Search results for: reliable facility location model

Authors: Fujio Akagi, Hiroaki Ito, Shin-Ichi Inage

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The aim of this study is to develop a combustion model that can be applied uniformly to laminar and turbulent premixed flames while considering the effect of the Lewis number (Le). The model considers the effect of Le on the transport equations of the reaction progress, which varies with the chemical species and temperature. The distribution of the reaction progress variable is approximated by a hyperbolic tangent function, while the other distribution of the reaction progress variable is estimated using the approximated distribution and transport equation of the reaction progress variable considering the Le. The validity of the model was evaluated under the conditions of propane with Le > 1 and methane with Le = 1 (equivalence ratios of 0.5 and 1). The estimated results were found to be in good agreement with those of previous studies under all conditions. A method of introducing a turbulence model into this model is also described. It was confirmed that conventional turbulence models can be expressed as an approximate theory of this model in a unified manner.

Keywords: combustion model, laminar flame, Lewis number, turbulent flame

Procedia PDF Downloads 116

Authors: S. W. Chen, W. K. Lin, J. R. Wang, C. Shih, H. T. Lin, H. C. Chang, W. Y. Li

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Kuosheng nuclear power plant (NPP) is a BWR/6 type NPP and located on the northern coast of Taiwan. First, Kuosheng NPP TRACE model were developed in this research. In order to assess the system response of Kuosheng NPP TRACE model, startup tests data were used to evaluate Kuosheng NPP TRACE model. Second, the over pressurization transient analysis of Kuosheng NPP TRACE model was performed. Besides, in order to confirm the mechanical property and integrity of fuel rods, FRAPTRAN analysis was also performed in this study.

Keywords: TRACE, safety analysis, BWR/6, FRAPTRA

Procedia PDF Downloads 557

Authors: S. Yunus, A. Suratman, N. Mohamad Nor, M. Othman

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This paper presents the measurement and simulation results by Finite Element Method (FEM) for earth resistance (R_DC) for interconnected vertical ground rod configurations. The soil resistivity was measured using the Wenner four-pin Method, and R_DC was measured using the Fall of Potential (FOP) method, as outlined in the standard. Genetic Algorithm (GA) is employed to interpret the soil resistivity to that of a 2-layer soil model. The same soil resistivity data that were obtained by Wenner four-pin method were used in FEM for simulation. This paper compares the results of R_DC obtained by FEM simulation with the real measurement at field site. A good agreement was seen for R_DC obtained by measurements and FEM. This shows that FEM is a reliable software to be used for design of earthing systems. It is also found that the parallel rod system has a better performance compared to a similar setup using a grid layout.

Keywords: earthing system, earth electrodes, finite element method, genetic algorithm, earth resistances

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

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Authors: H. Al-Hajeri

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The computation of the effectiveness of turbulence enhancement surface features, such as ribs as means of promoting mixing and hence heat transfer, has attracted the continued attention of the engineering community. In this study, the simulation of a three-dimensional cooling passage is carried out employing a number of turbulence models including Durbin model. The cooling passage consists of a square section duct whose upper and lower surfaces feature staggered cuboid ribs. The main objective of this paper is to provide comparisons of the performance of the v2-f model against other established turbulence models as implemented in the commercial CFD code Ansys Fluent. The present study demonstrates that the v2-f model can successfully capture the isothermal air flow phenomena in flow over obstacles.

Keywords: CFD, cooling passage, Durbin model, turbulence model

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Authors: Othman Maklouf, Abdunnaser Tresh

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Land vehicle navigation is subject of great interest today. Global Positioning System (GPS) is the main navigation system for positioning in such systems. GPS alone is incapable of providing continuous and reliable positioning, because of its inherent dependency on external electromagnetic signals. Inertial Navigation (INS) is the implementation of inertial sensors to determine the position and orientation of a vehicle. The availability of low-cost Micro-Electro-Mechanical-System (MEMS) inertial sensors is now making it feasible to develop INS using an inertial measurement unit (IMU). INS has unbounded error growth since the error accumulates at each step. Usually, GPS and INS are integrated with a loosely coupled scheme. With the development of low-cost, MEMS inertial sensors and GPS technology, integrated INS/GPS systems are beginning to meet the growing demands of lower cost, smaller size, and seamless navigation solutions for land vehicles. Although MEMS inertial sensors are very inexpensive compared to conventional sensors, their cost (especially MEMS gyros) is still not acceptable for many low-end civilian applications (for example, commercial car navigation or personal location systems). An efficient way to reduce the expense of these systems is to reduce the number of gyros and accelerometers, therefore, to use a partial IMU (ParIMU) configuration. For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a field experiment for a low-cost strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach, we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of our low-cost IMU (Inertial Measurement Unit) and because of the relatively small area of the trajectory.

