Search results for: shared parameter model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18854

Search results for: shared parameter model

17414 A Mathematical Model for Hepatitis B Virus Infection and the Impact of Vaccination on Its Dynamics

Authors: T. G. Kassem, A. K. Adunchezor, J. P. Chollom

Abstract:

This paper describes a mathematical model developed to predict the dynamics of Hepatitis B virus (HBV) infection and to evaluate the potential impact of vaccination and treatment on its dynamics. We used a compartmental model expressed by a set of differential equations based on the characteristic of HBV transmission. With these, we find the threshold quantity R0, then find the local asymptotic stability of disease free equilibrium and endemic equilibrium. Furthermore, we find the global stability of the disease free and endemic equilibrium.

Keywords: hepatitis B virus, epidemiology, vaccination, mathematical model

Procedia PDF Downloads 324
17413 Experimental Model for Instruction of Pre-Service Teachers in ICT Tools and E-Learning Environments

Authors: Rachel Baruch

Abstract:

This article describes the implementation of an experimental model for teaching ICT tools and digital environments in teachers training college. In most educational systems in the Western world, new programs were developed in order to bridge the digital gap between teachers and students. In spite of their achievements, these programs are limited due to several factors: The teachers in the schools implement new methods incorporating technological tools into the curriculum, but meanwhile the technology changes and advances. The interface of tools changes frequently, some tools disappear and new ones are invented. These conditions require an experimental model of training the pre-service teachers. The appropriate method for instruction within the domain of ICT tools should be based on exposing the learners to innovations, helping them to gain experience, teaching them how to deal with challenges and difficulties on their own, and training them. This study suggests some principles for this approach and describes step by step the implementation of this model.

Keywords: ICT tools, e-learning, pre-service teachers, new model

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17412 Finite Element Simulation of Four Point Bending of Laminated Veneer Lumber (LVL) Arch

Authors: Eliska Smidova, Petr Kabele

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This paper describes non-linear finite element simulation of laminated veneer lumber (LVL) under tensile and shear loads that induce cracking along fibers. For this purpose, we use 2D homogeneous orthotropic constitutive model of tensile and shear fracture in timber that has been recently developed and implemented into ATENA® finite element software by the authors. The model captures (i) material orthotropy for small deformations in both linear and non-linear range, (ii) elastic behavior until anisotropic failure criterion is fulfilled, (iii) inelastic behavior after failure criterion is satisfied, (iv) different post-failure response for cracks along and across the grain, (v) unloading/reloading behavior. The post-cracking response is treated by fixed smeared crack model where Reinhardt-Hordijk function is used. The model requires in total 14 input parameters that can be obtained from standard tests, off-axis test results and iterative numerical simulation of compact tension (CT) or compact tension-shear (CTS) test. New engineered timber composites, such as laminated veneer lumber (LVL), offer improved structural parameters compared to sawn timber. LVL is manufactured by laminating 3 mm thick wood veneers aligned in one direction using water-resistant adhesives (e.g. polyurethane). Thus, 3 main grain directions, namely longitudinal (L), tangential (T), and radial (R), are observed within the layered LVL product. The core of this work consists in 3 numerical simulations of experiments where Radiata Pine LVL and Yellow Poplar LVL were involved. The first analysis deals with calibration and validation of the proposed model through off-axis tensile test (at a load-grain angle of 0°, 10°, 45°, and 90°) and CTS test (at a load-grain angle of 30°, 60°, and 90°), both of which were conducted for Radiata Pine LVL. The second finite element simulation reproduces load-CMOD curve of compact tension (CT) test of Yellow Poplar with the aim of obtaining cohesive law parameters to be used as an input in the third finite element analysis. That is four point bending test of small-size arch of 780 mm span that is made of Yellow Poplar LVL. The arch is designed with a through crack between two middle layers in the crown. Curved laminated beams are exposed to high radial tensile stress compared to timber strength in radial tension in the crown area. Let us note that in this case the latter parameter stands for tensile strength in perpendicular direction with respect to the grain. Standard tests deliver most of the relevant input data whereas traction-separation law for crack along the grain can be obtained partly by inverse analysis of compact tension (CT) test or compact tension-shear test (CTS). The initial crack was modeled as a narrow gap separating two layers in the middle the arch crown. Calculated load-deflection curve is in good agreement with the experimental ones. Furthermore, crack pattern given by numerical simulation coincides with the most important observed crack paths.

