Search results for: reduced order models
21883 Adsorption Studies of Lead from Aqueos Solutions on Cocount Shell Activated Carbon
Authors: G. E. Sharaf El-Deen, S. E. A. Sharaf El-Deen
Abstract:
Activated carbon was prepared from coconut shell (ACS); a discarded agricultural waste was used to produce bioadsorbent through easy and environmental friendly processes. This activated carbon based biosorbent was evaluated for adsorptive removal of lead from water. The characterisation results showed this biosorbent had very high specific surface area and functional groups. The adsorption equilibrium data was well described by Langmuir, whilst kinetics data by pseudo-first order, pseudo-second order and Intraparticle diffusion models. The adsorption process could be described by the pseudo-second order kinetic.Keywords: coconut shell, activated carbon, adsorption isotherm and kinetics, lead removal
Procedia PDF Downloads 29721882 Modelling and Maping Malnutrition Toddlers in Bojonegoro Regency with Mixed Geographically Weighted Regression Approach
Authors: Elvira Mustikawati P.H., Iis Dewi Ratih, Dita Amelia
Abstract:
Bojonegoro has proclaimed a policy of zero malnutrition. Therefore, as an effort to solve the cases of malnutrition children in Bojonegoro, this study used the approach geographically Mixed Weighted Regression (MGWR) to determine the factors that influence the percentage of malnourished children under five in which factors can be divided into locally influential factor in each district and global factors that influence throughout the district. Based on the test of goodness of fit models, R2 and AIC values in GWR models are better than MGWR models. R2 and AIC values in MGWR models are 84.37% and 14.28, while the GWR models respectively are 91.04% and -62.04. Based on the analysis with GWR models, District Sekar, Bubulan, Gondang, and Dander is a district with three predictor variables (percentage of vitamin A, the percentage of births assisted health personnel, and the percentage of clean water) that significantly influence the percentage of malnourished children under five. Procedia PDF Downloads 29221881 A Review of Information Systems Development in Developing Countries
Authors: B. N. Asare, O. A. Ajigini
Abstract:
Information systems (IS) are highly important in the operation of private and public organisations in developing and developed countries. Developing countries are saddled with many project failures during the implementation of information systems. However, successful information systems are greatly needed in developing countries in order to enhance their economies. This paper is highly important in view of the high failure rate of information systems in developing countries which needs to be reduced to minimum acceptable levels by means of recommended interventions. This paper centres on a review of IS development in developing countries. The paper presents evidences of the IS successes and failures in developing countries and posits a model to address the IS failures. The proposed model can then be utilised by developing countries to reduce their IS project implementation failure rate. A comparison is drawn between IS development in developing countries and developed countries. The paper provides valuable information to assist in reducing IS failure, and developing IS models and theories on IS development for developing countries.Keywords: developing countries, information systems, IS development, information systems failure, information systems success, information systems success model
Procedia PDF Downloads 37021880 Archaeology Study of Soul Houses in Ancient Egypt on Five Models in the Grand Egyptian Museum
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 24821879 Air Pollution and Respiratory-Related Restricted Activity Days in Tunisia
Authors: Mokhtar Kouki Inès Rekik
Abstract:
This paper focuses on the assessment of the air pollution and morbidity relationship in Tunisia. Air pollution is measured by ozone air concentration and the morbidity is measured by the number of respiratory-related restricted activity days during the 2-week period prior to the interview. Socioeconomic data are also collected in order to adjust for any confounding covariates. Our sample is composed by 407 Tunisian respondents; 44.7% are women, the average age is 35.2, near 69% are living in a house built after the 1980, and 27.8% have reported at least one day of respiratory-related restricted activity. The model consists on the regression of the number of respiratory-related restricted activity days on the air quality measure and the socioeconomic covariates. In order to correct for zero-inflation and heterogeneity, we estimate several models (Poisson, Negative binomial, Zero inflated Poisson, Poisson hurdle, Negative binomial hurdle and finite mixture Poisson models). Bootstrapping and post-stratification techniques are used in order to correct for any sample bias. According to the Akaike information criteria, the hurdle negative binomial model has the greatest goodness of fit. The main result indicates that, after adjusting for socioeconomic data, the ozone concentration increases the probability of positive number of restricted activity days.Keywords: bootstrapping, hurdle negbin model, overdispersion, ozone concentration, respiratory-related restricted activity days
