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Featured ApplicationThis paper presents the application of a software program that is currently under development that provides feedback for the mapping activities that are carried out in built environments and analyses the congruence in the relationship between the flow of activities and their environments. Exemplary results were obtained in the case study of a healthcare emergency facility, although it is possible to apply this software in other types of complex environments. The obtained data allow facility managers to prioritize and reallocate activities when a change is required. It also shows unmapped relationships. It is important to investigate these data because they can indicate failures in the mapping process and can provide an opportunity to obtain a more complete understanding of the allocation and flow of activities. These data can also help us to identify points of conflict or opportunities for adjustment in the allocation of activities in order to improve the flow of activities.Due to the large number of activities that must be carried out by emergency-care services (ESs), the tasks of facility managers and architects are challenging and complex. Several strategies, guides, and diagnoses have already been developed in order to improve ESs. Part of the solution to this problem depends on obtaining a normative and universal understanding of the problem, and another part depends on conducting a specific and relational analysis between the environment and the flow of activities that are allocated within it. This paper presents the results of a study that was conducted using a software program that is currently under development for mapping the congruence relationship between activities and environments. Here, we present a discussion of the first results that were obtained with the instrument, which was applied to a single case. For this purpose, the fundamentals of the instrument, as well as the environment and the flows of an ES at a university hospital, are described. The forms of analysis, benefits, and limitations of the instrument were investigated, with a view towards its use in supporting the management and the design of large and complex environments, such as emergency departments. In this program, the relationships that are hidden from the managers, the designers, and the researchers due to the aforementioned complexity are revealed through the use of matrices. This mapping can supplement the decision making of the managers and the designers. The application showed advantages in modeling with fewer inputs, mainly in pre-design evaluations.
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Coarse-grained (CG) modeling has defined a well-established approach to accessing greater space and time scales inaccessible to the computationally expensive all-atomic (AA) molecular dynamics (MD) simulations. Popular methods of CG follow a bottom-up architecture to match properties of fine-grained or experimental data whose development is a daunting challenge for requiring the derivation of a new set of parameters in potential calculation. We proposed a novel physics-informed machine learning (PIML) framework for a CG model and applied it, as a verification, for modeling the SARS-CoV-2 spike glycoprotein. The PIML in the proposed framework employs a force-matching scheme with which we determined the force-field parameters. Our PIML framework defines its trainable parameters as the CG force-field parameters and predicts the instantaneous forces on each CG bead, learning the force field parameters to best match the predicted forces with the reference forces. Using the learned interaction parameters, CGMD validation simulations reach the microsecond time scale with stability, at a simulation speed 40,000 times faster than the conventional AAMD. Compared with the traditional iterative approach, our framework matches the AA reference structure with better accuracy. The improved efficiency enhances the timeliness of research and development in producing long-term simulations of SARS-CoV-2 and opens avenues to help illuminate protein mechanisms and predict its environmental changes.
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In this paper, a system dynamics model depicts the viral growth of COVID-19 at an exponential rate. The outbreak of Corona virus was started from the Feb 26, 2020 when the first case was reported in Pakistan. Local bodies and law enforcing agencies had taken initial preventive measures to restrict the COVID-19 to a particular locality but all in vain. The infected people were increasing every day rising the stocks of recoveries and deaths. Numbers of infected people were alarming and a need was felt to develop the model to calculate the existing reproduction number and transmission rate and highlight its varied values in coming days. People-oriented measures and government-based policies must be explored to fight against this deadly disease. This paper aims the development of epidemic model using the system dynamic framework on simulation software STELLA. The objective of the research is to experiment with the model to replicate the progression of the communicable disease and probe the multiple combinations of the people-based and government-based measures to reduce its spread. The containment measures are of two types;people-based measures and government-based measures and both directly affect the reproduction number and infection growth fraction for mitigating the spread of deadly coronavirus. Combined efforts of public and government can combat this pandemic. Reduced degree of reproduction number and infection growth fraction are the key metrics to judge and evaluate the effectiveness of containment measures. This research points to more holistic combination of public and government-oriented measures that play the vital role to flatten the curve and reduce its spread affecting the reproduction number. Simulation results have been traced to replicate the real-life settings against four combinations of containment measures in tabular form and graphical form. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Introduction: To meet the multi-user, cross-time-and-space, cross-platform online demand of work, and professional training teaching in nuclear reactor safety analysis under the normalization of Coronavirus Disease 2019. Method: Taking the nuclear accident simulation software PCTRAN as an example, this study adopts cloud computing technology to build the NasCloud, a nuclear accident simulation cloud platform based on Browser/Server architecture, and successfully realizes multi-user, cross-time-and-space, cross-platform applications. Targeting the AP1000, a pressurized water reactor nuclear power plant, the simulation of cold-leg Small Break Loss of Coolant Accident and cold-leg Large Break Loss of Coolant Accident were carried out to verify the correctness of the NasCloud's accident simulation function. Results: The result shows that the simulation functions and results of the NasCloud in multi-terminal are consistent with the single version of PCTRAN. At the same time, the platform has high scalability, concurrency and security characteristics. Discussion: Therefore, the nuclear accident simulation cloud platform built in this study can provide solutions for the work and training of nuclear reactor safety analysis, and provide reference for other engineering design and simulation software cloud to computing transformation. Copyright © 2023 Chen, Chen, Xie, Xiong and Yu.
