Search results for: fuzzy model identification.

Authors: M. Gomez, M. D. Murcia, E. Gomez, J. L. Gomez, N. Christofi

Abstract:

Excilamps are new UV sources with great potential for application in wastewater treatment. In the present work, a XeBr excilamp emitting radiation at 283 nm has been used for the photodegradation of 4-chlorophenol within a range of concentrations from 50 to 500 mg L-1. Total removal of 4-chlorophenol was achieved for all concentrations assayed. The two main photoproduct intermediates formed along the photodegradation process, benzoquinone and hydroquinone, although not being completely removed, remain at very low residual concentrations. Such concentrations are insignificant compared to the 4-chlorophenol initial ones and non-toxic. In order to simulate the process and scaleup, a kinetic model has been developed and validated from the experimental data.

Keywords: 4-chlorophenol, excilamps, kinetic model, photodegradation.

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Authors: Novi Khila Firani, Elisa Nesdyaningtyas

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Kwashiorkor is one of nutritional problem in Indonesia, which lead to decrease immune system. This condition causes susceptibility to infectious disease, especially tuberculosis. Development of new tuberculosis vaccine will be an important strategy to eliminate tuberculosis in kwashiorkor. Previous research showed that 38-kDa Mycobacterium tuberculosis protein is one of the potent immunogen. However, the role of oral immunization with 38- kDa Mycobacterium tuberculosis protein to the number of lymphocytes in the rat model of kwashiorkor is still unknown. We used kwashiorkor rat model groups with 4% and 2% low protein diet. Oral immunization with 38-kDa Mycobacterium tuberculosis protein given with 2 booster every week. The lymphocytes number were measured by flowcytometry. There was no significant difference between the number of lymphocytes in the normal rat group and the kwashiorkor rat groups. It may reveal the role of 38-kDa Mycobacterium tuberculosis protein as a potent immunogen that can increase the lymphocytes number from kwashiorkor rat model same as normal rat.

Keywords: kwashiorkor rat, lymphocytes, 38-kDa Mycobacterium tuberculosis protein

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Authors: E. Pikushchak, J. Dueck, L. Minkov

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In hydrocyclones, the particle separation efficiency is limited by the suspended fine particles, which are discharged with the coarse product in the underflow. It is well known that injecting water in the conical part of the cyclone reduces the fine particle fraction in the underflow. This paper presents a mathematical model that simulates the water injection in the conical component. The model accounts for the fluid flow and the particle motion. Particle interaction, due to hindered settling caused by increased density and viscosity of the suspension, and fine particle entrainment by settling coarse particles are included in the model. Water injection in the conical part of the hydrocyclone is performed to reduce fine particle discharge in the underflow. The model demonstrates the impact of the injection rate, injection velocity, and injection location on the shape of the partition curve. The simulations are compared with experimental data of a 50-mm cyclone.

Keywords: Classification, fine particle processing, hydrocyclone, water injection.

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Authors: Wen-Pai Wang, Mei-Ching Tang

Abstract:

The service sector continues to grow and the percentage of GDP accounted for by service industries keeps increasing. The growth and importance of service to an economy is not just a phenomenon of advanced economies, service is now a majority of the world gross domestic products. However, the performance evaluation process of new service development problems generally involves uncertain and imprecise data. This paper presents a 2-tuple fuzzy linguistic computing approach to dealing with heterogeneous information and information loss problems while the processes of subjective evaluation integration. The proposed method based on group decision-making scenario to assist business managers in measuring performance of new service development manipulates the heterogeneity integration processes and avoids the information loss effectively.

Keywords: Heterogeneity, Multigranular linguistic computing, New service development, Performance evaluation.

