Search results for: elaboration likelihood model

Authors: V. Radulescu, S. Dumitru

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Introduction: Determination of the temperature field inside a fluid in motion has many practical issues, especially in the case of turbulent flow. The phenomenon is greater when the solid walls have a different temperature than the fluid. The turbulent heat and mass transfer have an essential role in case of the thermal pollution, as it was the recorded during the damage of the Thermoelectric Power-plant Oradea (closed even today). Basic Methods: Solving the theoretical turbulent thermal pollution represents a particularly difficult problem. By using the semi-empirical theories or by simplifying the made assumptions, based on the experimental measurements may be assured the elaboration of the mathematical model for further numerical simulations. The three zones of flow are analyzed separately: the vicinity of the solid wall, the turbulent transition zone, and the turbulent core. For each area are determined the distribution law of temperature. It is determined the dependence of between the Stanton and Prandtl numbers with correction factors, based on measurements experimental. Major Findings/Results: The limitation of the laminar thermal substrate was determined based on the theory of Landau and Levice, using the assumption that the longitudinal component of the velocity pulsation and the pulsation’s frequency varies proportionally with the distance to the wall. For the calculation of the average temperature, the formula is used a similar solution as for the velocity, by an analogous mediation. On these assumptions, the numerical modeling was performed with a gradient of temperature for the turbulent flow in pipes (intact or damaged, with cracks) having 4 different diameters, between 200-500 mm, as there were in the Thermoelectric Power-plant Oradea. Conclusions: It was made a superposition between the molecular viscosity and the turbulent one, followed by addition between the molecular and the turbulent transfer coefficients, necessary to elaborate the theoretical and the numerical modeling. The concept of laminar boundary layer has a different thickness when it is compared the flow with heat transfer and that one without a temperature gradient. The obtained results are within the margin of error of 5%, between the semi-empirical classical theories and the developed model, based on the experimental data. Finally, it is obtained a general correlation between the Stanton number and the Prandtl number, for a specific flow (with associated Reynolds number).

Keywords: experimental measurements, numerical correlations, thermal pollution through pipelines, turbulent thermal flow

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

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Authors: Anna Avramenko, Heikki Haario

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This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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Authors: Jui-Ching Chou

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Numerical simulation is a popular method used to evaluate the effects of soil liquefaction on a structure or the effectiveness of a mitigation plan. Many constitutive models (UBCSAND model, PM4 model, SANISAND model, etc.) were presented to model the liquefaction phenomenon. In general, inputs of a constitutive model need to be calibrated against the soil cyclic resistance before being applied to the numerical simulation model. Then, simulation results can be compared with results from simplified liquefaction potential assessing methods. In this article, inputs of the UBCSAND model, a simple elastic-plastic stress-strain model, are calibrated against several popular generic liquefaction triggering curves of simplified liquefaction potential assessing methods via FLAC program. Calibrated inputs can provide engineers to perform a preliminary evaluation of an existing structure or a new design project.

Keywords: calibration, liquefaction, numerical simulation, UBCSAND Model

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

Abstract:

Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

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Authors: F. Z. Benabid, S. Kridi, F. Zouai, D. Benachour

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The aim of present work is to characterize the PP/TiO2 blends as composites, and study the effect of TiO2 on properties of different compositions and the evaluation of the effectiveness of the method used for filler treatment. Nanocomposite samples were synthesized by molten route in an internal mixer. The TiO2 nanoparticles were treated with stearic acid in order to obtain a good dispersion, and the demonstration of the effectiveness of the treatment on the morphology and roughness of the nanofiller was established by microstructural analysis by FTIR and AFM. The various developed nanocomposite compositions were characterized by different methods; i.e. FTIR, XRD, SEM and optical microscopy. Rheological, dielectric and mechanical studies were also performed. The results showed a remarkable increase in the impact strength results which increased about 39% compared to neat PP. The rheological study showed an increase in the fluidity in all developed composite compositions, involved by the good dispersion of TiO2 particles.

