Search results for: physical models

Authors: Kwan U. Kim, Jin Sim, Ryong Jin Jang, Sung Duk Kim

Abstract:

108 years have passed since a great number of physicists explained astronomical and physical phenomena by solving geodesic equations in Schwarzschild metric. However, when solving the geodesic equations in Schwarzschild metric, they did not correctly solve one branch of the component of space among spatial and temporal components of four-dimensional force and did not come up with physical laws correctly by means of physical analysis from the results obtained by solving the geodesic equations. In addition to it, they did not treat the astronomical and physical phenomena in a physical way based on the correct physical laws obtained from the solution of the geodesic equations in Schwarzschild metric. Therefore, some former scholars mentioned that Einstein’s theoretical basis of the general theory of relativity was obscure and incorrect, but they have not given a correct physical solution to the problems. Furthermore, since the general theory of relativity has not given a quantitative solution to obscure and incorrect problems, the generalization of gravitational theory has not been successfully completed yet, although the former scholars thought of it and tried to do it. In order to solve the problems it is necessary to explore the obscure and incorrect problems in general theory of relativity based on the physical laws and to find out the methodology of solving the problems. Therefore, first of all, as the first step for achieving the purpose, the right solution of the geodesic equation in Schwarzschild metric has been presented. Next, the correct physical laws found by making a physical analysis of the results have been presented, the obscure and incorrect problems have been shown, and an analysis of them has been made based on the physical laws. In addition, the experimental verification of the physical laws found by us has been made.

Keywords: equivalence principle, general relativity, geometrodynamics, Schwarzschild, Poincaré

Procedia PDF Downloads 50

Authors: Ayman Aboelkassem, Mahmoud Ali

Abstract:

Introduction: The models of soul houses have appeared in the prehistory, old kingdom and middle kingdom period. These soul houses represented the imagination of the deceased about his house in the afterlife, some of these soul houses were two floors and the study will examine five models of soul houses which were discovered near Saqqara site by an Egyptian mission. These models had been transferred to The Grand Egyptian Museum (GEM) to be ready to display at the new museum. We focus on models of soul houses (GEM Numbers, 1276, 1280, 1281, 1282, 8711) these models of soul houses were related to the old kingdom period. These models were all made of pottery, the five models have an oval shape and were decorated with relief. Methodology: The study will focus on the development of soul houses during the different periods in ancient Egypt, the function of soul houses, the kind of offerings which were put in it and the symbolism of the offerings colors in ancient Egyptian believe. Conclusion: This study is useful for the heritage and ancient civilizations especially when we talk about opening new museums like The Grand Egyptian Museum which will display a new collection of soul houses. The study of soul houses and The kinds of offerings which put in it reflect the economic situation in the Egyptian society and kinds of oils which were famous in ancient Egypt.

Keywords: archaeology study, Grand Egyptian Museum, relief, soul houses

Procedia PDF Downloads 234

Authors: Katarzyna Kamińska

Abstract:

The main purpose of the work is to present the results of the studies regarding joint physical custody in the Polish legal system. The issues addressed fit into the ongoing process of modernising family law regulations and their adaptation to changing social reality in Poland. The Polish legislator now faces a dilemma: whether to introduce into Polish law a developed substantive or procedural regulation of joint physical custody and then whether it should be considered a legal presumption. Joint physical custody after divorce or separation is theoretically possible in Poland. It can either follow from the court’s independent proposal based on the assessment of the circumstances or from the parenting plan submitted by parents wishing to jointly retain full parental authority. However, joint physical custody does not result directly from the Polish Family and Guardianship Code. Therefore, there is real legal uncertainty in this matter, which leads to different treatment of citizens by the public authorities and courts. Another problem is that joint physical custody is misunderstood by the Polish courts. The main thesis of the work is that joint physical custody does not only mean the system of symmetrical child care (50/50), and the possibility to award joint physical custody will require the courts to carefully weigh the pros and cons of such an arrangement in each individual case.

Keywords: joint physical custody, shared parenting, divorce, separation, parental authority

Procedia PDF Downloads 58

Authors: Tao Zhang, Fen Zhang

Abstract:

Physical evidence has emerged as an important concept for understanding customers' behavior in the service industry. While it is still not clear about the effect of physical evidence of themed casino hotels on customer value and satisfaction. After deciding on the research context, the processes of this research started with a review of literature in three subject areas: physical evidence, customer value, and customer satisfactions. Insights from the literature review and pilot interviews are important input that informs the development of the specific research questions. Data collection for this research will be done for two studies: a photo elicitation study and an in-depth interview study.

