Search results for: dilution model

Authors: Adji Achmad Rinaldo Fernandes

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SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Marcin Debowski, Marcin Zielinski, Magdalena Zielinska, Paulina Rusanowska

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The problem with digestate management is one of the most important factors influencing on the development and operation of biogas plant. Turbidity and bacterial contamination negatively affect the growth of algae, which can limit the use of the effluent in the production of algae biomass on a large scale. These problems can be overcome by cultivating of algae species resistant to environmental factors, such as Chlorella sp., Scenedesmus sp., or reducing load of organic compounds to prevent bacterial contamination. The effluent requires dilution and/or purification. One of the methods of effluent treatment is the use of a membrane technology such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO), depending on the membrane pore size and the cut off point. Membranes are a physical barrier to solids and particles larger than the size of the pores. MF membranes have the largest pores and are used to remove turbidity, suspensions, bacteria and some viruses. UF membranes remove also color, odor and organic compounds with high molecular weight. In treatment of wastewater or other waste streams, MF and UF can provide a sufficient degree of purification. NF membranes are used to remove natural organic matter from waters, water disinfection products and sulfates. RO membranes are applied to remove monovalent ions such as Na⁺ or K⁺. The effluent was used in UF for medium to cultivation of two microalgae: Chlorella sp. and Phaeodactylum tricornutum. Growth rates of Chlorella sp. and P. tricornutum were similar: 0.216 d⁻¹ and 0.200 d⁻¹ (Chlorella sp.); 0.128 d⁻¹ and 0.126 d⁻¹ (P. tricornutum), on synthetic medium and permeate from UF, respectively. The final biomass composition was also similar, regardless of the medium. Removal of nitrogen was 92% and 71% by Chlorella sp. and P. tricornutum, respectively. The fermentation effluents after UF and dilution were also used for cultivation of algae Scenedesmus sp. that is resistant to environmental conditions. The authors recommended the development of biorafinery based on the production of algae for the biogas production. There are examples of using a multi-stage membrane system to purify the liquid fraction from digestate. After the initial UF, RO is used to remove ammonium nitrogen and COD. To obtain a permeate with a concentration of ammonium nitrogen allowing to discharge it into the environment, it was necessary to apply three-stage RO. The composition of the permeate after two-stage RO was: COD 50–60 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 300–320 mg/dm³, total nitrogen 320–340 mg/dm³, total phosphorus 53 mg/dm³. However compostion of permeate after three-stage RO was: COD < 5 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 0 mg/dm³, total nitrogen 3.5 mg/dm³, total phosphorus < 0,05 mg/dm³. Last stage of RO might be replaced by ion exchange process. The negative aspect of membrane filtration systems is the fact that the permeate is about 50% of the introduced volume, the remainder is the retentate. The management of a retentate might involve recirculation to a biogas plant.

Keywords: digestate, membrane filtration, microalgae cultivation, Chlorella sp.

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Kusumawadee Thancharoen, Rungrat Nontawong, Thanawat Junsom

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Pathogenic bacterial flora was isolated from giant freshwater prawns, Macrobrachium rosenbergii. Infected shrimp samples were collected from BuaBan Aquafarm in Kalasin Province, Thailand, between June and September 2018. Bacterial species were isolated by serial dilution and plated on Thiosulfate Citrate Bile Salt Sucrose (TCBS) agar medium. A total 89 colonies were isolated and identified using the API 20E biochemical tests. Results showed the presence of genera Aeromonas, Citrobacter, Chromobacterium, Providencia, Pseudomonas, Stenotrophomonas and Vibrio. Maximum number of species was recorded in Pseudomonas (50.57%) with minimum observed in Chromobacterium and Providencia (1.12%).

Keywords: biochemical test, giant freshwater prawn, isolation, salt tolerance, shrimp diseases

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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Authors: J. Rhodes, V. Cheng, P. Lok

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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Debanjan Dey, Tamal Banerjee, Kaustubha Mohanty