Keywords: composites, PP, TiO2, comixing, mechanical treatment

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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: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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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: Aron Miranda Burgos, Ergon Cugler de Moraes Silva

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In the present article, it is observed that the constant advancement of issues related to misinformation impacts the guarantee of the public policy cycle. Thus, it is found that the dissemination of false information has a direct influence on each of the component stages of this cycle. Therefore, in order to maintain scientific and theoretical credibility in the qualitative analysis process, it was necessary to logically interpose the concepts of firehosing of falsehood, fake news, public policy cycle, as well as using the epistemological and pragmatic mechanism at the intersection of such academic concepts, such as the scientific method. It was found, through the analysis of official documents and public notes, how the multiple theoretical perspectives evidence the commitment of the provision and elaboration of public policies, verifying the way in which the fake news impact each part of the process in this atmosphere.

Keywords: firehosing of falsehood, governance, misinformation, post-truth

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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: Chandanee Wasana Kalansooriya

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Dietary behaviour is a crucial factor affecting diabetes control. With increasing rates of diabetes prevalence in Asian countries, examining their dietary patterns, which are largely based on rice, is timely required. It has been identified that higher consumption of some rice varieties is associated with increased risk of type 2 diabetes. Although diabetes patients are advised to consume healthier rice varieties, which contains low glycemic, several conditions, one of which food insecurity, make them difficult to preserve those healthy dietary guidelines. Hence this study tries to investigate how food security affects on making right decisions of rice consumption within diabetes affected households using a sample from Sri Lanka, a country which rice considered as the staple food and records the highest diabetes prevalence rate in South Asia. The study uses data from the Household Income and Expenditure Survey 2016, a nationally representative sample conducted by the Department of Census and Statistics, Sri Lanka. The survey used a two-stage stratified sampling method to cover different sectors and districts of the country and collected micro-data on demographics, health, income and expenditures of different categories. The study uses data from 2547 households which consist of one or more diabetes patients, based on the self-recorded health status. The Household Dietary Diversity Score (HDDS), which constructed based on twelve food groups, is used to measure the level of food security. Rice is categorized into three groups according to their Glycemic Index (GI), high GI, medium GI and low GI, and the likelihood and impact made by food security on each rice consumption categories are estimated using a Two-part Model. The shares of each rice categories out of total rice consumption is considered as the dependent variable to exclude the endogeneity issue between rice consumption and the HDDS. The results indicate that the consumption of medium GI rice is likely to increase with the increasing household food security, but low GI varieties are not. Households in rural and estate sectors are less likely and Tamil ethnic group is more likely to consume low GI rice varieties. Further, an increase in food security significantly decreases the consumption share of low GI rice, while it increases the share of medium GI varieties. The consumption share of low GI rice is largely affected by the ethnic variability. The effects of food security on the likelihood of consuming high GI rice varieties and changing its shares are statistically insignificant. Accordingly, the study concludes that a higher level of food security does not ensure diabetes patients are consuming healthy rice varieties or reducing consumption of unhealthy varieties. Hence policy attention must be directed towards educating people for making healthy dietary choices. Further, the study provides a room for further studies as it reveals considerable ethnic and sectorial differences in making healthy dietary decisions.

Keywords: diabetes, food security, glycemic index, rice consumption

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Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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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: Rakan Alajmi, Rahaf Alnazzawi, Yara Aljefri, Abdullah Alafif, Ali Alraddadi, Awadh Alamri