Keywords: casino, customer value, customer satisfaction, hotel, physical evidence

Procedia PDF Downloads 385

Authors: Gurleen Kaur

Abstract:

Being tall-short, fat-thin, black-white, etc. is an inevitable part of how people perceive you. This association of people with your external appearance carves out an identity for you. This paper will look at the reasons why people relate a person to a particular categorization on the basis of his/her physical appearance. The paper delves into reasons for this categorization into groups: Subconscious grouping, personal gain, ease of relating to the group, and social acceptance. Development of certain unique physical features also leads to a person relating himself to a collective identity. Thus, this paper will support the fact that physical appearance plays a crucial role in categorization of people into groups and hence forming a group identity for them. This paper is divided into three parts. The first part will discuss what physical appearance is and how is it linked to our daily lives. The second part will talk about why it works i.e. why this factor of external appearance is important in formation of identity. The last part will talk about the factors which lead to categorization of identity because of physical appearance.

Keywords: group identity, physical appearance, subconscious grouping, collective identity

Procedia PDF Downloads 405

Authors: Aline Giardin

Abstract:

Introduction: This review addresses the relationship between physical education and mental health and its main objective is to discuss the meanings that circulate in Psychiatric Hospitalization Units and Psychosocial Care Centers (CAPS) about the presence of physical education teachers and the practices developed by Them within these services. Material and methods: It is based on the theoretical contribution of the Psychiatric Reform and is methodologically inspired by the Bibliographic Review. Objectives: The objective of this review was to identify the main scientific evidence on the effects of physical activity on the main psychological aspects associated with mental health during the hospitalization process. Results: It was observed that physical activity has beneficial effects in the psychological, social and cognitive aspects, being thus a fundamental aspect of the lifestyle in promoting a healthy and successful treatment. In studies evaluating the effects of physical activity on mental health, the most frequently evaluated outcomes include anxiety, depression, and health-related quality of life (eg, self-esteem and self-efficacy). Evidence from epistemological studies indicates that the level of physical activity is positively associated with good mental health, when mental health is defined as good mood, general well-being and decreased symptoms. Conclusion: It is necessary to intervene and a greater interest of the professionals of physical education in the treatment with the people with mental disorders so that the negative symptoms are modified, through the aid of the physical activity, by better quality of life, physical condition, nutritional state and A healthy emotional appearance.

Keywords: health mental, physical activity, benefits, treatment

Procedia PDF Downloads 328

Authors: Ellie Abdi, Susana Juniu

Abstract:

The purpose of this presentation is to describe an interdisciplinary teaching program that integrates physical education concepts using a philosophical approach. The presentation includes a review of: a) the philosophy of American education, b) the philosophy of sports and physical education, c) the interdisciplinary physical education program, d) professional development programs, (e) the Success of this physical education program, f) future of physical education. This unique interdisciplinary program has been implemented in an urban school physical education discipline in East Orange, New Jersey for over 10 years. During the program the students realize that the bodies go through different experiences. The body becomes a place where a child can recognize in an enjoyable way to express and perceive particular feelings or mental states. Children may distinguish themselves to have high abilities in the social or other domains but low abilities in the field of athletics. The goal of this program for the individuals is to discover new skills, develop and demonstrate age appropriate mastery level at different tasks, therefore the program consists of 9 to 12 sports, including many game. Each successful experience increases the awareness ability. Engaging in sports and physical activities are social movements involving groups of children in situations such as teams, friends, and recreational settings, which serve as a primary socializing agent for teaching interpersonal skills. As a result of this presentation the audience will reflect and explore how to structure a physical education program to integrate interdisciplinary subjects with philosophical concepts.

Keywords: interdisciplinary disciplines, philosophical concepts, physical education, interdisciplinary teaching program

Procedia PDF Downloads 473

Authors: Mohamad Reza Khodabakhsh

Abstract:

Physical activity is important because it affects the stress and mental health of the elderly. The purpose of this research is to examine the relationship between the physical activity of the elderly and stress and mental health. The current research is correlational research, and the studied population includes all the elderly who are engaged in sports in the parks of Mashhad city in 2021. The whole community consists of 200 people. Sampling was done by the headcount method. The tool used in this research is a questionnaire. The physical activity questionnaire is Likert. General GHQ is based on the self-report method. The study method is correlation type to find the relationship between predictor and predicted variables, and the multiple regression method was used for the relationships between the sub-components. And the results showed that physical activity has the effect of reducing the stress of the elderly and improving their mental health. In general, the results of this research indicate the confirmation of the research hypotheses.

