Search results for: drying model

Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

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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: 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: Aliyu Usman, Muhaammed Bello Ibrahim, Yusuf D. Amartey, Jibrin M. Kaura

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This research is aimed at investigating the effect of using amorphous silica ash (ASA) obtained from rice husk as a partial replacement of ordinary Portland cement (OPC) on the mechanical and microstructure properties of cement paste and mortar. ASA was used in partial replacement of ordinary Portland cement in the following percentages 3 percent, 5 percent, 8 percent and 10 percent. These partial replacements were used to produce Cement-ASA paste and Cement-ASA mortar. ASA was found to contain all the major chemical compounds found in cement with the exception of alumina, which are SiO2 (91.5%), CaO (2.84%), Fe2O3 (1.96%), and loss on ignition (LOI) was found to be 9.18%. It also contains other minor oxides found in cement. Consistency of Cement-ASA paste was found to increase with increase in ASA replacement. Likewise, the setting time and soundness of the Cement-ASA paste also increases with increase in ASA replacements. The test on hardened mortar were destructive in nature which include flexural strength test on prismatic beam (40mm x 40mm x 160mm) at 2, 7, 14 and 28 days curing and compressive strength test on the cube size (40mm x 40mm, by using the auxiliary steel platens) at 2,7,14 and 28 days curing. The Cement-ASA mortar flexural and compressive strengths were found to be increasing with curing time and decreases with cement replacement by ASA. It was observed that 5 percent replacement of cement with ASA attained the highest strength for all the curing ages and all the percentage replacements attained the targeted compressive strength of 6N/mm2 for 28 days. There is an increase in the drying shrinkage of Cement-ASA mortar with curing time, it was also observed that the drying shrinkages for all the curing ages were greater than the control specimen all of which were greater than the code recommendation of less than 0.03%. The scanning electron microscope (SEM) was used to study the Cement-ASA mortar microstructure and to also look for hydration product and morphology.

Keywords: amorphous silica ash, cement mortar, cement paste, scanning electron microscope

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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: Katarzyna Baruch, Agata Szelag, Aleksandra Majchrzak, Tadeusz Kamisinski

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Methodology of measurement of sound absorption coefficient in scaled models is based on the ISO 354 standard. The measurement is realised indirectly - the coefficient is calculated from the reverberation time of an empty chamber as well as a chamber with an inserted sample. It is crucial to maintain the atmospheric conditions stable during both measurements. Possible differences may be amended basing on the formulas for atmospheric attenuation coefficient α given in ISO 9613-1. Model studies require scaling particular factors in compliance with specified characteristic numbers. For absorption coefficient measurement, these are for example: frequency range or the value of attenuation coefficient m. Thanks to the possibilities of modern electroacoustic transducers, it is no longer a problem to scale the frequencies which have to be proportionally higher. However, it may be problematic to reduce values of the attenuation coefficient. It is practically obtained by drying the air down to a defined relative humidity. Despite the change of frequency range and relative humidity of the air, ISO 9613-1 standard still allows the calculation of the amendment for little differences of the atmospheric conditions in the chamber during measurements. The paper discusses a number of theoretical analyses and experimental measurements performed in order to obtain consistency between the values of attenuation coefficient calculated from the formulas given in the standard and by measurement. The authors performed measurements of reverberation time in a chamber made in a 1/8 scale in a corresponding frequency range, i.e. 800 Hz - 40 kHz and in different values of the relative air humidity (40% 5%). Based on the measurements, empirical values of attenuation coefficient were calculated and compared with theoretical ones. In general, the values correspond with each other, but for high frequencies and low values of relative air humidity the differences are significant. Those discrepancies may directly influence the values of measured sound absorption coefficient and cause errors. Therefore, the authors made an effort to determine an amendment minimizing described inaccuracy.

Keywords: air absorption correction, attenuation coefficient, dimensional analysis, model study, scaled modelling

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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: 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: Daniela N. Correa-Llantén, Sebastián A. Muñoz-Ibacache, Mathilde Maire, Jenny M. Blamey

