Search results for: fuzzy inference model

Authors: Arafa A. Alholaisi, Jamal H. Madani, M. A. Alvi

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The radial form of nuclear matter distribution, charge and the shape of nuclei are essential properties of nuclei, and hence, are of great attention for several areas of research in nuclear physics. More than last three decades have witnessed a range of experimental means employing leptonic probes (such as muons, electrons etc.) for exploring nuclear charge distributions, whereas the hadronic probes (for example alpha particles, protons, etc.) have been used to investigate the nuclear matter distributions. In this paper, p-^9,11Li elastic scattering differential cross sections in the energy range  to  MeV have been studied by means of Coulomb modified Glauber scattering formalism. By applying the semi-phenomenological Bhagwat-Gambhir-Patil [BGP] nuclear density for loosely bound neutron rich ¹¹Li nucleus, the estimated matter radius is found to be 3.446 fm which is quite large as compared to so known experimental value 3.12 fm. The results of microscopic optical model based calculation by applying Bethe-Brueckner–Hartree–Fock formalism (BHF) have also been compared. It should be noted that in most of phenomenological density model used to reproduce the p-¹¹Li differential elastic scattering cross sections data, the calculated matter radius lies between 2.964 and 3.55 fm. The calculated results with phenomenological BGP model density and with nucleon density calculated in the relativistic mean-field (RMF) reproduces p-⁹Li and p-¹¹Li experimental data quite nicely as compared to Gaussian- Gaussian or Gaussian-Oscillator densities at all energies under consideration. In the approach described here, no free/adjustable parameter has been employed to reproduce the elastic scattering data as against the well-known optical model based studies that involve at least four to six adjustable parameters to match the experimental data. Calculated reaction cross sections σ_R for p-¹¹Li at these energies are quite large as compared to estimated values reported by earlier works though so far no experimental studies have been performed to measure it.

Keywords: Bhagwat-Gambhir-Patil density, Coulomb modified Glauber model, halo nucleus, optical limit approximation

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Authors: Jihane Saad, Thomas Lendormi, Caroline Le Marechal, Anne-marie Pourcher, Céline Druilhe, Jean-louis Lanoiselle

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Agricultural anaerobic digestion consists in the conversion of animal slurry and manure into biogas and digestate. They need, however, to be treated at 70 ºC during 60 min before anaerobic digestion according to the European regulation (EC n°1069/2009 & EU n°142/2011). The impact of such heat treatment on the outcome of bacteria has been poorly studied up to now. Moreover, a recent study¹ has shown that enterococci and clostridia are still detected despite the application of such thermal treatment, questioning the relevance of this approach for the hygienisation of digestate. The aim of this study is to establish the heat inactivation kinetics of two species of enterococci (Enterococcus faecalis and Enterococcus faecium) and two species of clostridia (Clostridioides difficile and Clostridium novyi as a non-toxic model for Clostridium botulinum of group III). A pure culture of each strain was prepared in a specific sterile medium at concentration of 10⁴ – 10⁷ MPN / mL (Most Probable number), depending on the bacterial species. Bacterial suspensions were then filled in sterilized capillary tubes and placed in a water or oil bath at desired temperature for a specific period of time. Each bacterial suspension was enumerated using a MPN approach, and tests were repeated three times for each temperature/time couple. The inactivation kinetics of the four indicator bacteria is described using the Weibull model and the classical Bigelow model of first-order kinetics. The Weibull model takes biological variation, with respect to thermal inactivation, into account and is basically a statistical model of distribution of inactivation times as the classical first-order approach is a special case of the Weibull model. The heat treatment at 70 ºC / 60 min contributes to a reduction greater than 5 log10 for E. faecium and E. faecalis. However, it results only in a reduction of about 0.7 log10 for C. difficile and an increase of 0.5 log10 for C. novyi. Application of treatments at higher temperatures is required to reach a reduction greater or equal to 3 log10 for C. novyi (such as 30 min / 100 ºC, 13 min / 105 ºC, 3 min / 110 ºC, and 1 min / 115 ºC), raising the question of the relevance of the application of heat treatment at 70 ºC / 60 min for these spore-forming bacteria. To conclude, the heat treatment (70 ºC / 60 min) defined by the European regulation is sufficient to inactivate non-sporulating bacteria. Higher temperatures (> 100 ºC) are required as far as spore-forming bacteria concerns to reach a 3 log10 reduction (sporicidal activity).