Keywords: relationship, physical activity, stress, mental health, elderly

Procedia PDF Downloads 73

Authors: Sh. Khoshemehry, M. J. Pourvaghar, M. E. Bahram

Abstract:

In modern life, daily physical activity is relatively reduced, which is why the incidence of some diseases associated with overweight and obesity, such as hypertension, diabetes and other chronic illnesses, even in young people are observed. Obesity and overweight is one of the most common metabolic disorders in industrialized countries and in developing countries. One consequence of pathological obesity is cardiovascular disease and metabolic syndrome. In the past, it was believed that adipose tissue was ineffective and served only for storing triglycerides. In this review article, it was tried to refer to the esteemed scientific sources about physical activity and responses of leptin.

Keywords: disease, leptin, obesity, physical activity

Procedia PDF Downloads 324

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

Procedia PDF Downloads 471

Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

Abstract:

The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

Procedia PDF Downloads 252

Authors: Megha Gupta, Nupur Prakash

Abstract:

Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

Procedia PDF Downloads 174

Authors: M. Alkhalidi, S. Neelamani, Z. Al-Zaqah

Abstract:

This paper investigates the interaction of single and twin offshore rubble mound breakwaters with regular and random water waves through physical modeling to assess their reflection, transmission and energy dissipation characteristics. Various combinations of wave heights and wave periods were utilized in a series of experiments, along with three different water depths. The single and twin permeable breakwater models were both constructed with one layer of rubbles. Both models had the same total volume; however, the single breakwater was of trapezoidal type while the twin breakwaters were of triangular type. Physical modeling experiments were carried out in the wave flume of the coastal engineering laboratory of Kuwait Institute for Scientific Research (KISR). Measurements of the six wave probes which were fixed in the two-dimensional wave flume were collected and used to determine the generated incident wave heights, as well as the reflected and transmitted wave heights resulting from the wave-breakwater interaction. The possible factors affecting the wave attenuation efficiency of the breakwater models are the relative water depth (d/L), wave steepness (H/L), relative wave height ((h-d)/Hi), relative height of the breakwater (h/d), and relative clear spacing between the twin breakwaters (S/h). The results indicated that the single and double breakwaters show different responds to the change in their relative height as well as the relative wave height which demonstrates that the effect of the relative water depth on wave reflection, transmission, and energy dissipation is highly influenced by the change in the relative breakwater height, the relative wave height and the relative breakwater spacing. In general, within the range of the relative water depth tested in this study, and under both regular and random waves, it is found that the single breakwater allows for lower wave transmission and shows higher energy dissipation effect than both of the tested twin breakwaters, and hence has the best overall performance.

Keywords: random waves, regular waves, relative water depth, relative wave height, single breakwater, twin breakwater, wave steepness

Procedia PDF Downloads 303

Authors: Amira Abdelrasoul, Huu Doan, Ali Lohi

Abstract:

An efficient and well-planned ultrafiltration process is becoming a necessity for monetary returns in the industrial settings. The aim of the present study was to develop a mathematical model for an accurate prediction of ultrafiltration membrane fouling of latex effluent applied to homogeneous and heterogeneous membranes with uniform and non-uniform pore sizes, respectively. The models were also developed for an accurate prediction of power consumption that can handle the large-scale purposes. The model incorporated the fouling attachments as well as chemical and physical factors in membrane fouling for accurate prediction and scale-up application. Both Polycarbonate and Polysulfone flat membranes, with pore sizes of 0.05 µm and a molecular weight cut-off of 60,000, respectively, were used under a constant feed flow rate and a cross-flow mode in ultrafiltration of the simulated paint effluent. Furthermore, hydrophilic ultrafilic and hydrophobic PVDF membranes with MWCO of 100,000 were used to test the reliability of the models. Monodisperse particles of 50 nm and 100 nm in diameter, and a latex effluent with a wide range of particle size distributions were utilized to validate the models. The aggregation and the sphericity of the particles indicated a significant effect on membrane fouling.

Keywords: membrane fouling, mathematical modeling, power consumption, attachments, ultrafiltration

Procedia PDF Downloads 456

Authors: Tai-Yue Wang, Yi-Ho Chen

Abstract:

In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model.

