Search results for: forecast accuracy unemployment rate.

Authors: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: Computational social science, movie preference, machine learning, SVM.

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Authors: M. Tarafdar Haque, A.M. Kashtiban

Abstract:

The electric power industry is currently undergoing an unprecedented reform. One of the most exciting and potentially profitable recent developments is increasing usage of artificial intelligence techniques. The intention of this paper is to give an overview of using neural network (NN) techniques in power systems. According to the growth rate of NNs application in some power system subjects, this paper introduce a brief overview in fault diagnosis, security assessment, load forecasting, economic dispatch and harmonic analyzing. Advantages and disadvantages of using NNs in above mentioned subjects and the main challenges in these fields have been explained, too.

Keywords: Neural network, power system, security assessment, fault diagnosis, load forecasting, economic dispatch, harmonic analyzing.

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Authors: Brahmi Brahim, Mohammad Habibur Rahman, Maarouf Saad, Cristóbal Ochoa Luna

Abstract:

A repetitive training movement is an efficient method to improve the ability and movement performance of stroke survivors and help them to recover their lost motor function and acquire new skills. The ETS-MARSE is seven degrees of freedom (DOF) exoskeleton robot developed to be worn on the lateral side of the right upper-extremity to assist and rehabilitate the patients with upper-extremity dysfunction resulting from stroke. Practically, rehabilitation activities are repetitive tasks, which make the assistive/robotic systems to suffer from repetitive/periodic uncertainties and external perturbations induced by the high-order dynamic model (seven DOF) and interaction with human muscle which impact on the tracking performance and even on the stability of the exoskeleton. To ensure the robustness and the stability of the robot, a new nonlinear backstepping control was implemented with designed tests performed by healthy subjects. In order to limit and to reject the periodic/repetitive disturbances, an iterative estimator was integrated into the control of the system. The estimator does not need the precise dynamic model of the exoskeleton. Experimental results confirm the robustness and accuracy of the controller performance to deal with the external perturbation, and the effectiveness of the iterative estimator to reject the repetitive/periodic disturbances.

Keywords: Backstepping control, iterative control, rehabilitation, ETS-MARSE.

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Authors: Li-Wei Liu, Cheng-Yu Tsai, Ming-Tsang Wu

Abstract:

The study investigated the 2011 TPGA Ever Rich Championship – North Bay Open spectators- on-the-site spectating motivations, experiences, and satisfactions. The research was conducted on a convenience sample of the on-the-spot spectators at the North Bay Golf and Country Club. A total of 200 questionnaires were distributed, of which 185 valid questionnaires were collected, approaching a 92.5% response rate. The data obtained was analyzed with statistical techniques. First, the data showed significant differences in motivations, experiences, and satisfactions relative to demographic variables among the on-the-spot spectators. Second, spectating motivation, experience, and satisfaction were significantly related to one another.

Keywords: Spectating motivation, spectating experience, spectating satisfaction.

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Authors: Omid Gervei, Ahmad Ayatollahi, Navid Gervei

Abstract:

In this paper we present an approach for 3D face recognition based on extracting principal components of range images by utilizing modified PCA methods namely 2DPCA and bidirectional 2DPCA also known as (2D) 2 PCA.A preprocessing stage was implemented on the images to smooth them using median and Gaussian filtering. In the normalization stage we locate the nose tip to lay it at the center of images then crop each image to a standard size of 100*100. In the face recognition stage we extract the principal component of each image using both 2DPCA and (2D) 2 PCA. Finally, we use Euclidean distance to measure the minimum distance between a given test image to the training images in the database. We also compare the result of using both methods. The best result achieved by experiments on a public face database shows that 83.3 percent is the rate of face recognition for a random facial expression.

Keywords: 3D face recognition, 2DPCA, (2D) 2 PCA, Rangeimage

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Authors: Dongwon Lee, Eon Kyeong Joo

Abstract:

In this paper, the performance of three types of serial concatenated convolutional codes (SCCC) is compared and analyzed in additive white Gaussian noise (AWGN) channel. In Type I, only the parity bits of outer encoder are passed to inner encoder. In Type II and Type III, both the information bits and the parity bits of outer encoder are transferred to inner encoder. As results of simulation, Type I shows the best bit error rate (BER) performance at low signal-to-noise ratio (SNR). On the other hand, Type III shows the best BER performance at high SNR in AWGN channel. The simulation results are analyzed using the distance spectrum.

Keywords: Distance spectrum, MAP algorithm, SCCC.