Procedia PDF Downloads 25221878 In Silico Modeling of Drugs Milk/Plasma Ratio in Human Breast Milk Using Structures Descriptors
Authors: Navid Kaboudi, Ali Shayanfar
Abstract:
Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.Keywords: logistic regression, breastfeeding, descriptors, penetration
Procedia PDF Downloads 6721877 The Effect of Symmetry on the Perception of Happiness and Boredom in Design Products
Authors: Michele Sinico
Abstract:
The present research investigates the effect of symmetry on the perception of happiness and boredom in design products. Three experiments were carried out in order to verify the degree of the visual expressive value on different models of bookcases, wall clocks, and chairs. 60 participants directly indicated the degree of happiness and boredom using 7-point rating scales. The findings show that the participants acknowledged a different value of expressive quality in the different product models. Results show also that symmetry is not a significant constraint for an emotional design project.Keywords: product experience, emotional design, symmetry, expressive qualities
Procedia PDF Downloads 14421876 Study and Conservation of Cultural and Natural Heritages with the Use of Laser Scanner and Processing System for 3D Modeling Spatial Data
Authors: Julia Desiree Velastegui Caceres, Luis Alejandro Velastegui Caceres, Oswaldo Padilla, Eduardo Kirby, Francisco Guerrero, Theofilos Toulkeridis
Abstract:
It is fundamental to conserve sites of natural and cultural heritage with any available technique or existing methodology of preservation in order to sustain them for the following generations. We propose a further skill to protect the actual view of such sites, in which with high technology instrumentation we are able to digitally preserve natural and cultural heritages applied in Ecuador. In this project the use of laser technology is presented for three-dimensional models, with high accuracy in a relatively short period of time. In Ecuador so far, there are not any records on the use and processing of data obtained by this new technological trend. The importance of the project is the description of the methodology of the laser scanner system using the Faro Laser Scanner Focus 3D 120, the method for 3D modeling of geospatial data and the development of virtual environments in the areas of Cultural and Natural Heritage. In order to inform users this trend in technology in which three-dimensional models are generated, the use of such tools has been developed to be able to be displayed in all kinds of digitally formats. The results of the obtained 3D models allows to demonstrate that this technology is extremely useful in these areas, but also indicating that each data campaign needs an individual slightly different proceeding starting with the data capture and processing to obtain finally the chosen virtual environments.Keywords: laser scanner system, 3D model, cultural heritage, natural heritage
Procedia PDF Downloads 30121875 Bridging the Gap between M and E, and KM: Towards the Integration of Evidence-Based Information and Policy Decision-Making
Authors: Xueqing Ivy Chen, Christo De Coning
Abstract:
It is clear from practice that a gap exists between Result-Based Monitoring and Evaluation (RBME) as a discipline, and Knowledge Management (KM) on the other hand. Whereas various government departments have institutionalised these functions, KM and M&E has functioned in isolation from each other in a practical sense in the public sector. It’s therefore necessary to explore the relationship between KM and M&E and the necessity for integration, so that a convergence of these disciplines can be established. An integration of KM and M&E will lead to integration and improvement of evidence-based information and policy decision-making. M&E and KM process models are available but the complementarity between specific process steps of these process models are not exploited. A need exists to clarify the relationships between these functions in order to ensure evidence based information and policy decision-making. This paper will depart from the well-known policy process models, such as the generic model and consider recent on the interface between policy, M&E and KM.Keywords: result-based monitoring and evaluation, RBME, knowledge management, KM, evident based decision making, public policy, information systems, institutional arrangement
Procedia PDF Downloads 14621874 Turbulent Forced Convection of Cu-Water Nanofluid: CFD Models Comparison
Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran
Abstract:
This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.Keywords: heat transfer, nanofluid, single-phase models, two-phase models
Procedia PDF Downloads 48021873 Comparison of Deep Convolutional Neural Networks Models for Plant Disease Identification
