Search results for: Adsorption models

Authors: Jürgen Geiser, Robert Röhle

Abstract:

In this paper we present modeling and simulation for physical vapor deposition for metallic bipolar plates. In the models we discuss the application of different models to simulate the transport of chemical reactions of the gas species in the gas chamber. The so called sputter process is an extremely sensitive process to deposit thin layers to metallic plates. We have taken into account lower order models to obtain first results with respect to the gas fluxes and the kinetics in the chamber. The model equations can be treated analytically in some circumstances and complicated multi-dimensional models are solved numerically with a software-package (UG unstructed grids, see [1]). Because of multi-scaling and multi-physical behavior of the models, we discuss adapted schemes to solve more accurate in the different domains and scales. The results are discussed with physical experiments to give a valid model for the assumed growth of thin layers.

Keywords: Convection-diffusion equations, multi-scale problem, physical vapor deposition, reaction equations, splitting methods.

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Authors: Reza Bazargan-Lari, Mohammad Ebrahim Bahrololoom, Afshin Nemati

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Heavy metals have bad effects on environment and soils and it can uptake by natural HAP .natural Hap is an inexpensive material that uptake large amounts of various heavy metals like Zn (II) .Natural HAP (N-HAP), extracted from bovine cortical bone ash, is a good choice for substitution of commercial HAP. Several experiments were done to investigate the sorption capacity of Zn (II) to N-HAP in various particles sizes, temperatures, initial concentrations, pH and reaction times. In this study, the sorption of Zinc ions from a Zn solution onto HAP particles with sizes of 1537.6 nm and 47.6 nm at three initial pH values of 4.50, 6.00 and 7.50 was studied. The results showed that better performance was obtained through a 47.6 nm particle size and higher pH values. The experimental data were analyzed using Langmuir, Freundlich, and Arrhenius equations for equilibrium, kinetic and thermodynamic studies. The analysis showed a maximum adsorption capacity of NHAP as being 1.562 mmol/g at a pH of 7.5 and small particle size. Kinetically, the prepared N-HAP is a feasible sorbent that retains Zn (II) ions through a favorable and spontaneous sorption process.

Keywords: Natural Hydroxyapatite, Heavy metal ions, Adsorption, Zn removal, kinetic model, bone ash

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Authors: N. Santatriniaina, J. Deseure, T.Q. Nguyen, H. Fontaine, C. Beitia, L. Rakotomanana

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Nowadays, with the increasing of the wafer's size and the decreasing of critical size of integrated circuit manufacturing in modern high-tech, microelectronics industry needs a maximum attention to challenge the contamination control. The move to 300 [mm] is accompanied by the use of Front Opening Unified Pods for wafer and his storage. In these pods an airborne cross contamination may occur between wafers and the pods. A predictive approach using modeling and computational methods is very powerful method to understand and qualify the AMCs cross contamination processes. This work investigates the required numerical tools which are employed in order to study the AMCs cross-contamination transfer phenomena between wafers and FOUPs. Numerical optimization and finite element formulation in transient analysis were established. Analytical solution of one dimensional problem was developed and the calibration process of physical constants was performed. The least square distance between the model (analytical 1D solution) and the experimental data are minimized. The behavior of the AMCs intransient analysis was determined. The model framework preserves the classical forms of the diffusion and convection-diffusion equations and yields to consistent form of the Fick's law. The adsorption process and the surface roughness effect were also traduced as a boundary condition using the switch condition Dirichlet to Neumann and the interface condition. The methodology is applied, first using the optimization methods with analytical solution to define physical constants, and second using finite element method including adsorption kinetic and the switch of Dirichlet to Neumann condition.

Keywords: AMCs, FOUP, cross-contamination, adsorption, diffusion, numerical analysis, wafers, Dirichlet to Neumann, finite elements methods, Fick’s law, optimization.

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Authors: N. Alharbi

Abstract:

E-government is becoming more important these days. However, the adoption of e-government is often slowed down by technical and non-technical security factors. Nowadays, there many security models that can make the e-government services more secure. This paper will explain the main security factors that affected the level of e-government security. Moreover, it will also analyse current existing models. Finally, the paper will suggest a comprehensive security model that will contain most of technical and non-technical factors.

Keywords: E-government, technical, non-technical, security model.

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Authors: Bernhard G. Humm, Janina Fengel

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Business process modeling has become an accepted means for designing and describing business operations. Thereby, consistency of business process models, i.e., the absence of modeling faults, is of upmost importance to organizations. This paper presents a concept and subsequent implementation for detecting faults in business process models and for computing a measure of their consistency. It incorporates not only syntactic consistency but also semantic consistency, i.e., consistency regarding the meaning of model elements from a business perspective.