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Behnam Amiri

Abstract:

Heat transfer of leaves is a crucial factor in optimal operation of metabolic functions in plants. In order to quantify this phenomenon in different leaves and investigate the influence of leaf shape on heat transfer, natural convection for pine, orange and olive leaves was simulated as representatives of different groups of leaf shapes. CFD techniques were used in this simulation with the purpose to calculate heat transfer of leaves in similar environmental conditions. The problem was simulated for steady state and threedimensional conditions. From obtained results, it was concluded that heat fluxes of all three different leaves are almost identical, however, total rate of heat transfer have highest and lowest values for orange leaves, and pine leaves, respectively.

Keywords: Computational fluid dynamic, heat flux, heat transfer, natural convection.

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Authors: Mohammad M. Toufigh, Ahad Ouria

Abstract:

This paper presents an analytical method to solve governing consolidation parabolic partial differential equation (PDE) for inelastic porous Medium (soil) with consideration of variation of equation coefficient under cyclic loading. Since under cyclic loads, soil skeleton parameters change, this would introduce variable coefficient of parabolic PDE. Classical theory would not rationalize consolidation phenomenon in such condition. In this research, a method based on time space mapping to a virtual time space along with superimposing rule is employed to solve consolidation of inelastic soils in cyclic condition. Changes of consolidation coefficient applied in solution by modification of loading and unloading duration by introducing virtual time. Mapping function is calculated based on consolidation partial differential equation results. Based on superimposing rule a set of continuous static loads in specified times used instead of cyclic load. A set of laboratory consolidation tests under cyclic load along with numerical calculations were performed in order to verify the presented method. Numerical solution and laboratory tests results showed accuracy of presented method.

Keywords: Mapping, Consolidation, Inelastic porous medium, Cyclic loading, Superimposing rule.

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Authors: E. Nemes-Nagy, E. Fogarasi, M. Croitoru, A. Nyárádi, K. Komlódi, S. Pál, A. Kovács, O. Kopácsy, R. Tripon, Z. Fazakas, C. Uzun, Z. Simon-Szabó, V. Balogh-Sămărghițan, E. Ernő Nagy, M. Szabó, M. Tilinca

Abstract:

Intense oxidative stress, increased glycated hemoglobin and mineral imbalance represent risk factors for complications in diabetic patients. Cardiovascular complications are most common in these patients, including nephropathy. This study was conducted in 2015 at the Procardia Laboratory in Tîrgu Mureș, Romania on 40 type 2 diabetic adults. Routine biochemical tests were performed on the Konleab 20XTi analyzer (serum glucose, total cholesterol, LDL and HDL cholesterol, triglyceride, creatinine, urea). We also measured serum uric acid, magnesium and calcium concentration by photometric procedures, potassium, sodium and chloride by ion selective electrode, and chromium by atomic absorption spectrometry in a group of patients. Glycated hemoglobin (HbA1c) dosage was made by reflectometry. Urine analysis was performed using the HandUReader equipment. The level of oxidative stress was measured by serum malondialdehyde dosage using the thiobarbituric acid reactive substances method. MDRD (Modification of Diet in Renal Disease) formula was applied for calculation of creatinine-derived glomerular filtration rate. GraphPad InStat software was used for statistical analysis of the data. The diabetic subject included in the study presented high MDA concentrations, showing intense oxidative stress. Calcium was deficient in 5% of the patients, chromium deficiency was present in 28%. The atherogenic cholesterol fraction was elevated in 13% of the patients. Positive correlation was found between creatinine and MDRD-creatinine values (p<0.0001), 68% of the patients presented increased creatinine values. The majority of the diabetic patients had good control of their diabetes, having optimal HbA1c values, 35% of them presented fasting serum glucose over 120 mg/dl and 18% had glucosuria. Intense oxidative stress and mineral deficiencies can increase the risk of cardiovascular complications in diabetic patients in spite of their good metabolic balance. More than two third of the patients present biochemical signs of nephropathy, cystatin C dosage and microalbuminuria could reveal better the kidney disorder, but glomerular filtration rate calculation formulas are also useful for evaluation of renal function.

Keywords: Cardiovascular risk, malondialdehyde, metabolic balance, minerals, type 2 diabetes.