Keywords: compact tension (CT) test, compact tension shear (CTS) test, fixed smeared crack model, four point bending test, laminated arch, laminated veneer lumber LVL, off-axis test, orthotropic elasticity, orthotropic fracture criterion, Radiata Pine LVL, traction-separation law, yellow poplar LVL, 2D constitutive model

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17411 Groundwater Flow Assessment Based on Numerical Simulation at Omdurman Area, Khartoum State, Sudan

Authors: Adil Balla Elkrail

Abstract:

Visual MODFLOW computer codes were selected to simulate head distribution, calculate the groundwater budgets of the area, and evaluate the effect of external stresses on the groundwater head and to demonstrate how the groundwater model can be used as a comparative technique in order to optimize utilization of the groundwater resource. A conceptual model of the study area, aquifer parameters, boundary, and initial conditions were used to simulate the flow model. The trial-and-error technique was used to calibrate the model. The most important criteria used to check the calibrated model were Root Mean Square error (RMS), Mean Absolute error (AM), Normalized Root Mean Square error (NRMS) and mass balance. The maps of the simulated heads elaborated acceptable model calibration compared to observed heads map. A time length of eight years and the observed heads of the year 2004 were used for model prediction. The predictive simulation showed that the continuation of pumping will cause relatively high changes in head distribution and components of groundwater budget whereas, the low deficit computed (7122 m3/d) between inflows and outflows cannot create a significant drawdown of the potentiometric level. Hence, the area under consideration may represent a high permeability and productive zone and strongly recommended for further groundwater development.

Keywords: aquifers, model simulation, groundwater, calibrations, trail-and- error, prediction

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17410 Contribution to the Analytical Study of the Stability of a DC-DC Converter (Boost) Used for MPPT Control

Authors: Mohamed Amarouayache, Badia Amrouche, Gharbi Akila, Boukadoume Mohamed

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This work is devoted to the modeling of DC-DC converter (boost) used for MPPT applications to set conditions of stability. For this, we establish a linear mathematical model of the DC-DC converter with an average small signal model. This model has allowed us to apply conventional linear methods of automation. A mathematical relationship between the duty cycle and the voltage of the panel has been set up. With this relationship we specify the conditions of the stability in closed-loop depending on the system parameters (the elements of storage capacity and inductance, PWM control).

Keywords: MPPT, PWM, stability, criterion of Routh, average small signal model

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17409 The Problem of Suffering: Job, The Servant and Prophet of God

