Search results for: Model Code 2020
17782 Trump’s COVID-19 Discourse: Downgrading the Fundamentals of the Political Fair Play
Authors: Gustavo Naranjo Maroto, Dolores Fernandez Martinez
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Context has always been essential to understand any reaction from every human being, and words, whether written or spoken, are definitely a powerful representative sample of human reaction. This study starts with an accurate breakdown of the context in which the current president of the US, Mr. Donald J. Trump is conveying his discourses in order to be able to judge them from a critical discourse analysis point of view. The present world’s scenario with a pandemic disease in form of Covid-19 that is threatening the world and certainly putting at risk the so called 'Welfare State', the role of the United States as the first superpower on earth nowadays, the very peculiar profile of President Trump not only as a politician but as a persona, and the fact of being on the verge of a very controversial presidential elections are without doubt a great and undeniable opportunity for the implementation of the critical discourse analysis methodology. Hence, this research will primarily analyze in detail some of the most interesting discourses delivered by Trump in different media since the very beginning of the outbreak of the coronavirus pandemic in the United States of America (February, 2020), sadly very often downplayed by President Trump, until the final result of the upcoming presidential election scheduled for Tuesday, November 3, 2020, where the political discourse has been dramatically downgraded to a very dangerous state, putting in jeopardy the fundamentals of the political fair play in terms of speech. Finally, the study will hopefully conclude with the final outcome of the data analyzed, allowing to picture how significant the context can be concerning linguistics on the one hand, in terms of shaping or altering the message that the issuer thought to convey in the first place, and on the other hand, generously assessing to what extend the recipients of the message are influenced by the message in terms of receptiveness.Keywords: Covid-19, critical discourse analysis, Donald J. Trump, political discourse
Procedia PDF Downloads 13017781 Application of Generalized Autoregressive Score Model to Stock Returns
Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke
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The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying
Procedia PDF Downloads 49917780 Reduction of Rotor-Bearing-Support Finite Element Model through Substructuring
Authors: Abdur Rosyid, Mohamed El-Madany, Mohanad Alata
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Due to simplicity and low cost, rotordynamic system is often modeled by using lumped parameters. Recently, finite elements have been used to model rotordynamic system as it offers higher accuracy. However, it involves high degrees of freedom. In some applications such as control design, this requires higher cost. For this reason, various model reduction methods have been proposed. This work demonstrates the quality of model reduction of rotor-bearing-support system through substructuring. The quality of the model reduction is evaluated by comparing some first natural frequencies, modal damping ratio, critical speeds and response of both the full system and the reduced system. The simulation shows that the substructuring is proven adequate to reduce finite element rotor model in the frequency range of interest as long as the numbers and the locations of master nodes are determined appropriately. However, the reduction is less accurate in an unstable or nearly-unstable system.Keywords: rotordynamic, finite element model, timoshenko beam, 3D solid elements, Guyan reduction method
Procedia PDF Downloads 27017779 A Unified Model for Orotidine Monophosphate Synthesis: Target for Inhibition of Growth of Mycobacterium tuberculosis
Authors: N. Naga Subrahmanyeswara Rao, Parag Arvind Deshpande
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Understanding nucleotide synthesis reaction of any organism is beneficial to know the growth of it as in Mycobacterium tuberculosis to design anti TB drug. One of the reactions of de novo pathway which takes place in all organisms was considered. The reaction takes places between phosphoribosyl pyrophosphate and orotate catalyzed by orotate phosphoribosyl transferase and divalent metal ion gives orotdine monophosphate, a nucleotide. All the reaction steps of three experimentally proposed mechanisms for this reaction were considered to develop kinetic rate expression. The model was validated using the data for four organisms. This model could successfully describe the kinetics for the reported data. The developed model can serve as a reliable model to describe the kinetics in new organisms without the need of mechanistic determination. So an organism-independent model was developed.Keywords: mechanism, nucleotide, organism, tuberculosis
Procedia PDF Downloads 33317778 Controlling the Expense of Political Contests Using a Modified N-Players Tullock’s Model