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Authors: Giulio Mangano, Alberto De Marco, Giovanni Zenezini

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The concept of City Logistics (CL) has emerged to improve the impacts of last mile freight distribution in urban areas. In this paper, a System Dynamics (SD) model exploring the dynamics of the diffusion of a ICT platform for CL management across different populations is proposed. For the development of the model two sources have been used. On the one hand, the major diffusion variables and feedback loops are derived from a literature review of existing diffusion models. On the other hand, the parameters are represented by the value propositions delivered by the platform as a response to some of the users’ needs. To extract the most important value propositions the Business Model Canvas approach has been used. Such approach in fact focuses on understanding how a company can create value for her target customers. These variables and parameters are thus translated into a SD diffusion model with three different populations namely municipalities, logistics service providers, and own account carriers. Results show that, the three populations under analysis fully adopt the platform within the simulation time frame, highlighting a strong demand by different stakeholders for CL projects aiming at carrying out more efficient urban logistics operations.

Keywords: City logistics, simulation, system dynamics, business model.

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Authors: Dipti Patra, Mridula J

Abstract:

In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.

Keywords: Texture Image Segmentation, Gray Level Cooccurrence Matrix, Markov Random Field Model, Ohta colour space, ICM algorithm.

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Authors: Padmakumar S., Vivek Agarwal, Kallol Roy

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A model based fault detection and diagnosis technique for DC motor is proposed in this paper. Fault detection using Kalman filter and its different variants are compared. Only incipient faults are considered for the study. The Kalman Filter iterations and all the related computations required for fault detection and fault confirmation are presented. A second order linear state space model of DC motor is used for this work. A comparative assessment of the estimates computed from four different observers and their relative performance is evaluated.

Keywords: DC motor model, Fault detection and diagnosis Kalman Filter, Unscented Kalman Filter

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Authors: Gulnaziya Issabayeva, Mohamed Kheireddine Aroua

Abstract:

commercially produced in Malaysia granular palm shell activated carbon (PSAC) was biomodified with bacterial biomass (Bacillus subtilis) to produce a hybrid biosorbent of higher efficiency. The obtained biosorbent was evaluated in terms of adsorption capacity to remove copper and zinc metal ions from aqueous solutions. The adsorption capacity was evaluated in batch adsorption experiments where concentrations of metal ions varied from 20 to 350 mg/L. A range of pH from 3 to 6 of aqueous solutions containing metal ions was tested. Langmuir adsorption model was used to interpret the experimental data. Comparison of the adsorption data of the biomodified and original palm shell activated carbon showed higher uptake of metal ions by the hybrid biosorbent. A trend in metal ions uptake increase with the increase in the solution-s pH was observed. The surface characterization data indicated a decrease in the total surface area for the hybrid biosorbent; however the uptake of copper and zinc by it was at least equal to the original PSAC at pH 4 and 5. The highest capacity of the hybrid biosorbent was observed at pH 5 and comprised 22 mg/g and 19 mg/g for copper and zinc, respectively. The adsorption capacity at the lowest pH of 3 was significantly low. The experimental results facilitated identification of potential factors influencing the adsorption of copper and zinc onto biomodified and original palm shell activated carbon.

Keywords: Adsorption, biomodification, copper, zinc, palm shell carbon.

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Authors: S. Panda, S. K. Tomar, R. Prasad, C. Ardil

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Reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM), using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Mihailov stability criterion and continued fraction expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. In the evolutionary technique method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Reduced Order Modeling, Stability, Continued Fraction Expansions, Mihailov Stability Criterion, Particle Swarm Optimization, Integral Squared Error.

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Authors: S. Channgam, A. Sae-Tang, T. Termsaithong

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In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions.

Keywords: Bak-Tang-Wiesenfeld sandpile model, avalanches, cross-correlation, prediction method.

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Authors: Jan Barák, Karel Fraňa, Jörg Stiller

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This work presents results of moist air condensation in heat exchanger. It describes theoretical knowledge and definition of moist air. Model with geometry of square canal was created for better understanding and postprocessing of condensation phenomena. Different approaches were examined on this model to find suitable software and model. Obtained knowledge was applied to geometry of real heat exchanger and results from experiment were compared with numerical results. One of the goals is to solve this issue without creating any user defined function in the applied code. It also contains summary of knowledge and outlook for future work.

Keywords: Condensation, exchanger, experiment, validation.

