Search results for: poisson random measures

Authors: A. S. Haruna

Abstract:

The incessant discomfort for Voluntary Counselling and Testing (VCT) exhibited by students in some tertiary institutions in Kano State, Nigeria is capable of causing Psychological Resistance as well as jeopardizing the purpose of HIV intervention. This study investigated the Prevalence of Psychological Resistance to VCT of HIV/AIDS among students of tertiary institutions in the state. Two null hypotheses were postulated and tested. Cross- Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841 following Stratified Random Sampling technique. A self-developed 20-item scale whose reliability coefficient is 0.83 was used for data collection. Data analyzed via Chi-square and t-test reveals a prevalence of 38% with males (Mean=0.34; SD=0.475) constituting 60% and females (Mean=0.45; SD=0.498) 40%. Also, the calculated chi-square and ttest were not significant at 0.05 as such the null hypotheses were upheld. Recommendation offered suggests the use of reinforcement and social support for students who patronize HIV/AIDS counselling.

Keywords: HIV/AIDS, Prevalence rate, Psychological Resistance, VCT.

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Authors: Kefaya Qaddoum

Abstract:

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: Neural network, conformal prediction, cancer classification, regression.

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Authors: Manjit Singh

Abstract:

Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG, heart rate variability, HRV, multiscale entropy, sampling frequency.

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Authors: Norah Alshahrani, Abdulaziz Almaleh

Abstract:

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

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

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Authors: Aleksandar Savanović

Abstract:

In this paper, we will analyze the relationship between the neo-liberal concept of property rights and redistribution policy. This issue is back in the focus of interest due to the crisis 2008. The crisis has reaffirmed the influence of the state on the free-market processes. The interference of the state with property relations reopened a classical question: is it legitimate to redistribute resources of a man in favor of another man with taxes? The dominant view is that the neoliberal philosophy of natural rights is incompatible with redistributive measures. In principle, this view can be accepted. However, when we look into the details of the theory of natural rights proposed by some coryphaei of neoliberal philosophy, such as Hayek, Nozick, Buchanan and Rothbard, we can see that it is not such an unequivocal view. 

Keywords: Economic neoliberalism, natural law, property, redistribution

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Authors: David B. Bracewell, Fuji Ren, Shingo Kuroiwa

Abstract:

We present a method to create special domain collections from news sites. The method only requires a single sample article as a seed. No prior corpus statistics are needed and the method is applicable to multiple languages. We examine various similarity measures and the creation of document collections for English and Japanese. The main contributions are as follows. First, the algorithm can build special domain collections from as little as one sample document. Second, unlike other algorithms it does not require a second “general" corpus to compute statistics. Third, in our testing the algorithm outperformed others in creating collections made up of highly relevant articles.

Keywords: Information Retrieval, News, Special DomainCollections,

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Authors: Mohammed Benbrahim, Adil Daoudi, Khalid Benjelloun, Aomar Ibenbrahim

Abstract:

The automatic discrimination of seismic signals is an important practical goal for earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, two classes of seismic signals recorded routinely in geophysical laboratory of the National Center for Scientific and Technical Research in Morocco are considered. They correspond to signals associated to local earthquakes and chemical explosions. The approach adopted for the development of an automatic discrimination system is a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "modified Mexican hat wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.

Keywords: Seismic signals, Wavelets, Dimensionality reduction, Artificial neural networks, Classification.

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Authors: Chung-Hsin Huang, Chien-Ching Chiu, Chun Jen Lin

Abstract:

The electromagnetic imaging of inhomogeneous dielectric cylinders buried in a slab medium by transverse electric (TE) wave illumination is investigated. Dielectric cylinders of unknown permittivities are buried in second space and scattered a group of unrelated waves incident from first space where the scattered field is recorded. By proper arrangement of the various unrelated incident fields, the difficulties of ill-posedness and nonlinearity are circumvented, and the permittivity distribution can be reconstructed through simple matrix operations. The algorithm is based on the moment method and the unrelated illumination method. Numerical results are given to demonstrate the capability of the inverse algorithm. Good reconstruction is obtained even in the presence of additive Gaussian random noise in measured data. In addition, the effect of noise on the reconstruction result is also investigated.