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 19321872 Time Series Regression with Meta-Clusters
Authors: Monika Chuchro
Abstract:
This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.Keywords: clustering, data analysis, data mining, predictive models
Procedia PDF Downloads 46221871 Adaptive Neuro Fuzzy Inference System Model Based on Support Vector Regression for Stock Time Series Forecasting
Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam
Abstract:
Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.Keywords: ANFIS, fuzzy time series, stock forecasting, SVR
Procedia PDF Downloads 23821870 The Effect of Institutions on Economic Growth: An Analysis Based on Bayesian Panel Data Estimation
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 6521869 An Analytical Study on the Vibration Reduction Method of Railway Station Using TPU
Authors: Jinho Hur, Minjung Shin, Heekyu Kim
Abstract:
In many places, new railway constructions in the city are being used to build a viaduct station to take advantage of the space below the line, for difficulty of securing railway site and disconnections of areas. The space under the viaduct has limited to use by noise and vibration. In order to use it for various purposes, reducing noise and vibration is required. The vibration reduction method for new structures is recently developed enough to use as accommodation, but the reduction method for existing structures is still far-off. In this study, it suggests vibration reduction method by filling vibration reduction material to column members which is path of structure-bone-noise from trains run. Because most of railroad stations are reinforced concrete structures. It compares vibration reduction of station applied the method and original station by FEM analysis. As a result, reduction of vibration acceleration level in bandwidth 15~30Hz can be reduced. Therefore, using this method for viaduct railroad station, vibration of station is expected to be reduced.Keywords: structure borne noise, TPU, viaduct rail station, vibration reduction method
Procedia PDF Downloads 53221868 CAD Tool for Parametric Design modification of Yacht Hull Surface Models
Authors: Shahroz Khan, Erkan Gunpinar, Kemal Mart
Abstract:
Recently parametric design techniques became a vital concept in the field of Computer Aided Design (CAD), which helps to provide sophisticated platform to the designer in order to automate the design process in efficient time. In these techniques, design process starts by parameterizing the important features of design models (typically the key dimensions), with the implementation of design constraints. The design constraints help to retain the overall shape of the model while modifying its parameters. However, the process of initializing an appropriate number of design parameters and constraints is the crucial part of parametric design techniques, especially for complex surface models such as yacht hull. This paper introduces a method to create complex surface models in favor of parametric design techniques, a method to define the right number of parameters and respective design constraints, and a system to implement design parameters in contract to design constraints schema. For this, in our proposed approach the design process starts by dividing the yacht hull into three sections. Each section consists of different shape lines, which form the overall shape of yacht hull. The shape lines are created using Cubic Bezier Curves, which allow larger design flexibility. Design parameters and constraints are defined on the shape lines in 3D design space to facilitate the designers for better and individual handling of parameters. Afterwards, shape modifiers are developed, which allow the modification of each parameter while satisfying the respective set of criteria and design constraints. Such as, geometric continuities should be maintained between the shape lines of the three sections, fairness of the hull surfaces should be preserved after modification and while design modification, effect of a single parameter should be negligible on other parameters. The constraints are defined individually on shape lines of each section and mutually between the shape lines of two connecting sections. In order to validate and visualize design results of our shape modifiers, a real time graphic interface is created.Keywords: design parameter, design constraints, shape modifies, yacht hull
Procedia PDF Downloads 29521867 Effect of Co-Infection With Intestinal Parasites on COVID-19 Severity: A Prospective Observational Cohort Study
Authors: Teklay Gebrecherkos, Dawit Wolday, Muhamud Abdulkader
Abstract:
Background: COVID-19 symptomatology in Africa appears significantly less serious than in the industrialized world. Our hypothesis for this phenomenon, being a different, more activated immune system due to parasite infections contributes to reduced COVID-19 outcome. We investigated this hypothesis in an endemic area in sub sub-saharan Africa. Methods: Ethiopian COVID-19 patients were enrolled and screened for intestinal parasites, between July 2020 and March 2021. The primary outcome was the proportion of patients with severe COVID-19. SARS-CoV-2 infection was confirmed by RT-PCR on samples obtained from nasopharyngeal swabs, while direct microscopic examination, modified Ritchie concentration, and Kato-Katz methods were used to identify parasites and ova from a fresh stool sample. Ordinal logistic regression models were used to estimate the association between parasite infection and COVID-19 severity. Models were adjusted for sex, age, residence, education level, occupation, body mass index, and comorbidities. Data were analyzed using STATA version 14. P-value <0.05 was considered statistically significant. Results: A total of 751 SARS-CoV-2 infected patients were enrolled, of whom 284 (37•8%) had an intestinal parasitic infection. Only 27/255 (10•6%) severe COVID-19 patients were co-infected with intestinal parasites, while 257/496 (51•8%) non-severe COVID-19 patients appeared parasite positive (p<0.0001). Patients co-infected with parasites had lower odds of developing severe COVID-19, with an adjusted odds ratio (AOR) of 0•14 (95% CI 0•09–0•24; p<0•0001) for all parasites, AOR 0•20 ([95% CI 0•11–0•38]; p<0•0001) for protozoa, and AOR 0•13 ([95% CI 0•07–0•26]; p<0•0001) for helminths. When stratified by species, co-infection with Entamoeba spp., Hymenolopis nana, and Schistosoma mansoni implied a lower probability of developing severe COVID-19. There were 11 deaths (1•5%), and all were among patients without parasites (p=0•009). Conclusions: Parasite co-infection is associated with a reduced risk of severe COVID-19 in African patients. Parasite-driven immunomodulatory responses may mute hyper-inflammation associated with severe COVID-19.Keywords: COVID-19, SARS-COV-2, intestinal parasite, RT-PCR, co-infection
Procedia PDF Downloads 5521866 Assessment of the Impact of Traffic Safety Policy in Barcelona, 2010-2019
Authors: Lluís Bermúdez, Isabel Morillo
Abstract:
Road safety involves carrying out a determined and explicit policy to reduce accidents. In the city of Barcelona, through the Local Road Safety Plan 2013-2018, in line with the framework that has been established at the European and state level, a series of preventive, corrective and technical measures are specified, with the priority objective of reducing the number of serious injuries and fatalities. In this work, based on the data from the accidents managed by the local police during the period 2010-2019, an analysis is carried out to verify whether the measures established in the Plan to reduce the accident rate have had an effect or not and to what extent. The analysis focuses on the type of accident and the type of vehicles involved. Different count regression models have been fitted, from which it can be deduced that the number of serious and fatal victims of the accidents that have occurred in the city of Barcelona has been reduced as the measures approved by the authorities.Keywords: accident reduction, count regression models, road safety, urban traffic
Procedia PDF Downloads 12421865 Active Control Effects on Dynamic Response of Elevated Water Storage Tanks
Authors: Ali Etemadi, Claudia Fernanda Yasar
Abstract:
Elevated water storage tank structures (EWSTs) are high elevated-ponderous structural systems and very vulnerable to seismic vibrations. In past earthquake events, many of these structures exhibit poor performance and experienced severe damage. The dynamic analysis of the EWSTs under earthquake loads is, therefore, of significant importance for the design of the structure and a key issue for the development of modern methods, such as active control design. In this study, a reduced model of the EWSTs is explained, which is based on a tuned mass damper model (TMD). Vibration analysis of a structure under seismic excitation is presented and then used to propose an active vibration controller. MATLAB/Simulink is employed for dynamic analysis of the system and control of the seismic response. A single degree of freedom (SDOF) and two degree of freedom (2DOF) models of ELSTs are going to be used to study the concept of active vibration control. Lab-scale experimental models similar to pendulum are applied to suppress vibrations in ELST under seismic excitation. One of the most important phenomena in liquid storage tanks is the oscillation of fluid due to the movements of the tank body because of its base motions during an earthquake. Simulation results illustrate that the EWSTs vibration can be reduced by means of an input shaping technique that takes into account the dominant mode shape of the structure. Simulations with which to guide many of our designs are presented in detail. A simple and effective real-time control for seismic vibration damping can be, therefore, design and built-in practice.Keywords: elevated water storage tank, tuned mass damper model, real time control, shaping control, seismic vibration control, the laplace transform
Procedia PDF Downloads 14321864 Copula-Based Estimation of Direct and Indirect Effects in Path Analysis Models
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 3021863 Order Optimization of a Telecommunication Distribution Center through Service Lead Time