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Background: The distribution of physicians in different specialties across Saudi Arabia is determined by the career choices of medical students. Dermatology residency program is one of the highly competitive programs here in Saudi Arabia. Assessing and understanding the factors perceived to be attractive in choosing dermatology will aid the directors of the specialty programs to plan for a more balanced workforce distribution to better suit the needs of the specialties. Aim: The aim of our study is to determine and assess the factors perceived to be significantly attractive when choosing dermatology as a future specialty. Methods: The study is a cross-sectional study conducted in King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia. A validated questionnaire was sent electronically to clinical year medical students. In addition to the questionnaire, gender, grade point average, preferred specialty, and other socio-demographic data were assessed. Results: A total of 121 clinical years medical students completed the questionnaire, 8 (6.6%) preferred dermatology as a specialty. 76 (62.8%) of the participants score a grade point average of more than 4.5 and 83 students (68.6%) chose their specialty during clinical years. The appeal of being a dermatologist (P= 0.047), the portrayal of different specialities in the media (P= 0.005), and the likelihood that dermatologists can influence patients’ lives (P=0.010) were shown to be significantly attractive factors. Conclusion: There are many factors that are affecting students’ choices when choosing a medical specialty. The appeal of being a dermatologist, the portrayal of different specialities in the media, and the likelihood that dermatologists can influence patients’ lives were shown to be significantly attractive factors when choosing dermatology as a future specialty. Recognizing medical students’ specialty perception will lead them to a proper specialty tailored to their needs.

Keywords: dermatology, career choice, medical specialties, student's perception

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Authors: Chloe Shu-Hua Yeh

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Effects of videogame play on players cognitive abilities is a growing research field in the recent decades, however, little is known about how ‘out-of-school’ use of videogame influences creativity. This interdisciplinary research explores the cognitive and emotional effects of two different types of online videogames (an action videogame and a non-action videogame) on subsequent creativity performances using a within-participant design study with 36 participants. Results showed that after playing the action game participants performed higher originality, elaboration and flexibility than after playing the causal game. The results explored effects of emotional states elicited during playing the games suggesting that arousal may be a significant emotional factor which influence subsequent creativity performance. The cognitive and emotional effects of videogame were discussed followed with implications for emotion-creativity-videogame play research, game designers, educational practitioners and parents.

Keywords: attentional breadth, creativity, emotion, videogame play

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Authors: A. Harras, A. Tsuji, K. Terada

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Tracking of moving people has gained a matter of great importance due to rapid technological advancements in the field of computer vision. The objective of this study is to design a motion based detection and tracking multiple walking pedestrians randomly in different directions. In our proposed method, Gaussian mixture model (GMM) is used to determine moving persons in image sequences. It reacts to changes that take place in the scene like different illumination; moving objects start and stop often, etc. Background noise in the scene is eliminated through applying morphological operations and the motions of tracked people which is determined by using the Kalman filter. The Kalman filter is applied to predict the tracked location in each frame and to determine the likelihood of each detection. We used a benchmark data set for the evaluation based on a side wall stationary camera. The actual scenes from the data set are taken on a street including up to eight people in front of the camera in different two scenes, the duration is 53 and 35 seconds, respectively. In the case of walking pedestrians in close proximity, the proposed method has achieved the detection ratio of 87%, and the tracking ratio is 77 % successfully. When they are deferred from each other, the detection ratio is increased to 90% and the tracking ratio is also increased to 79%.

Keywords: automatic detection, tracking, pedestrians, counting

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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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: 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: Tarek S. Jamil, H. A. Abbas, Rabab A. Nasr, Eman S. Mansor, Rose-Noëlle Vannier

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The citrate manner (Pechini method) was utilized in elaboration of a novel Nano-sized BaFe(1-x)CuxO3 (x=0.01, 0.05 and 0.10). The prepared photocatalysts were characterized by x-ray diffraction, diffuse reflectance, TEM and the surface area. The prepared samples have a mixture of cubic perovskite structure (main) and orthorhombic phases. The effect of different loads of copper as dopant on the structural properties as well as the photocatalytic activity was demonstrated. The lattice parameter and the unit cell volume of the prepared materials are given. Doping with copper increased the photocatalytic activity of BaFeO3 several times in abstraction of hazardous atrazine that causes acute problems in drinking water treatment facilities. This may be reasoned to low band gap energy of copper doped BaFe(1-x)CuxO3 attributed to oxygen vacancies formation.