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Authors: Hongjun Liu, Cunxiao Gao, Jintao Tao, Wei Zhao, Yishan Wang

Abstract:

A compact tunable 10 W picosecond source based on Yb-doped fiber amplification of gain switch laser diode has been demonstrated. A gain switch semiconductor laser diode was used as the seed source, and a multi-stage single mode Yb-doped fiber preamplifier was combined with two large mode area double-clad Yb-doped fiber main amplifiers to construct the amplification system. The tunable pulses with high stability and excellent beam quality (M2<1.2) of 10 W average power 150 ps pulse duration at 1 MHz repetition rate were obtained. The central wavelength with the line width of 2.5-3 nm was tunable from 1053 nm to 1073 nm.

Keywords: Fiber laser, fiber amplifier, picosecond laser, highpower laser

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Authors: Harish Ramesh Babu, Marco Böcker, Mario Raddatz, Sebastian Henkel, Horst Biermann, Uwe Gampe

Abstract:

Thermal power machines are subjected to cyclic loading conditions under elevated temperatures. At these extreme conditions, the durability of the components has a significant influence. The material mechanical behaviour has to be known in detail for a failsafe construction. For this study a nickel-based alloy is considered, the deformation and fatigue behaviour of the material is analysed under cyclic loading. A viscoplastic model is used for calculating the deformation behaviour as well as to simulate the rate-dependent and cyclic plasticity effects. Finally, the cyclic deformation results of the finite element simulations are compared with low cycle fatigue (LCF) experiments.

Keywords: Complex low cycle fatigue, elevated temperatures, IN718, viscoplastic.

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Authors: Ramin Javadzadeh, Emad Javadzadeh

Abstract:

Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.

Keywords: CLA-AIS, failure surface, optimization methods, rock slope.

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Authors: M. Rezvani, M. Ahangari, F. Zaefarian

Abstract:

In a field experiment, growth parameters of soybean cultivars in different weeding regimes was investigated. The trial was split plot in a randomized complete block design. The four cultivars and two lines of soybean (Glycine max L.) including: Sahar, Hill, Sari, Telar, 032 and 033 in main plot and weeding regime consist of no weeding (control), one weeding (35 days after planting) and two weeding (35+20 days after planting) were randomized in sub plot. The results showed that during the growth season 033 had the highest dry matter in two weeding. In two weeding regime the dry matter decreased. ). In all weeding regimes 033 had the highest CGR (Figs. 3a, 3b and 3c), which cleared this cultivar ability compare to the others. This cultivar by increasing its leaf area could do more photosynthesis, so, have a higher CGR.

Keywords: Crop growth rate, Density, Leaf area index

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Authors: Ghada Badr, Manar Hosny, Nuha Bintayyash, Eman Albilali, Souad Larabi Marie-Sainte

Abstract:

The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms.

Keywords: Median problem, phylogenetic tree, permutation, genetic algorithm, beam search, genome rearrangement distance.

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Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

Abstract:

Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, Charnes Cooper & Rhodes (CCR) Model, network data envelopment analysis, Iran electricity power chain.

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Authors: C. Blatier, M. El Methni, F. Carpentier, S. Abdellaoui, C. Kock, M. Maillard

Abstract:

International literature emphasizes on the concern regarding the phenomenon of aggression in hospital. This paper focuses on the reality of aggressive interactions reigning within an emergency triage involving three chaps of protagonists: the professionals, the patients and their carers. The data collection was made from a grid of observation, in which the various variables exposed in the literature were integrated. They observations took place around the clock, for three weeks, at the rate of one week a month. In this research 331 aggressive interactions have been listed and analyzed by means of the software SPSS. This research is one of the very few continuous observation surveys in the literature. It shows the various human factors at play in the emergence of aggressive interaction. The data may be used both for taking steps in primary prevention, thanks to the analysis of interaction modes, and in secondary prevention by integrating the useful results in situational prevention.

Keywords: Aggressive interaction, emergency unit, observational study.

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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Authors: M. Soryani, N. Rafat

Abstract:

Dealing with hundreds of features in character recognition systems is not unusual. This large number of features leads to the increase of computational workload of recognition process. There have been many methods which try to remove unnecessary or redundant features and reduce feature dimensionality. Besides because of the characteristics of Farsi scripts, it-s not possible to apply other languages algorithms to Farsi directly. In this paper some methods for feature subset selection using genetic algorithms are applied on a Farsi optical character recognition (OCR) system. Experimental results show that application of genetic algorithms (GA) to feature subset selection in a Farsi OCR results in lower computational complexity and enhanced recognition rate.

Keywords: Feature Subset Selection, Genetic Algorithms, Optical Character Recognition.

