Search results for: model of the universe
15420 Uncertainty in Risk Modeling
Authors: Mueller Jann, Hoffmann Christian Hugo
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Conventional quantitative risk management in banking is a risk factor of its own, because it rests on assumptions such as independence and availability of data which do not hold when rare events of extreme consequences are involved. There is a growing recognition of the need for alternative risk measures that do not make these assumptions. We propose a novel method for modeling the risk associated with investment products, in particular derivatives, by using a formal language for specifying financial contracts. Expressions in this language are interpreted in the category of values annotated with (a formal representation of) uncertainty. The choice of uncertainty formalism thus becomes a parameter of the model, so it can be adapted to the particular application and it is not constrained to classical probabilities. We demonstrate our approach using a simple logic-based uncertainty model and a case study in which we assess the risk of counter party default in a portfolio of collateralized loans.Keywords: risk model, uncertainty monad, derivatives, contract algebra
Procedia PDF Downloads 57615419 Comparison Analysis of CFD Turbulence Fluid Numerical Study for Quick Coupling
Authors: JoonHo Lee, KyoJin An, JunSu Kim, Young-Chul Park
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In this study, the fluid flow characteristics and performance numerical study through CFD model of the Non-split quick coupling for flow control in hydraulic system equipment for the aerospace business group focused to predict. In this study, we considered turbulence models for the application of Computational Fluid Dynamics for the CFD model of the Non-split Quick Coupling for aerospace business. In addition to this, the adequacy of the CFD model were verified by comparing with standard value. Based on this analysis, accurate the fluid flow characteristics can be predicted. It is, therefore, the design of the fluid flow characteristic contribute the reliability for the Quick Coupling which is required in industries on the basis of research results.Keywords: CFD, FEM, quick coupling, turbulence
Procedia PDF Downloads 38415418 Deepfake Detection for Compressed Media
Authors: Sushil Kumar Gupta, Atharva Joshi, Ayush Sonawale, Sachin Naik, Rajshree Khande
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The usage of artificially created videos and audio by deep learning is a major problem of the current media landscape, as it pursues the goal of misinformation and distrust. In conclusion, the objective of this work targets generating a reliable deepfake detection model using deep learning that will help detect forged videos accurately. In this work, CelebDF v1, one of the largest deepfake benchmark datasets in the literature, is adopted to train and test the proposed models. The data includes authentic and synthetic videos of high quality, therefore allowing an assessment of the model’s performance against realistic distortions.Keywords: deepfake detection, CelebDF v1, convolutional neural network (CNN), xception model, data augmentation, media manipulation
Procedia PDF Downloads 915417 Designing a Model for Preparing Reports on the Automatic Earned Value Management Progress by the Integration of Primavera P6, SQL Database, and Power BI: A Case Study of a Six-Storey Concrete Building in Mashhad, Iran
Authors: Hamed Zolfaghari, Mojtaba Kord
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Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that it is not linked to planning software such as Microsoft Project, which lacks the database required for data storage. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, HR reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.Keywords: primavera P6, SQL, Power BI, EVM, integration management
Procedia PDF Downloads 10815416 Artificial Neural Network Based Parameter Prediction of Miniaturized Solid Rocket Motor
Authors: Hao Yan, Xiaobing Zhang
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The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model
Procedia PDF Downloads 9015415 Verification of a Simple Model for Rolling Isolation System Response
Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly
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Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system
Procedia PDF Downloads 25015414 Assessment of Modern RANS Models for the C3X Vane Film Cooling Prediction
Authors: Mikhail Gritskevich, Sebastian Hohenstein
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The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.Keywords: discrete holes film cooling, Reynolds Averaged Navier-Stokes (RANS), Reynolds stress tensor anisotropy, turbulent heat transfer
Procedia PDF Downloads 42015413 Islamic Finance: What is the Outlook for Italy?