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The biosynthesis of nanoparticles by microorganisms, on the contrary to chemical synthesis, is an environmentally-friendly process which has low energy requirements. In this investigation, we used the microorganism Geobacillus wiegelii, strain GWE1, an aerobic thermophile belonging to genus Geobacillus, isolated from a drying oven. This microorganism has the ability to reduce selenite evidenced by the change of color from colorless to red in the culture. Elemental analysis and composition of the particles were verified using transmission electron microscopy and energy-dispersive X-ray analysis. The nanoparticles have a defined spherical shape and a selenium elemental state. Previous experiments showed that the presence of the whole microorganism for the reduction of selenite was not necessary. The results strongly suggested that an intracellular NADPH/NADH-dependent reductase mediates selenium nanoparticles synthesis under aerobic conditions. The enzyme was purified and identified by mass spectroscopy MALDI-TOF TOF technique. The enzyme is a 1-pyrroline-5-carboxylate dehydrogenase. Histograms of nanoparticles sizes were obtained. Size distribution ranged from 40-160 nm, where 70% of nanoparticles have less than 100 nm in size. Spectroscopic analysis showed that the nanoparticles are composed of elemental selenium. To analyse the effect of pH in size and morphology of nanoparticles, the synthesis of them was carried out at different pHs (4.0, 5.0, 6.0, 7.0, 8.0). For thermostability studies samples were incubated at different temperatures (60, 80 and 100 ºC) for 1 h and 3 h. The size of all nanoparticles was less than 100 nm at pH 4.0; over 50% of nanoparticles have less than 100 nm at pH 5.0; at pH 6.0 and 8.0 over 90% of nanoparticles have less than 100 nm in size. At neutral pH (7.0) nanoparticles reach a size around 120 nm and only 20% of them were less than 100 nm. When looking at temperature effect, nanoparticles did not show a significant difference in size when they were incubated between 0 and 3 h at 60 ºC. Meanwhile at 80 °C the nanoparticles suspension lost its homogeneity. A change in size was observed from 0 h of incubation at 80ºC, observing a size range between 40-160 nm, with 20% of them over 100 nm. Meanwhile after 3 h of incubation at size range changed to 60-180 nm with 50% of them over 100 nm. At 100 °C the nanoparticles aggregate forming nanorod structures. In conclusion, these results indicate that is possible to modulate size and shape of biologically synthesized nanoparticles by modulating pH and temperature.

Keywords: genus Geobacillus, NADPH/NADH-dependent reductase, selenium nanoparticles, biosynthesis

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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: Vinci Mojamdar, Govind S. Gupta

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Moving beds in the presence of gas flow are widely used in metallurgical and chemical industries like blast furnaces, catalyst reforming, drying, etc. Pressure drop studies in co- and counter – current conditions have been done by a few researchers. However, to the best of authours knowledge, proper pressure drop study with lateral gas injection lacks especially in the presence of cavity and nozzle protrusion inside the packed bed. The latter study is more useful for metallurgical industries for the processes such as blast furnaces, shaft reduction and, COREX. In this experimental work, a two dimensional cold model with slot type nozzle for lateral gas injection along with the plastic beads as packing material and dry air as gas have been used. The variation of pressure drop is recorded at various horizontal and vertical directions in the presence of cavity and nozzle protrusion. The study has been performed in both moving and stationary beds. Also, the experiments have been carried out in both increasing as well as decreasing gas flow conditions. Experiments have been performed at various gas flow rates and packed bed heights. Some interesting results have been reported such as there is no pressure variation in the moving bed for both the increasing and decreasing gas flow condition that is different from the stationary bed. Pressure hysteresis loop has been observed in a stationary bed.

Keywords: lateral gas injection, moving bed, pressure drop, pressure hysteresis, stationary bed

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Authors: Merlin Simo Tagne, Romain Rémond

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This study provides the sorption isotherm, its hysteresis and their mass transfer properties of four Central Africa Tropical woods largely used for building construction: frake, lotofa, sapelle and ayous. Characterization of these three species in particular and Central Africa tropical woods, in general, was necessary to develop conservation and treatment of wood after first transformation using the drying. Isotherms were performed using a dynamic vapor sorption apparatus (Surface Measurement Systems) at 20 and 40°C. The mass diffusivity was determined in steady state using a specific vapometer. Permeability was determined using a specialized device developed to measure over a wide range of permeability values. Permeability and mass transfer properties are determined in the tangential direction with a ‘false’ quartersawn cutting (sapelle and lotofa) and in the radial direction with a ‘false’ flatsawn cutting (ayous and frake). The sample of sapelle, ayous and frake are heartwood when lotofa contains as well as heartwood than sapwood. Results obtained showed that the temperature effect on sorption behavior was low than relative humidity effect. We also observed a low difference between the sorption behavior of our woods and hysteresis of sorption decreases when the temperature increases. Hailwood-Horrobin model’s predicts the isotherms of adsorption and desorption of ours woods and parameters of this model are proposed. Results on the characterization of mass transfer properties showed that, in the steady state, mass diffusivity decreases exponentially when basal density increases. In the phase of desorption, mass diffusivity is great than in the phase of adsorption. The permeability of ours woods are greater than Australian hardwoods but lower than temperate woods. It is difficult to define a relationship between permeability and mass diffusivity.

