Search results for: Computational Fluid Dynamics (CFD) model

Authors: G. Renuka Devi

Abstract:

This paper presents design and analysis of fault tolerate feature of n-phase induction motor drive. The n-phase induction motor (more than 3-phases) has a number of advantages over conventional 3-phase induction motor, it has low torque pulsation with increased torque density, more fault tolerant feature, low current ripple with increased efficiency. When increasing the number of phases, it has reduced current per phase without increasing per phase voltage, resulting in an increase in the total power rating of n-phase motors in the same volume machine. In this paper, the theory of operation of a multi-phase induction motor is discussed. The detailed study of d-q modeling of n-phase induction motors is elaborated. The d-q model of n-phase (5, 6, 7, 9 and 12) induction motors is developed in a MATLAB/Simulink environment. The steady state and dynamic performance of the multi-phase induction motor is studied under varying load conditions. Comparison of 5-phase induction is presented under normal and fault conditions.

Keywords: d-q model, dynamic Response, fault tolerant feature, matlab/simulink, multi-phase induction motor, transient response.

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Authors: Sang Hoon Kang, Seong-Min Yoon

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Little attention has been paid to information transmission between the portfolios of large stocks and small stocks in the Korean stock market. This study investigates the return and volatility transmission mechanisms between large and small stocks in the Korea Exchange (KRX). This study also explores whether bad news in the large stock market leads to a volatility of the small stock market that is larger than the good news volatility of the large stock market. By employing the Granger causality test, we found unidirectional return transmissions from the large stocks to medium and small stocks. This evidence indicates that pat information about the large stocks has a better ability to predict the returns of the medium and small stocks in the Korean stock market. Moreover, by using the asymmetric GARCH-BEKK model, we observed the unidirectional relationship of asymmetric volatility transmission from large stocks to the medium and small stocks. This finding suggests that volatility in the medium and small stocks following a negative shock in the large stocks is larger than that following a positive shock in the large stocks.

Keywords: Asymmetric GARCH-BEKK model, Asymmetric volatility transmission, Causality, Korean stock market, Spillover effect

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Authors: Kevin Anderson, Sukhwinder Singh Sandhu, Nouh Anies, Shilpa Ravichandra, Steven Dobbs, Donald Edberg

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This paper presents the results of a Finite Element based vibration analysis of a solar powered Unmanned Aerial Vehicle (UAV). The purpose of this paper was to quantify the free vibration, forced vibration response due to differing point inputs in order to predict the relative response magnitudes and frequencies at various wing locations of vibration induced power generators (magnet in coil) excited by gust and/or control surface pulse-decays used to help power the flight of the electric UAV. A Fluid Structure Interaction (FSI) study was performed in order to ascertain pertinent design stresses and deflections as well as aerodynamic parameters of the UAV airfoil. The 10 ft span airfoil is modeled using Mylar as the primary material. Results show that the free mode in bending is 4.8 Hz while the first forced bending mode is on range of 16.2 to 16.7 Hz depending on the location of excitation. The free torsional bending mode is 28.3 Hz, and the first forced torsional mode is range of 26.4 to 27.8 Hz, depending on the location of excitation. The FSI results predict the coefficients of aerodynamic drag and lift of 0.0052 and 0.077, respectively, which matches hand-calculations used to validate the Finite Element based results. FSI based maximum von Mises stresses and deflections were found to be 0.282 MPa and 3.4 mm, respectively. Dynamic pressures on the airfoil range from 1.04 to 1.23 kPa corresponding to velocity magnitudes in range of 22 to 66 m/s.

Keywords: ANSYS, finite element, FSI, UAV, vibrations.