Authors: Paolo Pietro Biancone
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The spread of Islamic financial instruments is an opportunity to offer integration for the immigrant population and to attract, through the specific products, the richness of sovereign funds from the "Arab" countries. However, it is important to consider the possibility of comparing a traditional finance model, which in recent times has given rise to many doubts, with an "alternative" finance model, where the ethical aspect arising from religious principles is very important.Keywords: banks, Europe, Islamic finance, Italy
Procedia PDF Downloads 27015412 Critique of the City-Machine: Dismantling the Scientific Socialist Utopia of Soviet Territorialization
Authors: Rachel P. Vasconcellos
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The Russian constructivism is usually enshrined in history as another ''modernist ism'', that is, as an artistic phenomenon related to the early twentieth century‘s zeitgeist. What we aim in this essay is to analyze the constructivist movement not over the Art History field neither through the aesthetic debate, but through a geographical critical theory, taking the main idea of construction in the concrete sense of production of space. Seen from the perspective of the critique of space, the constructivist production is presented as a plan of totality, designed as socialist society‘s spatiality, contemplating and articulating all its scalar levels: the objects of everyday life, the building, the city and the territory. The constructivist avant-garde manifests a geographical ideology, launching the foundation‘s basis of modern planning ideology. Taken in its political sense, the artistic avant-garde of the Russian Revolution intended to anticipate the forms of a social future already put in progress: their plastic research pointed to new formal expressions to revolutionary contents. With the foundation of new institutions under a new State, it was given to the specialized labor of artists, architects, and planners the task of designing the socialist society, based on the thesis of scientific socialism. Their projects were developed under the politico-economics imperatives to the Soviet modernization – that is: the structural needs of industrialization and inclusion of all people in the productive work universe. This context shapes the creative atmosphere of the constructivist avant-garde, which uses the methods of engineering to the transform everyday life. Architecture, urban planning, and state planning integrated must then operate as spatial arrangement morphologically able to produce socialist life. But due to the intrinsic contradictions of the process, the rational and geometric aesthetic of the City-Machine appears, finally, as an image of a scientific socialist utopia.Keywords: city-machine, critique of space, production of space, soviet territorialization
Procedia PDF Downloads 27715411 The BL-5D Model: The Development of a Model of Instructional Design for Blended Learning Activities
Authors: Damian Gordon, Paul Doyle, Anna Becevel, Júlia Vilafranca Molero, Cinta Gascon, Arianna Vitiello, Tina Baloh
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It has long been recognized that the creation of any teaching content can be enhanced if the development process follows a pre-defined approach, which is often referred to as an instructional design methodology. These methodologies typically define a number of stages, or phases, that an educator should undertake to help ensure the quality of the final teaching content that is developed. In this paper, we present an instructional design methodology that is focused specifically on the introduction of blended resources into a heretofore bricks-and-mortar course. To achieve this, research was undertaken concerning a range of models of instructional design, as well as literature covering some of the key challenges and “pain points” of blending. Following this, our model, the BL-5D model, is presented, which incorporates some key questions at each stage of this five-stage methodology to guide the development process. Finally, a discussion of some of the key themes and issues that have been uncovered in this work is presented, as well as a template for a blended learning case study that emerged from this approach.Keywords: blended learning, challenges of blended learning, design methodologies, instructional design
Procedia PDF Downloads 11915410 Numerical Simulation of a Three-Dimensional Framework under the Action of Two-Dimensional Moving Loads
Authors: Jia-Jang Wu