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Reinforcement learning (RL) has been applied to a variety of fields such as gaming and robot navigation. We study the application of RL in crowd simulation by proposing an automatic parameter tuning system based on Proximal Policy Optimization (PPO). The system can be used with any crowd simulation software to improve the quality of the simulation by automatically assigning parameters to each agent during the simulation. Our experiments indicate that the automatic parameter tuning system can reduce unexpected congestions in counterflow scenarios. In addition, by utilizing the improved commonly used crowd simulation algorithms and our parame-ter tunning system, we can represent social distancing behavior of pedestrians under COVID-19, where pedestrians comply to the suggested social distance when they have enough space to move while they reduce their social distances to others when there is limited space. © 2022 IEEE.
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The rapidly growing market of eSports has become a lucrative industry. Sim racing is one of the traditional sports that gain increasing popularity in eSports. With raising profits, lucrative sponsoring contracts, and competitive price money, incentives for fraud are also on the upraise. This is further facilitated by the COVID-19 pandemic, which led to the substitution of live eSport events by virtual formats. Particularly, in sim racing it becomes increasingly challenging to verify the contestants identity in virtual events. Here, we propose and evaluate a generic workflow to identify personal driving style by transforming raw racing data (including measurements extracted from the simulation software and connected simulator hardware) into a comparable representation (fingerprint). As data base we used an extensive collection of telemetry data recorded from the racing simulation Assetto Corsa on 3 immersive motion simulators. The set contains over 2,000 laps of seven player recorded in weekly sessions. The experiments demonstrate the feasibility to distinguish players using the proposed method on different tracks, car models, and motion simulators. Due to the extensive experiments, we could achieve a driver separation score of up to 89%. The raw data and the raw results are made publicly available on Github. © 2022 IEEE.
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The core idea available is IoT, which can be integrated into a traditional communication network to solve many problems. This paper deals with the development of a Social Distance Detector for safety purpose in this COVID-19 pandemic. To keep us safe from maintaining a social distance from people. A detector system is developed to make an alarm while the social distancing is not maintained properly. The detector system is developed by using Tinker cad IoT Simulation software. It is a Circuit design Arduino Simulator created by Soft logic to simulate and assemble. The sensors and tools make the circuit working by embedding Arduino-UNO-R3, ultrasonic sensor, breadboard and Piezo Buzzer. © 2022 IEEE.
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Complex flow simulations are conventionally performed on HPC clusters. However, the limited availability of HPC resources and steep learning curve of executing on traditional supercomputer infrastructure has drawn attention towards deploying flow simulation software on the cloud. We showcase how a complex computational framework-that can evaluate COVID-19 transmission risk in various indoor classroom scenarios-can be ed and deployed on cloud services. The availability of such cloud-based personalized planning tools can enable educational institutions, medical institutions, public sector workers (courthouses, police stations, airports, etc.), and other entities to comprehensively evaluate various in-person interaction scenarios for transmission risk. We deploy the simulation framework on the Azure cloud framework, utilizing the Dendro-ktmesh generation tool and PETSc solvers. The cloud ion is provided by RocketML cloud infrastructure. We compare the performance of the cloud machines with state-of-the-art HPC machine TACC Frontera. Our results suggest that cloud-based HPC resources are a viable strategy for a diverse array of end-users to rapidly and efficiently deploy simulation software. © 2021 IEEE.
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The global pandemic declared by the WHO in March 2020 made urgent the need for an affordable adult ventilator for the Philippine market. An existing low-cost infant ventilator developed by Dr. Enrique Ostrea Jr was redesigned and upgraded into one suitable for adult use. A team of Doctors, Engineers, and Technicians was gathered to work on the project. The team was tasked to develop a low-cost, pressure- and volume-controlled ventilator suitable for adult and infant use in the shortest possible time. A model of the ventilator was created using the simulation software Scilab. The model was used to predict its behavior and guide the design of the ventilator. Experiments were conducted to validate the results from the model. It was found that the model satisfactorily predicted the dynamics of the flow inside the ventilator. The modeling and validation activities helped us build the new low-cost ventialtor in less than four months. © 2021 IEEE.