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Authors: J. R. Mudakavi, K. Puttanna

Abstract:

Chromium in the environment is considered as one of the most toxic elements probably next only to mercury and arsenic. It is acutely toxic, mutagenic and carcinogenic in the environment. Chromium contamination of soil and underground water due to industrial activities is a very serious problem in several parts of India covering Karnataka, Tamil Nadu, Andhra Pradesh etc. Functionally modified Activated Carbon Fabrics (ACF) offer targeted chromium removal from drinking water and industrial effluents. Activated carbon fabric is a light weight adsorbing material with high surface area and low resistance to fluid flow. We have investigated surface modification of ACF using various acids in the laboratory through batch as well as through continuous flow column experiments with a view to develop the optimum conditions for chromium removal. Among the various acids investigated, phosphoric acid modified ACF gave best results with a removal efficiency of 95% under optimum conditions. Optimum pH was around 2 – 4 with 2 hours contact time. Continuous column experiments with an effective bed contact time (EBCT) of 5 minutes indicated that breakthrough occurred after 300 bed volumes. Adsorption data followed a Freundlich isotherm pattern. Nickel adsorbs preferentially and sulphate reduces chromium adsorption by 50%. The ACF could be regenerated up to 52.3% using 3 M NaOH under optimal conditions. The process is simple, economical, energy efficient and applicable to industrial effluents and drinking water.

Keywords: Activated carbon fabric, adsorption, drinking water, hexavalent chromium.

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Authors: Xuling Zhang, Yong Wang, Xingyun Liu, Shuangxue Xu

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Based on positive psychology, this study presented a mediated moderation model in which character strengths moderated the relationship between interpersonal relationship, job satisfaction and subjective well-being, with job satisfaction taking the mediation role among them. A total of 912 teachers participated in four surveys, which include the Oxford Happiness Questionnaire, Values in Action Inventory of Strengths, job satisfaction questionnaire, and the interpersonal relationship questionnaire. The results indicated that: (1) Taking interpersonal relationship as a typical work environmental variable, the result shows that it is significantly correlated to subjective well-being. (2) The character strengths of "kindness", “authenticity” moderated the effect of the teachers’ interpersonal relationship on subjective well-being. (3) The teachers’ job satisfaction mediated the above mentioned moderation effects. In general, this study shows that the teachers’ interpersonal relationship affects their subjective well-being, with their job satisfaction as mediation and character strengths of “kindness” and “authenticity” as moderation. The managerial implications were also discussed.

Keywords: Character strength, subjective well-being, job satisfaction, interpersonal relationship.

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Authors: Nieto Bernal W., Luna Amaya C.

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This paper aims to present a framework for the organizational knowledge management, which seeks to deploy a standardized structure for the integrated management of knowledge is a common language based on domains, processes and global indicators inspired by the COBIT framework 5 (ISACA, 2012), which supports the integration of three technologies, enterprise information architecture (EIA), the business process modeling (BPM) and service-oriented architecture (SOA). The Gomak Framework is a management platform that seeks to integrate the information technology infrastructure, the structure of applications, information infrastructure, and business logic and business model to support a sound strategy of organizational knowledge management, low process-based approach and concurrent engineering. Concurrent engineering (CE) is a systematic approach to integrated product development that respond to customer expectations, involving all perspectives in parallel, from the beginning of the product life cycle. (European Space Agency, 2000).

Keywords: Business Process Modeling, Enterprise Information Architecture, Government and Knowledge Management, Service Oriented Architecture, Process Management.

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Authors: Y. Lacroix, J.-F. Malbranque

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We present a chronological evolution for naval telecommunication networks. We distinguish periods: with or without multiplexers, with switch systems, with federative systems, with medium switching, and with medium switching with wireless networks. This highlights the introduction of new layers and technology in the architecture. These architectures are presented using layer models of transmission, in a unified way, which enables us to integrate pre-existing models. A ship of a naval fleet has internal communications (i.e. applications' networks of the edge) and external communications (i.e. the use of the means of transmission between edges). We propose architectures, deduced from the layer model, which are the point of convergence between the networks on board and the HF, UHF radio, and satellite resources. This modelling allows to consider end-to-end naval communications, and in a more global way, that is from the user on board towards the user on shore, including transmission and networks on the shore side. The new architectures need take care of quality of services for end-to-end communications, the more remote control develops a lot and will do so in the future. Naval telecommunications will be more and more complex and will use more and more advanced technologies, it will thus be necessary to establish clear global communication schemes to grant consistency of the architectures. Our latest model has been implemented in a military naval situation, and serves as the basic architecture for the RIFAN2 network.

Keywords: Equilibrium beach profile, eastern tombolo of Giens, potential function, erosion.