Authors: Barbara Pemberton

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Now that people of all faiths are experiencing suffering due to many global issues, shared narratives may provide common ground in which true understanding of each other may take root. This paper will consider the all too common problem of suffering and address how adherents of the three great monotheistic religions seek understanding and the appropriate believer’s response from the same story found within their respective sacred texts. Most scholars from each of these three traditions—Judaism, Christianity, and Islam— consider the writings of the Tanakh/Old Testament to at least contain divine revelation. While they may not agree on the extent of the revelation or the method of its delivery, they do share stories as well as a common desire to glean God’s message for God’s people from the pages of the text. One such shared story is that of Job, the servant of Yahweh--called Ayyub, the prophet of Allah, in the Qur’an. Job is described as a pious, righteous man who loses everything—family, possessions, and health—when his faith is tested. Three friends come to console him. Through it, all Job remains faithful to his God who rewards him by restoring all that was lost. All three hermeneutic communities consider Job to be an archetype of human response to suffering, regarding Job’s response to his situation as exemplary. The story of Job addresses more than the distribution of the evil problem. At stake in the story is Job’s very relationship to his God. Some exegetes believe that Job was adapted into the Jewish milieu by a gifted redactor who used the original ancient tale as the “frame” for the biblical account (chapters 1, 2, and 4:7-17) and then enlarged the story with the complex center section of poetic dialogues creating a complex work with numerous possible interpretations. Within the poetic center, Job goes so far as to question God, a response to which Jews relate, finding strength in dialogue—even in wrestling with God. Muslims only embrace the Job of the biblical narrative frame, as further identified through the Qur’an and the prophetic traditions, considering the center section an errant human addition not representative of a true prophet of Islam. The Qur’anic injunction against questioning God also renders the center theologically suspect. Christians also draw various responses from the story of Job. While many believers may agree with the Islamic perspective of God’s ultimate sovereignty, others would join their Jewish neighbors in questioning God, not anticipating answers but rather an awareness of his presence—peace and hope becoming a reality experienced through the indwelling presence of God’s Holy Spirit. Related questions are as endless as the possible responses. This paper will consider a few of the many Jewish, Christian, and Islamic insights from the ancient story, in hopes adherents within each tradition will use it to better understand the other faiths’ approach to suffering.

Keywords: suffering, Job, Qur'an, tanakh

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17408 Combustion Analysis of Suspended Sodium Droplet

Authors: T. Watanabe

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Combustion analysis of suspended sodium droplet is performed by solving numerically the Navier-Stokes equations and the energy conservation equations. The combustion model consists of the pre-ignition and post-ignition models. The reaction rate for the pre-ignition model is based on the chemical kinetics, while that for the post-ignition model is based on the mass transfer rate of oxygen. The calculated droplet temperature is shown to be in good agreement with the existing experimental data. The temperature field in and around the droplet is obtained as well as the droplet shape variation, and the present numerical model is confirmed to be effective for the combustion analysis.

Keywords: analysis, combustion, droplet, sodium

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17407 Prosody Generation in Neutral Speech Storytelling Application Using Tilt Model

Authors: Manjare Chandraprabha A., S. D. Shirbahadurkar, Manjare Anil S., Paithne Ajay N.

Abstract:

This paper proposes Intonation Modeling for Prosody generation in Neutral speech for Marathi (language spoken in Maharashtra, India) story telling applications. Nowadays audio story telling devices are very eminent for children. In this paper, we proposed tilt model for stressed words in Marathi for speech modification. Tilt model predicts modification in tone of neutral speech. GMM is used to identify stressed words for modification.

Keywords: tilt model, fundamental frequency, statistical parametric speech synthesis, GMM

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17406 Teaching Young Children Social and Emotional Learning through Shared Book Reading: Project GROW