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Authors: M. Abouelatta, A. Shaker, M. El-Banna, G. T. Sayah, C. Gontrand, A. Zekry

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In this paper, a methodology for physically modeling the intrinsic MOS part and the drift region of the n-channel Laterally Double-diffused MOSFET (LDMOS) is presented. The basic physical effects like velocity saturation, mobility reduction, and nonuniform impurity concentration in the channel are taken into consideration. The analytical model is implemented using MATLAB. A comparison of the simulations from technology computer aided design (TCAD) and that from the proposed analytical model, at room temperature, shows a satisfactory accuracy which is less than 5% for the whole voltage domain.

Keywords: LDMOS, MATLAB, RESURF, modeling, TCAD.

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

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

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

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Authors: P. Pongsumpun

Abstract:

Malaria is transmitted to the human by biting of infected Anopheles mosquitoes. This disease is a serious, acute and chronic relapsing infection to humans. Fever, nausea, vomiting, back pain, increased sweating anemia and splenomegaly (enlargement of the spleen) are the symptoms of the patients who infected with this disease. It is caused by the multiplication of protozoa parasite of the genus Plasmodium. Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium ovale are the four types of Plasmodium malaria. A mathematical model for the transmission of Plasmodium Malaria is developed in which the human and vector population are divided into two classes, the susceptible and the infectious classes. In this paper, we formulate the dynamical model of Plasmodium falciparum and Plasmodium vivax malaria. The standard dynamical analysis is used for analyzing the behavior for the transmission of this disease. The Threshold condition is found and numerical results are shown to confirm the analytical results.

Keywords: Dynamical analysis, Malaria, mathematical model, threshold condition.

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Authors: B. Ghanbarian-Alavijeh, A.M. Liaghat, S. Sohrabi

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Saturated hydraulic conductivity is one of the soil hydraulic properties which is widely used in environmental studies especially subsurface ground water. Since, its direct measurement is time consuming and therefore costly, indirect methods such as pedotransfer functions have been developed based on multiple linear regression equations and neural networks model in order to estimate saturated hydraulic conductivity from readily available soil properties e.g. sand, silt, and clay contents, bulk density, and organic matter. The objective of this study was to develop neural networks (NNs) model to estimate saturated hydraulic conductivity from available parameters such as sand and clay contents, bulk density, van Genuchten retention model parameters (i.e. r θ , α , and n) as well as effective porosity. We used two methods to calculate effective porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s θ is saturated water content, FC θ is water content retained at -33 kPa matric potential, and inf θ is water content at the inflection point. Total of 311 soil samples from the UNSODA database was divided into three groups as 187 for the training, 62 for the validation (to avoid over training), and 62 for the test of NNs model. A commercial neural network toolbox of MATLAB software with a multi-layer perceptron model and back propagation algorithm were used for the training procedure. The statistical parameters such as correlation coefficient (R2), and mean square error (MSE) were also used to evaluate the developed NNs model. The best number of neurons in the middle layer of NNs model for methods (1) and (2) were calculated 44 and 6, respectively. The R2 and MSE values of the test phase were determined for method (1), 0.94 and 0.0016, and for method (2), 0.98 and 0.00065, respectively, which shows that method (2) estimates saturated hydraulic conductivity better than method (1).

Keywords: Neural network, Saturated hydraulic conductivity, Soil physical properties.

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Authors: Syahril Ridzuan Ab Rahim, Ibrahim Ahmad, Mohd Azizi Chik, Ahmad Zafir Md. Rejab, and U. Hashim