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This work introduces a generalization of the classical Tullock’s model of one-stage contests under complete information with multiple unlimited numbers of contestants. In classical Tullock’s model, the contest winner is not necessarily the highest bidder. Instead, the winner is determined according to a draw in which the winning probabilities are the relative contestants’ efforts. The Tullock modeling fits well political contests, in which the winner is not necessarily the highest effort contestant. This work presents a modified model which uses a simple non-discriminating rule, namely, a parameter to influence the total costs planned for an election, for example, the contest designer can control the contestants' efforts. The winner pays a fee, and the losers are reimbursed the same amount. Our proposed model includes a mechanism that controls the efforts exerted and balances competition, creating a tighter, less predictable and more interesting contest. Additionally, the proposed model follows the fairness criterion in the sense that it does not alter the contestants' probabilities of winning compared to the classic Tullock’s model. We provide an analytic solution for the contestant's optimal effort and expected reward.Keywords: contests, Tullock's model, political elections, control expenses
Procedia PDF Downloads 14317777 Fama French Four Factor Model: A Study of Nifty Fifty Companies
Authors: Deeksha Arora
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The study aims to explore the applicability of the widely used asset pricing models, namely, Capital Asset Pricing Model (CAPM) and the Fama-French Four Factor Model in the Indian equity market. The study will be based on the companies that form part of the Nifty Fifty Index for a period of five years: 2011 to 2016. The asset pricing model is examined by forming portfolios on the basis of three variables – market capitalization (size effect), book-to-market equity ratio (value effect) and profitability. The study provides a basis to test the presence of the Fama-French Four factor model in Indian stock market. This study may provide a basis for future research in the generalized asset pricing model comprising of multiple risk factors.Keywords: book to market equity, Fama French four factor model, market capitalization, profitability, size effect, value effect
Procedia PDF Downloads 26117776 The Effectiveness of a Hybrid Diffie-Hellman-RSA-Advanced Encryption Standard Model
Authors: Abdellahi Cheikh
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With the emergence of quantum computers with very powerful capabilities, the security of the exchange of shared keys between two interlocutors poses a big problem in terms of the rapid development of technologies such as computing power and computing speed. Therefore, the Diffie-Hellmann (DH) algorithm is more vulnerable than ever. No mechanism guarantees the security of the key exchange, so if an intermediary manages to intercept it, it is easy to intercept. In this regard, several studies have been conducted to improve the security of key exchange between two interlocutors, which has led to interesting results. The modification made on our model Diffie-Hellman-RSA-AES (DRA), which encrypts the information exchanged between two users using the three-encryption algorithms DH, RSA and AES, by using stenographic photos to hide the contents of the p, g and ClesAES values that are sent in an unencrypted state at the level of DRA model to calculate each user's public key. This work includes a comparative study between the DRA model and all existing solutions, as well as the modification made to this model, with an emphasis on the aspect of reliability in terms of security. This study presents a simulation to demonstrate the effectiveness of the modification made to the DRA model. The obtained results show that our model has a security advantage over the existing solution, so we made these changes to reinforce the security of the DRA model.Keywords: Diffie-Hellmann, DRA, RSA, advanced encryption standard
Procedia PDF Downloads 9317775 Project Management Agile Model Based on Project Management Body of Knowledge Guideline
Authors: Mehrzad Abdi Khalife, Iraj Mahdavi
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This paper presents the agile model for project management process. For project management process, the Project Management Body of Knowledge (PMBOK) guideline has been selected as platform. Combination of computational science and artificial intelligent methodology has been added to the guideline to transfer the standard to agile project management process. The model is the combination of practical standard, computational science and artificial intelligent. In this model, we present communication model and protocols to keep process agile. Here, we illustrate the collaboration man and machine in project management area with artificial intelligent approach.Keywords: artificial intelligent, conceptual model, man-machine collaboration, project management, standard