Authors: Stephanie Al Otaiba, Kyle Roberts

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Background and Significance Globally far too many students read below grade level; thus improving literacy outcomes is vital. Research suggests that non-cognitive factors, including Social and Emotional Learning (SEL) are linked to success in literacy outcomes. Converging evidence exists that early interventions are more effective than later remediation; therefore teachers need strategies to support early literacy while developing students’ SEL and their vocabulary, or language, for learning. This presentation describe findings from a US federally-funded project that trained teachers to provide an evidence-based read-aloud program for young children, using commercially available books with multicultural characters and themes to help their students “GROW”. The five GROW SEL themes include: “I can name my feelings”, “I can learn from my mistakes”, “I can persist”, “I can be kind to myself and others”, and “I can work toward and achieve goals”. Examples of GROW vocabulary (from over 100 words taught across the 5 units) include: emotions, improve, resilient, cooperate, accomplish, responsible, compassion, adapt, achieve, analyze. Methodology This study used a mixed methods research design, with qualitative methods to describe data from teacher feedback surveys (regarding satisfaction, feasibility), observations of fidelity of implementation, and with quantitative methods to assess the effect sizes for student vocabulary growth. GROW Intervention and Teacher Training Procedures Researchers trained classroom teachers to implement GROW. Each thematic unit included four books, vocabulary cards with images of the vocabulary words, and scripted lessons. Teacher training included online and in-person training; researchers incorporated virtual reality videos of instructors with child avatars to model lessons. Classroom teachers provided 2-3 20 min lessons per week ranging from short-term (8 weeks) to longer-term trials for up to 16 weeks. Setting and Participants The setting for the study included two large urban charter schools in the South. Data was collected across two years; during the first year, participants included 7 kindergarten teachers and 108 and the second year involved an additional set of 5 kindergarten and first grade teachers and 65 students. Initial Findings The initial qualitative findings indicate teachers reported the lessons to be feasible to implement and they reported that students enjoyed the books. Teachers found the vocabulary words to be challenging and important. They were able to implement lessons with fidelity. Quantitative analyses of growth for each taught word suggest that students’ growth on taught words ranged from large (ES = .75) to small (<.20). Researchers will contrast the effects for more and less successful books within the GROW units. Discussion and Conclusion It is feasible for teachers of young students to effectively teach SEL vocabulary and themes during shared book reading. Teachers and students enjoyed the books and students demonstrated growth on taught vocabulary. Researchers will discuss implications of the study and about the GROW program for researchers in learning sciences, will describe some limitations about research designs that are inherent in school-based research partnerships, and will provide some suggested directions for future research and practice.

Keywords: early literacy, learning science, language and vocabulary, social and emotional learning, multi-cultural

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17405 A Model-Driven Approach of User Interface for MVP Rich Internet Application

Authors: Sarra Roubi, Mohammed Erramdani, Samir Mbarki

Abstract:

This paper presents an approach for the model-driven generating of Rich Internet Application (RIA) focusing on the graphical aspect. We used well known Model-Driven Engineering (MDE) frameworks and technologies, such as Eclipse Modeling Framework (EMF), Graphical Modeling Framework (GMF), Query View Transformation (QVTo) and Acceleo to enable the design and the code automatic generation of the RIA. During the development of the approach, we focused on the graphical aspect of the application in terms of interfaces while opting for the Model View Presenter pattern that is designed for graphics interfaces. The paper describes the process followed to define the approach, the supporting tool and presents the results from a case study.

Keywords: metamodel, model-driven engineering, MVP, rich internet application, transformation, user interface

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17404 Kauffman Model on a Network of Containers

Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

Abstract:

In the description of the origin of life, there are still some open gaps, e.g., the formation of macromolecules cannot be fully explained so far. The Kauffman model proposes the existence of autocatalytic sets of macromolecules which mutually catalyze reactions leading to each other’s formation. Usually, this model is simulated in one well-stirred pot only, with a continuous inflow of small building blocks, from which larger molecules are created by a set of catalyzed ligation and cleavage reactions. This approach represents the picture of the primordial soup. However, the conditions on the early Earth must have differed geographically, leading to spatially different outcomes whether a specific reaction could be performed or not. Guided by this picture, the Kauffman model is simulated in a large number of containers in parallel, with neighboring containers being connected by diffusion. In each container, only a subset of the overall reaction set can be performed. Under specific conditions, this approach leads to a larger probability for the existence of an autocatalytic metabolism than in the original Kauffman model.

Keywords: agglomeration, autocatalytic set, differential equation, Kauffman model

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17403 Estimation of Probabilistic Fatigue Crack Propagation Models of AZ31 Magnesium Alloys under Various Load Ratio Conditions by Using the Interpolation of a Random Variable

Authors: Seon Soon Choi

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The essential purpose is to present the good fatigue crack propagation model describing a stochastic fatigue crack growth behavior in a rolled magnesium alloy, AZ31, under various load ratio conditions. Fatigue crack propagation experiments were carried out in laboratory air under four conditions of load ratio, R, using AZ31 to investigate the crack growth behavior. The stochastic fatigue crack growth behavior was analyzed using an interpolation of random variable, Z, introduced to an empirical fatigue crack propagation model. The empirical fatigue models used in this study are Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was found that the random variable is useful in describing the stochastic fatigue crack growth behaviors under various load ratio conditions. The good probabilistic model describing a stochastic fatigue crack growth behavior under various load ratio conditions was also proposed.