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The objective of this research is to develop a general technique so that one may predict the dynamic behaviour of a three-dimensional scale crane model subjected to time-dependent moving point forces by means of conventional finite element computer packages. To this end, the whole scale crane model is divided into two parts: the stationary framework and the moving substructure. In such a case, the dynamic responses of a scale crane model can be predicted from the forced vibration responses of the stationary framework due to actions of the four time-dependent moving point forces induced by the moving substructure. Since the magnitudes and positions of the moving point forces are dependent on the relative positions between the trolley, moving substructure and the stationary framework, it can be found from the numerical results that the time histories for the moving speeds of the moving substructure and the trolley are the key factors affecting the dynamic responses of the scale crane model.Keywords: moving load, moving substructure, dynamic responses, forced vibration responses
Procedia PDF Downloads 35215409 Social Collaborative Learning Model Based on Proactive Involvement to Promote the Global Merit Principle in Cultivating Youths' Morality
Authors: Wera Supa, Panita Wannapiroon
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This paper is a report on the designing of the social collaborative learning model based on proactive involvement to Promote the global merit principle in cultivating youths’ morality. The research procedures into two phases, the first phase is to design the social collaborative learning model based on proactive involvement to promote the global merit principle in cultivating youths’ morality, and the second is to evaluate the social collaborative learning model based on proactive involvement. The sample group in this study consists of 15 experts who are dominant in proactive participation, moral merit principle and youths’ morality cultivation from executive level, lecturers and the professionals in information and communication technology expertise selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. This study has explored that there are four significant factors in promoting the hands-on collaboration of global merit scheme in order to implant virtues to adolescences which are: 1) information and communication Technology Usage; 2) proactive involvement; 3) morality cultivation policy, and 4) global merit principle. The experts agree that the social collaborative learning model based on proactive involvement is highly appropriate.Keywords: social collaborative learning, proactive involvement, global merit principle, morality
Procedia PDF Downloads 38815408 Two Concurrent Convolution Neural Networks TC*CNN Model for Face Recognition Using Edge
Authors: T. Alghamdi, G. Alaghband
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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.
Procedia PDF Downloads 15315407 Recycling, Reuse and Reintegration of Steel Plant Fines
Authors: R. K. Agrawal, Shiv Agrawal
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Fines and micro create fundamental problems of respiration. From mines to mills steel plants generate lot of pollutants. Legislation & Government laws are stricter day by day & each plant has to think of recycling, reuse &reintegration of pollutants generated during the process of steel making. This paper deals with experiments conducted in Bhilai Steel Plant and Real Ispat and Power Limited for reuse, recycle & reintegrate some of the steel making process fines. Iron ore fines with binders have been agglomerated to be used as a part of the charge for small furnaces. This will improve yield at nominal cost. Rolling mill fines have been recycled to increase the yield of sinter making. This will solve the problems of fine disposal. Huge saving on account of recycling will be achieved. Lime fines after briquetting is used along with prime lime. Lime fines have also been used as a binding material during production of fly ash bricks. These fines serve as low-cost binder. Experiments have been conducted along with coke breeze & gas cleaning plant sludge. As a result, the anti-sloping compound has been developed for converter vessels. Dolo char and Char during Sponge Iron production have been successfully used in power generation and brick making. Pellets have been made with ventilation dust & flue dust. These samples have been tried as a coolant in the converter. Pellets have been made with Sinter Plant electrostatic precipitator micro fines with liquid binder. Trials have been conducted to reuse these pellets in sinter making. Coke breeze from coke-ovens fines and mill scale along with binders were agglomerated. This was used in furnace after attaining required screening and reactivity index. These actions will definitely bring social, economic and environment-friendly universe.Keywords: briquette, dolo char, electrostatic precipitator, pellet, sinter
Procedia PDF Downloads 39115406 Mathematical Modeling of the Water Bridge Formation in Porous Media: PEMFC Microchannels
Authors: N. Ibrahim-Rassoul, A. Kessi, E. K. Si-Ahmed, N. Djilali, J. Legrand