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Authors: Mahdi Kiani, Hassan Salarieh, Aria Alasty, S. Mahdi Darbandi

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The design and implementation of the hybrid control method for a three-pole active magnetic bearing (AMB) is proposed in this paper. The system is inherently nonlinear and conventional nonlinear controllers are a little complicated, while the proposed hybrid controller has a piecewise linear form, i.e. linear in each sub-region. A state-feedback hybrid controller is designed in this study, and the unmeasurable states are estimated by an observer. The gains of the hybrid controller are obtained by the Linear Quadratic Regulator (LQR) method in each sub-region. To evaluate the performance, the designed controller is implemented on an experimental setup in static mode. The experimental results show that the proposed method can efficiently stabilize the three-pole AMB system. The simplicity of design, domain of attraction, uncomplicated control law, and computational time are advantages of this method over other nonlinear control strategies in AMB systems.

Keywords: Active magnetic bearing, three pole AMB, hybrid control, Lyapunov function.

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Authors: J. Y. Jang, Y. W. Lee, C. N. Lin, C. H. Wang

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The reheating furnace is used to reheat the steel slabs before the hot-rolling process. The supported system includes the stationary/moving beams, and the skid buttons which block some thermal radiation transmitted to the bottom of the slabs. Therefore, it is important to analyze the steel slab temperature distribution during the heating period. A three-dimensional mathematical transient heat transfer model for the prediction of temperature distribution within the slab has been developed. The effects of different skid button height (H=60mm, 90mm, and 120mm) and different gap distance between two slabs (S=50mm, 75mm, and 100mm) on the slab skid mark formation and temperature profiles are investigated. Comparison with the in-situ experimental data from Steel Company in Taiwan shows that the present heat transfer model works well for the prediction of thermal behavior of the slab in the reheating furnace. It is found that the skid mark severity decreases with an increase in the skid button height. The effect of gap distance is important only for the slab edge planes, while it is insignificant for the slab central planes.

Keywords: 3-D, slab, transient heat conduction, reheating furnace, thermal radiation.

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Authors: G.Kavitha, V.Sankaranarayanan

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Grid computing provides a virtual framework for controlled sharing of resources across institutional boundaries. Recently, trust has been recognised as an important factor for selection of optimal resources in a grid. We introduce a new method that provides a quantitative trust value, based on the past interactions and present environment characteristics. This quantitative trust value is used to select a suitable resource for a job and eliminates run time failures arising from incompatible user-resource pairs. The proposed work will act as a tool to calculate the trust values of the various components of the grid and there by improves the success rate of the jobs submitted to the resource on the grid. The access to a resource not only depend on the identity and behaviour of the resource but also upon its context of transaction, time of transaction, connectivity bandwidth, availability of the resource and load on the resource. The quality of the recommender is also evaluated based on the accuracy of the feedback provided about a resource. The jobs are submitted for execution to the selected resource after finding the overall trust value of the resource. The overall trust value is computed with respect to the subjective and objective parameters.

Keywords: access control, feedback, grid computing, reputation, security, trust, trust parameter.

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Authors: S. Kulsri, M. Jaroensutasinee, K. Jaroensutasinee

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We developed a new method based on quasimolecular modeling to simulate the cavity flow in three cavity shapes: rectangular, half-circular and bucket beer in cgs units. Each quasi-molecule was a group of particles that interacted in a fashion entirely analogous to classical Newtonian molecular interactions. When a cavity flow was simulated, the instantaneous velocity vector fields were obtained by using an inverse distance weighted interpolation method. In all three cavity shapes, fluid motion was rotated counter-clockwise. The velocity vector fields of the three cavity shapes showed a primary vortex located near the upstream corners at time t ~ 0.500 s, t ~ 0.450 s and t ~ 0.350 s, respectively. The configurational kinetic energy of the cavities increased as time increased until the kinetic energy reached a maximum at time t ~ 0.02 s and, then, the kinetic energy decreased as time increased. The rectangular cavity system showed the lowest kinetic energy, while the half-circular cavity system showed the highest kinetic energy. The kinetic energy of rectangular, beer bucket and half-circular cavities fluctuated about stable average values 35.62 x 103, 38.04 x 103 and 40.80 x 103 ergs/particle, respectively. This indicated that the half-circular shapes were the most suitable shape for a shrimp pond because the water in shrimp pond flows best when we compared with rectangular and beer bucket shape.