Keywords: Slab Medium, Unrelated Illumination Method, TEWave Illumination, Inhomogeneous Cylinders.

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Authors: Fahad Suleiman

Abstract:

The aim of this paper is to study students’ view on mathematics learning in Katsina State Senior Secondary Schools of Nigeria, such as their conceptions of mathematics, attitudes toward mathematics learning, etc. A questionnaire was administered to a random sample of 1,225 senior secondary two (SS II) students of Katsina State in Nigeria. The data collected showed a clear picture of the hurdles that affect the teaching and learning of mathematics in our schools. Problems such as logistics and operational which include shortage of mathematics teachers, non–availability of a mathematics laboratory, etc. were identified. It also depicted the substantial trends of changing views and attitudes toward mathematics across secondary schools. Students’ responses to the conception of mathematics were consistent and they demonstrated some specific characteristics of their views in learning mathematics. This survey has provided useful information regarding students’ needs and aspirations in mathematics learning for curriculum planners and frontline teachers for future curriculum reform and implementation.

Keywords: Attitude, education, mathematics, students.

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Authors: Sattam Allahawiah, Haroon Altarawneh, Sameer Alamro

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Because of its global reach, reduction of time restraints, and ability to reduce costs and increase sales, use of the Internet, the World Wide Web (WWW), and related technologies can be a competitive tool in the arsenal of small and medium-sized enterprises (SMEs). Countries the world over are interested in the successful adoption of the Internet by SMEs. Because a vast majority of jobs come from that sector, greater financial success of SMEs translates into greater job growth and, subsequently, higher tax revenue to the government. This research investigated the level of Internet usage for business solutions by small and medium enterprises in Jordan. Through the survey of a random sample of 100 firms with less than 500 employees and from data obtained from this survey that formed the basis for our study, we found that a majority of respondents use the Internet in business activities , the adoption of the Internet as a business tool is limited to a brochure where Web site which primarily provides one way. As such, there wasn't interactive information about the company and its products and services.

Keywords: Internet, SMEs, e-commerce, website, e-business, IT.

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Authors: Lubna Shaheen

Abstract:

Palestinian cities face the challenges of land scarcity, high population growth rates, rapid urbanization, uneven development and territorial fragmentation. Due to geopolitical constrains and the absence of an effective Palestinian planning institution, urban development in Palestinian cities has not followed any discernable planning scheme. This has led to a number of internal contradictions in the structure of cities, and adversely affected land use, the provision of urban services, and the quality of the living environment. This paper explores these challenges, and the potential that exists for introducing a more sustainable urban development pattern in Palestinian cities. It assesses alternative development approaches with a particular focus on sustainable development, promoting ecodevelopment imperatives, limiting random urbanization, and meeting present and future challenges, including fulfilling the needs of the people and conserving the scarce land and limited natural resources. This paper concludes by offering conceptual proposals and guidelines for promoting sustainable physical development in Palestinian cities.

Keywords: Palestinian Cities, Rapid urbanization, Sustainableurban development.

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Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma, Hirendra Das

Abstract:

Signature represents an individual characteristic of a person which can be used for his / her validation. For such application proper modeling is essential. Here we propose an offline signature recognition and verification scheme which is based on extraction of several features including one hybrid set from the input signature and compare them with the already trained forms. Feature points are classified using statistical parameters like mean and variance. The scanned signature is normalized in slant using a very simple algorithm with an intention to make the system robust which is found to be very helpful. The slant correction is further aided by the use of an Artificial Neural Network (ANN). The suggested scheme discriminates between originals and forged signatures from simple and random forgeries. The primary objective is to reduce the two crucial parameters-False Acceptance Rate (FAR) and False Rejection Rate (FRR) with lesser training time with an intension to make the system dynamic using a cluster of ANNs forming a multiple classifier system.

Keywords: offline, algorithm, FAR, FRR, ANN.

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Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

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This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation.