Keywords: Business process modeling, model analysis, semantic consistency, Semantic Web

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Authors: S. Shahrooi, I. H. Metselaar, Z. Huda

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When considering the development of constitutive equations describing the behavior of materials under cyclic plastic strains, different kinds of formulations can be adopted. The primary intention of this study is to develop computer programming of plasticity models to accurately predict the life of engineering components. For this purpose, the energy or cyclic strain is computed in multi-surface plasticity models in non-proportional loading and to present their procedures and codes results.

Keywords: Strain energy, cyclic plasticity model, multi-surface model, codes result.

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

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The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: Comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events.

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Authors: Nophaket Napong

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Rooted in the study of social functioning of space in architecture, Space Syntax (SS) and the more recent Network Pattern (NP) researches demonstrate the 'spatial structures' of city, i.e. the hierarchical patterns of streets, junctions and alley ends. Applying SS and NP models, planners can conceptualize the real city-s patterns. Although, both models yield the optimal path of the city their underpinning displays of the city-s spatial configuration differ. The Axial Map analyzes the topological non-distance-based connectivity structure, whereas, the Central-Node Map and the Shortcut-Path Map, in contrast, analyze the metrical distance-based structures. This research contrasts and combines them to understand various forms of city-s structures. It concludes that, while they reveal different spatial structures, Space Syntax and Network Pattern urban models support each the other. Combining together they simulate the global access and the locally compact structures namely the central nodes and the shortcuts for the city.

Keywords: Street pattern, space syntax, syntactic and metrical models, network pattern models.

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Authors: A. Ahmadi Nadooshan, S. Daneshmand, C. Aghanajafi

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Traditionally, wind tunnel models are made of metal and are very expensive. In these years, everyone is looking for ways to do more with less. Under the right test conditions, a rapid prototype part could be tested in a wind tunnel. Using rapid prototype manufacturing techniques and materials in this way significantly reduces time and cost of production of wind tunnel models. This study was done of fused deposition modeling (FDM) and their ability to make components for wind tunnel models in a timely and cost effective manner. This paper discusses the application of wind tunnel model configuration constructed using FDM for transonic wind tunnel testing. A study was undertaken comparing a rapid prototyping model constructed of FDM Technologies using polycarbonate to that of a standard machined steel model. Testing covered the Mach range of Mach 0.3 to Mach 0.75 at an angle-ofattack range of - 2° to +12°. Results from this study show relatively good agreement between the two models and rapid prototyping Method reduces time and cost of production of wind tunnel models. It can be concluded from this study that wind tunnel models constructed using rapid prototyping method and materials can be used in wind tunnel testing for initial baseline aerodynamic database development.

Keywords: Polycarbonate, Fabrication, FDM, Model, RapidPrototyping, Wind Tunnel.

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Authors: Yongyoon Suh, Chulhyun Kim, Moon-soo Kim

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As the trend of manufacturing is being dominated depending on services, products and processes are more and more related with sophisticated services. Thus, this research starts with the discussion about integration of the product, process, and service in the innovation process. In particular, this paper sets out some foundations for a theory of service innovation in the field of manufacturing, and proposes the dynamic model of service innovation related to product and process. Two dynamic models of service innovation are suggested to investigate major tendencies and dynamic variations during the innovation cycle: co-innovation and sequential innovation. To structure dynamic models of product, process, and service innovation, the innovation stages in which two models are mainly achieved are identified. The research would encourage manufacturers to formulate strategy and planning for service development with product and process.

Keywords: dynamic model, service innovation, service innovation models, innovation cycle, manufacturing industry.

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Authors: Alexander Breitholz, Wolfgang Arlt, Ki-Pung Yoo

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Group contribution based models are widely used in industrial applications for its convenience and flexibility. Although a number of group contribution models have been proposed, there were certain limitations inherent to those models. Models based on group contribution excess Gibbs free energy are limited to low pressures and models based on equation of state (EOS) cannot properly describe highly nonideal mixtures including acids without introducing additional modification such as chemical theory. In the present study new a new approach derived from quantum chemistry have been used to calculate necessary EOS group interaction parameters. The COSMO-RS method, based on quantum mechanics, provides a reliable tool for fluid phase thermodynamics. Benefits of the group contribution EOS are the consistent extension to hydrogen-bonded mixtures and the capability to predict polymer-solvent equilibria up to high pressures. The authors are confident that with a sufficient parameter matrix the performance of the lattice EOS can be improved significantly.

Keywords: COSMO-RS, Equation of State, Group contribution, Lattice Fluid, Phase equilibria.