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The static and dynamic formation of liquid water bridges is analyzed using a combination of visualization experiments in a microchannel with a mathematical model. This paper presents experimental and theoretical findings of water plug/capillary bridge formation in a 250 μm squared microchannel. The approach combines mathematical and numerical modeling with experimental visualization and measurements. The generality of the model is also illustrated for flow conditions encountered in manipulation of polymeric materials and formation of liquid bridges between patterned surfaces. The predictions of the model agree favorably the observations as well as with the experimental recordings.Keywords: green energy, mathematical modeling, fuel cell, water plug, gas diffusion layer, surface of revolution
Procedia PDF Downloads 53015405 East West Discourse: An Esoteric Comparison of the Western Philosophy and the Eastern Vedanta
Authors: Chandrabati Chakraborty
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The progressive emergence, in the course of the evolution of life, mind and personality, requires us to assume a creative Principle operating timeless Reality in the temporal. The difference between Western philosophy and that of India, concerns the origin and the purpose of the philosophical enquiry. While the former wonders at the external world, the latter is awareness of perennial suffering associated with human existence. The present world suffers from a basic form of rootlessness,reflecting many psychological, philosophical studies. Alienation,a major theme of human condition in the contemporary epoch has emerged as natural consequences of existential predicament. As Edmund Fuller also observes that individuals suffer not only from famine, ruin or even war but also from devastating inner problems, which are that of estrangement, hopelessness and utter despair. This existentialism is thus considered by Jean Wahl as the “Philosophies of existence”.The post world war scenario well analyses the chaos,annihilation,frustration and anguished estrangement. In such conditions when the West cries out , “What is there?I know first of all that I am.But who am I?.....I am sepeated.What I am seperated from I cannot name it. But I am seperated.”(Dostoevsky:The Confession), Vedantic philosophy looks upon the Pilgrim’s Progress of Humanity as being essentially one,operationg squarely within the bounds of reality, reflecting a basic human experience, outbraving indecorous dictims that have failed to give due honour to human beings,echoing for centuries the Sanskrit slokas with ultimate certitude: II Esa Atma samaha plusina samo masakena samo nagena sama ebhis tribhir lokaih.....sama nena sarvena II (The Atman (Divine Soul) is the same in the ant, the same in the gnat, the same in the elephant, the same in these three worlds....the same in the whole Universe). The present paper aims at a comparative study of cultural and philosophical expression taking into view extensive illustrations from Western Philosophers and The Vedantic,Upanishadic lores of Indian philosophy.Keywords: existentialism, Vedanta, philosophy, absurdism
Procedia PDF Downloads 9015404 Automatic Classification of Lung Diseases from CT Images
Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari
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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification
Procedia PDF Downloads 15515403 Supervised-Component-Based Generalised Linear Regression with Multiple Explanatory Blocks: THEME-SCGLR
Authors: Bry X., Trottier C., Mortier F., Cornu G., Verron T.
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We address component-based regularization of a Multivariate Generalized Linear Model (MGLM). A set of random responses Y is assumed to depend, through a GLM, on a set X of explanatory variables, as well as on a set T of additional covariates. X is partitioned into R conceptually homogeneous blocks X1, ... , XR , viewed as explanatory themes. Variables in each Xr are assumed many and redundant. Thus, Generalised Linear Regression (GLR) demands regularization with respect to each Xr. By contrast, variables in T are assumed selected so as to demand no regularization. Regularization is performed searching each Xr for an appropriate number of orthogonal components that both contribute to model Y and capture relevant structural information in Xr. We propose a very general criterion to measure structural relevance (SR) of a component in a block, and show how to take SR into account within a Fisher-scoring-type algorithm in order to estimate the model. We show how to deal with mixed-type explanatory variables. The method, named THEME-SCGLR, is tested on simulated data.Keywords: Component-Model, Fisher Scoring Algorithm, GLM, PLS Regression, SCGLR, SEER, THEME
Procedia PDF Downloads 39615402 A Model Towards Creating Positive Accounting Classroom Conditions That Supports Successful Learning at School
Authors: Vine Petzer, Mirna Nel