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Global scalar properties are calculated based on higher occupied molecular orbital (HOMO) and lower unoccupied molecular orbital (LUMO) energy to study the interaction between ionic liquids with Bituminous and Anthracite coal using density function theory (DFT) method. B3LYP/6-31G* calculation predicts HOMO-LUMO energy gap, electronegativity, global hardness, global softness, chemical potential and global softness for individual compounds with their clusters. HOMO-LUMO interaction, electron delocalization, electron donating and accepting is the main source of attraction between individual compounds with their complexes. Cation used in this study: 1-butyl-1-methylpyrrolidinium [BMPYR], 1-methyl -3-propylimmidazolium [MPIM], Tributylmethylammonium [TMA] and Tributylmethylphosphonium [MTBP] with the combination of anion: bis(trifluromethylsulfonyl)imide [Tf2N], methyl carbonate [CH3CO3], dicyanamide [N(CN)2] and methylsulfate [MESO4]. Basically three-tier approach comprising HOMO/LUMO energy, Scalar quantity and infinite dilution activity coefficient (IDAC) by sigma profile generation with COSMO-RS (Conductor like screening model for real solvent) model was chosen for simultaneous interaction. [BMPYR]CH3CO3] (1-butyl-1-methylpyrrolidinium methyl carbonate) and [MPIM][CH3CO3] (1-methyl -3-propylimmidazolium methyl carbonate ) are the best effective ILs on the basis of HOMO-LUMO band gap for Anthracite and Bituminous coal respectively and the corresponding band gap is 0.10137 hartree for Anthracite coal and 0.12485 hartree for Bituminous coal. Further ionic liquids are screened quantitatively with all the scalar parameters and got the same result based on CH-π interaction which is found for HOMO-LUMO gap. To check our findings IDAC were predicted using quantum chemical based COSMO-RS methodology which gave the same trend as observed our scalar quantity calculation. Thereafter a qualitative measurement is doing by sigma profile analysis which gives complementary behavior between IL and coal that means highly miscible with each other.

Keywords: coal-ionic liquids cluster, COSMO-RS, DFT method, HOMO-LUMO interaction

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Tahir Imran Qureshi

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This study was aimed at finding out effects of potential influence of alkalinity on the treatment of landfill leachate through the growth of algae at varying dilution rates and toxicity potential. pH control proved to be an effective factor influencing on algal growth. With the use of algae Scenedesmus sp. for the treatment of leachate, a sharp increase in the growth of algae was recorded until pH 9. However, at pH 9.3 and 25 °C temperature, the growing trend of algae population showed a weakening tendency with the increase of total alkalinity in the leachate solution. Highest growth of algae was recorded in the leachate samples with alkalinity ranged at 1500-2500 mg CaCO3/L under neutral condition at pH 7 after 48 hours of cultivation time. Under the similar conditions, total nitrogen and total phosphorous in the leachate also reduced to 80% and 85%, respectively, however, no significant removal of COD was observed during the course of experiment.

Keywords: leachate treatment, microalgae, nutrient removal, ammonia toxicity

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Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

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Authors: Purnima Dhall, Rita Kumar

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Introduction: River Yamuna, in the national capital territory (NCT), and also the primary source of drinking water for the city. Delhi discharges about 3,684 MLD of sewage through its 18 drains in to the Yamuna. Water quality monitoring is an important aspect of water management concerning to the pollution control. Public concern and legislation are now a day’s demanding better environmental control. Conventional method for estimating BOD5 has various drawbacks as they are expensive, time-consuming, and require the use of highly trained personnel. Stringent forthcoming regulations on the wastewater have necessitated the urge to develop analytical system, which contribute to greater process efficiency. Biosensors offer the possibility of real time analysis. Methodology: In the present study, a novel rapid method for the determination of biochemical oxygen demand (BOD) has been developed. Using the developed method, the BOD of a sample can be determined within 2 hours as compared to 3-5 days with the standard BOD3-5day assay. Moreover, the test is based on specified consortia instead of undefined seeding material therefore it minimizes the variability among the results. The device is coupled to software which automatically calculates the dilution required, so, the prior dilution of the sample is not required before BOD estimation. The developed BOD-Biosensor makes use of immobilized microorganisms to sense the biochemical oxygen demand of industrial wastewaters having low–moderate–high biodegradability. The method is quick, robust, online and less time consuming. Findings: The results of extensive testing of the developed biosensor on drains demonstrate that the BOD values obtained by the device correlated with conventional BOD values the observed R2 value was 0.995. The reproducibility of the measurements with the BOD biosensor was within a percentage deviation of ±10%. Advantages of developed BOD biosensor • Determines the water pollution quickly in 2 hours of time; • Determines the water pollution of all types of waste water; • Has prolonged shelf life of more than 400 days; • Enhanced repeatability and reproducibility values; • Elimination of COD estimation. Distinctiveness of Technology: • Bio-component: can determine BOD load of all types of waste water; • Immobilization: increased shelf life > 400 days, extended stability and viability; • Software: Reduces manual errors, reduction in estimation time. Conclusion: BiosensorBOD can be used to measure the BOD value of the real wastewater samples. The BOD biosensor showed good reproducibility in the results. This technology is useful in deciding treatment strategies well ahead and so facilitating discharge of properly treated water to common water bodies. The developed technology has been transferred to M/s Forbes Marshall Pvt Ltd, Pune.