Keywords: Quasi-molecular modelling, particle modelling, lid driven cavity flow.

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Authors: Elham Ahmadi, Roshaali Khaturia, Pardis Sahraei, Mohammad Niyayesh, Omid Fatahi Valilai

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Nowadays, Information Technology (IT) is changing the way traditional enterprise management concepts work. One of the most dominant IT achievements is the Blockchain Technology. This technology enables the distributed collaboration of stakeholders for their interactions while fulfilling the security and consensus rules among them. This paper has focused on the application of Blockchain technology to enhance one of traditional inventory management models. The Vendor Managed Inventory (VMI) has been considered one of the most efficient mechanisms for vendor inventory planning by the suppliers. While VMI has brought competitive advantages for many industries, however its centralized mechanism limits the collaboration of a pool of suppliers and vendors simultaneously. This paper has studied the recent research for VMI application in industries and also has investigated the applications of Blockchain technology for decentralized collaboration of stakeholders. Focusing on sustainability issue for total supply chain consisting suppliers and vendors, it has proposed a Blockchain based VMI conceptual model. The different capabilities of this model for enabling the collaboration of stakeholders while maintaining the competitive advantages and sustainability issues have been discussed.

Keywords: Vendor Managed Inventory, Blockchain Technology, supply chain planning, sustainability.

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Authors: Negar Banan, Mohd Talib Latif

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This study investigated the relationship between urban and rural ozone concentrations and quantified the extent to which ambient rural conditions and the concentrations of other pollutants can be used to predict urban ozone concentrations. The study describes the variations of ozone in weekday and weekends as well as the daily maximum recorded at selected monitoring stations. The results showed that Putrajaya station had the highest concentrations of O3 on weekend due the titration of NO during the weekday. Additionally, Jerantut had the lowest average concentration with a reading value high on Wednesdays. The comparisons of average and maximum concentrations of ozone for the three stations showed that the strongest significant correlation is recorded in Jerantut station with the value R2= 0.769. Ozone concentrations originating from a neighbouring urban site form a better predictor to the urban ozone concentrations than widespread rural ozone at some levels of temporal averaging. It is found that in urban and rural of Malaysian peninsular, the concentration of ozone depends on the concentration of NOx and seasonal meteorological factors. The HYSPLIT Model (the northeast monsoon) showed that the wind direction can also influence the concentration of ozone in the atmosphere in the studied areas.

Keywords: Ozone, Hysplit model, Weekend effect, Daily Average and Daily maximum, Malaysia

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Authors: K.Ting, K. T. Chen, Y. L. Su, C. J. Chang

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In medical therapy, laser has been widely used to conduct cosmetic, tumor and other treatments. During the process of laser irradiation, there may be thermal damage caused by excessive laser exposure. Thus, the establishment of a complete thermal analysis model is clinically helpful to physicians in reference data. In this study, porcine liver in place of tissue was subjected to laser irradiation to set up the experimental data considering the explored impact on surface thermal field and thermal damage region under different conditions of power, laser irradiation time, and distance between laser and porcine liver. In the experimental process, the surface temperature distribution of the porcine lever was measured by the infrared thermal imager. In the part of simulation, the bio heat transfer Pennes-s equation was solved by software SYSWELD applying in welding process. The double ellipsoid function as a laser source term is firstly considered in the prediction for surface thermal field and internal tissue damage. The simulation results are compared with the experimental data to validate the mathematical model established here in.

Keywords: laser infrared thermal imager, bio-heat transfer, double ellipsoid function.