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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting
Procedia PDF Downloads 14615401 Resistance and Sub-Resistances of RC Beams Subjected to Multiple Failure Modes
Authors: F. Sangiorgio, J. Silfwerbrand, G. Mancini
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Geometric and mechanical properties all influence the resistance of RC structures and may, in certain combination of property values, increase the risk of a brittle failure of the whole system. This paper presents a statistical and probabilistic investigation on the resistance of RC beams designed according to Eurocodes 2 and 8, and subjected to multiple failure modes, under both the natural variation of material properties and the uncertainty associated with cross-section and transverse reinforcement geometry. A full probabilistic model based on JCSS Probabilistic Model Code is derived. Different beams are studied through material nonlinear analysis via Monte Carlo simulations. The resistance model is consistent with Eurocode 2. Both a multivariate statistical evaluation and the data clustering analysis of outcomes are then performed. Results show that the ultimate load behaviour of RC beams subjected to flexural and shear failure modes seems to be mainly influenced by the combination of the mechanical properties of both longitudinal reinforcement and stirrups, and the tensile strength of concrete, of which the latter appears to affect the overall response of the system in a nonlinear way. The model uncertainty of the resistance model used in the analysis plays undoubtedly an important role in interpreting results.Keywords: modelling, Monte Carlo simulations, probabilistic models, data clustering, reinforced concrete members, structural design
Procedia PDF Downloads 47215400 Soft Computing Employment to Optimize Safety Stock Levels in Supply Chain Dairy Product under Supply and Demand Uncertainty
Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih
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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization
Procedia PDF Downloads 12515399 Learning Algorithms for Fuzzy Inference Systems Composed of Double- and Single-Input Rule Modules
Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima
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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.Keywords: Box-Jenkins's problem, double-input rule module, fuzzy inference model, obstacle avoidance, single-input rule module
Procedia PDF Downloads 35215398 Improving Reading Comprehension Skills of Elementary School Students through Cooperative Integrated Reading and Composition Model Using Padlet
Authors: Neneng Hayatul Milah
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The most important reading skill for students is comprehension. Understanding the reading text will have an impact on learning outcomes. However, reading comprehension instruction in Indonesian elementary schools is lacking. A more effective learning model is needed to enhance students' reading comprehension. This study aimed to evaluate the effectiveness of the CIRC (Cooperative Integrated Reading and Composition) model with Padlet integration in improving the reading comprehension skills of grade IV students in elementary schools in Cimahi City, Indonesia. This research methodology was quantitative with a pre-experiment research type and one group pretest-posttest research design. The sample of this study consisted of 30 students. The results of statistical analysis showed that there was a significant effect of using the CIRC learning model using Padlet on improving students' reading comprehension skills of narrative text. The mean score of students' pretest was 67.41, while the mean score of the posttest increased to 84.82. The paired sample t-test resulted in a t-count score of -13.706 with a significance score of <0.001, which is smaller than α = 0.05. This research is expected to provide useful insights for educational practitioners on how the use of the CIRC model using Padlet can improve the reading comprehension skills of elementary school students.Keywords: reading comprehension skills, CIRC, Padlet, narrative text
Procedia PDF Downloads 3215397 CFD Study of Subcooled Boiling Flow at Elevated Pressure Using a Mechanistic Wall Heat Partitioning Model
Authors: Machimontorn Promtong, Sherman C. P. Cheung, Guan H. Yeoh, Sara Vahaji, Jiyuan Tu