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Authors: Berna Eren Tokgoz, Mahdi Safa, Seokyon Hwang

Abstract:

Power distribution systems are essential and crucial infrastructures for the development and maintenance of a sustainable society. These systems are extremely vulnerable to various types of natural and man-made disasters. The assessment of resilience focuses on preparedness and mitigation actions under pre-disaster conditions. It also concentrates on response and recovery actions under post-disaster situations. The aim of this study is to present a methodology to assess the resilience of electric power distribution poles against wind-related events. The proposed methodology can improve the accuracy and rapidity of the evaluation of the conditions and the assessment of the resilience of poles. The methodology provides a metric for the evaluation of the resilience of poles under pre-disaster and post-disaster conditions. The metric was developed using mathematical expressions for physical forces that involve various variables, such as physical dimensions of the pole, the inclination of the pole, and wind speed. A three-dimensional imaging technology (photogrammetry) was used to determine the inclination of poles. Based on expert opinion, the proposed metric was used to define zones to visualize resilience. Visual representation of resilience is helpful for decision makers to prioritize their resources before and after experiencing a wind-related disaster. Multiple electric poles in the City of Beaumont, TX were used in a case study to evaluate the proposed methodology.  

Keywords: Photogrammetry, power distribution systems, resilience metric, system resilience, wind-related disasters.

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

Abstract:

Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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Authors: Ali Mamizadeh, Ires Iskender

Abstract:

The most important parameter in transformers life expectancy is the hot-spot temperature level which accelerates the rate of aging of the insulation. The aim of this paper is to present thermal models for transformers loaded at prefabricated MV/LV transformer substations and outdoor situations. The hot-spot temperature of transformers is studied using their top-oil temperature rise models. The thermal models proposed for hot-spot and top-oil temperatures of different operating situations are compared. Since the thermal transfer is different for indoor and outdoor transformers considering their operating conditions, their hot-spot thermal models differ from each other. The proposed thermal models are verified by the results obtained from the experiments carried out on a typical 1600 kVA, 30 /0.4 kV, ONAN transformer for both indoor and outdoor situations.

Keywords: Hot-spot Temperature, Dynamic Thermal Model, MV/LV Prefabricated, Oil Immersed Transformers

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Authors: Shiva Abdoli, Daniel T. Semere

Abstract:

Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.

Keywords: Process parameters, cutting process, energy efficiency, Material Removal Rate (MRR).

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Authors: C. Rattanakawin, S. Vasailor

Abstract:

Acid leaching of flotation concentrate of oxide copper ore containing mainly of malachite was performed in a standard agitation tank with various parameters. The effects of solid to liquid ratio, sulfuric acid concentration, agitation speed, leaching temperature and time were examined to get proper conditions. The best conditions are 1:8 solid to liquid ratio, 10% concentration by weight, 250 rev/min, 30 ^oC and 5-min leaching time in respect. About 20% Cu grade assayed by atomic absorption technique with 98% copper recovery was obtained from these combined optimum conditions. Dissolution kinetics of the concentrate was approximated as a logarithmic function. As a result, the first-order reaction rate is suggested from this leaching study.

Keywords: Agitation leaching, dissolution kinetics, flotation concentrate, oxide copper ore, sulfuric acid.

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Authors: Juhee Lee, Yongjun Lee

Abstract:

In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: Finite volume method, fluid flow, laminar flow, unstructured grid.

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Authors: Shuh Liang

Abstract:

This article provides empirical evidence on the effect of domestic and international factors on the U.S. current account deficit. Linear dynamic regression and vector autoregression models are employed to estimate the relationships during the period from 1986 to 2011. The findings of this study suggest that the current and lagged private saving rate and foreign current account for East Asian economies have played a vital role in affecting the U.S. current account. Additionally, using Granger causality tests and variance decompositions, the change of the productivity growth and foreign domestic demand are determined to influence significantly the change of the U.S. current account. To summarize, the empirical relationship between the U.S. current account deficit and its determinants is sensitive to alternative regression models and specifications.

Keywords: Current account deficit, productivity growth, foreign demand, vector autoregression.

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Authors: A. Lubis, S. S. Pasulu, Z. Hikmah, A. Endaryanto, A. Harsono

Abstract:

Infection by group A streptococci (GAS) can trigger an autoantibody that cause a poststreptococcal reactive arthritis (PSRA). Four patients with PSRA aged 10 years to 14 years old with the main complaint of joint pain for five days to 10 days after suffering a fever and sore throat. The joint pain was persistent, additive, and non migratory. All patients revealed an increase in erythrocyte sedimentation rate (ESR) and anti-streptolysin O (ASLO), but the chest x-ray, electrocardiography, and echocardiography were normal. Bone imaging showed no destruction on the affected joint. Jones Criteria were not fulfilled in all patients. Erythromycin and ibuprofen were given in all patients and an improvement was shown. Erythromycin was continued for one year and routine controls were conducted for cardiac evaluation. The prognosis of all the patients was good.