Keywords: heat treatment, enterococci, clostridia, inactivation kinetics

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Authors: Sushil Kumar, M. Dakshina Murty

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Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

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Authors: Benjamin A. Ha, Marco Morselli, Xinhui Paige Zhang, Elizabeth A. C. Heath-Heckman, Jonathan B. Puritz, David K. Jacobs

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Next-generation sequencing has enhanced the ability to acquire massive amounts of sequence data to address classic population genetic questions for non-model organisms. Targeted approaches allow for cost effective or more precise analyses of relevant sequences; although, many such techniques require a known genome and it can be costly to purchase probes from a company. This is challenging for non-model organisms with no published genome and can be expensive for large population genetic studies. Expressed exome capture sequencing (EecSeq) synthesizes probes in the lab from expressed mRNA, which is used to capture and sequence the coding regions of genomic DNA from a pooled suite of samples. A normalization step produces probes to recover transcripts from a wide range of expression levels. This approach offers low cost recovery of a broad range of genes in the genome. This research project expands on EecSeq to investigate if mRNA from one taxon may be used to capture relevant sequences from a series of increasingly less closely related taxa. For this purpose, we propose to use the endangered Northern Tidewater goby, Eucyclogobius newberryi, a non-model organism that inhabits California coastal lagoons. mRNA will be extracted from E. newberryi to create probes and capture exomes from eight other taxa, including the more at-risk Southern Tidewater goby, E. kristinae, and more divergent species. Captured exomes will be sequenced, analyzed bioinformatically and phylogenetically, then compared to previously generated phylogenies across this group of gobies. This will provide an assessment of the utility of the technique in cross-species studies and for analyzing low genetic variation within species as is the case for E. kristinae. This method has potential applications to provide economical ways to expand population genetic and evolutionary biology studies for non-model organisms.

Keywords: coastal lagoons, endangered species, non-model organism, target capture method

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Authors: Mohammad Safaeipour, Yousef Amer

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This study directs its focus on developing a conceptual model to offer a systematic and integrated method to weigh the related measures and evaluate a competence of hospitals and rank of the selected hospitals that involve and consider the stakeholders’ key performance indicators (KPI’s). The Analytical Hierarchy Process (AHP) approach will use to weigh the dimensions and related sub- components. The weights and performance scores will combine by using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and rank the selected hospitals. The results of this study provide interesting insight into the necessity of process improvement implementation in which hospital that received the lowest ranking score.

Keywords: performance measurement system, PMS, hospitals, AHP, TOPSIS

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Authors: Juliana A. Knocikova, Yann Bouret, Médéric Argentina, Laurent Counillon

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Cell volume, together with membrane potential and intracellular hydrogen ion concentration, is an essential biophysical parameter for normal cellular activity. Cell volumes can be altered by osmotically active compounds and extracellular tonicity. In this study, a simple mathematical model of osmotically induced cell swelling and shrinking is presented. Emphasis is given to water diffusion across the membrane. The mathematical description of the cellular behavior consists in a system of coupled ordinary differential equations. We compare experimental data of cell volume alterations driven by differences in osmotic pressure with mathematical simulations under hypotonic and hypertonic conditions. Implications for a future model are also discussed.

Keywords: eukaryotic cell, mathematical modeling, osmosis, volume alterations

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

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Authors: Ramiz M. Shubbar, Dong In Lee, Hatem A. Gzar, Arthur S. Rood