Procedia PDF Downloads 33917774 Parameter Estimation for the Oral Minimal Model and Parameter Distinctions Between Obese and Non-obese Type 2 Diabetes
Authors: Manoja Rajalakshmi Aravindakshana, Devleena Ghosha, Chittaranjan Mandala, K. V. Venkateshb, Jit Sarkarc, Partha Chakrabartic, Sujay K. Maity
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Oral Glucose Tolerance Test (OGTT) is the primary test used to diagnose type 2 diabetes mellitus (T2DM) in a clinical setting. Analysis of OGTT data using the Oral Minimal Model (OMM) along with the rate of appearance of ingested glucose (Ra) is performed to study differences in model parameters for control and T2DM groups. The differentiation of parameters of the model gives insight into the behaviour and physiology of T2DM. The model is also studied to find parameter differences among obese and non-obese T2DM subjects and the sensitive parameters were co-related to the known physiological findings. Sensitivity analysis is performed to understand changes in parameter values with model output and to support the findings, appropriate statistical tests are done. This seems to be the first preliminary application of the OMM with obesity as a distinguishing factor in understanding T2DM from estimated parameters of insulin-glucose model and relating the statistical differences in parameters to diabetes pathophysiology.Keywords: oral minimal model, OGTT, obese and non-obese T2DM, mathematical modeling, parameter estimation
Procedia PDF Downloads 8917773 Model Order Reduction Using Hybrid Genetic Algorithm and Simulated Annealing
Authors: Khaled Salah
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Model order reduction has been one of the most challenging topics in the past years. In this paper, a hybrid solution of genetic algorithm (GA) and simulated annealing algorithm (SA) are used to approximate high-order transfer functions (TFs) to lower-order TFs. In this approach, hybrid algorithm is applied to model order reduction putting in consideration improving accuracy and preserving the properties of the original model which are two important issues for improving the performance of simulation and computation and maintaining the behavior of the original complex models being reduced. Compared to conventional mathematical methods that have been used to obtain a reduced order model of high order complex models, our proposed method provides better results in terms of reducing run-time. Thus, the proposed technique could be used in electronic design automation (EDA) tools.Keywords: genetic algorithm, simulated annealing, model reduction, transfer function
Procedia PDF Downloads 14217772 Assessing the Feasibility of Italian Hydrogen Targets with the Open-Source Energy System Optimization Model TEMOA - Italy
Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi
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Hydrogen is expected to become a game changer in the energy transition, especially enabling sector coupling possibilities and the decarbonization of hard-to-abate end-uses. The Italian National Recovery and Resilience Plan identifies hydrogen as one of the key elements of the ecologic transition to meet international decarbonization objectives, also including it in several pilot projects for the early development in Italy. This matches the European energy strategy, which aims to make hydrogen a leading energy carrier of the future, setting ambitious goals to be accomplished by 2030. The huge efforts needed to achieve the announced targets require to carefully investigate of their feasibility in terms of economic expenditures and technical aspects. In order to quantitatively assess the hydrogen potential within the Italian context and the feasibility of the planned investments and projects, this work uses the TEMOA-Italy energy system model to study pathways to meet the strict objectives above cited. The possible hydrogen development has been studied both in the supply-side and demand-side of the energy system, also including storage options and distribution chains. The assessment comprehends alternative hydrogen production technologies involved in a competition market, reflecting the several possible investments declined by the Italian National Recovery and Resilience Plan to boost the development and spread of this infrastructure, including the sector coupling potential with natural gas through the currently existing infrastructure and CO2 capture for the production of synfuels. On the other hand, the hydrogen end-uses phase covers a wide range of consumption alternatives, from fuel-cell vehicles, for which both road and non-road transport categories are considered, to steel, and chemical industries uses and cogeneration for residential and commercial buildings. The model includes both high and low TRL technologies in order to provide a consistent outcome for the future decades as it does for the present day, and since it is developed through the use of an open-source code instance and database, transparency and accessibility are fully granted.Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA
Procedia PDF Downloads 10017771 Towards an Enhanced Compartmental Model for Profiling Malware Dynamics
Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova
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We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.Keywords: cybersecurity, epidemiology, cyber epidemiology, malware
Procedia PDF Downloads 10517770 Artificial Neural Networks Application on Nusselt Number and Pressure Drop Prediction in Triangular Corrugated Plate Heat Exchanger
Authors: Hany Elsaid Fawaz Abdallah
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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations
Procedia PDF Downloads 8617769 Hidden Oscillations in the Mathematical Model of the Optical Binary Phase Shift Keying (BPSK) Costas Loop
Authors: N. V. Kuznetsov, O. A. Kuznetsova, G. A. Leonov, M. V. Yuldashev, R. V. Yuldashev
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Nonlinear analysis of the phase locked loop (PLL)-based circuits is a challenging task. Thus, the simulation is widely used for their study. In this work, we consider a mathematical model of the optical Costas loop and demonstrate the limitations of simulation approach related to the existence of so-called hidden oscillations in the phase space of the model.Keywords: optical Costas loop, mathematical model, simulation, hidden oscillation
Procedia PDF Downloads 43917768 Numerical Study on the Effects of Truncated Ribs on Film Cooling with Ribbed Cross-Flow Coolant Channel
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To evaluate the effect of the ribs on internal structure in film hole and the film cooling performance on outer surface, the numerical study investigates on the effects of rib configuration on the film cooling performance with ribbed cross-flow coolant channel. The base smooth case and three ribbed cases, including the continuous rib case and two cross-truncated rib cases with different arrangement, are studied. The distributions of adiabatic film cooling effectiveness and heat transfer coefficient are obtained under the blowing ratios with the value of 0.5 and 1.0, respectively. A commercial steady RANS (Reynolds-averaged Navier-Stokes) code with realizable k-ε turbulence model and enhanced wall treatment were performed for numerical simulations. The numerical model is validated against available experimental data. The two cross-truncated rib cases produce approximately identical cooling effectiveness compared with the smooth case under lower blowing ratio. The continuous rib case significantly outperforms the other cases. With the increase of blowing ratio, the cases with ribs are inferior to the smooth case, especially in the upstream region. The cross-truncated rib I case produces the highest cooling effectiveness among the studied the ribbed channel case. It is found that film cooling effectiveness deteriorates with the increase of spiral intensity of the cross-flow inside the film hole. Lower spiral intensity leads to a better film coverage and thus results in better cooling effectiveness. The distinct relative merits among the cases at different blowing ratios are explored based on the aforementioned dominant mechanism. With regard to the heat transfer coefficient, the smooth case has higher heat transfer intensity than the ribbed cases under the studied blowing ratios. The laterally-averaged heat transfer coefficient of the cross-truncated rib I case is higher than the cross-truncated rib II case.Keywords: cross-flow, cross-truncated rib, film cooling, numerical simulation
Procedia PDF Downloads 13417767 Discrete Element Method Simulation of Crushable Pumice Sand
Authors: Sayed Hessam Bahmani, Rolsndo P. Orense
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From an engineering point of view, pumice particles are problematic because of their crushability and compressibility due to their vesicular nature. Currently, information on the geotechnical characteristics of pumice sands is limited. While extensive empirical and laboratory tests can be implemented to characterize their behavior, these are generally time-consuming and expensive. These drawbacks have motivated attempts to study the effects of particle breakage of pumice sand through the Discrete Element Method (DEM). This method provides insights into the behavior of crushable granular material at both the micro and macro-level. In this paper, the results of single-particle crushing tests conducted in the laboratory are simulated using DEM through the open-source code YADE. This is done to better understand the parameters necessary to represent the pumice microstructure that governs its crushing features, and to examine how the resulting microstructure evolution affects a particle’s properties. The DEM particle model is then used to simulate the behavior of pumice sand during consolidated drained triaxial tests. The results indicate the importance of incorporating particle porosity and unique surface textures in the material characterization and show that interlocking between the crushed particles significantly influences the drained behavior of the pumice specimen.Keywords: pumice sand, triaxial compression, simulation, particle breakage