Keywords: supply chain, price promotion, mathematical models, dominant retailer

Procedia PDF Downloads 388

Authors: Menan M. Elsayed, Hussein A. Heshmat

Abstract:

The aim of the study is to assess the effect of resistance training on muscle strength and physical performance of volleyball players of Physical Education College, Helwan University. The researcher used the experimental method of pre-post measurements of one group of 10 volleyball players. The execution of the program was through the period of 12/8/2018 to 12/10/2018; included 24 training units, 3 training units weekly for 8 weeks. The training program revealed an improvement in post measurement of muscle strength, IGF₁ (insulin-like growth factor 1), and physical performance of players. It may be concluded that the resistance training may include changes in hormones and muscle fibers leading to hypertrophy of the muscle and physical performance. It is recommended to use the results of the study in rationing the loads and training programs.

Keywords: IGF₁, muscle strength, physical performance, resistance training, volleyball players

Procedia PDF Downloads 174

Authors: Mohammad Anwar, Shah Waliullah

Abstract:

This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

Procedia PDF Downloads 58

Authors: Alam Ali, Ashok Kumar Pathak

Abstract:

Path analysis is a statistical technique used to evaluate the direct and indirect effects of variables in path models. One or more structural regression equations are used to estimate a series of parameters in path models to find the better fit of data. However, sometimes the assumptions of classical regression models, such as ordinary least squares (OLS), are violated by the nature of the data, resulting in insignificant direct and indirect effects of exogenous variables. This article aims to explore the effectiveness of a copula-based regression approach as an alternative to classical regression, specifically when variables are linked through an elliptical copula.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

Procedia PDF Downloads 15

Authors: Shani Brathwaite, Deborah Villarroel-Lamb

Abstract:

Wave run-up may be defined as the time-varying position of the landward extent of the water’s edge, measured vertically from the mean water level position. The hydrodynamics of the swash zone and the accurate prediction of maximum wave run-up, play a critical role in the study of coastal engineering. The understanding of these processes is necessary for the modeling of sediment transport, beach recovery and the design and maintenance of coastal engineering structures. However, due to the complex nature of the swash zone, there remains a lack of detailed knowledge in this area. Particularly, there has been found to be insufficient consideration of bed porosity and ultimately infiltration/exfiltration processes, in the development of wave run-up models. Theoretically, there should be an inverse relationship between maximum wave run-up and beach porosity. The greater the rate of infiltration during an event, associated with a larger bed porosity, the lower the magnitude of the maximum wave run-up. Additionally, most models have been developed using data collected on North American or Australian beaches and may have limitations when used for operational forecasting in Trinidad. This paper aims to assess the influence and significance of infiltration and exfiltration processes on wave run-up magnitudes within the swash zone. It also seeks to pay particular attention to how well various empirical formulae can predict maximum run-up on contrasting beaches in Trinidad. Traditional surveying techniques will be used to collect wave run-up and cross-sectional data on various beaches. Wave data from wave gauges and wave models will be used as well as porosity measurements collected using a double ring infiltrometer. The relationship between maximum wave run-up and differing physical parameters will be investigated using correlation analyses. These physical parameters comprise wave and beach characteristics such as wave height, wave direction, period, beach slope, the magnitude of wave setup, and beach porosity. Most parameterizations to determine the maximum wave run-up are described using differing parameters and do not always have a good predictive capability. This study seeks to improve the formulation of wave run-up by using the aforementioned parameters to generate a formulation with a special focus on the influence of infiltration/exfiltration processes. This will further contribute to the improvement of the prediction of sediment transport, beach recovery and design of coastal engineering structures in Trinidad.

Keywords: beach porosity, empirical models, infiltration, swash, wave run-up

Procedia PDF Downloads 337

Authors: Anjli Pathak, Harshit Sosan Lakra, Smriti Mishra

Abstract:

The increasing urbanization affects the external environment in which people exist and imposes livelihood vulnerability to shocks and stresses. Although research on the linkages between urbanization and vulnerability has been increasing, only a few studies have examined the caste/ethnicity in livelihood vulnerability. In this study, we explore how physical capital influences vulnerability among indigenous people in the context of livelihood. The study identifies the dimensions and indicators of physical capital that influence the profile of household vulnerability in the livelihood-building process. The result identified five dimensions and 19 indicators of livelihood vulnerability. The study also visualizes the inter-relationship between physical capital and other livelihood capital in formulating the livelihood vulnerability framework.