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Air pollution is one of the biggest environmental problems in Baghdad, Iraq. The Daura refinery located nearest the center of Baghdad, represents the largest industrial area, which transmits enormous amounts of pollutants, therefore study the gaseous pollutants and particulate matter are very important to the environment and the health of the workers in refinery and the people whom leaving in areas around the refinery. Actually, some studies investigated the studied area before, but it depended on the basic Gaussian equation in a simple computer programs, however, that kind of work at that time is very useful and important, but during the last two decades new largest production units were added to the Daura refinery such as, PU_3 (Power unit_3 (Boiler 11&12)), CDU_1 (Crude Distillation unit_70000 barrel_1), and CDU_2 (Crude Distillation unit_70000 barrel_2). Therefore, it is necessary to use new advanced model to study air pollution at the region for the new current years, and calculation the monthly emission rate of pollutants through actual amounts of fuel which consumed in production unit, this may be lead to accurate concentration values of pollutants and the behavior of dispersion or transport in study area. In this study to the best of author’s knowledge CALPUFF model was used and examined for first time in Iraq. CALPUFF is an advanced non-steady-state meteorological and air quality modeling system, was applied to investigate the pollutants concentration of SO2, NO2, CO, and PM1-10μm, at areas adjacent to Daura refinery which located in the center of Baghdad in Iraq. The CALPUFF modeling system includes three main components: CALMET is a diagnostic 3-dimensional meteorological model, CALPUFF (an air quality dispersion model), CALPOST is a post processing package, and an extensive set of preprocessing programs produced to interface the model to standard routinely available meteorological and geophysical datasets. The targets of this work are modeling and simulation the four pollutants (SO2, NO2, CO, and PM1-10μm) which emitted from Daura refinery within one year. Emission rates of these pollutants were calculated for twelve units includes thirty plants, and 35 stacks by using monthly average of the fuel amount consumption at this production units. Assess the performance of CALPUFF model in this study and detect if it is appropriate and get out predictions of good accuracy compared with available pollutants observation. CALPUFF model was investigated at three stability classes (stable, neutral, and unstable) to indicate the dispersion of the pollutants within deferent meteorological conditions. The simulation of the CALPUFF model showed the deferent kind of dispersion of these pollutants in this region depends on the stability conditions and the environment of the study area, monthly, and annual averages of pollutants were applied to view the dispersion of pollutants in the contour maps. High values of pollutants were noticed in this area, therefore this study recommends to more investigate and analyze of the pollutants, reducing the emission rate of pollutants by using modern techniques and natural gas, increasing the stack height of units, and increasing the exit gas velocity from stacks.

Keywords: CALPUFF, daura refinery, Iraq, pollutants

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Authors: Firman Riyudha, Endrik Mifta Shaiful

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The spread of drug users is one kind of behavioral epidemiology that becomes a threat to every country in the world. This problem caused various crisis simultaneously, including financial or economic crisis, social, health, until human crisis. Most drug users are teenagers at school age. A new deterministic model would be constructed to determine the dynamics of the spread of drug users by considering level of education in a susceptible population. Based on the analytical model, two equilibria points were obtained; there were E₀ (zero user) and E₁ (endemic equilibrium). Existence of equilibrium and local stability of equilibria depended on the Basic Reproduction Ratio (R₀). This parameter was defined as the expected rate of secondary prevalence and primary prevalence in virgin population along spreading primary prevalence. The zero-victim equilibrium would be locally asymptotically stable if R₀ < 1 while if R₀ > 1 the endemic equilibrium would be locally asymptotically stable. The result showed that R₀ was proportional to the rate of interaction of each susceptible population based on educational level with the users' population. It is concluded that there was a need to be given a control in interaction, so that drug users population could be minimized. Numerical simulations were also provided to support analytical results.

Keywords: drugs users, level education, mathematical model, stability

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: Nadhia Maharany Siara, Muammal, Ilham Nurhakim, Rofifah Yusadi, M. Adie Putra Tanggara, I. Nyoman Suluh Wijaya

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Urbanization in urban areas has impact to the demand of land use for housing, and it began to occur development in the high-density area called Kampung Kota. Kampung Kota grows and develops without planning or organically. The existence of Kampung Kota, becoming identity of the city development in Indonesia, gives self-identity to the city planning in Indonesia, but the existence of Kampung Kota in the development of the city in Indonesia is often considered as a source of environment, health, and social problems. This cause negative perception about the sustainability of Kampung Kota. This research aims to identify morphology and sustainability level of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City. So far, there have not been many studies that define sustainability of Kampung Kota especially from the perspective of Kampung Kota morphology as a part of urban housing areas. This research took place in in Polehan Sub-District, Blimbing District, Malang City which is one of the oldest Kampung Kota in Malang City. Identification of the sustainability level in this research is done by defining the morphology of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City with a descriptive approach to the observation case (Kampung Kota Polehan Sub-District). After that, definition of sustainability level is defined by quantifying the spatial structure by using the criteria from the new urbanism model which consist of buildings and populations density, compactness, diversity and mix land uses and sustainable transportation. In this case, the use of new urbanism model approach is very appropriate. New Urbanism is a design-driven strategy that is based on traditional forms to minimize urban sprawl in the suburbs. The result obtained from this study is the hometown of the level of sustainability in Polehan Sub-District, Blimbing District, Malang City of 3.2 and can be considered to have a good sustainability.