Keywords: GPS, IMU, Kalman filter, materials engineering

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Authors: Cebrail Çiflikli, Emre Öner Tartan

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Parallel to the fast worldwide increase of elderly population and spreading unhealthy life habits, there is a significant rise in the number of patients and health problems. The supervision of people who have health problems and oversight in detection of people who have potential risks, bring a considerable cost to health system and increase workload of physician. To provide an efficient solution to this problem, in the recent years mobile applications have shown their potential for wide usage in health monitoring. In this paper we present an Android mobile application that records and evaluates ECG signal using Pan-Tompkins algorithm for QRS detection. The application model includes an alarm mechanism that is proposed to be used for sending message including abnormality information and location information to health supervisor.

Keywords: Android mobile application, ECG monitoring, QRS detection, Pan-Tompkins Algorithm

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Authors: Maba Boniface Matadi

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This paper analyses the model of Malaria endemic from the point of view of the group theoretic approach. The study identified new independent variables that lead to the transformation of the nonlinear model. Furthermore, corresponding determining equations were constructed, and new symmetries were found. As a result, the findings of the study demonstrate of the integrability of the model to present an invariant solution for the Malaria model.

Keywords: group theory, lie symmetry, invariant solutions, malaria

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Authors: Ghulam Haider Haidaree, Nsenda Lukumwena

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Today the world of research enjoys abundant data, available in virtually any field, technology, science, and business, politics, etc. This is commonly referred to as big data. This offers a great deal of precision and accuracy, supportive of an in-depth look at any decision-making process. When and if well used, Big Data affords its users with the opportunity to produce substantially well supported and good results. This paper leans extensively on big data to investigate possible smart solutions to urban mobility and related issues, namely road traffic accidents, its casualties, and fatalities based on multiple factors, including age, gender, location occurrences of accidents, etc. Multiple technologies were used in combination to produce an Information Communication Technology (ICT) based solution with embedded technology. Those technologies include principally Geographic Information System (GIS), Orange Data Mining Software, Bayesian Statistics, to name a few. The study uses the Leeds accident 2016 to illustrate the thinking process and extracts thereof a model that can be tested, evaluated, and replicated. The authors optimistically believe that the proposed model will significantly and smartly help to flatten the curve of road traffic accidents in the fast-growing population densities, which increases considerably motor-based mobility.

Keywords: accident factors, geographic information system, information communication technology, mobility

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Authors: Ilhan Keskin, Hasan Bulent Kantarci

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In this study, one of the tools of Islamic financing known as “Sukuk” a non-interest bearing investment which has started to be implemented in Turkey and the world as a whole is discussed. In order to increase the vitality and efficiency of the economy, by taking lessons from the recent economic crisis new developments in the banking and investment sector are being expanded. The purpose of all investors is to obtain more revenue through the use of capital. The inability of traditional investment tools to meet the expectations of investors and the interest based financial system where one investor benefits at the expense of another there has been the need for a different, reliable and non-interest bearing financial market that is consistent with the Islamic rule. As a result an alternative and more reliable interest free financing tool “Sukuk” rental certificates covering people who are sensitive to Islamic rules, appeal to all segments, hidden remaining capital that contributes to the economy, reduce disparities in income distribution, common risk sharing system of profit and loss sharing has emerged. Today, for the structural countries by examining the state of the world market economy the applicability, enactment and future issues associated with this attractive kind of Islamic finance namely the “Sukuk” market has been explained.

Keywords: Islamic finance, islamic markets, non-interest bearing, rental certificates

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Authors: Javier López

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This Paper presents the evaluation model designed for the virtual education branch of The “Universidad Manuela Beltrán, Bogotá-Colombia”. This was the result of a research, developed as a case study, which had three stages: Document review, observation, and a perception survey for teachers. In the present model, the evaluation is a cross-cutting issue to the educational process. Therefore, it consists in a group of actions and guidelines which lead to analyze the student’s learning process from the admission, during the academic training, and to the graduation. This model contributes to the evaluation components which might interest other educational institutions or might offer methodological guidance to consolidate an own model