Keywords: magnesium alloys, fatigue crack propagation model, load ratio, interpolation of random variable

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17402 Comprehensive Critical Review for Static and Dynamic Soil-Structure Interaction Between Winkler, Pasternak and Three-Dimensional Method of Buried Pipelines

Authors: N. E.Sam, S. R.Singh

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Pipeline infrastructure are a valuable asset to the country that help in transporting fluid and gas from one place to another and contribute in keeping the country functioning both physically and economically. During seismic activity, additional loads are acted on the buried pipelines becoming a salient parameter to be studied in soil pipe interaction. Winkler Beam Theory is a commonly used approach for design of underground buried structures however this theory does not take into account shear and dynamic loading parameters in consideration. Shear can be addressed in Pasternak Theory – an improved model of Winkler Theory. However dynamic loading condition and horizontal displacement is not considered in either method. A comprehensive critical review between Winkler Beam Method, Pasternak Method and Three-Dimensional Method in finite element analysis is to be done in this paper for seismic forces. Study of the influence of depth and displacement of soil in correspondence to stiffness value and influence of horizontal displacement for design of underground structures is considered.

Keywords: finite element, pasternak theory, seismic, soil-structure interaction, three-dimensional theory, winkler theory

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17401 A Nonlinear Parabolic Partial Differential Equation Model for Image Enhancement

Authors: Tudor Barbu

Abstract:

We present a robust nonlinear parabolic partial differential equation (PDE)-based denoising scheme in this article. Our approach is based on a second-order anisotropic diffusion model that is described first. Then, a consistent and explicit numerical approximation algorithm is constructed for this continuous model by using the finite-difference method. Finally, our restoration experiments and method comparison, which prove the effectiveness of this proposed technique, are discussed in this paper.

Keywords: anisotropic diffusion, finite differences, image denoising and restoration, nonlinear PDE model, anisotropic diffusion, numerical approximation schemes

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17400 Precise Identification of Clustered Regularly Interspaced Short Palindromic Repeats-Induced Mutations via Hidden Markov Model-Based Sequence Alignment

Authors: Jingyuan Hu, Zhandong Liu

Abstract:

CRISPR genome editing technology has transformed molecular biology by accurately targeting and altering an organism’s DNA. Despite the state-of-art precision of CRISPR genome editing, the imprecise mutation outcome and off-target effects present considerable risk, potentially leading to unintended genetic changes. Targeted deep sequencing, combined with bioinformatics sequence alignment, can detect such unwanted mutations. Nevertheless, the classical method, Needleman-Wunsch (NW) algorithm may produce false alignment outcomes, resulting in inaccurate mutation identification. The key to precisely identifying CRISPR-induced mutations lies in determining optimal parameters for the sequence alignment algorithm. Hidden Markov models (HMM) are ideally suited for this task, offering flexibility across CRISPR systems by leveraging forward-backward algorithms for parameter estimation. In this study, we introduce CRISPR-HMM, a statistical software to precisely call CRISPR-induced mutations. We demonstrate that the software significantly improves precision in identifying CRISPR-induced mutations compared to NW-based alignment, thereby enhancing the overall understanding of the CRISPR gene-editing process.