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The wide range of industrial applications involved with boiling flows promotes the necessity of establishing fundamental knowledge in boiling flow phenomena. For this purpose, a number of experimental and numerical researches have been performed to elucidate the underlying physics of this flow. In this paper, the improved wall boiling models, implemented on ANSYS CFX 14.5, were introduced to study subcooled boiling flow at elevated pressure. At the heated wall boundary, the Fractal model, Force balance approach and Mechanistic frequency model are given for predicting the nucleation site density, bubble departure diameter, and bubble departure frequency. The presented wall heat flux partitioning closures were modified to consider the influence of bubble sliding along the wall before the lift-off, which usually happens in the flow boiling. The simulation was performed based on the Two-fluid model, where the standard k-ω SST model was selected for turbulence modelling. Existing experimental data at around 5 bars were chosen to evaluate the accuracy of the presented mechanistic approach. The void fraction and Interfacial Area Concentration (IAC) are in good agreement with the experimental data. However, the predicted bubble velocity and Sauter Mean Diameter (SMD) are over-predicted. This over-prediction may be caused by consideration of only dispersed and spherical bubbles in the simulations. In the future work, the important physical mechanisms of bubbles, such as merging and shrinking during sliding on the heated wall will be incorporated into this mechanistic model to enhance its capability for a wider range of flow prediction.Keywords: subcooled boiling flow, computational fluid dynamics (CFD), mechanistic approach, two-fluid model
Procedia PDF Downloads 31815396 Multi-Objective Multi-Period Allocation of Temporary Earthquake Disaster Response Facilities with Multi-Commodities
Authors: Abolghasem Yousefi-Babadi, Ali Bozorgi-Amiri, Aida Kazempour, Reza Tavakkoli-Moghaddam, Maryam Irani
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All over the world, natural disasters (e.g., earthquakes, floods, volcanoes and hurricanes) causes a lot of deaths. Earthquakes are introduced as catastrophic events, which is accident by unusual phenomena leading to much loss around the world. Such could be replaced by disasters or any other synonyms strongly demand great long-term help and relief, which can be hard to be managed. Supplies and facilities are very important challenges after any earthquake which should be prepared for the disaster regions to satisfy the people's demands who are suffering from earthquake. This paper proposed disaster response facility allocation problem for disaster relief operations as a mathematical programming model. Not only damaged people in the earthquake victims, need the consumable commodities (e.g., food and water), but also they need non-consumable commodities (e.g., clothes) to protect themselves. Therefore, it is concluded that paying attention to disaster points and people's demands are very necessary. To deal with this objective, both commodities including consumable and need non-consumable commodities are considered in the presented model. This paper presented the multi-objective multi-period mathematical programming model regarding the minimizing the average of the weighted response times and minimizing the total operational cost and penalty costs of unmet demand and unused commodities simultaneously. Furthermore, a Chebycheff multi-objective solution procedure as a powerful solution algorithm is applied to solve the proposed model. Finally, to illustrate the model applicability, a case study of the Tehran earthquake is studied, also to show model validation a sensitivity analysis is carried out.Keywords: facility location, multi-objective model, disaster response, commodity
Procedia PDF Downloads 25715395 Source Identification Model Based on Label Propagation and Graph Ordinary Differential Equations
Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang
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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.Keywords: source identification, ordinary differential equations, label propagation, complex networks
Procedia PDF Downloads 2015394 The Value of Store Choice Criteria on Perceived Patronage Intentions
Authors: Susana Marques
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Research on how store environment cues influence consumers’ store choice decision criteria, such as store operations, product quality, monetary price, store image and sales promotion, is sparse. Especially absent research on the simultaneous impact of multiple store environment cues. The authors propose a comprehensive store choice model that includes: three types of store environment cues as exogenous constructs; various store choice criteria as possible mediating constructs, and store patronage intentions as an endogenous construct. On the basis of testing with a sample of 561 customers of hypermarkets, the model is partially supported. This study used structural equation modelling to test the proposed model.Keywords: store choice, store patronage, structural equation modelling, retailing
Procedia PDF Downloads 27215393 The Growth Curve of Gompertz Model in Body Weight of Slovak Mixed-Sex Goose Breeds
Authors: Cyril Hrncar, Jozef Bujko, Widya P. B. Putra