Authors: Tamás Hartványi, Ferenc Tóth
Abstract:
European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.Keywords: CTO, aggregated planning, demand simulation, changeover time
Procedia PDF Downloads 26121862 Management of Cultural Heritage: Bologna Gates
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 41721861 Comparative Mesh Sensitivity Study of Different Reynolds Averaged Navier Stokes Turbulence Models in OpenFOAM
Authors: Zhuoneng Li, Zeeshan A. Rana, Karl W. Jenkins
Abstract:
In industry, to validate a case, often a multitude of simulation are required and in order to demonstrate confidence in the process where users tend to use a coarser mesh. Therefore, it is imperative to establish the coarsest mesh that could be used while keeping reasonable simulation accuracy. To date, the two most reliable, affordable and broadly used advanced simulations are the hybrid RANS (Reynolds Averaged Navier Stokes)/LES (Large Eddy Simulation) and wall modelled LES. The potentials in these two simulations will still be developed in the next decades mainly because the unaffordable computational cost of a DNS (Direct Numerical Simulation). In the wall modelled LES, the turbulence model is applied as a sub-grid scale model in the most inner layer near the wall. The RANS turbulence models cover the entire boundary layer region in a hybrid RANS/LES (Detached Eddy Simulation) and its variants, therefore, the RANS still has a very important role in the state of art simulations. This research focuses on the turbulence model mesh sensitivity analysis where various turbulence models such as the S-A (Spalart-Allmaras), SSG (Speziale-Sarkar-Gatski), K-Omega transitional SST (Shear Stress Transport), K-kl-Omega, γ-Reθ transitional model, v2f are evaluated within the OpenFOAM. The simulations are conducted on a fully developed turbulent flow over a flat plate where the skin friction coefficient as well as velocity profiles are obtained to compare against experimental values and DNS results. A concrete conclusion is made to clarify the mesh sensitivity for different turbulence models.Keywords: mesh sensitivity, turbulence models, OpenFOAM, RANS
Procedia PDF Downloads 25421860 3D Point Cloud Model Color Adjustment by Combining Terrestrial Laser Scanner and Close Range Photogrammetry Datasets
Authors: M. Pepe, S. Ackermann, L. Fregonese, C. Achille
Abstract:
3D models obtained with advanced survey techniques such as close-range photogrammetry and laser scanner are nowadays particularly appreciated in Cultural Heritage and Archaeology fields. In order to produce high quality models representing archaeological evidences and anthropological artifacts, the appearance of the model (i.e. color) beyond the geometric accuracy, is not a negligible aspect. The integration of the close-range photogrammetry survey techniques with the laser scanner is still a topic of study and research. By combining point cloud data sets of the same object generated with both technologies, or with the same technology but registered in different moment and/or natural light condition, could construct a final point cloud with accentuated color dissimilarities. In this paper, a methodology to uniform the different data sets, to improve the chromatic quality and to highlight further details by balancing the point color will be presented.Keywords: color models, cultural heritage, laser scanner, photogrammetry
Procedia PDF Downloads 27421859 Data-Centric Anomaly Detection with Diffusion Models
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 7721858 Generative Adversarial Network Based Fingerprint Anti-Spoofing Limitations
Authors: Yehjune Heo
Abstract:
Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.Keywords: anti-spoofing, CNN, fingerprint recognition, GAN
Procedia PDF Downloads 17921857 Biosorption of Phenol onto Water Hyacinth Activated Carbon: Kinetics and Isotherm Study
Authors: Manoj Kumar Mahapatra, Arvind Kumar
Abstract:
Batch adsorption experiments were carried out for the removal of phenol from its aqueous solution using water hyancith activated carbon (WHAC) as an adsorbent. The sorption kinetics were analysed using pseudo-first order kinetics and pseudo-second order model, and it was observed that the sorption data tend to fit very well in pseudo-second order model for the entire sorption time. The experimental data were analyzed by the Langmuir and Freundlich isotherm models. Equilibrium data fitted well to the Freundlich model with a maximum biosorption capacity of 31.45 mg/g estimated using Langmuir model. The adsorption intensity 3.7975 represents a favorable adsorption condition.Keywords: adsorption, isotherm, kinetics, phenol
Procedia PDF Downloads 43821856 Copula Markov Switching Multifractal Models for Forecasting Value-at-Risk
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 16121855 Digital Marketing Maturity Models: Overview and Comparison
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 33321854 Energy Models for Analyzing the Economic Wide Impact of the Environmental Policies
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 518