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Authors: K.Sowmyan, A.Siddarth, D.Menaka

Abstract:

Several methods have been proposed for color image compression but the reconstructed image had very low signal to noise ratio which made it inefficient. This paper describes a lossy compression technique for color images which overcomes the drawbacks. The technique works on spatial domain where the pixel values of RGB planes of the input color image is mapped onto two dimensional planes. The proposed technique produced better results than JPEG2000, 2DPCA and a comparative study is reported based on the image quality measures such as PSNR and MSE.Experiments on real time images are shown that compare this methodology with previous ones and demonstrate its advantages.

Keywords: Color Image compression, spatial domain, planereduction, root mean square, image restoration

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Authors: K. Vandenboer, L. Dolphen, A. Bezuijen

Abstract:

Backward erosion piping is an important failure mechanism for water-retaining structures, a phenomenon that results in the formation of shallow pipes at the interface of a sandy or silty foundation and a cohesive cover layer. This paper studies the effect of two soil types on backward erosion piping; both in case of a homogeneous sand layer, and in a vertically layered sand sample, where the pipe is forced to subsequently grow through the different layers. Two configurations with vertical sand layers are tested; they both result in wider pipes and higher critical gradients, thereby making this an interesting topic in research on measures to prevent backward erosion piping failures.

Keywords: Backward erosion piping, embankments, physical modelling, sand.

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Authors: Z. Saidi, A.O. Boudraa, J.C. Cexus, S. Bourennane

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In this paper, a new time-delay estimation technique based on the cross IB-energy operator [5] is introduced. This quadratic energy detector measures how much a signal is present in another one. The location of the peak of the energy operator, corresponding to the maximum of interaction between the two signals, is the estimate of the delay. The method is a fully data-driven approach. The discrete version of the continuous-time form of the cross IBenergy operator, for its implementation, is presented. The effectiveness of the proposed method is demonstrated on real underwater acoustic signals arriving from targets and the results compared to the cross-correlation method.

Keywords: Teager-Kaiser energy operator, Cross-energyoperator, Time-Delay, Underwater acoustic signals.

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Authors: Encarnación Álvarez, Rosa M. García-Fernández, Francisco J. Blanco-Encomienda, Juan F. Muñoz

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The European Union Survey on Income and Living Conditions (EU-SILC) is a popular survey which provides information on income, poverty, social exclusion and living conditions of households and individuals in the European Union. The EU-SILC contains variables which may contain outliers. The presence of outliers can have an impact on the measures and indicators used by the EU-SILC. In this paper, we used data sets from various countries to analyze the presence of outliers. In addition, we obtain some indicators after removing these outliers, and a comparison between both situations can be observed. Finally, some conclusions are obtained.

Keywords: Headcount index, poverty line, risk of poverty, skewness coefficient.

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Authors: N. Mpofu, M. Sears

Abstract:

In this paper, we propose a novel algorithm for delineating the endocardial wall from a human heart ultrasound scan. We assume that the gray levels in the ultrasound images are independent and identically distributed random variables with different Rician Inverse Gaussian (RiIG) distributions. Both synthetic and real clinical data will be used for testing the algorithm. Algorithm performance will be evaluated using the expert radiologist evaluation of a soft copy of an ultrasound scan during the scanning process and secondly, doctor’s conclusion after going through a printed copy of the same scan. Successful implementation of this algorithm should make it possible to differentiate normal from abnormal soft tissue and help disease identification, what stage the disease is in and how best to treat the patient. We hope that an automated system that uses this algorithm will be useful in public hospitals especially in Third World countries where problems such as shortage of skilled radiologists and shortage of ultrasound machines are common. These public hospitals are usually the first and last stop for most patients in these countries.

Keywords: Endorcardial Wall, Rician Inverse Distributions, Segmentation, Ultrasound Images.