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The growth curve of poultry is important to evaluate the farming management system. This study was aimed to estimate the growth curve of body weight in goose. The growth curve in this study was estimated with non-linear Gompertz model through CurveExpert 1.4. software. Three Slovak mixed-sex goose breeds of Landes (L), Pomeranian (P) and Steinbacher (S) were used in this study. Total of 28 geese (10 L, 8 P and 10 S) were used to estimate the growth curve. Research showed that the asymptotic weight (A) in those geese were reached of 5332.51 g (L), 6186.14 g (P) and 5048.27 g (S). Thus, the maturing rate (k) in each breed were similar (0.05 g/day). The weight of inflection was reached of 1960.48 g (L), 2274.32 g (P) and 1855.98 g (S). The time of inflection (ti) was reached of 25.6 days (L), 26.2 days (P) and 27.80 days (S). The maximum growth rate (MGR) was reached of 98.02 g/day (L), 113.72 g/day (P) and 92.80 g/day (S). Hence, the coefficient of determination (R2) in Gompertz model was 0.99 for each breed. It can be concluded that Pomeranian geese had highest of growth trait than the other breeds.Keywords: body weight, growth curve, inflection, Slovak geese, Gompertz model
Procedia PDF Downloads 14715392 Food Security Model and the Role of Community Empowerment: The Case of a Marginalized Village in Mexico, Tatoxcac, Puebla
Authors: Marco Antonio Lara De la Calleja, María Catalina Ovando Chico, Eduardo Lopez Ruiz
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Community empowerment has been proved to be a key element in the solution of the food security problem. As a result of a conceptual analysis, it was found that agricultural production, economic development and governance, are the traditional basis of food security models. Although the literature points to social inclusion as an important factor for food security, no model has considered it as the basis of it. The aim of this research is to identify different dimensions that make an integral model for food security, with emphasis on community empowerment. A diagnosis was made in the study community (Tatoxcac, Zacapoaxtla, Puebla), to know the aspects that impact the level of food insecurity. With a statistical sample integrated by 200 families, the Latin American and Caribbean Food Security Scale (ELCSA) was applied, finding that: in households composed by adults and children, have moderated food insecurity, (ELCSA scale has three levels, low, moderated and high); that result is produced mainly by the economic income capacity and the diversity of the diet on its food. With that being said, a model was developed to promote food security through five dimensions: 1. Regional context of the community; 2. Structure and system of local food; 3. Health and nutrition; 4. Information and technology access; and 5. Self-awareness and empowerment. The specific actions on each axis of the model, allowed a systemic approach needed to attend food security in the community, through the empowerment of society. It is concluded that the self-awareness of local communities is an area of extreme importance, which must be taken into account for participatory schemes to improve food security. In the long term, the model requires the integrated participation of different actors, such as government, companies and universities, to solve something such vital as food security.Keywords: community empowerment, food security, model, systemic approach
Procedia PDF Downloads 37215391 A Comprehensive Metamodel of an Urbanized Information System: Experimental Case
Authors: Leila Trabelsi
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The urbanization of Information Systems (IS) is an effective approach to master the complexity of the organization. It strengthens the coherence of IS and aligns it with the business strategy. Moreover, this approach has significant advantages such as reducing Information Technologies (IT) costs, enhancing the IS position in a competitive environment and ensuring the scalability of the IS through the integration of technological innovations. Therefore, the urbanization is considered as a business strategic decision. Thus, its embedding becomes a necessity in order to improve the IS practice. However, there is a lack of experimental cases studying meta-modelling of Urbanized Information System (UIS). The aim of this paper addresses new urbanization content meta-model which permits modelling, testing and taking into consideration organizational aspects. This methodological framework is structured according to two main abstraction levels, a conceptual level and an operational level. For each of these levels, different models are proposed and presented. The proposed model for has been empirically tested on company. The findings of this paper present an experimental study of urbanization meta-model. The paper points out the significant relationships between dimensions and their evolution.Keywords: urbanization, information systems, enterprise architecture, meta-model
Procedia PDF Downloads 437