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Authors: Hyunchul Ahn, Kyoung-Jae Kim

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Corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has been one of the attractive research topics in the literature. In recent years, multiclass classification models such as artificial neural network (ANN) or multiclass support vector machine (MSVM) have become a very appealing machine learning approaches due to their good performance. However, most of them have only focused on classifying samples into nominal categories, thus the unique characteristic of the credit rating - ordinality - has been seldom considered in their approaches. This study proposes new types of ANN and MSVM classifiers, which are named OMANN and OMSVM respectively. OMANN and OMSVM are designed to extend binary ANN or SVM classifiers by applying ordinal pairwise partitioning (OPP) strategy. These models can handle ordinal multiple classes efficiently and effectively. To validate the usefulness of these two models, we applied them to the real-world bond rating case. We compared the results of our models to those of conventional approaches. The experimental results showed that our proposed models improve classification accuracy in comparison to typical multiclass classification techniques with the reduced computation resource.

Keywords: Artificial neural network, Corporate credit rating, Support vector machines, Ordinal pairwise partitioning

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Authors: Oulad Naoui Noureddine, Cherif ELAmine, Djehiche Abdelkader

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Water resources management includes several disciplines; the modeling of rainfall-runoff relationship is the most important discipline to prevent natural risks. There are several models to study rainfall-runoff relationship in watersheds. However, the majority of these models are not applicable in all basins of the world.  In this study, a new stochastic method called The Only Corresponding Competitor method (OCC) was used for the hydrological modeling of M’ZAB   Watershed (South East of Algeria) to adapt a few empirical models for any hydrological regime.  The results obtained allow to authorize a certain number of visions, in which it would be interesting to experiment with hydrological models that improve collectively or separately the data of a catchment by the OCC method.

Keywords: Empirical model, modeling, OCC, rainfall-runoff relationship.

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Authors: Jesus Orbe, Vicente Nunez-Anton

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In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. In this context, most of the studies in the literature can be located in two possible general classes of regression models: models that study the effect the covariates have on the hazard function; and models that study the effect the covariates have on the censored response variable. Proposals in this paper are in the second class of models and, more specifically, on least squares based model approach. Thus, using the bootstrap estimate of the bias, we try to improve the estimation of the regression parameters by reducing their bias, for small sample sizes. Simulation results presented in the paper show that, for reasonable sample sizes and censoring levels, the bias is always smaller for the new proposals.

Keywords: Censored response variable, regression, bias.

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Authors: Eleftherios Giovanis

Abstract:

In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms significant the Logit and Probit models in the out-of sample period. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.

Keywords: ANFIS, discrete choice models, financial crisis, USeconomy

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Authors: Isabel Brás, Artur Figueirinha, Bruno Esteves, Luísa P. Cruz-Lopes

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The agriculture lignocellulosic by-products are receiving increased attention, namely in the search for filter materials that retain contaminants from water. These by-products, specifically almond and hazelnut shells are abundant in Portugal once almond and hazelnuts production is a local important activity. Hazelnut and almond shells have as main constituents lignin, cellulose and hemicelluloses, water soluble extractives and tannins. Along the adsorption of heavy metals from contaminated waters, water soluble compounds can leach from shells and have a negative impact in the environment. Usually, the chemical characterization of treated water by itself may not show environmental impact caused by the discharges when parameters obey to legal quality standards for water. Only biological systems can detect the toxic effects of the water constituents. Therefore, the evaluation of toxicity by biological tests is very important when deciding the suitability for safe water discharge or for irrigation applications.

The main purpose of the present work was to assess the potential impacts of waters after been treated for heavy metal removal by hazelnut and almond shells adsorption systems, with short term acute toxicity tests.

To conduct the study, water at pH 6 with 25 mg.L^-1 of lead, was treated with 10 g of shell per litre of wastewater, for 24 hours. This procedure was followed for each bark. Afterwards the water was collected for toxicological assays; namely bacterial resistance, seed germination, Lemna minor L. test and plant grow. The effect in isolated bacteria strains was determined by disc diffusion method and the germination index of seed was evaluated using lettuce, with temperature and humidity germination control for 7 days. For aquatic higher organism, Lemnas were used with 4 days contact time with shell solutions, in controlled light and temperature. For terrestrial higher plants, biomass production was evaluated after 14 days of tomato germination had occurred in soil, with controlled humidity, light and temperature.

Toxicity tests of water treated with shells revealed in some extent effects in the tested organisms, with the test assays showing a close behaviour as the control, leading to the conclusion that its further utilization may not be considered to create a serious risk to the environment.

Keywords: Acute toxicity tests, adsorption, lignocellulosic wastes, risk assessment.