Keywords: CRISPR, HMM, sequence alignment, gene editing

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17399 Gender Differences in Morbid Obese Children: Clinical Significance of Two Diagnostic Obesity Notation Model Assessment Indices

Authors: Mustafa M. Donma, Orkide Donma, Murat Aydin, Muhammet Demirkol, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

Abstract:

Childhood obesity is an ever increasing global health problem, affecting both developed and developing countries. Accurate evaluation of obesity in children requires difficult and detailed investigation. In our study, obesity in children was evaluated using new body fat ratios and indices. Assessment of anthropometric measurements, as well as some ratios, is important because of the evaluation of gender differences particularly during the late periods of obesity. A total of 239 children; 168 morbid obese (MO) (81 girls and 87 boys) and 71 normal weight (NW) (40 girls and 31 boys) children, participated in the study. Informed consent forms signed by the parents were obtained. Ethics Committee approved the study protocol. Mean ages (years)±SD calculated for MO group were 10.8±2.9 years in girls and 10.1±2.4 years in boys. The corresponding values for NW group were 9.0±2.0 years in girls and 9.2±2.1 years in boys. Mean body mass index (BMI)±SD values for MO group were 29.1±5.4 kg/m2 and 27.2±3.9 kg/m2 in girls and boys, respectively. These values for NW group were calculated as 15.5±1.0 kg/m2 in girls and 15.9±1.1 kg/m2 in boys. Groups were constituted based upon BMI percentiles for age-and-sex values recommended by WHO. Children with percentiles >99 were grouped as MO and children with percentiles between 85 and 15 were considered NW. The anthropometric measurements were recorded and evaluated along with the new ratios such as trunk-to-appendicular fat ratio, as well as indices such as Index-I and Index-II. The body fat percent values were obtained by bio-electrical impedance analysis. Data were entered into a database for analysis using SPSS/PASW 18 Statistics for Windows statistical software. Increased waist-to-hip circumference (C) ratios, decreased head-to-neck C, height ‘to’ ‘two’-‘to’-waist C and height ‘to’ ‘two’-‘to’-hip C ratios were observed in parallel with the development of obesity (p≤0.001). Reference value for height ‘to’ ‘two’-‘to’-hip ratio was detected as approximately 1.0. Index-II, based upon total body fat mass, showed much more significant differences between the groups than Index-I based upon weight. There was not any difference between trunk-to-appendicular fat ratios of NW girls and NW boys (p≥0.05). However, significantly increased values for MO girls in comparison with MO boys were observed (p≤0.05). This parameter showed no difference between NW and MO states in boys (p≥0.05). However, statistically significant increase was noted in MO girls compared to their NW states (p≤0.001). Trunk-to-appendicular fat ratio was the only fat-based parameter, which showed gender difference between NW and MO groups. This study has revealed that body ratios and formula based upon body fat tissue are more valuable parameters than those based on weight and height values for the evaluation of morbid obesity in children.

Keywords: anthropometry, childhood obesity, gender, morbid obesity

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17398 Artificial Neural Network to Predict the Optimum Performance of Air Conditioners under Environmental Conditions in Saudi Arabia

Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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17397 Dynamic Investigation of Brake Squeal Problem in The Presence of Kinematic Nonlinearities

Authors: Shahroz Khan, Osman Taha Şen

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In automotive brake systems, brake noise has been a major problem, and brake squeal is one of the critical ones which is an instability issue. The brake squeal produces an audible sound at high frequency that is irritating to the human ear. To study this critical problem, first a nonlinear mathematical model with three degree of freedom is developed. This model consists of a point mass that simulates the brake pad and a sliding surface that simulates the brake rotor. The model exposes kinematic and clearance nonlinearities, but no friction nonlinearity. In the formulation, the friction coefficient is assumed to be constant and the friction force does not change direction. The nonlinear governing equations of the model are first obtained, and numerical solutions are sought for different cases. Second, a computational model for the squeal problem is developed with a commercial software, and computational solutions are obtained with two different types of contact cases (solid-to-solid and sphere-to-plane). This model consists of three rigid bodies and several elastic elements that simulate the key characteristics of a brake system. The response obtained from this model is compared with numerical solutions in time and frequency domain.