Keywords: Kampung Kota, new urbanism model, sustainability, urban morphology

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: Shigeyuki Haruyama, Ken Kaminishi, Junji Kaneko, Tadayuki Kyoutani, Siti Ruhana Omar, Oke Oktavianty

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This study is used as a definition method to the value and function in manufacturing sector. In concurrence of discussion about present condition of modeling method, until now definition of 1D-CAE is ambiguity and not conceptual. Across all the physics fields, those methods are defined with the formulation of differential algebraic equation which only applied time derivation and simulation. At the same time, we propose semi-acausal modeling concept and differential algebraic equation method as a newly modeling method which the efficiency has been verified through the comparison of numerical analysis result between the semi-acausal modeling calculation and FEM theory calculation.

Keywords: system model, physical models, empirical models, conservation law, differential algebraic equation, object-oriented

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Authors: Xueli Tang, Lei Zhao, Shenghao Zhu

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This study investigates the income distribution in a dynamic assignment model with human capital accumulation and endogenous firm size. Positive assortative matching between bosses and workers arises in labor market equilibrium. We solve the stationary equilibrium of two endogenous functions, the matching rule and human capital distribution; we also decompose two channels affecting the equilibrium matching rule, firm-size effect, and endogenous distribution effect. Finally, we perform a perturbation analysis of the equilibrium matching rule and the wage function and examine the effects of technology improvement on income inequality.

Keywords: income distribution, matching, human-capital accumulation, firm size, perturbation method

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Authors: M. N. Nwodo, Y. P. Cheng, N. H. Minh

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In the process of recovering oil in weak sandstone formations, the strength of sandstones around the wellbore is weakened due to the increase of effective stress/load from the completion activities around the cavity. The weakened and de-bonded sandstone may be eroded away by the produced fluid, which is termed sand production. It is one of the major trending subjects in the petroleum industry because of its significant negative impacts, as well as some observed positive impacts. For efficient sand management therefore, there has been need for a reliable study tool to understand the mechanism of sanding. One method of studying sand production is the use of the widely recognized Discrete Element Method (DEM), Particle Flow Code (PFC3D) which represents sands as granular individual elements bonded together at contact points. However, there is limited knowledge of the particle-scale behavior of the weak sandstone, and the parameters that affect sanding. This paper aims to investigate the reliability of using PFC3D and a simple Darcy flow in understanding the sand production behavior of a weak sandstone. An isotropic tri-axial test on a weak oil sandstone sample was first simulated at a confining stress of 1MPa to calibrate and validate the parallel bond models of PFC3D using a 10m height and 10m diameter solid cylindrical model. The effect of the confining stress on the number of bonds failure was studied using this cylindrical model. With the calibrated data and sample material properties obtained from the tri-axial test, simulations without and with fluid flow were carried out to check on the effect of Darcy flow on bonds failure using the same model geometry. The fluid flow network comprised of every four particles connected with tetrahedral flow pipes with a central pore or flow domain. Parametric studies included the effects of confining stress, and fluid pressure; as well as validating flow rate – permeability relationship to verify Darcy’s fluid flow law. The effect of model size scaling on sanding was also investigated using 4m height, 2m diameter model. The parallel bond model successfully calibrated the sample’s strength of 4.4MPa, showing a sharp peak strength before strain-softening, similar to the behavior of real cemented sandstones. There seems to be an exponential increasing relationship for the bigger model, but a curvilinear shape for the smaller model. The presence of the Darcy flow induced tensile forces and increased the number of broken bonds. For the parametric studies, flow rate has a linear relationship with permeability at constant pressure head. The higher the fluid flow pressure, the higher the number of broken bonds/sanding. The DEM PFC3D is a promising tool to studying the micromechanical behavior of cemented sandstones.