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Students at Al-Balqa' Applied University, Jordan, are being interviewed about their experiences with online simulation software during the Covid-19 pandemic. In this study, a descriptive method was employed. 667 undergraduate students were asked to fill out a 25-item questionnaire. During the Covid-19 epidemic, undergraduate students showed a modest level of proficiency in using simulation software via online instruction, according to the study's findings. Al-Balqa' Applied University undergraduate students' perspectives vary according to gender (in favor of females) and discipline, according to the findings (in favor of the Electrical engineering discipline.). Academic evaluation, on the other hand, does not show any statistically significant differences amongst pupils. As a result, there appears to be no statistically significant difference in academic evaluation across pupils (GPA). It's important to do more research like this one on simulation software implementation in higher education institutions, according to this study © The Author 2022. This work is licensed under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) that allows others to share and adapt the material for any purpose (even commercially), in any medium with an acknowledgement of the work's authorship and initial publication in this journal
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In recent years, the volume of parcels sold electronically has increased significantly. The current pandemic period has amplified this, as the volume of e-shop transactions has grown even more. Due to the COVID-19 pandemic and related restrictive measures, most shops are closed in the Czech Republic. Customers most often use e-shops to buy goods. As a result, the volume of parcel transport, which is provided by parcel carriers, is increasing to finish customers. Improving distribution logistics and the entire logistic system are constantly under pressure in the context of existing competition, maintaining the declared level of customer service and increasing volume of parcels. One way to streamline the logistic distribution process is to use RFID technology as one of the automatic identification technologies. The aim of the article is to create the proposal for the use of RFID technology in the distribution process of parcels in order to make it more effective. Simulation software the Witness Horizon will used to achieve the aim. The software uses the dynamic simulation to evaluate the benefits of using RFID technology before its implementation. © 2021 Kaunas University of Technology. All rights reserved.
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As India is in its developing stage and the traffic on the other side in India is very heterogeneous or mixed in its nature and the average growth rate of vehicles in India is about 8%. With the increase rate of urbanization in India it will lead to the considerable traffic and travel growth on the roads which will result in vehicular delays, long queues and traffic congestion. So, in this paper with the help of traffic simulation software, i.e. VISSIM, three simulation of an unsignalized intersection {Dadour and Una-Jahu, Nerchowk Rd. (NH-21),H.P} will be analyzed and will compare them on the basis of vehicular delays and long queues. These three simulation will be analyzed on the basis of real world traffic data which is less from the expectations due to the pandemic covid-19, theoretical traffic data (increase in real data by 30%) and theoretical traffic data {with traffic signals as theoretical data follows warrant 1 (Min. Vehicular Volume) shown in IRC:93:1985}. Result showed that with increase in vehicular data there was not so much variation in vehicular delays, whereas there was an increase in long queues or queue stops and whilst third simulation (with traffic lights) is done it shows that it overcomes the queue stops of the intersection. © 2022, Springer Nature Singapore Pte Ltd.
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In 2020 the residential sector witnessed a complete transformation of the way people live and occupy the spaces. Indeed, different Countries introduced total lockdowns as a measure to contain and prevent the spread of COVID-19, forcing people to stay at home. These measures impact the indoor hygrothermal environment: higher internal thermal loads and moisture generation rate may create the perfect situation to support mould growth. This project aims to understand the impacts of increased work-from-home practices on the hygrothermal performance of residential buildings. The assessment uses a two-step methodology: firstly, whole building transient simulations (software trnsys) are used to generate the indoor temperature and humidity profiles, secondly hygrothermal transient simulations (software WUFI) are used to quantify the risk of mould growth. This research reveals the inadequacy of current design and construction practices to support flexible occupation patterns. © 2021 Institute of Physics Publishing. All rights reserved.
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Logistics and operations consulting has traditionally adopted discrete-event simulation software, such as Simio and Arena, to visualize dynamic processes and complex systems across a wide range of environments. Without the effort of extensive programming however, these tools lack the ability to separate objects and people interacting with each other and occupying the same space. This lack of separation is a problem for logistics and operations consulting, where dynamics between different activities and physical interactions between people are key. Especially within the context of COVID-19, incorporating social distancing behaviors into our built environments is of growing importance. In this regard, pedestrian simulation software offers an alternative solution to modeling logistics and operations processes, behavioral interactions, and spatial considerations. As logistics consultants, we work with architects to iterate building designs and ensure that sufficient space is provided for back-of-house operations, staff circulation, and vehicle movements. Pedestrian simulation knowledge and tools respond to these challenges by combining dynamic agents and fixed spaces together into one platform, adding physical barriers that impact queues and waiting areas, and incorporating the ability to realistically model and customize distinct behavior types, such as abled and disabled persons. In modeling the most realistic versions of our projects' environments, we can also identify opportunities to improve equity and resilience within the design. The goal of this study is to use specific case studies that utilized the software MassMotion and demonstrate how pedestrian simulation modeling has improved the outcome of logistics consulting projects in a changing world. © 2021 IISE Annual Conference and Expo 2021. All rights reserved.
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Medical disaster response training is provided for international students in Kawauchi Village to share the lessons learnt from the accident at Fukushima Daiichi nuclear power plant. At present, this is difficult due to the coronavirus disease 2019 (COVID-19) pandemic. The purpose of this article is to report the development of hands-on medical training software on a topic that does not require in-person attendance. The 'Kawauchi Legends' disaster simulator was developed as a useful tool to teach the medical response to various disasters, and this was applied in a 3-day webinar in October 2020. Fourteen students participated in the webinar and successfully learnt medical management, manipulating their avatars in the virtual environment. This software can be an effective substitute for in-person disaster training without physical involvement. Such innovative teaching methods mean that lessons from the Fukushima accident can continue to be shared, even in the COVID-19 pandemic situation.