Keywords: contact force, nonlinearities, brake squeal, vehicle brake

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17396 Development of a Wind Resource Assessment Framework Using Weather Research and Forecasting (WRF) Model, Python Scripting and Geographic Information Systems

Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

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17395 The Process of Crisis: Model of Its Development in the Organization

Authors: M. Mikušová

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The main aim of this paper is to present a clear and comprehensive picture of the process of a crisis in the organization which will help to better understand its possible developments. For a description of the sequence of individual steps and an indication of their causation and possible variants of the developments, a detailed flow diagram with verbal comment is applied. For simplicity, the process of the crisis is observed in four basic phases called: symptoms of the crisis, diagnosis, action and prevention. The model highlights the complexity of the phenomenon of the crisis and that the various phases of the crisis are interweaving.

Keywords: crisis, management, model, organization

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17394 Intergenerational Succession within Family Businesses: The Role of Sharing and Creation Knowledge

Authors: Wissal Ben Arfi, Jean-Michel Sahut

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The purpose of this paper is to provide a deeper understanding of the succession process from a knowledge management perspective. By doing that, succession process in family businesses, as an environment for creating and sharing knowledge, was explored. Design/Methodology/Approach: To support our reasoning, we collected qualitative data through 16 in-depth interviews conducted with all decision makers involved in the family businesses succession process in France. These open-ended responses were subsequently exposed to thematic discourse analysis. Findings: Central to this exhibit is the nature and magnitude of knowledge creation and sharing among the actors within the family succession context and how can tacit knowledge sharing facilitate the succession process. We also identified factors that inhibit down the knowledge creation and sharing processes. The sharing and creation of knowledge among members of a family business appear to be a complex process that must be part of a strategy for change. This implies that it requests trust and takes a certain amount of time because it requires organizational change and a clear and coherent strategic vision that is accepted and assimilated by all the members. Professional and leadership skills are of particular importance in knowledge sharing and creation processes. In most cases, tacit knowledge is crucial when it is shared and accumulated collectively. Our findings reveal that managers should find ways of implementing knowledge sharing and creation processes while acknowledging the succession process within family firms. This study highlights the importance of generating knowledge strategies in order to enhance the performance and the success of intergenerational succession. The empirical outcomes contribute to enrich the field of succession management process and enhance the role of knowledge in shaping family performance and longevity. To a large extent, the lessons learned from the study of succession processes in family-owned businesses are that when there is a deliberate effort to introduce a knowledge-based approach, this action becomes a seminal event in the life of the organization. Originality/Value: The paper contributes to the deep understanding of interactions among actors by examining the knowledge creation and sharing processes since current researches in family succession focused on aspects such as personal development of potential, intra-family succession intention, decision-making processes in family businesses. Besides, as succession is one of the key factors that determine the longevity and the performance of family businesses, it also contributes to literature by examining how tacit knowledge is transferred, shared and created in family businesses and how this can facilitate the intergenerational succession process.

Keywords: family-owned businesses, succession process, knowledge, performance

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17393 Classification Based on Deep Neural Cellular Automata Model

Authors: Yasser F. Hassan

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Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

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17392 Optimization of Scheduling through Altering Layout Using Pro-Model

Authors: Zouhair Issa Ahmed, Ahmed Abdulrasool Ahmed, Falah Hassan Abdulsada

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This paper presents a layout of a factory using Pro-Model simulation by choosing the best layout that gives the highest productivity and least work in process. The general problem is to find the best sequence in which jobs pass between the machines which are compatible with the technological constraints and optimal with respect to some performance criteria. The best simulation with Pro-Model program increased productivity and reduced work in process by balancing lines of production compared with the current layout of factory when productivity increased from 45 products to 180 products through 720 hours.

Keywords: scheduling, Pro-Model, simulation, balancing lines of production, layout planning, WIP

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17391 Parameter Study for TPU Nanofibers Fabricated via Centrifugal Spinning

Authors: Yasin Akgül, Yusuf Polat, Emine Canbay, Ali Kılıç

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Electrospinning is the most common method to produce nanofibers. However, low production rate is still a big challenge for industrial applications of this method. In this study, morphology of nanofibers obtained from namely centrifugal spinning was investigated. Dominant process parameters acting on the fiber diameter and fiber orientation were discussed.