Keywords: urbanization, livelihood vulnerability, indigenous people, physical capital

Procedia PDF Downloads 54

Authors: Florin Leon, Silvia Curteanu

Abstract:

Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

Procedia PDF Downloads 290

Authors: S. Nikpour, S. Vahidi, H. Haghani

Abstract:

Introduction: Exercise has mental and physical health benefits for patients with advanced stage cancer who actively receive chemotherapy, yet little is known about patients’ levels of interest in becoming more active or their confidence in increasing their activity level. Methods and materials: A convenience sample of 200 patients with advanced-stage cancer who were receiving chemotherapy completed self-report measures assessing physical activity level, mood, and quality-of-life variables. Qualitative data on patient-perceived benefits of, and barriers to, physical activity also were collected, coded by independent raters, and organized by predominant themes. Results: Current physical activity level, physical activity outcome expectations, and positive mood were significantly associated with self-efficacy. Fatigue was the most frequently listed barrier to physical activity; improved physical strength and health were the most commonly listed benefits. Participants identified benefits related to both general health and cancer-symptom management that were related to exercise. 59.5% of participants reported that they were seriously planning to increase or maintain their physical activity level, and over 40% reported having interest in receiving an intervention to become more active. Conclusion: These results suggested that many advanced-stage cancer patients who receive chemotherapy are interested in maintaining or increasing their physical activity level and in receiving professional support for exercise. In addition, these individuals identified general health and cancer-specific benefits of, and barriers to, physical activity. Future research will investigate how these findings may be incorporated into physical activity interventions for advanced-stage oncology patients receiving medical treatment.

Keywords: physical activity, cancer, self-efficacy

Procedia PDF Downloads 518

Authors: Alfonso Ippolito, Cristiana Bartolomei

Abstract:

A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

Procedia PDF Downloads 401

Authors: Stephanie Chen, Mitja Echim, Christof Büskens

Abstract:

To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

Procedia PDF Downloads 384

Authors: G. A. Khalid, R. Prabhu, W. Whittington, M. D. Jones

Abstract:

To establish a causal relationship of infant head injury consequences, this present study addresses the necessary challenges of cranial geometry and the physical response complexities of the paediatric head tissues. Herein, we describe a new approach to characterising and understanding infant head impact mechanics by developing printed head models, using high resolution clinical postmortem imaging, to provide the most complete anatomical representation currently available, and biological material response data-matched polypropylene polymers, to replicate the relative mechanical response properties of immature cranial bone, sutures and fontanelles. Additive manufacturing technology was applied to creating a physical polymeric model of a newborn infant skull, using PolyJet printed materials. Infant skull materials responses, were matched by a response characterisation study, utilising uniaxial tensile testing (1 mm min-1 loading rate), to determine: the stiffness, ultimate tensile strength and maximum strain of rigid and rubber additively manufactured acrylates. The results from the mechanical experiments confirm that the polymeric materials RGD835 Vero White Plus (White), representing the frontal and parietal bones; RGD8510- DM Rigid Light Grey25 (Grey), representing the occipital bone; and FLX9870-DM (Black) representing the suture and fontanelles, were found to show a close stiffness -correlation (E) at ambient temperatures. A 3D physical model of infant head was subsequently printed from the matched materials and subsequently validated against results obtained from a series of Post Mortem Human Surrogate (PMHS) tests. A close correlation was demonstrated between the model impact tests and the PMHS. This study, therefore, represents a key step towards applying printed physical models to understanding head injury biomechanics and is useful in the efforts to predict and mitigate head injury consequences in infants, whether accidental or by abuse.

Keywords: infant head trauma, infant skull, material response, post mortem human subjects, polyJet printing

Procedia PDF Downloads 128

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

Abstract:

Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

Procedia PDF Downloads 67

Authors: Giriraj Achari, Malay Bhattacharyya

Abstract:

In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models.

Keywords: Copula, Markov Switching, multifractal, value-at-risk

Procedia PDF Downloads 148

Authors: Elina Bakhtieva

Abstract:

The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis

Procedia PDF Downloads 322

Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

Abstract:

Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: energy models, environmental policy instruments, mitigating CO2 emission, economic wide impact

Procedia PDF Downloads 508

Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

Abstract:

Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

Procedia PDF Downloads 80