Keywords: model, evaluation, virtual education, learning process

Procedia PDF Downloads 446

Authors: Ayşegül Bilge, Merve Uğuryol, Şeyda Dülgerler, Mustafa Yıldız

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The purpose of this research is to prove the Attitude towards Using Complementary Treatments Scale reliability and validity. The research is a methodological type of research that has been planned to determine the validity and reliability of the Attitude towards Using Complementary Treatments Scale. The scale has been developed by the researchers. In the scale, there are 23 questions including complementary and modern therapies individuals apply when they have health problems 4-item Likert-type evaluation has been carried out in preparing the questionnaire. High score obtained from the scale indicates a positive attitude towards complementary therapies. In the course of validity assessment of the scale, expert opinion has been received, and the content validity of the scale has been determined by using Kendall coefficient correlation test (Wa=0.200, p = 0.460). In the course of the reliability assessment of the scale, total score correlations of 23 materials have been examined, and those under 0.20 correlation limit has been removed from the scale correlation. As a result, the scale was left to be 13 items. In the internal consistency tests of the analyses, Cronbach's alpha value has been found to be 0.79. As a result, of the validity analyses of the Attitude towards Using Complementary Treatments Scale, the content and language validity analyses has been found to be at the expected level. It has been determined to be a highly reliable scale as the result of the reliability analyses. In conclusion, Attitude towards Using Complementary Treatments Scale is a valid and reliable scale.

Keywords: alternative health care, complementary treatment, instrument development, nursing practice

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Preethy Mary Donald, Renjith George

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Oral tori are localized non-neoplastic protuberances of maxilla and mandible. Torus palatinus (TP) is found on the midline of the roof of mouth existing as single growth or in clusters. Torus mandibularis(TM) is located on the lingual aspect of the mandible commonly between canine and premolar region. Etiology of their presence was not clear and was found to be multifactorial. Their variations in relation to age, gender, ethnicity and also the characteristics of TP and TM have become the interest of multiple studies. The objectives of this study were to determine the prevalence of torus palatinus (TP) and torus mandibularis (TM) among patients who have visited outpatient department, Faculty of Dentistry, Melaka Manipal Medical College. 108 patients were examined for the presence of oral tori at the outpatient department, Faculty of Dentistry, Melaka-Manipal Medical College. Factors such as age, gender, ethnicity of the patients and size, shape, location of the oral tori were studied. For TP, Malays (62.96%) have been found to have the highest prevalence than Chinese (43.3%) and Indians (35.71%). For TM, Chinese (7.46%) had predominated compared to Malays (7.41%) and Indians (0%). There is no significant association between occurrence of TP and TM with age, gender and ethnicity. For Torus palatinus, the most common size was Grade 1(1-3mm), most common location was molar region, and the most common shape was spindle. For Torus mandibularis, the most frequent location was canine premolar region and exists in unilateral single or bilateral single fashion. The overall prevalence rates were 47.2% for TP and 6.48% for TM. However, there is no significant association between occurrence of TP and TM with age, gender and ethnicity. The results showed variations in clinical characteristics and support the findings that occurrence of tori is a dynamic phenomenon which is multifactorial owing to the environmental factors such as stress from occlusion and dietary habits. It could be due to the genetic make-up of the individual.

Keywords: torus palatinus, torus mandibularis, age, gender

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Authors: Jenan Abu Qadourah

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The suitable surface areas for the ST and PV installation are determined based on incident solar irradiation on different surfaces, shading analysis and suitable architectural area for integration considering limitations due to the constructions, available surfaces area and use of the available surfaces for other purposes. The incident solar radiation on the building surfaces and the building solar exposure analysis of the location of Amman, Jordan, is performed with Autodesk Ecotect analysis 2011 simulation software. The building model geometry within the typical urban context is created in “SketchUp,” which is then imported into Ecotect. The hourly climatic data of Amman, Jordan selected are the same ones used for the building simulation in IDA ICE and Polysun simulation software.

Keywords: photovoltaic, solar thermal, solar incident, simulation, building façade, solar potential

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Authors: R. Faiez, M. Mashhoudi, F. Najafi

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Implicit in most large-scale numerical analyses of the crystal growth from the melt is the assumption that the shape and position of the phase boundary are determined by the transport phenomena coupled strongly to the melt hydrodynamics. In the present numerical study, the interface shape-effect on the convective interactions in a Czochralski oxide melt is described. It was demonstrated that thermos-capillary flow affects inversely the phase boundaries of distinct shapes. The in homogenity of heat flux and the location of the stagnation point at the crystallization front were investigated. The forced convection effect on the point displacement at the boundary found to be much stronger for the flat plate interface compared to the cone-shaped one with and without the Marangoni flow.