Procedia PDF Downloads 24217766 Reference Model for the Implementation of an E-Commerce Solution in Peruvian SMEs in the Retail Sector
Authors: Julio Kauss, Miguel Cadillo, David Mauricio
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E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.Keywords: e-commerce, retail, SMEs, reference model
Procedia PDF Downloads 31917765 Living Heritage(s) And Decoloniality: A Situational Analysis of the Great Zimbabwe World Heritage Site
Authors: Revai Boterere
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The study explores the decolonial theory in the context of engaging with living heritages in the formally colonised through the case of the Great Zimbabwe World Heritage Site. It followed a qualitative research paradigm in the form of a situational analysis, with both primary and secondary data sources examined to enable an analysis focusing on the decolonial discourse and practice at Great Zimbabwe. Unlike the dominant model (in terms of interpretation) used at Great Zimbabwe, that of Thomas Huffman, which views the site as ruins, new literature (Ashton Sinamai, 2017, 2020; Webber Ndoro, 1994, 2005; ShadreckChirikure 2008, etal 2016; Njabulo Chipanguraetal 2019) on zimbabwe culture, Great Zimbabwe World Heritage Site is a living site, a shrine, and a cultural landscape. it argue that the new literature, perhaps decolonial, remain in the hands of academics and not synthesised down to the interpreters. This is a problem, and it needs to be addressed. There is need of a pragmatic thrust to decolonisation at the Great Zimbabwe World Heritage Site. Though there are efforts to involve local communities at Great Zimbabwe as a decolonial approach, there is need to reorder the current system of producing knowledge in place. This paper will unpack these debates of decoloniality between what Huffman’s propositions of the interpretation of Great Zimbabwe vis-a-vis the new decolonial school of thought by local researchers.Keywords: cultural tourism, decoloniality, living heritage, local community
Procedia PDF Downloads 10417764 A Multivariate Exploratory Data Analysis of a Crisis Text Messaging Service in Order to Analyse the Impact of the COVID-19 Pandemic on Mental Health in Ireland
Authors: Hamda Ajmal, Karen Young, Ruth Melia, John Bogue, Mary O'Sullivan, Jim Duggan, Hannah Wood
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The Covid-19 pandemic led to a range of public health mitigation strategies in order to suppress the SARS-CoV-2 virus. The drastic changes in everyday life due to lockdowns had the potential for a significant negative impact on public mental health, and a key public health goal is to now assess the evidence from available Irish datasets to provide useful insights on this issue. Text-50808 is an online text-based mental health support service, established in Ireland in 2020, and can provide a measure of revealed distress and mental health concerns across the population. The aim of this study is to explore statistical associations between public mental health in Ireland and the Covid-19 pandemic. Uniquely, this study combines two measures of emotional wellbeing in Ireland: (1) weekly text volume at Text-50808, and (2) emotional wellbeing indicators reported by respondents of the Amárach public opinion survey, carried out on behalf of the Department of Health, Ireland. For this analysis, a multivariate graphical exploratory data analysis (EDA) was performed on the Text-50808 dataset dated from 15th June 2020 to 30th June 2021. This was followed by time-series analysis of key mental health indicators including: (1) the percentage of daily/weekly texts at Text-50808 that mention Covid-19 related issues; (2) the weekly percentage of people experiencing anxiety, boredom, enjoyment, happiness, worry, fear and stress in Amárach survey; and Covid-19 related factors: (3) daily new Covid-19 case numbers; (4) daily stringency index capturing the effect of government non-pharmaceutical interventions (NPIs) in Ireland. The cross-correlation function was applied to measure the relationship between the different time series. EDA of the Text-50808 dataset reveals significant peaks in the volume of texts on days prior to level 3 lockdown and level 5 lockdown in October 2020, and full level 5 lockdown in December 2020. A significantly high positive correlation was observed between the percentage of texts at Text-50808 that reported Covid-19 related issues and the percentage of respondents experiencing anxiety, worry and boredom (at a lag of 1 week) in Amárach survey data. There is a significant negative correlation between percentage of texts with Covid-19 related issues and percentage of respondents experiencing happiness in Amárach survey. Daily percentage of texts at Text-50808 that reported Covid-19 related issues to have a weak positive correlation with daily new Covid-19 cases in Ireland at a lag of 10 days and with daily stringency index of NPIs in Ireland at a lag of 2 days. The sudden