Keywords: biosensor, biochemical oxygen demand, immobilized, monitoring, Yamuna

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

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Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

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Authors: H. Namazi, H. T. N. Kuan

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It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

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Authors: Yanshuang Zhang, Byungho Jeong

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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. 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, research activities

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Authors: Zainab Magaji Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

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The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: validation, verification, formal, theorem prover

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: A. Lakrim, D. Tahri

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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: S. Jayasinghe, W. G. D. Wickramasingha, V. Karunaratne, D. N. Karunaratne, A. Ekanayake

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Multi-drug resistant microbial pathogens are a serious global health problem, and hence, there is an urgent necessity for discovering new drug therapeutics. However, finding alternatives is a one of the biggest challenges faced by the global drug industry due to the spiraling high cost and serious side effects associated with modern medicine. On the other hand, plants and their secondary metabolites can be considered as good sources of scaffolds to provide structurally diverse bioactive compounds as potential therapeutic agents. 6β-hydroxy betunolic acid is a triterpenoid isolated from bark of Schumacheria castaneifolia which is an endemic plant to Sri Lanka which has shown antibacterial activity against both Staphylococcus aureus (ATCC 29213) and methicillin-resistant S. aureus with Minimum Inhibition Concentration (MIC) of 16 µg/ml. The objective of this study was to determine the anti-bacterial activity for the derivatives of 6β- hydroxy betunolic acid against standard strains of Staphylococcus aureus (ATCC 29213 and ATCC 25923), Enterococcus faecalis (ATCC 29212), Escherichia coli (ATCC 35218 and ATCC 25922), Pseudomonas aeruginosa (ATCC 27853), carbepenemas produce Kebsiella pneumonia (ATCC BAA 1705) and carbepenemas non produce Kebsiella pneumonia (ATCC BAA 1706) and four stains of clinically isolated methicillin resistance S. aureus and Acinetobacter. Structural analogues of 6β-hydroxy betunolic acid were synthesized by modifying the carbonyl group at C-3 to obtain olefin and oxime, the hydroxyl group at C-6 position to a ketone, the carboxylic acid at C-17 to obtain amide and halo ester and the olefin group at C-20 position to obtain epoxide. Chemical structures of the synthesized analogues were confirmed with spectroscopic data and antibacterial activity was determined through broth micro dilution assay. Results revealed that 6β- hydroxy betunolic acid shows significant antibacterial activity only against the Gram positive strains and it was inactive against all the tested Gram negative strains for the tested concentration range. However, structural modifications into oxime and olefin at C-3, ketone at C-6 and epoxide at C-20 decreased its antibacterial activity against the gram positive organisms and it was totally lost with the both modifications at C-17 into amide and ester. These results concluded that the antibacterial activity of 6β- hydroxy betunolic acid and derivatives is predominantly depending on the cell wall difference of the bacteria and the presence of carboxylic acid at C-17 is highly important for the antibacterial activity against Gram positive organisms.

Keywords: antibacterial activity, 6β- hydroxy betunolic acid, broth micro dilution assay, structure activity relationship

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

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Authors: Yuriy A. Shevchenko, Konstantin V. Nefedev

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We consider the antiferromagnetic systems of Ising spins located at the sites of the hexagonal, triangular and pyrochlore lattices. Such systems can be diluted to a certain concentration level by randomly replacing the magnetic spins with nonmagnetic ones. Quite recently we studied density of states (DOS) was calculated by the Wang-Landau method. Based on the obtained data, we calculated the dependence of the residual entropy (entropy at a temperature tending to zero) on the dilution concentration for quite large systems (more than 2000 spins). In the current study, we obtained the same data for small systems (less than 20 spins) by a complete search of all possible magnetic configurations and compared the result with the result for large systems. The shape of the curve remains unchanged in both cases, but the specific values of the residual entropy are different because of the finite size effect.

Keywords: entropy, pyrochlore, spin ice, Wang-Landau algorithm

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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