Keywords: centrifugal spinning, electrospinning, nanofiber, TPU nanofibers

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17390 Commercial Automobile Insurance: A Practical Approach of the Generalized Additive Model

Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

Abstract:

The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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17389 On Stochastic Models for Fine-Scale Rainfall Based on Doubly Stochastic Poisson Processes

Authors: Nadarajah I. Ramesh

Abstract:

Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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17388 Reconstruction of Holographic Dark Energy in Chameleon Brans-Dicke Cosmology

Authors: Surajit Chattopadhyay

Abstract:

Accelerated expansion of the current universe is well-established in the literature. Dark energy and modified gravity are two approaches to account for this accelerated expansion. In the present work, we consider scalar field models of dark energy, namely, tachyon and DBI essence in the framework of chameleon Brans-Dicke cosmology. The equation of state parameter is reconstructed and the subsequent cosmological implications are studied. We examined the stability for the obtained solutions of the crossing of the phantom divide under a quantum correction of massless conformally invariant fields and we have seen that quantum correction could be small when the phantom crossing occurs and the obtained solutions of the phantom crossing could be stable under the quantum correction. In the subsequent phase, we have established a correspondence between the NHDE model and the quintessence, the DBI-essence and the tachyon scalar field models in the framework of chameleon Brans–Dicke cosmology. We reconstruct the potentials and the dynamics for these three scalar field models we have considered. The reconstructed potentials are found to increase with the evolution of the universe and in a very late stage they are observed to decay.

Keywords: dark energy, holographic principle, modified gravity, reconstruction

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17387 Turbulent Forced Convection of Cu-Water Nanofluid: CFD Models Comparison

Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

Abstract:

This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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17386 Particle Filter Implementation of a Non-Linear Dynamic Fall Model

Authors: T. Kobayashi, K. Shiba, T. Kaburagi, Y. Kurihara

Abstract:

For the elderly living alone, falls can be a serious problem encountered in daily life. Some elderly people are unable to stand up without the assistance of a caregiver. They may become unconscious after a fall, which can lead to serious aftereffects such as hypothermia, dehydration, and sometimes even death. We treat the subject as an inverted pendulum and model its angle from the equilibrium position and its angular velocity. As the model is non-linear, we implement the filtering method with a particle filter which can estimate true states of the non-linear model. In order to evaluate the accuracy of the particle filter estimation results, we calculate the root mean square error (RMSE) between the estimated angle/angular velocity and the true values generated by the simulation. The experimental results give the highest accuracy RMSE of 0.0141 rad and 0.1311 rad/s for the angle and angular velocity, respectively.

Keywords: fall, microwave Doppler sensor, non-linear dynamics model, particle filter

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17385 A Gastro-Intestinal Model for a Rational Design of in vitro Systems to Study Drugs Bioavailability

Authors: Pompa Marcello, Mauro Capocelli, Vincenzo Piemonte

Abstract:

This work focuses on a mathematical model able to describe the gastro-intestinal physiology and providing a rational tool for the design of an artificial gastro-intestinal system. This latter is mainly devoted to analyse the absorption and bioavailability of drugs and nutrients through in vitro tests in order to overcome (or, at least, to partially replace) in vivo trials. The provided model realizes a conjunction ring (with extended prediction capability) between in vivo tests and mechanical-laboratory models emulating the human body. On this basis, no empirical equations controlling the gastric emptying are implemented in this model as frequent in the cited literature and all the sub-unit and the related system of equations are physiologically based. More in detail, the model structure consists of six compartments (stomach, duodenum, jejunum, ileum, colon and blood) interconnected through pipes and valves. Paracetamol, Ketoprofen, Irbesartan and Ketoconazole are considered and analysed in this work as reference drugs. The mathematical model has been validated against in vivo literature data. Results obtained show a very good model reliability and highlight the possibility to realize tailored simulations for different couples patient-drug, including food adsorption dynamics.

Keywords: gastro-intestinal model, drugs bioavailability, paracetamol, ketoprofen

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