peaks in text volume at Text-50808 immediately prior to new restrictions in Ireland indicate an association between a rise in mental health concerns following the announcement of new restrictions. There is also a high correlation between emotional wellbeing variables in the Amárach dataset and the number of weekly texts at Text-50808, and this confirms that Text-50808 reflects overall public sentiment. This analysis confirms the benefits of the texting service as a community surveillance tool for mental health in the population. This initial EDA will be extended to use multivariate modeling to predict the effect of additional Covid-19 related factors on public mental health in Ireland.Keywords: COVID-19 pandemic, data analysis, digital health, mental health, public health, digital health
Procedia PDF Downloads 14217763 Measurement of Influence of the COVID-19 Pandemic on Efficiency of Japan’s Railway Companies
Authors: Hideaki Endo, Mika Goto
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The global outbreak of the COVID-19 pandemic has seriously affected railway businesses. The number of railway passengers decreased due to the decline in the number of commuters and business travelers to avoid crowded trains and a sharp drop in inbound tourists visiting Japan. This has affected not only railway businesses but also related businesses, including hotels, leisure businesses, and retail businesses at station buildings. In 2021, the companies were divided into profitable and loss-making companies. This division suggests that railway companies, particularly loss-making companies, needed to decrease operational inefficiency. To measure the impact of COVID-19 and discuss the sustainable management strategies of railway companies, we examine the cost inefficiency of Japanese listed railway companies by applying stochastic frontier analysis (SFA) to their operational and financial data. First, we employ the stochastic frontier cost function approach to measure inefficiency. The cost frontier function is formulated as a Cobb–Douglas type, and we estimated parameters and variables for inefficiency. This study uses panel data comprising 26 Japanese-listed railway companies from 2005 to 2020. This period includes several events deteriorating the business environment, such as the financial crisis from 2007 to 2008 and the Great East Japan Earthquake of 2011, and we compare those impacts with those of the COVID-19 pandemic after 2020. Second, we identify the characteristics of the best-practice railway companies and examine the drivers of cost inefficiencies. Third, we analyze the factors influencing cost inefficiency by comparing the profiles of the top 10 railway companies and others before and during the pandemic. Finally, we examine the relationship between cost inefficiency and the implementation of efficiency measures for each railway company. We obtained the following four findings. First, most Japanese railway companies showed the lowest cost inefficiency (most efficient) in 2014 and the highest in 2020 (least efficient) during the COVID-19 pandemic. The second worst occurred in 2009 when it was affected by the financial crisis. However, we did not observe a significant impact of the 2011 Great East Japan Earthquake. This is because no railway company was influenced by the earthquake in this operating area, except for JR-EAST. Second, the best-practice railway companies are KEIO and TOKYU. The main reason for their good performance is that both operate in and near the Tokyo metropolitan area, which is densely populated. Third, we found that non-best-practice companies had a larger decrease in passenger kilometers than best-practice companies. This indicates that passengers made fewer long-distance trips because they refrained from inter-prefectural travel during the pandemic. Finally, we found that companies that implement more efficiency improvement measures had higher cost efficiency and they effectively used their customer databases through proactive DX investments in marketing and asset management.Keywords: COVID-19 pandemic, stochastic frontier analysis, railway sector, cost efficiency
Procedia PDF Downloads 7317762 Estimating X-Ray Spectra for Digital Mammography by Using the Expectation Maximization Algorithm: A Monte Carlo Simulation Study
Authors: Chieh-Chun Chang, Cheng-Ting Shih, Yan-Lin Liu, Shu-Jun Chang, Jay Wu
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With the widespread use of digital mammography (DM), radiation dose evaluation of breasts has become important. X-ray spectra are one of the key factors that influence the absorbed dose of glandular tissue. In this study, we estimated the X-ray spectrum of DM using the expectation maximization (EM) algorithm with the transmission measurement data. The interpolating polynomial model proposed by Boone was applied to generate the initial guess of the DM spectrum with the target/filter combination of Mo/Mo and the tube voltage of 26 kVp. The Monte Carlo N-particle code (MCNP5) was used to tally the transmission data through aluminum sheets of 0.2 to 3 mm. The X-ray spectrum was reconstructed by using the EM algorithm iteratively. The influence of the initial guess for EM reconstruction was evaluated. The percentage error of the average energy between the reference spectrum inputted for Monte Carlo simulation and the spectrum estimated by the EM algorithm was -0.14%. The normalized root mean square error (NRMSE) and the normalized root max square error (NRMaSE) between both spectra were 0.6% and 2.3%, respectively. We conclude that the EM algorithm with transmission measurement data is a convenient and useful tool for estimating x-ray spectra for DM in clinical practice.Keywords: digital mammography, expectation maximization algorithm, X-Ray spectrum, X-Ray