Keywords: computer simulation, fluid flow, interface shape, thermos-capillary effect

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Authors: S. Ananthakrishnan, U. H. Acharya

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Whether shopping in a retail location or via the internet, consumers expect to receive their products intact. When products arrive damaged or over-packaged, the result can be customer dissatisfaction and increased cost for retailers and manufacturers. The packaging performance depends on both the transport situation and the packaging design. During transportation, the packaged products are subjected to the variation in vibration levels from transport vehicles that vary in frequency and acceleration while moving to their destinations. Spirits manufactured by this Company were being transported to various parts of the country by road. There were instances of package breaking and customer complaints. The vibration experienced on a straight road at some speed may not be same as the vibration experienced by the same vehicle on a curve at the same speed. This vibration may negatively affect the product or packing. Hence, it was necessary to conduct a physical road test to understand the effect of vibration in the packaged products. The field transit trial has to be done before the transportations, which results in high investment. The company management was interested in developing an in-house test environment which would adequately represent the transit conditions. With the objective to develop an in-house test condition that can accurately simulate the mechanical loading scenario prevailing during the storage, handling and transportation of the products a brainstorming was done with the concerned people to identify the critical factors affecting vibration rate. Position of corrugated box, the position of bottle and speed of vehicle were identified as factors affecting the vibration rate. Several packing scenarios were identified by Design of Experiment methodology and simulated in the in-house test facility. Each condition was observed for 30 minutes, which was equivalent to 1000 km. The achieved vibration level was considered as the response. The average achieved in the simulated experiments was near to the third quartile (Q3) of the actual data. Thus, we were able to address around three-fourth of the actual phenomenon. Most of the cases in transit could be reproduced. The recommended test condition could generate a vibration level ranging from 9g to 15g as against a maximum of only 7g that was being generated earlier. Thus, the Company was able to test the packaged cartons satisfactorily in the house itself before transporting to the destinations, assuring itself that the breakages of the bottles will not happen.

Keywords: ANOVA, Corrugated box, DOE, Quartile

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Authors: Dulal Bhaumik, Fei Jie, Runa Bhaumik, Bikas Sinha

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Human brain is an amazingly complex network. Aberrant activities in this network can lead to various neurological disorders such as multiple sclerosis, Parkinson’s disease, Alzheimer’s disease and autism. fMRI has emerged as an important tool to delineate the neural networks affected by such diseases, particularly autism. In this paper, we propose mixed-effects models together with an appropriate procedure for controlling false discoveries to detect disrupted connectivities in whole brain studies. Results are illustrated with a large data set known as Autism Brain Imaging Data Exchange or ABIDE which includes 361 subjects from 8 medical centers. We believe that our findings have addressed adequately the small sample inference problem, and thus are more reliable for therapeutic target for intervention. In addition, our result can be used for early detection of subjects who are at high risk of developing neurological disorders.

Keywords: ABIDE, autism spectrum disorder, fMRI, mixed-effects model

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Authors: Cynthia A. Gallardo, Kelly S. Hall, Kristopher Garza, Linda Challoo, Mais Nijim

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Dual-enrollment programs have become more prevalent in college and high school settings. Also known as early college programs, dual-enrollment programs help students acquire a head start in earning college credit for post-secondary studies. The number and percentage of high school students who take college courses while in high school is growing. However, little is known about how dual-enrolled students fare. The classroom environment is important to learning. This study compares dually enrolled high school students who take courses that yield college credit either within their high school or at some other location. Mann-Whitney U was the statistical test used. Mean proportions were compared for each of the five standard letter grades earned across the state of Texas. Results indicated that students earn similar passing A, B, and C grades when they take dual-enrollment courses at their high school location but are more likely to fail if they take dual-enrollment courses at non-high school locations. Implications of results are that student success rate of dual-enrollment college courses may have a significant difference between the locations and student performance.

