. The aim of this study was to investigate the status of these parameters as well as the associations among them in children with obesity, a low-grade inflammatory state. The study was performed on groups of children with normal body mass index (N-BMI) and obesity. 43 children were included in each group. Based upon age- and sex-adjusted BMI percentile tables prepared by the World Health Organization, children whose values varied between 85 and 15 were included in N-BMI group. Children, whose BMI percentile values were between 99 and 95, comprised obese (OB) group. Institutional ethical committee approval and informed consent forms were taken prior to the study. Anthropometric measurements (weight, height, waist circumference, hip circumference, head circumference, neck circumference) and blood pressure values (systolic blood pressure and diastolic blood pressure) were recorded. Routine biochemical analyses, including serum iron, total iron binding capacity (TIBC), transferrin saturation percent (Tf Sat %) and ferritin, were performed. sTWEAK levels were determined by enzyme-linked immunosorbent assay. study data were evaluated using appropriate statistical tests performed by the statistical program SPSS. Serum iron levels were 91 ± 34 mcrg/dl and 75 ± 31 mcrg/dl in N-BMI and OB children, respectively. The corresponding values for TIBC, Tf Sat %, ferritin were 265 mcrg/dl vs. 299 mcrg/dl, 37.2 ± 19.1% vs. 26.7 ± 14.6%, and 41 ± 25 ng/ml vs 44 ± 26 ng/ml. In N-BMI and OB groups, sTWEAK concentrations were measured as 351 ng/L and 325 ng/L, respectively (p > 0.05). Correlation analysis revealed significant associations between sTWEAK levels and iron related parameters (p < 0.05) except ferritin. In conclusion, iron contributes to apoptosis. Children with iron deficiency have decreased apoptosis rate in comparison with that of healthy children. sTWEAK is an inducer of apoptosis. OB children had lower levels of both iron and sTWEAK. Low levels of sTWEAK are associated with several types of cancers and poor survival. Although iron deficiency state was not observed in this study, the correlations detected between decreased sTWEAK and decreased iron as well as Tf Sat % values were valuable findings, which point out decreased apoptosis. This may induce a proinflammatory state, potentially leading to malignancies in the future lives of OB children.

Keywords: Apoptosis, children, iron-related parameters, obesity, soluble tumor necrosis factor-like weak inducer of apoptosis.

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Authors: M. G. Albanesi, R. Amadeo

Abstract:

In this paper, a new approach for quality assessment tasks in lossy compressed digital video is proposed. The research activity is based on the visual fixation data recorded by an eye tracker. The method involved both a new paradigm for subjective quality evaluation and the subsequent statistical analysis to match subjective scores provided by the observer to the data obtained from the eye tracker experiments. The study brings improvements to the state of the art, as it solves some problems highlighted in literature. The experiments prove that data obtained from an eye tracker can be used to classify videos according to the level of impairment due to compression. The paper presents the methodology, the experimental results and their interpretation. Conclusions suggest that the eye tracker can be useful in quality assessment, if data are collected and analyzed in a proper way.

Keywords: eye tracker, video compression, video qualityassessment, visual attention

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

Abstract:

A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian Automotive Sector, Stock Market Decisions, Equity Portfolio Analysis, Decision Tree Classifiers, Statistical Data Analysis.

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Authors: Antonio Mauricio F. L. Miranda de Sá

Abstract:

Partial coherence between two signals removing the contribution of a periodic, deterministic signal is proposed for evaluating the interrelationship in multivariate systems. The estimator expression was derived and shown to be independent of such periodic signal. Simulations were used for obtaining its critical value, which were found to be the same as those for Gaussian signals, as well as for evaluating the technique. An Illustration with eletroencephalografic (EEG) signals during photic stimulation is also provided. The application of the proposed technique in both simulation and real EEG data indicate that it seems to be very specific in removing the contribution of periodic sources. The estimate independence of the periodic signal may widen partial coherence application to signal analysis, since it could be used together with simple coherence to test for contamination in signals by a common, periodic noise source.

Keywords: Partial coherence, periodic input, spectral analysis, statistical signal processing.

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