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Authors: Y. N. Phang, E. F. Loh

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Many researchers have suggested the use of zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) models in modeling overdispersed medical count data with extra variations caused by extra zeros and unobserved heterogeneity. The studies indicate that ZIP and ZINB always provide better fit than using the normal Poisson and negative binomial models in modeling overdispersed medical count data. In this study, we proposed the use of Zero Inflated Inverse Trinomial (ZIIT), Zero Inflated Poisson Inverse Gaussian (ZIPIG) and zero inflated strict arcsine models in modeling overdispered medical count data. These proposed models are not widely used by many researchers especially in the medical field. The results show that these three suggested models can serve as alternative models in modeling overdispersed medical count data. This is supported by the application of these suggested models to a real life medical data set. Inverse trinomial, Poisson inverse Gaussian and strict arcsine are discrete distributions with cubic variance function of mean. Therefore, ZIIT, ZIPIG and ZISA are able to accommodate data with excess zeros and very heavy tailed. They are recommended to be used in modeling overdispersed medical count data when ZIP and ZINB are inadequate.

Keywords: Zero inflated, inverse trinomial distribution, Poisson inverse Gaussian distribution, strict arcsine distribution, Pearson’s goodness of fit.

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Authors: Amal Kr Sarma, H Zeen Devi, N Nimai Singh

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The Constraints imposed by non-thermal leptogenesis on the survival of the neutrino mass models describing the presently available neutrino mass patterns, are studied numerically. We consider the Majorana CP violating phases coming from right-handed Majorana mass matrices to estimate the baryon asymmetry of the universe, for different neutrino mass models namely quasi-degenerate, inverted hierarchical and normal hierarchical models, with tribimaximal mixings. Considering two possible diagonal forms of Dirac neutrino mass matrix as either charged lepton or up-quark mass matrix, the heavy right-handed mass matrices are constructed from the light neutrino mass matrix. Only the normal hierarchical model leads to the best predictions of baryon asymmetry of the universe, consistent with observations in non-thermal leptogenesis scenario.

Keywords: Thermal leptogenesis, Non-thermal leptogenesis.

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Authors: Sally A. Brown

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Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aide teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: Explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role.

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Authors: Kee-Leong Tan, Cheng-Suan Lee, Hui-Na Chua

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This paper presents three models which enable the customisation of Universal Description, Discovery and Integration (UDDI) query results, based on some pre-defined and/or real-time changing parameters. These proposed models detail the requirements, design and techniques which make ranking of Web service discovery results from a service registry possible. Our contribution is two fold: First, we present an extension to the UDDI inquiry capabilities. This enables a private UDDI registry owner to customise or rank the query results, based on its business requirements. Second, our proposal utilises existing technologies and standards which require minimal changes to existing UDDI interfaces or its data structures. We believe these models will serve as valuable reference for enhancing the service discovery methods within a private UDDI registry environment.

Keywords: Web service, discovery, semantic, SOA, registry, UDDI.

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: Speech recognition, acoustic phonetic, artificial intelligence, Hidden Markov Models (HMM), statistical models of speech recognition, human machine performance.

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Authors: Giovanni Incerti, Luigi Solazzi, Candida Petrogalli

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This paper describes three lumped parameters models for the study of the dynamic behavior of a boom crane. The models here proposed allows to evaluate the fluctuations of the load arising from the rope and structure elasticity and from the type of the motion command imposed by the winch. A calculation software was developed in order to determine the actual acceleration of the lifted mass and the dynamic overload during the lifting phase. Some application examples are presented, with the aim of showing the correlation between the magnitude of the stress and the type of the employed motion command.

Keywords: Crane, dynamic model, overloading condition, vibration.

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Authors: Olayinka Omotosho, Anthony Amori

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Cassava peels and bamboo waste materials discarded from construction are two sources of waste that could constitute serious menace where they exist in large quantities and inadequately handled. The study examined the physicochemical characteristics of activated carbon materials derived from cassava peels and bamboo waste materials discarded from construction site. Both materials were subjected to carbonization and chemical activation using zinc chloride. Results show that the chemical activation of the materials had a more effect on pore formation in cassava peels than in bamboo materials. Bamboo material exhibited a reverse trend for zinc and sulphate ion decontamination efficiencies as the value of zinc chloride impregnation varied unlike cassava peel carbon biomass which exhibited a more consistent result of decontamination efficiency for the seven contaminants tested. Although waste bamboo biomass exhibited higher adsorption intensity as indicated by values of decontamination for most of the contaminants tested, the cassava peel carbon biomass showed a more balanced adsorption level.