Keywords: educational leadership, dual-enrollment, student performance, college

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Authors: A. Ishag Mohamed, A. A. Rabah

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The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

Procedia PDF Downloads 650

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Da LI, Peng Xu

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Recent extreme weather events, such as the 2021 European floods and North American heatwaves, have exposed the vulnerability of energy systems to both extreme demand scenarios and potential physical damage. Current integrated energy system designs often overlook performance under these challenging conditions. This research, focusing on a regional integrated energy system in Ningbo, China, proposes a distinct design method to optimize system reliability during extreme events. A multi-scenario model was developed, encompassing various extreme load conditions and potential system damages caused by severe weather. Based on this model, a comprehensive reliability improvement scheme was designed, incorporating a gradient approach to address different levels of disaster severity through the integration of advanced technologies like distributed energy storage. The scheme's effectiveness was validated through Monte Carlo simulations. Results demonstrate significant enhancements in energy supply reliability and peak load reduction capability under extreme scenarios. The findings provide several insights for improving energy system adaptability in the face of climate-induced challenges, offering valuable references for building reliable energy infrastructure capable of withstanding both extreme demands and physical threats across a spectrum of disaster intensities.

Keywords: extreme weather events, integrated energy systems, reliability improvement, climate change adaptation

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Luke S. Carlos A. Thompson

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The medical model of disability, though beneficial for the medical professional, is often exclusionary, restrictive and dehumanizing when applied to the lived experience of disability. As a result, a critique of this model was constructed called the social model of disability. Much of the language used to articulate the purpose behind the social model of disability can be summed up within the word inclusion. However, this essay asserts that inclusiveness is an incomplete aspiration. The social model, as it currently stands, does not aid in creating a society where those with impairments actually belong. Rather, the social model aids in lessening the visibility, or negative consequence of, difference. Therefore, the social model does not invite society to welcome those with physical and intellectual impairments. It simply aids society in ignoring the existence of impairment by removing explicit forms of exclusion. Rather than simple inclusion, then, this essay uses John Swinton’s concept of friendship and Jean Vanier’s understanding of belonging to better articulate the intended outcome of the social model—a society where everyone can belong.

Keywords: belong, community, differently-able, disability, exclusion, friendship, inclusion, normality

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Authors: Mershack O. Tetteh, Albert P. C. Chan, Amos Darko, Gabriel Nani

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International construction joint ventures (ICJVs) have evolved as an effective approach to sustainable development, given their myriad socio-economic and environmental benefits. Yet, they are not free of barriers and risks. In many studies, it is termed as risks for convenience’s sake. While the barriers and risks continue to affect the success of ICJVs, a systematic and reliable approach for managing them has yet to be developed. This study aims to identify and classify the barriers and risks factors affecting ICJVs through a systematic literature review. Based on a critical review of 54 papers published in peer-reviewed journals from 1990 to 2019, a conceptual framework was proposed for managing the barriers and risks in ICJV operations. The review showed that the barriers can be grouped into six including inter-organizational differences, lack of expertise and confidence, lack of effective planning and strategies, lack of knowledge of ICJV’s fundamentals, conflicts among ICJV entities, and management difficulties. The risks were also categorized into six: policy and political risks, legal risks, financial risks, management risks, project and technical risks, and market risks. The developed model would help practitioners achieve more efficient resource allocation and bring new perspectives for managerial practices in ICJVs. Moreover, it is positioned to alleviate the negligence of previous studies that combined the barriers and risks factors as one checklist.

Keywords: barriers, construction, international construction joint venture, risks, sustainable development

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Feda Negesse

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One of the most important indicators of research quality is a good data - collection instrument that can yield reliable and valid data. The Swadesh wordlist has been used for more than half a century for collecting data in comparative and historical linguistics though arbitrariness is observed in its application and size. This research compare s the classification results of the 100 Swadesh wordlist with those of its subsets to determine if reducing the size of the wordlist impact s its effectiveness. In the comparison, the 100, 50 and 40 wordlists were used to compute lexical distances of 29 Cushitic and Semitic languages spoken in Ethiopia and neighbouring countries. Gabmap, a based application, was employed to compute the lexical distances and to divide the languages into related clusters. The study shows that the subsets are not as effective as the 100 wordlist in clustering languages into smaller subgroups but they are equally effective in di viding languages into bigger groups such as subfamilies. It is noted that the subsets may lead to an erroneous classification whereby unrelated languages by chance form a cluster which is not attested by a comparative study. The chance to get a wrong result is higher when the subsets are used to classify languages which are not closely related. Though a further study is still needed to settle the issues around the size of the Swadesh wordlist, this study indicates that the 50 and 40 wordlists cannot be recommended as reliable substitute s for the 100 wordlist under all circumstances. The choice seems to be determined by the objective of a researcher and the degree of affiliation among the languages to be classified.