Keywords: discrete element method, fluid flow, parametric study, sand production/bonds failure

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Authors: Gozel Judakova, Markus Bause

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We present and analyze reliable numerical techniques for simulating complex flow and transport phenomena related to natural gas transportation in pipelines. Such kind of problems are of high interest in the field of petroleum and environmental engineering. Modeling and understanding natural gas flow and transformation processes during transportation is important for the sake of physical realism and the design and operation of pipeline systems. In our approach a two fluid flow model based on a system of coupled hyperbolic conservation laws is considered for describing natural gas flow undergoing hydratization. The accurate numerical approximation of two-phase gas flow remains subject of strong interest in the scientific community. Such hyperbolic problems are characterized by solutions with steep gradients or discontinuities, and their approximation by standard finite element techniques typically gives rise to spurious oscillations and numerical artefacts. Recently, stabilized and discontinuous Galerkin finite element techniques have attracted researchers’ interest. They are highly adapted to the hyperbolic nature of our two-phase flow model. In the presentation a streamline upwind Petrov-Galerkin approach and a discontinuous Galerkin finite element method for the numerical approximation of our flow model of two coupled systems of Euler equations are presented. Then the efficiency and reliability of stabilized continuous and discontinous finite element methods for the approximation is carefully analyzed and the potential of the either classes of numerical schemes is investigated. In particular, standard benchmark problems of two-phase flow like the shock tube problem are used for the comparative numerical study.

Keywords: discontinuous Galerkin method, Euler system, inviscid two-fluid model, streamline upwind Petrov-Galerkin method, twophase flow

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Authors: Matza Gusto Andika, Malinda Sabrina, Syarie Fatunnisa

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Aerodynamic and aeroelastics studies on the hanger bridge profile are important to analyze the aerodynamic phenomenon and Aeroelastics stability of hanger. Wind tunnel tests were conducted on a model of H-beam profile from hanger bridge. The purpose of this study is to investigate steady aerodynamic characteristics such as lift coefficient (Cl), drag coefficient (Cd), and moment coefficient (Cm) under the different angle of attack for preliminary prediction of aeroelastics stability problems. After investigation the steady aerodynamics characteristics from the model, dynamic testing is also conducted in wind tunnel to know the aeroelastics phenomenon which occurs at the H-beam hanger bridge profile. The studies show that the torsional vortex induced vibration occur when the wind speed is 7.32 m/s until 9.19 m/s with maximum amplitude occur when the wind speed is 8.41 m/s. The result of wind tunnel testing is matching to hanger vibration where occur in the field, so wind tunnel studies has successful to model the problem. In order that the H-beam profile is not good enough for the hanger bridge and need to be modified to minimize the Aeroelastics problem. The modification can be done with structure dynamics modification or aerodynamics modification.

Keywords: aerodynamics, aeroelastic, hanger bridge, h-beam profile, vortex induced vibration, wind tunnel

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Ahmed Fradi

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In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Adji Achmad Rinaldo Fernandes

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Regression analysis is a statistical method that is able to describe and predict causal relationships between individuals. Not all relationships have a known curve shape; often, there are relationship patterns that cannot be known in the shape of the curve; besides that, a cause can have an impact on more than one effect, so that between effects can also have a close relationship in it. Regression analysis that can be done to find out the relationship can be brought closer to the semiparametric regression of truncated spline biresponse. The purpose of this study is to examine the function estimator and determine the best model of truncated spline biresponse semiparametric regression. The results of the secondary data study showed that the best model with the highest order of quadratic and a maximum of two knots with a Goodness of fit value in the form of Adjusted R2 of 88.5%.

Keywords: biresponse, farmer attachment, farmer loyalty, truncated spline

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: N. Sopipan

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In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, exponential smoothing, Holt-Winter model

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Authors: Tusar Kanti Dash, Ganapati Panda

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The evaluation of speech quality and intelligence is critical to the overall effectiveness of the Speech Enhancement Algorithms. Several intrusive and non-intrusive measures are employed to calculate these parameters. Non-Intrusive Evaluation is most challenging as, very often, the reference clean speech data is not available. In this paper, a novel non-intrusive speech evaluation measure is proposed using audio features derived from the Stockwell transform. These features are used with the Light Gradient Boosting Machine for the effective prediction of speech quality and intelligibility. The proposed model is analyzed using noisy and reverberant speech from four databases, and the results are compared with the standard Intrusive Evaluation Measures. It is observed from the comparative analysis that the proposed model is performing better than the standard Non-Intrusive models.