Keywords: photocatalysis, nano-sized, BaFeO3, copper doping, atrazine

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Authors: Dmitriy V. Chulkov

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Escalation of commitment is defined as continuation of a project after receiving negative information about it. While literature in management and psychology identified various factors contributing to escalation behavior, this phenomenon has received little analysis in economics, potentially due to the apparent irrationality of escalation. In this study, we present an economic model of escalation with asymmetric information in a principal-agent setup where the agents are responsible for a project selection decision and discover the outcome of the project before the principal. Our theoretical model complements the existing literature on several accounts. First, we link the incentive to escalate commitment to a project with the turnover decision by the manager. When a manager learns the outcome of the project and stops it that reveals that a mistake was made. There is an incentive to continue failing projects and avoid admitting the mistake. This incentive is enhanced when the agent may voluntarily resign from the firm before the outcome of the failing project is revealed, and thus not bear the full extent of reputation damage due to project failure. As long as some successful managers leave the firm for extraneous reasons, outside firms find it difficult to link failing projects with certainty to managers that left a firm. Second, we demonstrate that non-CEO managers have reputation concerns separate from those of the CEO, and thus may escalate commitment to projects they oversee, when such escalation can attenuate damage to reputation from impending project failure. Such incentive for escalation will be present for non-CEO managers if the CEO delegates responsibility for a project to a non-CEO executive. If reputation matters for promotion to the CEO, the incentive for a rising executive to escalate in order to protect reputation is distinct from that of a CEO. Third, our theoretical model is supported by empirical analysis of changes in the firm’s operations measured by the presence of discontinued operations at the time of turnover among the top four members of the top management team. Discontinued operations are indicative of termination of failing projects at a firm. The empirical results demonstrate that in a large dataset of over three thousand publicly traded U.S. firms for a period from 1993 to 2014 turnover by top executives significantly increases the likelihood that the firm discontinues operations. Furthermore, the type of turnover matters as this effect is strongest when at least one non-CEO member of the top management team leaves the firm and when the CEO departure is due to a voluntary resignation and not to a retirement or illness. Empirical results are consistent with the predictions of the theoretical model and suggest that escalation of commitment is primarily observed in decisions by non-CEO members of the top management team.

Keywords: discontinued operations, escalation of commitment, executive turnover, top management teams

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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: Mariam Ismail, Kazeem Rufai, Jeremiah Balogun

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A study was conducted to apply fuzzy logic to the development of a monitoring model for child pornography based on associated risk factors, which can be used by forensic experts or integrated into forensic systems for the early detection of child pornographic activities. A number of methods were adopted in the study, which includes an extensive review of related works was done in order to identify the factors that are associated with child pornography following which they were validated by an expert sex psychologist and guidance counselor, and relevant data was collected. Fuzzy membership functions were used to fuzzify the associated variables identified alongside the risk of the occurrence of child pornography based on the inference rules that were provided by the experts consulted, and the fuzzy logic expert system was simulated using the Fuzzy Logic Toolbox available in the MATLAB Software Release 2016. The results of the study showed that there were 4 categories of risk factors required for assessing the risk of a suspect committing child pornography offenses. The results of the study showed that 2 and 3 triangular membership functions were used to formulate the risk factors based on the 2 and 3 number of labels assigned, respectively. The results of the study showed that 5 fuzzy logic models were formulated such that the first 4 was used to assess the impact of each category on child pornography while the last one takes the 4 outputs from the 4 fuzzy logic models as inputs required for assessing the risk of child pornography. The following conclusion was made; there were factors that were related to personal traits, social traits, history of child pornography crimes, and self-regulatory deficiency traits by the suspects required for the assessment of the risk of child pornography crimes committed by a suspect. Using the values of the identified risk factors selected for this study, the risk of child pornography can be easily assessed from their values in order to determine the likelihood of a suspect perpetuating the crime.