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Authors: Ali Gholami

Abstract:

In this research the Preparation of Land use map of scanner LISS III satellite data, belonging to the IRS in the Aghche region in Isfahan province, is studied carefully. For this purpose, the IRS satellite images of August 2008 and various land preparation uses in region including rangelands, irrigation farming, dry farming, gardens and urban areas were separated and identified. Therefore, the GPS and Erdas Imaging software were used and three methods of Maximum Likelihood, Mahalanobis Distance and Minimum Distance were analyzed. In each of these methods, matrix error and Kappa index were calculated and accuracy of each method, based on percentages: 53.13, 56.64 and 48.44, were obtained respectively. Considering the low accuracy of these methods in separation of land preparation use, the visual interpretation of the map was used. Finally, regional visits of 150 points were noted at random and no error was observed. It shows that the map prepared by visual interpretation is in high accuracy. Although the probable errors due to visual interpretation and geometric correction might happen but the desired accuracy of the map which is more than 85 percent is reliable.

Keywords: Land use map, Aghche Region, Erdas Imagine, satellite images

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Authors: Teerawach Khamkorn, Laongtip Mathurasa, Savittree Rochanasmita Arnold, Witthaya Mekhum

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This research is aimed at studying the nature of problems and demands of the training for community leaders in the upper northeastern region of Thailand. Population and group samplings are based on 360 community leaders in the region who have experienced prior training from the Udonthani Rajabhat University. Stratified random samplings have been drawn upon 186 participants. The research tools is questionnaires. The frequency, percentage and standard deviation are employed in data analysis. The findings indicate that most of community leaders are males and senior adults. The problems in training are associated with the inconveniences of long-distance travelling to training locations, inadequacy of learning centers and training sites and high training costs. The demand of training is basically motivated by a desire for self-development in modern knowledge in keeping up-to-date with the changing world and the need for technological application and facilitation in shortening the distance to training locations and in limiting expensive training costs.

Keywords: Community leaders, Distance Training, Management, Technology.

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Authors: Sangsuree Vasupongayya

Abstract:

To provide a better understanding of fair share policies supported by current production schedulers and their impact on scheduling performance, A relative fair share policy supported in four well-known production job schedulers is evaluated in this study. The experimental results show that fair share indeed reduces heavy-demand users from dominating the system resources. However, the detailed per-user performance analysis show that some types of users may suffer unfairness under fair share, possibly due to priority mechanisms used by the current production schedulers. These users typically are not heavy-demands users but they have mixture of jobs that do not spread out.

Keywords: Fair share, Parallel job scheduler, Backfill, Measures

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Authors: Frank Emmert-Streib, Matthias Dehmer

Abstract:

Inferring the network structure from time series data is a hard problem, especially if the time series is short and noisy. DNA microarray is a technology allowing to monitor the mRNA concentration of thousands of genes simultaneously that produces data of these characteristics. In this study we try to investigate the influence of the experimental design on the quality of the result. More precisely, we investigate the influence of two different types of random single gene perturbations on the inference of genetic networks from time series data. To obtain an objective quality measure for this influence we simulate gene expression values with a biologically plausible model of a known network structure. Within this framework we study the influence of single gene knock-outs in opposite to linearly controlled expression for single genes on the quality of the infered network structure.

Keywords: Dynamic Bayesian networks, microarray data, structure learning, Markov chain Monte Carlo.

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Authors: Nina Bijedic, Drazena Gaspar, Mirsad Hadzikadic

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Corruption is an influential and widespread problem. One part of it is so-called petty corruption, related to large-scale bribe giving by ordinary citizens trying to influence the works of public administration or public services. As it is with all means of corruption, petty corruption is related to the level of democracy (or administration efficiency) in a society. The developed model captures some of the factors related to corruptive behavior, as well as people’s attitude towards petty corruption. It has four basic elements: user’s perception of corruption in the society of interest, the influence of social interactions, the influence of penalizing mechanism, and influence of campaigns against petty corruption. The model is agent-based, developed in NetLogo, with a lot of random settings that provide a wider scope of responses. Interactions of different settings for variables of elements provide insight into the influence of each element on attitude towards petty corruption, as well as petty corruptive behavior.

Keywords: Agent based model, attitude, influence, petty corruption, society.