Keywords: classification, Cushitic, Swadesh, wordlist

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Authors: Urmi Khatri

Abstract:

Capital asset pricing model (CAPM) draws a direct relationship between the risk and the expected rate of return. There was a criticism on the beta and the assumptions of CAPM, as they are not applicable in the real world. Fama French Three Factor Model and Fama French Five Factor Model have given different factors, which have an impact on the return of any asset like size, value, investment and profitability. This study proposes to see Capital Asset pricing Model through the lenses of the quality aspect. In the study, the six factors are studied. The Fama French Five Factor Model and addition of the quality dimension are studied. Here, Graham’s seven quality and quantity criteria are measured to determine the score of the sample firms. Thus, this study tries to check the model fit. The beta coefficient of the quality dimension and the R square value is seen to determine validity of the proposed model. The sample is drawn from the firms listed on Indian Stock Exchange (BSE). For the study, only nonfinancial firms are been selected. The time period of the study is from January 1999 to December 2019. Hence, the primary objective of the study is to check how robust the model becomes after giving the quality dimension to the capital asset pricing model in addition to the size, value, profitability and investment.

Keywords: asset pricing model, CAPM, Graham’s score, G-score, multifactor model, quality

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Authors: Daniel Tscharnuter, Eliza Truszkiewicz, Gerald Pinter

Abstract:

High-quality surfaces of plastic parts can be achieved in a very cost-effective manner using in-mold processes, where e.g. scratch resistant or high gloss polymer films are pre-formed and subsequently receive their support structure by injection molding. The pre-forming may be done by high-pressure forming. In this process, a polymer sheet is heated and subsequently formed into the mold by pressurized air. Due to the heat transfer to the cooled mold the polymer temperature drops below its glass transition temperature. This ensures that the deformed microstructure is retained after depressurizing, giving the sheet its final formed shape. The development of a forming process relies heavily on the experience of engineers and trial-and-error procedures. Repeated mold design and testing cycles are however both time- and cost-intensive. It is, therefore, desirable to study the process using reliable computer simulations. Through simulations, the construction of the mold and the effect of various process parameters, e.g. temperature levels, non-uniform heating or timing and magnitude of pressure, on the deformation of the polymer sheet can be analyzed. Detailed knowledge of the deformation is particularly important in the forming of polymer films with integrated electro-optical functions. Care must be taken in the placement of devices, sensors and electrical and optical paths, which are far more sensitive to deformation than the polymers. Reliable numerical prediction of the deformation of the polymer sheets requires sophisticated material models. Polymer films are often either transversely isotropic or orthotropic due to molecular orientations induced during manufacturing. The anisotropic behavior affects the resulting strain field in the deformed film. For example, parts of the same shape but different strain fields may be created by varying the orientation of the film with respect to the mold. The numerical simulation of the high-pressure forming of such films thus requires material models that can capture the nonlinear anisotropic mechanical behavior. There are numerous commercial polymer grades for the engineers to choose from when developing a new part. The effort required for comprehensive material characterization may be prohibitive, especially when several materials are candidates for a specific application. We, therefore, propose a class of models for compressible hyperelasticity, which may be determined from basic experimental data and which can capture key features of the mechanical response. Invariant-based hyperelastic models with a reduced number of invariants are formulated in a semi-numerical way, such that the models are determined from a single uniaxial tensile tests for isotropic materials, or two tensile tests in the principal directions for transversely isotropic or orthotropic materials. The simulation of the high pressure forming of an orthotropic polymer film is finally done using an orthotropic formulation of the hyperelastic model.

Keywords: hyperelastic, anisotropic, polymer film, thermoforming

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Authors: Saurabh Ahluwalia, Sul Kassicieh

Abstract:

The conventional wisdom has maintained that being in proximity to entrepreneurial ecosystems helps startups to raise financing, develop and grow. In this paper, we examine the effect of a major component of an entrepreneurial ecosystem- financial or venture capital clusters on the exit of a startup through mergers and acquisitions (M&A). We find that the presence of a venture capitalist in a venture capital (VC) cluster is a major success factor for M&A exits. The location of startups in the top VC clusters did not turn out to be significant for success. Our results are robust to different specifications of the model that use different time periods, types of success, the reputation of VC, industry and the quality of the startup company. Our results provide evidence for VCs, startups and policymakers who want to better understand the components of entrepreneurial ecosystems and their relation to the M&A exits of startups.

Keywords: financial institution, mergers and acquisitions, startup financing, venture capital

Procedia PDF Downloads 194