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Authors: Nemir Al-Azzawi, Harsa A. Mat Sakim, Wan Ahmed K. Wan Abdullah, Yasmin Mohd Yacob

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Feature-based registration is an effective technique for clinical use, because it can greatly reduce computational costs. However, this technique, which estimates the transformation by using feature points extracted from two images, may cause misalignments. To handle with this limitation, we propose to extract the salient edges and extracted control points (CP) of medical images by using efficiency of multiresolution representation of data nonsubsampled contourlet transform (NSCT) that finds the best feature points. The MR images were first decomposed using the NSCT, and then Edge and CP were extracted from bandpass directional subband of NSCT coefficients and some proposed rules. After edge and CP extraction, mutual information was adopted for the registration of feature points and translation parameters are calculated by using particle swarm optimization (PSO). The experimental results showed that the proposed method produces totally accurate performance for registration medical CT-MR images.

Keywords: Feature-based registration, mutual information, nonsubsampled contourlet transform, particle swarm optimization.

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Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: Land cover, tropospheric ozone, WRF-Chem, air quality assessment.

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Authors: Mei-Se Chien, Chien-Chiang Lee, Sin-Jie Cai

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The main purpose of this paper is to investigate thelong-run equilibrium and short-run dynamics of international housing prices when macroeconomic variables change. We apply the Pedroni’s, panel cointegration, using the unbalanced panel data analysis of 33 countries over the period from 1980Q1 to 2013Q1, to examine the relationships among house prices and macroeconomic variables. Our empirical results of panel data cointegration tests support the existence of a cointegration among these macroeconomic variables and house prices. Besides, the empirical results of panel DOLS further present that a 1% increase in economic activity, long-term interest rates, and construction costs cause house prices to respectively change 2.16%, -0.04%, and 0.22% in the long run.Furthermore, the increasing economic activity and the construction cost would cause strongerimpacts on the house prices for lower income countries than higher income countries.The results lead to the conclusion that policy of house prices growth can be regarded as economic growth for lower income countries. Finally, in America region, the coefficient of economic activity is the highest, which displays that increasing economic activity causes a faster rise in house prices there than in other regions. There are some special cases whereby the coefficients of interest rates are significantly positive in America and Asia regions.

Keywords: House prices, Macroeconomic Variables, Panel cointegration, Dynamic OLS.

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Authors: M. Sitoe, O. Zacarias

Abstract:

University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: Evasion and retention, cross validation, bagging, stacking.

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Authors: M. Kosandi, V. Susanti, N. I. Subono, E. Kartini

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This paper discusses the risk of glorification trap in combating human trafficking, as it is shown in the case of Indonesia. Based on a research on Indonesian combat against trafficking in 2017-2018, this paper shows the tendency of misinterpretation and misapplication of the Indonesian anti-trafficking law into misusing the law for glorification, to create an image of certain extent of achievement in combating human trafficking. The objective of this paper is to explain the persistent occurrence of human trafficking crimes despite the significant progress of anti-trafficking efforts of Indonesian government. The research was conducted in 2017-2018 by qualitative approach through observation, depth interviews, discourse analysis, and document study, applying the three-dimensional model for analyzing human trafficking in the source country. This paper argues that the drive for glorification of achievement in the combat against trafficking has trapped Indonesian government in the loop of misinterpretation, misapplication, and misuse of the anti-trafficking law. In return, the so-called crime against humanity remains high and tends to increase in Indonesia.

Keywords: Human trafficking, anti-trafficking policy, transnational crime, source country, glorification trap.

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: Distillation, machine learning, neural networks, quantization.

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Authors: K. Benyounes, A. Benmounah

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Cement-based grouts has been used successfully to repair cracks in many concrete structures such as bridges, tunnels, buildings and to consolidate soils or rock foundations. In the present study the rheological characterization of cement grout with water/binder ratio (W/B) is fixed at 0.5. The effect of the replacement of cement by bentonite (2 to 10% wt) in presence of superplasticizer (0.5% wt) was investigated. Several rheological tests were carried out by using controlled-stress rheometer equipped with vane geometry in temperature of 20°C. To highlight the influence of bentonite and superplasticizer on the rheological behavior of grout cement, various flow tests in a range of shear rate from 0 to 200 s-1 were observed. Cement grout showed a non-Newtonian viscosity behavior at all concentrations of bentonite. Three parameter model Herschel- Bulkley was chosen for fitting of experimental data. Based on the values of correlation coefficients of the estimated parameters, The Herschel-Bulkley law model well described the rheological behavior of the grouts. Test results showed that the dosage of bentonite increases the viscosity and yield stress of the system and introduces more thixotropy. While the addition of both bentonite and superplasticizer with cement grout improve significantly the fluidity and reduced the yield stress due to the action of dispersion of SP.