Procedia PDF Downloads 72817761 Kinetic Façade Design Using 3D Scanning to Convert Physical Models into Digital Models
Authors: Do-Jin Jang, Sung-Ah Kim
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In designing a kinetic façade, it is hard for the designer to make digital models due to its complex geometry with motion. This paper aims to present a methodology of converting a point cloud of a physical model into a single digital model with a certain topology and motion. The method uses a Microsoft Kinect sensor, and color markers were defined and applied to three paper folding-inspired designs. Although the resulted digital model cannot represent the whole folding range of the physical model, the method supports the designer to conduct a performance-oriented design process with the rough physical model in the reduced folding range.Keywords: design media, kinetic facades, tangible user interface, 3D scanning
Procedia PDF Downloads 41217760 A Large Language Model-Driven Method for Automated Building Energy Model Generation
Authors: Yake Zhang, Peng Xu
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The development of building energy models (BEM) required for architectural design and analysis is a time-consuming and complex process, demanding a deep understanding and proficient use of simulation software. To streamline the generation of complex building energy models, this study proposes an automated method for generating building energy models using a large language model and the BEM library aimed at improving the efficiency of model generation. This method leverages a large language model to parse user-specified requirements for target building models, extracting key features such as building location, window-to-wall ratio, and thermal performance of the building envelope. The BEM library is utilized to retrieve energy models that match the target building’s characteristics, serving as reference information for the large language model to enhance the accuracy and relevance of the generated model, allowing for the creation of a building energy model that adapts to the user’s modeling requirements. This study enables the automatic creation of building energy models based on natural language inputs, reducing the professional expertise required for model development while significantly decreasing the time and complexity of manual configuration. In summary, this study provides an efficient and intelligent solution for building energy analysis and simulation, demonstrating the potential of a large language model in the field of building simulation and performance modeling.Keywords: artificial intelligence, building energy modelling, building simulation, large language model
Procedia PDF Downloads 2417759 Performance of Buildings with Base-Isolation System under Geometric Irregularities
Authors: Firoz Alam Faroque, Ankur Neog
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Earthquake causes significant loss of lives and severe damage to infrastructure. Base isolator is one of the most suitable solutions to make a building earthquake resistant. Base isolation consists of installing an isolator along with the steel plates covered with pads of strong material like steel, rubber, etc. In our study, we have used lead rubber bearing (LRB). The basic idea of seismic isolation is based on the reduction of the earthquake-induced inertia forces by shifting the fundamental period of the structure out of dangerous resonance range, and concentration of the deformation and energy dissipation demands at the isolation and energy dissipation systems, which are designed for this purpose. In this paper, RC frame buildings have been modeled and analyzed by response spectrum method using ETABS software. The LRB used in the model is designed as per uniform building code (UBC) 97. It is found that time period for the base isolated structures are higher than that of the fixed base structure and the value of base shear significantly reduces in the case of base-isolated buildings. It has also been found that buildings with vertical irregularities give better performance as compared to building with plan irregularities using base isolators.Keywords: base isolation, base shear, irregularities in buildings, lead rubber bearing (LRB)
Procedia PDF Downloads 32317758 An Improved Model of Estimation Global Solar Irradiation from in situ Data: Case of Oran Algeria Region