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This research presents the development of simulation modeling for WIP management in semiconductor fabrication. Manufacturing simulation modeling is needed for productivity optimization analysis due to the complex process flows involved more than 35 percent re-entrance processing steps more than 15 times at same equipment. Furthermore, semiconductor fabrication required to produce high product mixed with total processing steps varies from 300 to 800 steps and cycle time between 30 to 70 days. Besides the complexity, expansive wafer cost that potentially impact the company profits margin once miss due date is another motivation to explore options to experiment any analysis using simulation modeling. In this paper, the simulation model is developed using existing commercial software platform AutoSched AP, with customized integration with Manufacturing Execution Systems (MES) and Advanced Productivity Family (APF) for data collections used to configure the model parameters and data source. Model parameters such as processing steps cycle time, equipment performance, handling time, efficiency of operator are collected through this customization. Once the parameters are validated, few customizations are made to ensure the prior model is executed. The accuracy for the simulation model is validated with the actual output per day for all equipments. The comparison analysis from result of the simulation model compared to actual for achieved 95 percent accuracy for 30 days. This model later was used to perform various what if analysis to understand impacts on cycle time and overall output. By using this simulation model, complex manufacturing environment like semiconductor fabrication (fab) now have alternative source of validation for any new requirements impact analysis.

Keywords: Advanced Productivity Family (APF), Complementary Metal Oxide Semiconductor (CMOS), Manufacturing Execution Systems (MES), Work In Progress (WIP).

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Authors: Syerina Azlin Md Nasir, Nor Laila Md Noor, Suriyati Razali

Abstract:

The growing interest on national heritage preservation has led to intensive efforts on digital documentation of cultural heritage knowledge. Encapsulated within this effort is the focus on ontology development that will help facilitate the organization and retrieval of the knowledge. Ontologies surrounding cultural heritage domain are related to archives, museum and library information such as archaeology, artifacts, paintings, etc. The growth in number and size of ontologies indicates the well acceptance of its semantic enrichment in many emerging applications. Nowadays, there are many heritage information systems available for access. Among others is community-based e-museum designed to support the digital cultural heritage preservation. This work extends previous effort of developing the Traditional Malay Textile (TMT) Knowledge Model where the model is designed with the intention of auxiliary mapping with CIDOC CRM. Due to its internal constraints, the model needs to be transformed in advance. This paper addresses the issue by reviewing the previous harmonization works with CIDOC CRM as exemplars in refining the facets in the model particularly involving TMT-Artifact class. The result is an extensible model which could lead to a common view for automated mapping with CIDOC CRM. Hence, it promotes integration and exchange of textile information especially batik-related between communities in e-museum applications.

Keywords: automated mapping, cultural heritage, knowledgemodel, textile practice

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Authors: Husna Hasan, Norfatin Salam, Mohd Bakri Adam

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Extreme temperature of several stations in Malaysia is modelled by fitting the monthly maximum to the Generalized Extreme Value (GEV) distribution. The Mann-Kendall (MK) test suggests a non-stationary model. Two models are considered for stations with trend and the Likelihood Ratio test is used to determine the best-fitting model. Results show that half of the stations favour a model which is linear for the location parameters. The return level is the level of events (maximum temperature) which is expected to be exceeded once, on average, in a given number of years, is obtained.

Keywords: Extreme temperature, extreme value, return level.

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Authors: Sunho Ki, Daehwan Kim, Seongwon Cho, Sun-Tae Chung, Jaemin Kim, Yun-Kwang Hong, Chang Joon Park, Dongmin Kwon, Minhee Kang, Yusung Kim, Younghan Yoon

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AAM (active appearance model) has been successfully applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard AAM-based face alignment method.

Keywords: AAM, Face Alignment, Feature Extraction, PCA

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Authors: Weerachi Sarakorn, I-Ming Tang

Abstract:

A mathematical model for the transmission of SARS is developed. In addition to dividing the population into susceptible (high and low risk), exposed, infected, quarantined, diagnosed and recovered classes, we have included a class called untraced. The model simulates the Gompertz curves which are the best representation of the cumulative numbers of probable SARS cases in Hong Kong and Singapore. The values of the parameters in the model which produces the best fit of the observed data for each city are obtained by using a differential evolution algorithm. It is seen that the values for the parameters needed to simulate the observed daily behaviors of the two epidemics are different.

Keywords: SARS, mathematical modelling, differential evolution algorithm.