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Authors: M. Sultana, A. Rahman, S. Chowdhury

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Road authorities have confronted problems to maintaining the serviceability of road infrastructure systems by using various traditional methods of contracting. As a solution to these problems, many road authorities have started contracting out road maintenance works to the private sector based on performance measures. This contracting method is named Performance-Based Maintenance Contracting (PBMC). It is considered more costeffective than other traditional methods of contracting. It has a substantial success records in many developed and developing countries over the last two decades. This paper discusses and analyses the potential issues to be considered before the introduction of PBMC in a country.

Keywords: Contracting, Performance-Based Maintenance, Road infrastructure

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Authors: José Peralta, Gabriela Peretti, Eduardo Romero, Carlos Marqués

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This paper proposes a new performance characterization for the test strategy intended for second order filters denominated Transient Analysis Method (TRAM). We evaluate the ability of the addressed test strategy for detecting deviation faults under simultaneous statistical fluctuation of the non-faulty parameters. For this purpose, we use Monte Carlo simulations and a fault model that considers as faulty only one component of the filter under test while the others components adopt random values (within their tolerance band) obtained from their statistical distributions. The new data reported here show (for the filters under study) the presence of hard-to-test components and relatively low fault coverage values for small deviation faults. These results suggest that the fault coverage value obtained using only nominal values for the non-faulty components (the traditional evaluation of TRAM) seem to be a poor predictor of the test performance.

Keywords: testing, fault analysis, analog filter test, parametric faults detection.

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Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular / nanoscale models is demonstrated.

Keywords: Cement composite, Mechanical Properties, Molecular Dynamics, Plasticizer additives.

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Authors: S. Loumi, H. Merrad, F. Alilat, B. Sansal

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In this article, we propose a methodology for the characterization of the suspended matter along Algiers-s bay. An approach by multi layers perceptron (MLP) with training by back propagation of the gradient optimized by the algorithm of Levenberg Marquardt (LM) is used. The accent was put on the choice of the components of the base of training where a comparative study made for four methods: Random and three alternatives of classification by K-Means. The samples are taken from suspended matter image, obtained by analytical model based on polynomial regression by taking account of in situ measurements. The mask which selects the zone of interest (water in our case) was carried out by using a multi spectral classification by ISODATA algorithm. To improve the result of classification, a cleaning of this mask was carried out using the tools of mathematical morphology. The results of this study presented in the forms of curves, tables and of images show the founded good of our methodology.

Keywords: Classification K-means, mathematical morphology, neural network MLP, remote sensing, suspended particulate matter

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Authors: A. Chellil, I. Gahlouz, S. Lecheb, A. Nour, S. Chellil, H. Mechakra, H. Kebir

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In this paper, the experimental study for the instability of a separator rotor is presented, under dynamic loading response in the harmonic analysis condition. The global measurement and analysis of vibration on the cement separator RC500 is carried, the points of measurement used are radial dots, vertical, horizontal and oblique. The measures of trends and spectral analysis for reconnaissance of the main anomalies, the main defects in the separator and manifestation, the results prove that the defects effect has a negative effect on the stability of the rotor. Experimentally the study of the rotor in transient system allowed to determine the vibratory responses due to the unbalances and various excitations.

Keywords: Rotor, experimental, defect, frequency, specter.

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper presents an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: Cloud, enhancing security, Fog, IoT, telehealth.

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Authors: Sedighe Arabameri, Nasser Salmasi

Abstract:

In this researcha particle swarm optimization (PSO) algorithm is proposedfor no-wait flowshopsequence dependent setuptime scheduling problem with weighted earliness-tardiness penalties as the criterion (
|, |Σ   " ).The smallestposition value (SPV) rule is applied to convert the continuous value of position vector of particles in PSO to job permutations.A timing algorithm is generated to find the optimal schedule and calculate the objective function value of a given sequence in PSO algorithm. Twodifferent neighborhood structures are applied to improve the solution quality of PSO algorithm.The first one is based on variable neighborhood search (VNS) and the second one is a simple one with invariable structure. In order to compare the performance of two neighborhood structures, random test problems are generated and solved by both neighborhood approaches.Computational results show that the VNS algorithmhas better performance than the other one especially for the large sized problems.

Keywords: minimization of summation of weighed earliness and tardiness, no-wait flowshop scheduling, particle swarm optimization, sequence dependent setup times

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