Keywords: Arthritis, group A streptococcus, autoantibody, Jones criteria.

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Authors: A. M. Maqableh

Abstract:

Modelling techniques for a fluid coupling taken from published literature have been extended to include the effects of the filling and emptying of the coupling with oil and the variation in losses when the coupling is partially full. In the model, the fluid flow inside the coupling is considered to have two principal velocity components; one circumferentially about the coupling axis (centrifugal head) and the other representing the secondary vortex within the coupling itself (vortex head). The calculation of liquid mass flow rate circulating between the two halves of the coupling is based on: the assumption of a linear velocity variation in the circulating vortex flow; the head differential in the fluid due to the speed difference between the two shafts; and the losses in the circulating vortex flow as a result of the impingement of the flow with the blades in the coupling and friction within the passages between the blades.

Keywords: Fluid Coupling, Mathematical Modelling, partially filled.

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Authors: A. Zahiri, A. A. Dehghani

Abstract:

Although many researchers have studied the flow hydraulics in compound channels, there are still many complicated problems in determination of their flow rating curves. Many different methods have been presented for these channels but extending them for all types of compound channels with different geometrical and hydraulic conditions is certainly difficult. In this study, by aid of nearly 400 laboratory and field data sets of geometry and flow rating curves from 30 different straight compound sections and using artificial neural networks (ANNs), flow discharge in compound channels was estimated. 13 dimensionless input variables including relative depth, relative roughness, relative width, aspect ratio, bed slope, main channel side slopes, flood plains side slopes and berm inclination and one output variable (flow discharge), have been used in ANNs. Comparison of ANNs model and traditional method (divided channel method-DCM) shows high accuracy of ANNs model results. The results of Sensitivity analysis showed that the relative depth with 47.6 percent contribution, is the most effective input parameter for flow discharge prediction. Relative width and relative roughness have 19.3 and 12.2 percent of importance, respectively. On the other hand, shape parameter, main channel and flood plains side slopes with 2.1, 3.8 and 3.8 percent of contribution, have the least importance.

Keywords: ANN model, compound channels, divided channel method (DCM), flow rating curve

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Authors: Majed Omar Al-Dwairi

Abstract:

This paper evaluate the multilevel modulation for different techniques such as amplitude shift keying (M-ASK), MASK, differential phase shift keying (M-ASK-Bipolar), Quaternary Amplitude Shift Keying (QASK) and Quaternary Polarization-ASK (QPol-ASK) at a total bit rate of 107 Gbps. The aim is to find a costeffective very high speed transport solution. Numerical investigation was performed using Monte Carlo simulations. The obtained results indicate that some modulation formats can be operated at 100Gbps in optical communication systems with low implementation effort and high spectral efficiency.

Keywords: Optical communication, multilevel amplitude shift keying (M-ASK), Differential phase shift keying (DPSK), Quaternary Amplitude Shift Keying (QASK), Quaternary Polarization-ASK (QPol-ASK).

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Authors: Ronal Muresano, Andrea Pagano

Abstract:

Nowadays, the mathematical/statistical applications are developed with more complexity and accuracy. However, these precisions and complexities have brought as result that applications need more computational power in order to be executed faster. In this sense, the multicore environments are playing an important role to improve and to optimize the execution time of these applications. These environments allow us the inclusion of more parallelism inside the node. However, to take advantage of this parallelism is not an easy task, because we have to deal with some problems such as: cores communications, data locality, memory sizes (cache and RAM), synchronizations, data dependencies on the model, etc. These issues are becoming more important when we wish to improve the application’s performance and scalability. Hence, this paper describes an optimization method developed for Systemic Model of Banking Originated Losses (SYMBOL) tool developed by the European Commission, which is based on analyzing the application's weakness in order to exploit the advantages of the multicore. All these improvements are done in an automatic and transparent manner with the aim of improving the performance metrics of our tool. Finally, experimental evaluations show the effectiveness of our new optimized version, in which we have achieved a considerable improvement on the execution time. The time has been reduced around 96% for the best case tested, between the original serial version and the automatic parallel version.

Keywords: Algorithm optimization, Bank Failures, OpenMP, Parallel Techniques, Statistical tool.

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