Keywords: Zinc chloride, cassava peels, activated carbon, bamboo waste, SEM.

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Authors: S.A. Alqallaf, S.A. Al-Mawsawi, A. Haider

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In order to evaluate the performance of a unified power flow controller (UPFC), mathematical models for steady state and dynamic analysis are to be developed. The steady state model is mainly concerned with the incorporation of the UPFC in load flow studies. Several load flow models for UPFC have been introduced in literature, and one of the most reliable models is the decoupled UPFC model. In spite of UPFC decoupled load flow model simplicity, it is more robust compared to other UPFC load flow models and it contains unique capabilities. Some shortcoming such as additional set of nonlinear equations are to be solved separately after the load flow solution is obtained. The aim of this study is to investigate the different control strategies that can be realized in the decoupled load flow model (individual control and combined control), and the impact of the location of the UPFC in the network on its control parameters.

Keywords: UPFC, Decoupled model, Load flow.

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Authors: Yanshuang Zhang, Byungho Jeong

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In many cases, there are some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrate models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long term research project is given to compare the suggested model with the MpO model.

Keywords: DEA, Super-efficiency, Time Lag.

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Authors: Shewit Tsegaye, Kinde A. Fante

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This paper presents the comparison and performance evaluation of synchronous machine excitation models. The two models, DC1A and AC4A, are among the IEEE standardized model structures for representing the wide variety of synchronous machine excitation systems. The performance evaluation of these models is done using SIMULINK simulation software. The simulation results obtained using transient analysis show that the DC1A excitation system is more reliable and stable than AC4A excitation system.

Keywords: Excitation system, synchronous machines, AC and DC regulators.

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Authors: Verónica Diaz Quezada

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This research examines the teaching models used by secondary math teachers when teaching logarithmic, quadratic and exponential functions. For this, descriptive case studies have been carried out on 5 secondary teachers. These teachers have been chosen from 3 scientific-humanistic and technical schools, in Chile. Data have been obtained through non-participant class observation and the application of a questionnaire and a rubric to teachers. According to the results, the didactic model that prevails is the one that starts with an interactive strategy, moves to a more content-based structure, and ends with a reinforcement stage. Nonetheless, there is always influence from teachers, their methods, and the group of students.

Keywords: Teaching models, math teachers, functions, secondary education.

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Authors: Dalila Hamami, Baghdad Atmani

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Modelling is a widely used tool to facilitate the evaluation of disease management. The interest of epidemiological models lies in their ability to explore hypothetical scenarios and provide decision makers with evidence to anticipate the consequences of disease incursion and impact of intervention strategies.

All models are, by nature, simplification of more complex systems. Models that involve diseases can be classified into different categories depending on how they treat the variability, time, space, and structure of the population. Approaches may be different from simple deterministic mathematical models, to complex stochastic simulations spatially explicit.

Thus, epidemiological modelling is now a necessity for epidemiological investigations, surveillance, testing hypotheses and generating follow-up activities necessary to perform complete and appropriate analysis.

The state of the art presented in the following, allows us to position itself to the most appropriate approaches in the epidemiological study.

Keywords: Bio-PEPA, Cellular automata, Epidemiological modelling, multi agent system, ordinary differential equations, PEPA, Process Algebra, Tuberculosis.

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Authors: Thomas I. Kounitis

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The purpose of this paper is to investigate the influence of a number of variables on the conditional mean and conditional variance of credit spread changes. The empirical analysis in this paper is conducted within the context of bivariate GARCH-in- Mean models, using the so-called BEKK parameterization. We show that credit spread changes are determined by interest-rate and equityreturn variables, which is in line with theory as provided by the structural models of default. We also identify the credit spread change volatility as an important determinant of credit spread changes, and provide evidence on the transmission of volatility between the variables under study.

Keywords: Credit spread changes, GARCH-in-Mean models, structural framework, volatility transmission.

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Authors: Muñoz-Sanchez, Victor Manuel, Perez-Flores, Antonio Manuel

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The main objective of this paper is to establish the relationship between models of state organization and the various types of collective identity expressed by the Spanish. The question of nationalism and identity ascription in Spain has always been a topic of special importance due to the presence in that country of territories where the population emits very different opinions of nationalist sentiment than the rest of Spain. The current situation of sovereignty challenge of Catalonia to the central government exemplifies the importance of the subject matter. In order to analyze this process of interrelation, we use a secondary data mining by applying the multiple correspondence analysis technique (MCA). As a main result a typology of four types of expression of collective identity based on models of State organization are shown, which are connected with the party position on this issue.

Keywords: Models of organization of the state, nationalism, collective identity, Spain, political parties.

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