Keywords: non-Intrusive speech evaluation, S-transform, light GBM, speech quality, and intelligibility

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Authors: Farhan Beg

Abstract:

A space vector based pulse width modulation control technique for the three-phase PWM converter is proposed in this paper. The proposed control scheme is based on a synchronous reference frame model. High performance and efficiency is obtained with regards to the DC bus voltage and the power factor considerations of the PWM rectifier thus leading to low losses. MATLAB/SIMULINK are used as a platform for the simulations and a SIMULINK model is presented in the paper. The results show that the proposed model demonstrates better performance and properties compared to the traditional SPWM method and the method improves the dynamic performance of the closed loop drastically. For the space vector based pulse width modulation, sine signal is the reference waveform and triangle waveform is the carrier waveform. When the value of sine signal is larger than triangle signal, the pulse will start producing to high; and then when the triangular signals higher than sine signal, the pulse will come to low. SPWM output will change by changing the value of the modulation index and frequency used in this system to produce more pulse width. When more pulse width is produced, the output voltage will have lower harmonics contents and the resolution will increase.

Keywords: power factor, SVPWM, PWM rectifier, SPWM

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Authors: Huixin Wei, Shibin Wang, Linan Li, Lei Zhou, Xinhao Tu

Abstract:

Facial skin is a biomedical material with complex mechanical properties of anisotropy, viscoelasticity, and hyperelasticity. The mechanical properties of facial skin are crucial for a number of applications including facial plastic surgery, animation, dermatology, cosmetic industry, and impact biomechanics. Skin is a complex multi-layered material which can be broadly divided into three main layers, the epidermis, the dermis, and the hypodermis. Collagen fibers account for 75% of the dry weight of dermal tissue, and it is these fibers which are responsible for the mechanical properties of skin. Many research on the anisotropic mechanical properties are mainly concentrated on in vitro, but there is a great difference between in vivo and in vitro for mechanical properties of the skin. In this study, we presented a method to measure the mechanical properties of facial skin in vivo. Digital image correlation (DIC) and indentation tests were used to obtain the experiment data, including the deformation of facial surface and indentation force-displacement curve. Then, the experiment was simulated using a finite element (FE) model. Application of Computed Tomography (CT) and reconstruction techniques obtained the real tissue geometry. A three-dimensional FE model of facial skin, including a bi-layer system, was obtained. As the epidermis is relatively thin, the epidermis and dermis were regarded as one layer and below it was hypodermis in this study. The upper layer was modeled as a Gasser-Ogden-Holzapfel (GOH) model to describe hyperelastic and anisotropic behaviors of the dermis. The under layer was modeled as a linear elastic model. In conclusion, the material properties of two-layer were determined by minimizing the error between the FE data and experimental data.

Keywords: facial skin, indentation test, finite element, digital image correlation, computed tomography

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Authors: Estela Macedo Alves

Abstract:

This paper is an overview on public policy analysis focused on the study of Brazilian public policy making process. The methodology is based on the review of some theories on the subject, linking them to Brazilian reality. The study presents basic policy analysis concepts, such as policy, polity and politics. It is emphasized John Kingdon's Multiple Stream Model, because of its clarifying aspects concerning public policies formulation process in democratic countries. In this path it was possible to establish interpretations on environmental public policies in Brazil and understand its methods, instead of presenting only a case study. At the end, it is possible to connect theory with Brazilian reality, identifying negative and positive points of its political processes and structure.

Keywords: Brazilian policies, environmental public policy, multiple stream model, public policy analysis

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Authors: Oday Al-Mamoori, J. Enrique Martinez-Rueda

Abstract:

'C' shape yielding devices (C-devices) are effective tools for introducing supplemental sources of energy dissipation by hysteresis. Studies have shown that C-devices made of mild steel can be successfully applied as integral parts of seismic retrofitting schemes. However, explicit modelling of these devices can become cumbersome, expensive and time consuming. The device under study in this article has been previously used in non-invasive dissipative bracing for seismic retrofitting. The device is cut from a mild steel plate and has an overall shape that resembles that of a rectangular portal frame with circular interior corner transitions to avoid stress concentration and to control the extension of the dissipative region of the device. A number of inelastic finite element (FE) analyses using either inelastic 2D plane stress elements or inelastic fibre frame elements are reported and used to calibrate a 1D equivalent inelastic spring model that effectively reproduces the cyclic response of the device. The more elaborate FE model accounts for the frictional forces developed between the steel plate and the bolts used to connect the C-device to structural members. FE results also allow the visualization of the inelastic regions of the device where energy dissipation is expected to occur. FE analysis results are in a good agreement with experimental observations.