Keywords: tropical woods, sorption isotherm, diffusion coefficient, gas permeability, Central Africa

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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: Abu Yousuf, Maksudur Rahman Khan, Ahasanul Karim, Amirul Islam, Minhaj Uddin Monir, Sharmin Sultana, Domenico Pirozzi

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Traditional biodiesel feedstock like edible oils or plant oils, animal fats and cooking waste oil have been replaced by microbial oil in recent research of biodiesel synthesis. The well-known community of microbial oil producers includes microalgae, oleaginous yeast and seaweeds. Conventional transesterification of microbial oil to produce biodiesel is lethargic, energy consuming, cost-ineffective and environmentally unhealthy. This process follows several steps such as microbial biomass drying, cell disruption, oil extraction, solvent recovery, oil separation and transesterification. Therefore, direct transesterification of biodiesel synthesis has been studying for last few years. It combines all the steps in a single reactor and it eliminates the steps of biomass drying, oil extraction and separation from solvent. Apparently, it seems to be cost-effective and faster process but number of difficulties need to be solved to make it large scale applicable. The main challenges are microbial cell disruption in bulk volume and make faster the esterification reaction, because water contents of the medium sluggish the reaction rate. Several methods have been proposed but none of them is up to the level to implement in large scale. It is still a great challenge to extract maximum lipid from microbial cells (yeast, fungi, algae) investing minimum energy. Electroporation technique results a significant increase in cell conductivity and permeability caused due to the application of an external electric field. Electroporation is required to alter the size and structure of the cells to increase their porosity as well as to disrupt the microbial cell walls within few seconds to leak out the intracellular lipid to the solution. Therefore, incorporation of electroporation techniques contributed in direct transesterification of microbial lipids by increasing the efficiency of biodiesel production rate.

Keywords: biodiesel, electroporation, microbial lipids, transesterification

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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: Christina Drosou, Konstantina E. Kyriakopoulou, Andreas Bimpilas, Dimitrios Tsimogiannis, Magdalini C. Krokida

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Rationale: Agiorgitiko is one of the most widely-grown and commercially well-established red wine varieties in Greece. Each year viticulture industry produces a large amount of waste consisting of grape skins and seeds (pomace) during a short period. Grapes contain polyphenolic compounds which are partially transferred to wine during winemaking. Therefore, winery wastes could be an alternative cheap source for obtaining such compounds with important antioxidant activity. Specifically, red grape waste contains anthocyanins and flavonols which are characterized by multiple biological activities, including cardioprotective, anti-inflammatory, anti-carcinogenic, antiviral and antibacterial properties attributed mainly to their antioxidant activity. Ultrasound assisted extraction (UAE) is considered an effective way to recover phenolic compounds, since it combines the advantage of mechanical effect with low temperature. Moreover, green solvents can be used in order to recover extracts intended for used in the food and nutraceutical industry. Apart from the extraction, pre-treatment process like drying can play an important role on the preservation of the grape pomace and the enhancement of its antioxidant capacity. Objective: The aim of this study is to recover natural extracts from winery waste with high antioxidant capacity using green solvents so they can be exploited and utilized as enhancers in food or nutraceuticals. Methods: Agiorgitiko grape pomace was dehydrated by air drying (AD) and accelerated solar drying (ASD) in order to explore the effect of the pre-treatment on the recovery of bioactive compounds. UAE was applied in untreated and dried samples using water and water: ethanol (1:1) as solvents. The total antioxidant potential and phenolic content of the extracts was determined using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and Folin-Ciocalteu method, respectively. Finally, the profile of anthocyanins and flavonols was specified using HPLC-DAD analysis. The efficiency of processes was determined in terms of extraction yield, antioxidant activity, phenolic content and the anthocyanins and flavovols profile. Results & Discussion: The experiments indicated that the pre-treatment was essential for the recovery of highly nutritious compounds from the pomace as long as the extracts samples showed higher phenolic content and antioxidant capacity. Water: ethanol (1:1) was considered a more effective solvent on the recovery of phenolic compounds. Moreover, ASD grape pomace extracted with the solvent system exhibited the highest antioxidant activity (IC50=0.36±0.01mg/mL) and phenolic content (TPC=172.68±0.01mgGAE/g dry extract), followed by AD and untreated pomace. The major compounds recovered were malvidin3-O-glucoside and quercetin3-O-glucoside according to the HPLC analysis. Conclusions: Winery waste can be exploited for the recovery of nutritious compounds using green solvents such as water or ethanol. The pretreatment of the pomace can significantly affect the concentration of phenolic compounds, while UAE is considered a highly effective extraction process.

Keywords: agiorgitico grape pomace, antioxidants, phenolic compounds, ultrasound assisted extraction

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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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