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Authors: N. Manavizadeh , M. Rabbani , H. Sotudian , F. Jolai

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Mixed Model Production is the practice of assembling several distinct and different models of a product on the same assembly line without changeovers and then sequencing those models in a way that smoothes the demand for upstream components. In this paper, we consider an objective function which minimizes total stoppage time and total idle time and it is presented sequence dependent set up time. Many studies have been done on the mixed model assembly lines. But in this paper we specifically focused on reducing the idle times. This is possible through various help policies. For improving the solutions, some cases developed and about 40 tests problem was considered. We use scatter search for optimization and for showing the efficiency of our algorithm, experimental results shows behavior of method. Scatter search and help policies can produce high quality answers, so it has been used in this paper.

Keywords: mixed model assembly lines, Scatter search, help policies, idle time, Stoppage time

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Authors: Monica Chiş

Abstract:

Software metric is a measure of some property of a piece of software or its specification. The aim of this paper is to present an application of evolutionary decision trees in software engineering in order to classify the software modules that have or have not one or more reported defects. For this some metrics are used for detecting the class of modules with defects or without defects.

Keywords: Evolutionary decision trees, decision trees, softwaremetrics.

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Authors: Mehdi Kheradmand, Mehdi Azhdary Moghaddam, Abdolreza Zahiri, Khalil Ghorbani

Abstract:

In modeling phenomena, the presence of local conditions may cause the use of a general relation not to produce good results and thus fail to demonstrate local changes. If possible, identifying homogenous limits and providing simple linear relations for each of these limits will increase the accuracy of models. Accordingly, the models are divided into simpler and smaller problems to solve complicated problems, and the obtained answers will be combined. This simple idea can be applied to decision tree models. For this aim, the input data values are divided into several sub-intervals or sub-regions, and an appropriate model is extracted for an appropriate model or equation. This research proposes the M5 decision tree method as a solution to accurately compute the flow discharge in meandering compound channels.

Keywords: Stage-discharge relationship, decision tree, M5 decision tree model, meandering compound channels.

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Authors: Rida B. Arieby, Hameed N. Hameed

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In this work, tensile tests on high density polyethylene have been carried out under various constant strain rate and strain rate jump tests. The dependency of the true stress and specially the variation of volume strain have been investigated, the volume strain due to the phenomena of damage was determined in real time during the tests by an optical extensometer called Videotraction. A modified constitutive equations, including strain rate and damage effects, are proposed, such a model is based on a non-equilibrium thermodynamic approach called (DNLR). The ability of the model to predict the complex nonlinear response of this polymer is examined by comparing the model simulation with the available experimental data, which demonstrate that this model can represent the deformation behavior of the polymer reasonably well.

Keywords: Strain rate jump tests, Volume Strain, High Density Polyethylene, Large strain, Thermodynamics approach.

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Authors: L. Yettou

Abstract:

In this study, the calculations of proton emission spectra produced by ⁶³Cu(n,xp) and ⁶⁵Cu(n,xp) reactions are used in the framework of preequilibrium models using the EMPIRE code and TALYS code. Exciton Model predidtions combined with the Kalbach angular distribution systematics and the Hybrid Monte Carlo Simulation (HMS) were used. The effects of levels densities and those of a-parameter have been investigated for our calculations. The comparison with experimental data shows clear improvement over the Exciton Model and HMS calculations.

Keywords: Preequilibrium models, level density, level density a-parameter, 63Cu(n, xp) and 65Cu(n, xp) reactions.

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Authors: Machimontorn Promtong, Sherman C. P. Cheung, Guan H. Yeoh, Sara Vahaji, Jiyuan Tu

Abstract:

The wide range of industrial applications involved with boiling flows promotes the necessity of establishing fundamental knowledge in boiling flow phenomena. For this purpose, a number of experimental and numerical researches have been performed to elucidate the underlying physics of this flow. In this paper, the improved wall boiling models, implemented on ANSYS CFX 14.5, were introduced to study subcooled boiling flow at elevated pressure. At the heated wall boundary, the Fractal model, Force balance approach and Mechanistic frequency model are given for predicting the nucleation site density, bubble departure diameter, and bubble departure frequency. The presented wall heat flux partitioning closures were modified to consider the influence of bubble sliding along the wall before the lift-off, which usually happens in the flow boiling. The simulation was performed based on the Two-fluid model, where the standard k-ω SST model was selected for turbulence modelling. Existing experimental data at around 5 bars were chosen to evaluate the accuracy of the presented mechanistic approach. The void fraction and Interfacial Area Concentration (IAC) are in good agreement with the experimental data. However, the predicted bubble velocity and Sauter Mean Diameter (SMD) are over-predicted. This over-prediction may be caused by consideration of only dispersed and spherical bubbles in the simulations. In the future work, the important physical mechanisms of bubbles, such as merging and shrinking during sliding on the heated wall will be incorporated into this mechanistic model to enhance its capability for a wider range of flow prediction.

Keywords: CFD, mechanistic model, subcooled boiling flow, two-fluid model.

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Authors: J. R. Wang, H. C. Chang, A. L. Ho, J. H. Yang, S. W. Chen, C. Shih

Abstract:

The purpose of the study is to analyze the load rejection transient of ABWR by using TRACE, PARCS, and SNAP codes. This study has some steps. First, using TRACE, PARCS, and SNAP codes establish the model of ABWR. Second, the key parameters are identified to refine the TRACE/PARCS/SNAP model further in the frame of a steady state analysis. Third, the TRACE/PARCS/SNAP model is used to perform the load rejection transient analysis. Finally, the FSAR data are used to compare with the analysis results. The results of TRACE/PARCS are consistent with the FSAR data for the important parameters. It indicates that the TRACE/PARCS/SNAP model of ABWR has a good accuracy in the load rejection transient.

Keywords: ABWR, TRACE, PARCS, SNAP.

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Authors: Guo Xiuhua, Sun Tao, Wu Haifeng, He Wen, Liang Zhigang, Zhang Mengxia, Guo Aimin, Wang Wei

Abstract:

Purpose: To explore the use of Curvelet transform to extract texture features of pulmonary nodules in CT image and support vector machine to establish prediction model of small solitary pulmonary nodules in order to promote the ratio of detection and diagnosis of early-stage lung cancer. Methods: 2461 benign or malignant small solitary pulmonary nodules in CT image from 129 patients were collected. Fourteen Curvelet transform textural features were as parameters to establish support vector machine prediction model. Results: Compared with other methods, using 252 texture features as parameters to establish prediction model is more proper. And the classification consistency, sensitivity and specificity for the model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based on texture features extracted from Curvelet transform, support vector machine prediction model is sensitive to lung cancer, which can promote the rate of diagnosis for early-stage lung cancer to some extent.

Keywords: CT image, Curvelet transform, Small pulmonary nodules, Support vector machines, Texture extraction.

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Authors: M. A. Meslem

Abstract:

For precise geoid determination, we use a reference field to subtract long and medium wavelength of the gravity field from observations data when we use the remove-compute-restore technique. Therefore, a comparison study between considered models should be made in order to select the optimal reference gravity field to be used. In this context, two recent global geopotential models have been selected to perform this comparison study over Northern Algeria. The Earth Gravitational Model (EGM2008) and the Global Gravity Model (GECO) conceived with a combination of the first model with anomalous potential derived from a GOCE satellite-only global model. Free air gravity anomalies in the area under study have been used to compute residual data using both gravity field models and a Digital Terrain Model (DTM) to subtract the residual terrain effect from the gravity observations. Residual data were used to generate local empirical covariance functions and their fitting to the closed form in order to compare their statistical behaviors according to both cases. Finally, height anomalies were computed from both geopotential models and compared to a set of GPS levelled points on benchmarks using least squares adjustment. The result described in details in this paper regarding these two models has pointed out a slight advantage of GECO global model globally through error degree variances comparison and ground-truth evaluation.

Keywords: Quasigeoid, gravity anomalies, covariance, GGM.

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: Deregulated energy market, forecasting, machine learning, system marginal price, energy efficiency and quality.

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