Keywords: Cement grout, bentonite, superplasticizer, viscosity, yield stress.

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Authors: Alhaji M. H. Conteh, Xiangbin Yan, Alfred V Gborie

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Rice, which is the staple food in Sierra Leone, is consumed on a daily basis. It is the most imperative food crop extensively grown by farmers across all ecologies in the country. Though much attention is now given to rice grain production through the small holder commercialization programme (SHCP), however, no attention has been given in investigating the limitations faced by rice producers. This paper will contribute to attempts to overcome the development challenges caused by food insecurity. The objective of this paper is thus, to analysis the relationship between rice production and the domestic retail price of rice. The study employed a log linear model in which, the quantity of rice produced is the dependent variable, quantity of rice imported, price of imported rice and price of domestic rice as explanatory variables. Findings showed that, locally produced rice is even more expensive than the imported rice per ton, and almost all the inhabitants in the capital city which hosts about 65% of the entire population of the country favor imported rice, as it is free from stones with other impurities. On the other hand, to control price and simultaneously increase rice production, the government should purchase the rice from the farmers and then sell to private retailers.

Keywords: Domestic price of rice, Econometric model, Rice production, Sierra Leone.

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Authors: F. Djaafar, B. Hadri, G. Bachir

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This paper presents the design parameters for a thin film 3J InGaP/GaAs/Ge solar cell with a simulated maximum efficiency of 32.11% using Tcad Silvaco. Design parameters include the doping concentration, molar fraction, layers’ thickness and tunnel junction characteristics. An initial dual junction InGaP/GaAs model of a previous published heterojunction cell was simulated in Tcad Silvaco to accurately predict solar cell performance. To improve the solar cell’s performance, we have fixed meshing, material properties, models and numerical methods. However, thickness and layer doping concentration were taken as variables. We, first simulate the InGaP\GaAs dual junction cell by changing the doping concentrations and thicknesses which showed an increase in efficiency. Next, a triple junction InGaP/GaAs/Ge cell was modeled by adding a Ge layer to the previous dual junction InGaP/GaAs model with an InGaP /GaAs tunnel junction.

Keywords: Heterojunction, modeling, simulation, thin film, Tcad Silvaco.

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Authors: Dong Wook Lee

Abstract:

This paper presents a method to analyze the stiffness of the expansion joint with structural support using a hybrid method combining computational and analytical methods. Many expansion joints found in tubes and ducts of mechanical structures are designed to absorb thermal expansion mismatch between their structural members and deal with misalignments introduced from the assembly/manufacturing processes. One of the important design perspectives is the system’s vibrational characteristics. We calculate the stiffness as a characterization parameter for structural joint systems using a combined Finite Element Analysis (FEA) and an analytical method. We apply the methods to two sample applications: external configurations of aircraft engines and nuclear power plant structures.

Keywords: Expansion joint, expansion joint stiffness, Finite Element Analysis, FEA, nuclear power plants, aircraft engine external configurations.

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Authors: Ju-Hong Lee, Chong-Jia Ciou, Yuan-Hau Yang

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This paper deals with the problem of two-dimensional (2-D) recursive doubly complementary (DC) digital filter design. We present a structure of 2-D recursive DC filters by using 2-D symmetric half-plane (SHP) recursive digital all-pass lattice filters (DALFs). The novelty of using 2-D SHP recursive DALFs to construct a 2-D recursive DC digital lattice filter is that the resulting 2-D SHP recursive DC digital lattice filter provides better performance than the existing 2-D SHP recursive DC digital filter. Moreover, the proposed structure possesses a favorable 2-D DC half-band (DC-HB) property that allows about half of the 2-D SHP recursive DALF’s coefficients to be zero. This leads to considerable savings in computational burden for implementation. To ensure the stability of a designed 2-D SHP recursive DC digital lattice filter, some necessary constraints on the phase of the 2-D SHP recursive DALF during the design process are presented. Design of a 2-D diamond-shape decimation/interpolation filter is presented for illustration and comparison.