Authors: Houcine Naim, Abdelatif Hassini, Noureddine Benabadji, Alex Van Den Bossche
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In this paper, two models to estimate the overall monthly average daily radiation on a horizontal surface were applied to the site of Oran (35.38 ° N, 0.37 °W). We present a comparison between the first one is a regression equation of the Angstrom type and the second model is developed by the present authors some modifications were suggested using as input parameters: the astronomical parameters as (latitude, longitude, and altitude) and meteorological parameters as (relative humidity). The comparisons are made using the mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE), and mean absolute bias error (MABE). This comparison shows that the second model is closer to the experimental values that the model of Angstrom.Keywords: meteorology, global radiation, Angstrom model, Oran
Procedia PDF Downloads 22917757 Expert Review on Conceptual Design Model of Assistive Courseware for Low Vision (AC4LV) Learners
Authors: Nurulnadwan Aziz, Ariffin Abdul Mutalib, Siti Mahfuzah Sarif
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This paper reports an ongoing project regarding the development of Conceptual Design Model of Assistive Courseware for Low Vision (AC4LV) learners. Having developed the intended model, it has to be validated prior to producing it as guidance for the developers to develop an AC4LV. This study requires two phases of validation process which are through expert review and prototyping method. This paper presents a part of the validation process which is findings from experts review on Conceptual Design Model of AC4LV which has been carried out through a questionnaire. Results from 12 international and local experts from various respectable fields in Human-Computer Interaction (HCI) were discussed and justified. In a nutshell, reviewed Conceptual Design Model of AC4LV was formed. Future works of this study are to validate the reviewed model through prototyping method prior to testing it to the targeted users.Keywords: assistive courseware, conceptual design model, expert review, low vision learners
Procedia PDF Downloads 54417756 Application of Model Tree in the Prediction of TBM Rate of Penetration with Synthetic Minority Oversampling Technique
Authors: Ehsan Mehryaar
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The rate of penetration is (RoP) one of the vital factors in the cost and time of tunnel boring projects; therefore, predicting it can lead to a substantial increase in the efficiency of the project. RoP is heavily dependent geological properties of the project site and TBM properties. In this study, 151-point data from Queen’s water tunnel is collected, which includes unconfined compression strength, peak slope index, angle with weak planes, and distance between planes of weaknesses. Since the size of the data is small, it was observed that it is imbalanced. To solve that problem synthetic minority oversampling technique is utilized. The model based on the model tree is proposed, where each leaf consists of a support vector machine model. Proposed model performance is then compared to existing empirical equations in the literature.Keywords: Model tree, SMOTE, rate of penetration, TBM(tunnel boring machine), SVM
Procedia PDF Downloads 17317755 An Agent-Based Modeling and Simulation of Human Muscle
Authors: Sina Saadati, Mohammadreza Razzazi
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In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness
Procedia PDF Downloads 11217754 Multinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data
Authors: Wanhyun Cho, Soonja Kang, Sanggoon Kim, Soonyoung Park
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We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.Keywords: multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, importance sampling, approximate posterior distribution, marginal likelihood evidence
Procedia PDF Downloads 44117753 The Use of Haar Wavelet Mother Signal Tool for Performance Analysis Response of Distillation Column (Application to Moroccan Case Study)
Authors: Mahacine Amrani
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This paper aims at reviewing some Moroccan industrial applications of wavelet especially in the dynamic identification of a process model using Haar wavelet mother response. Two recent Moroccan study cases are described using dynamic data originated by a distillation column and an industrial polyethylene process plant. The purpose of the wavelet scheme is to build on-line dynamic models. In both case studies, a comparison is carried out between the Haar wavelet mother response model and a linear difference equation model. Finally it concludes, on the base of the comparison of the process performances and the best responses, which may be useful to create an estimated on-line internal model control and its application towards model-predictive controllers (MPC). All calculations were implemented using AutoSignal Software.Keywords: process performance, model, wavelets, Haar, Moroccan
Procedia PDF Downloads 316