Keywords: fuzzy, membership functions, pornography, risk factors

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Authors: Mulusew G. Jebena, David Lindstrom, Tefera Belachew, Craig Hadley, Carl Lachat, Patrick Kolsteren

Abstract:

Background: The biological and psychosocial consequence of food insecurity on physical health and nutritional status has been reported. But, its effect on mental health during adolescence remains unexplored. Thus, the main aim of this analysis is to examine the mechanism by which food insecurity is linked to mental health among adolescents living in Jimma, Southwest Ethiopia. Methods: We used data from third round observation of Jimma Longitudinal Family and Youth Survey (JLFSY). A total of 1,521 adolescents included for the main analysis. Food insecurity was measured using 5-items scale and The Self Reporting Questionnaire (SRQ-20) was used to measure mental distress. Structural equation modeling analysis was done using maximum likelihood estimation method. Model diagnostics test was reported. All p values were two tailed and P value ≤ 0.05 was used to determine statistical significance. Results: The prevalence of mental distress was 20.8%, 95% CI: (18.8, 22.9). After adjusted for covariates, the final model depicts food insecurity was associated with adolescent mental distress (β=.324). This analysis showed 94.1% of the effect of food insecurity on mental distress is direct. By contrast, 5.9% of the food insecurity effect is mediated by physical health. In addition, Self-rated health (β=.356), socioeconomic status (β=-.078) parental educational (β= .170), living in urban (β= .193) and female headed household (β=.205) were associated with adolescent mental distress. Conclusions: This finding highlights the direct effect of food insecurity on adolescent mental distress. Therefore, any intervention aimed to improve mental distress of adolescents should consider strategies to improve access to sufficient, safe, and nutritious food. Beside this, prevention of underlying factors such as psychosomatic health illness and improving socio economic status is also very critical. Furthermore longitudinal relationship of the long term effect of food insecurity on mental health should be investigated.

Keywords: adolescent, Ethiopia, food insecurity, mental health

Procedia PDF Downloads 586

Authors: Nebojsa Stefanovic, Sasa Milijic, Natasa Danilovic Hristic

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Spatial plan of the special purpose area constitutes a basic tool in the planning of infrastructure corridor of a highway. The aim of the plan is to define the planning basis and provision of spatial conditions for the construction and operation of the highway, as well as for developing other infrastructure systems in the corridor. This paper presents a methodology and approach to the preparation of the Spatial Plan for the special purpose area for the infrastructure corridor of the highway E-80, Section Niš-Merdare in Serbia. The applied methodological approach is based on the combined application of the integrative and participatory method in the decision-making process on the sustainable development of the highway corridor. It was found that, for the planning and management of the infrastructure corridor, a key problem is coordination of spatial and urban planning, strategic environmental assessment and sectoral traffic planning and designing. Through the development of the plan, special attention is focused on increasing the accessibility of the local and regional surrounding, reducing the adverse impacts on the development of settlements and the economy, protection of natural resources, natural and cultural heritage, and the development of other infrastructure systems in the corridor of the highway. As a result of the applied methodology, this paper analyzes the basic features such as coverage, the concept, protected zones, service facilities and objects, the rules of development and construction, etc. Special emphasis is placed to methodology and results of the Strategic Environmental Assessment of the Spatial Plan, and to the importance of protection measures, with the special significance of air and noise protection measures. For evaluation in the Strategic Environmental Assessment, a multicriteria expert evaluation (semi-quantitative method) of planned solutions was used in relation to the set of goals and relevant indicators, based on the basic set of indicators of sustainable development. Evaluation of planned solutions encompassed the significance and size, spatial conditions and probability of the impact of planned solutions on the environment, and the defined goals of strategic assessment. The framework of the implementation of the Spatial Plan is presented, which is determined for the simultaneous elaboration of planning solutions at two levels: the strategic level of the spatial plan and detailed urban plan level. It is also analyzed the relationship of the Spatial Plan to other applicable planning documents for the planning area. The effects of this methodological approach relate to enabling integrated planning of the sustainable development of the infrastructure corridor of the highway and its surrounding area, through coordination of spatial, urban and sectoral traffic planning and design, as well as the participation of all key actors in the adoption and implementation of planned decisions. By the conclusions of the paper, it is pointed to the direction for further research, particularly in terms of harmonizing methodology of planning documentation and preparation of technical-design documentation.

Keywords: corridor, environment, highway, impact, methodology, spatial plan, urban

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

Abstract:

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

Procedia PDF Downloads 637