Keywords: All-pass digital filter, doubly complementary, lattice structure, symmetric half-plane digital filter, sampling rate conversion.

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Authors: Ghada A. El Khayat

Abstract:

This paper argues that a product development exercise involves in addition to the conventional stages, several decisions regarding other aspects. These aspects should be addressed simultaneously in order to develop a product that responds to the customer needs and that helps realize objectives of the stakeholders in terms of profitability, market share and the like. We present a framework that encompasses these different development dimensions. The framework shows that a product development methodology such as the Quality Function Deployment (QFD) is the basic tool which allows definition of the target specifications of a new product. Creativity is the first dimension that enables the development exercise to live and end successfully. A number of group processes need to be followed by the development team in order to ensure enough creativity and innovation. Secondly, packaging is considered to be an important extension of the product. Branding strategies, quality and standardization requirements, identification technologies, design technologies, production technologies and costing and pricing are also integral parts to the development exercise. These dimensions constitute the proposed framework. The paper also presents a mathematical model used to calculate the design targets based on the target costing principle. The framework is used to study a case of a new product development in the telecommunications services sector.

Keywords: Product Development Framework, Quality FunctionDeployment, Mathematical Models, Telecommunications.

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Authors: M. Sadeghi, A.H. Jafari, S.M.P. Firoozabadi

Abstract:

Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.

Keywords: Chaos, Deep Brain Stimulation, Parkinson's Disease, Stimulation Parameters, tremor.

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Authors: Emari Hossien

Abstract:

This study examined the underlying dimensions of brand equity in the chocolate industry. For this purpose, researchers developed a model to identify which factors are influential in building brand equity. The second purpose was to assess brand loyalty and brand images mediating effect between brand attitude, brand personality, brand association with brand equity. The study employed structural equation modeling to investigate the causal relationships between the dimensions of brand equity and brand equity itself. It specifically measured the way in which consumers’ perceptions of the dimensions of brand equity affected the overall brand equity evaluations. Data were collected from a sample of consumers of chocolate industry in Iran. The results of this empirical study indicate that brand loyalty and brand image are important components of brand equity in this industry. Moreover, the role of brand loyalty and brand image as mediating factors in the intention of brand equity are supported. The principal contribution of the present research is that it provides empirical evidence of the multidimensionality of consumer based brand equity, supporting Aaker´s and Keller´s conceptualization of brand equity. The present research also enriched brand equity building by incorporating the brand personality and brand image, as recommended by previous researchers. Moreover, creating the brand equity index in chocolate industry of Iran particularly is novel.

Keywords: brand equity, brand personality, structural equationmodeling, Iran.

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Authors: G. Tanapornraweekit, W. Kulsirikasem

Abstract:

This paper presents the simulation of fragmentation warhead using a hydrocode, Autodyn. The goal of this research is to determine the lethal range of such a warhead. This study investigates the lethal range of warheads with and without steel balls as preformed fragments. The results from the FE simulation, i.e. initial velocities and ejected spray angles of fragments, are further processed using an analytical approach so as to determine a fragment hit density and probability of kill of a modelled warhead. In order to simulate a plenty of preformed fragments inside a warhead, the model requires expensive computation resources. Therefore, this study attempts to model the problem in an alternative approach by considering an equivalent mass of preformed fragments to the mass of warhead casing. This approach yields approximately 7% and 20% difference of fragment velocities from the analytical results for one and two layers of preformed fragments, respectively. The lethal ranges of the simulated warheads are 42.6 m and 56.5 m for warheads with one and two layers of preformed fragments, respectively, compared to 13.85 m for a warhead without preformed fragment. These lethal ranges are based on the requirement of fragment hit density. The lethal ranges which are based on the probability of kill are 27.5 m, 61 m and 70 m for warheads with no preformed fragment, one and two layers of preformed fragments, respectively.

Keywords: Lethal Range, Natural Fragment, Preformed Fragment, Warhead.

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

Abstract:

Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, stereotypical motor movements, repetitive gesture, kinect, artificial neural network.

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