Keywords: C-device, equivalent nonlinear spring, FE analyses, reversed cyclic tests

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Authors: Safak Isik, Ozalp Vayvay

Abstract:

Strategic partnerships with suppliers play a vital role for the long-term value-based supply chain. This strategic collaboration keeps still being one of the top priority of many business organizations in order to create more additional value; benefiting mainly from supplier’s specialization, capacity and innovative power, securing supply and better managing costs and quality. However, many organizations encounter difficulties in initiating, developing and managing those partnerships and many attempts result in failures. One of the reasons for such failure is the incompatibility of members of this partnership or in other words wrong supplier selection which emphasize the significance of the selection process since it is the beginning stage. An effective selection process of strategic suppliers is critical to the success of the partnership. Although there are several research studies to select the suppliers in literature, only a few of them is related to strategic supplier selection for long-term partnership. The purpose of this study is to propose a conceptual model for the selection of strategic partnership suppliers. A two-stage approach has been used in proposed model incorporating first segmentation and second selection. In the first stage; considering the fact that not all suppliers are strategically equal and instead of a long list of potential suppliers, Kraljic’s purchasing portfolio matrix can be used for segmentation. This supplier segmentation is the process of categorizing suppliers based on a defined set of criteria in order to identify types of suppliers and determine potential suppliers for strategic partnership. In the second stage, from a pool of potential suppliers defined at first phase, a comprehensive evaluation and selection can be performed to finally define strategic suppliers considering various tangible and intangible criteria. Since a long-term relationship with strategic suppliers is anticipated, criteria should consider both current and future status of the supplier. Based on an extensive literature review; strategical, operational and organizational criteria have been determined and elaborated. The result of the selection can also be used to determine suppliers who are not ready for a partnership but to be developed for strategic partnership. Since the model is based on multiple criteria for both stages, it provides a framework for further utilization of Multi-Criteria Decision Making (MCDM) techniques. The model may also be applied to a wide range of industries and involve managerial features in business organizations.

Keywords: Kraljic’s matrix, purchasing portfolio, strategic supplier selection, supplier collaboration, supplier partnership, supplier segmentation

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Authors: Abdmohammad Mousavi, Mohsen Shams, Mehdi Akbartabar Toori, Ali Mousavizadeh, Mohammad Ali Morowatisharifabad

Abstract:

The effectiveness of Transtheoretical Model (TTM) on nutritional behavior change and lose weight has been subject to questions by some studies. The objective of this study was to determine the effect of nutritional behavior change and lose weight interventions based on TTM in obese and overweight women. This experimental study that was a 8 months trial nutritional behavior change and weight loss program based on TTM with two conditions and pre–post intervention measurements weight mean. 299 obese and overweight 20-44 years old women were selected from two health centers include training (142) and control (157) groups in Yasuj, a city in south west of Iran. Data were analyzed using paired T-test and One–Way ANOVA tests. In baseline, adherence with nutritional healthy behavior in training group(9.4%) compare with control(38.8%) were different significantly(p=.003), weight mean of training(Mean=78.02 kg, SD=11.67) compared with control group(Mean=77.23 kg, SD=10.25) were not (P=.66). In post test, adherence with nutritional healthy behavior in training group(70.1%) compare with control (37.4%) were different significantly (p=.000), weight mean of training (Mean=74.65 kg, SD=10.93, p=.000) compare with pre test were different significantly and control (Mean=77.43 kg, SD=10.43, p=.411) were not. The training group has lost 3.37 kg weight, whereas the control group has increased .2 kg weight. These results supported the applicability of the TTM for women weight lose intervention.

Keywords: nutritional behavior, Transtheoretical Model, weight lose, women

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