scholarly journals Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1626
Author(s):  
Svetozar Zarko Valtchev ◽  
Ali Asgary ◽  
Michael Chen ◽  
Felippe A. Cronemberger ◽  
Mahdi M. Najafabadi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Rapid Assessment ◽  
Real Data ◽  
Interdisciplinary Teams ◽  
Major Focus ◽  
Data Simulation ◽  
Agent Based ◽  
Simulation Based ◽  
New Methodologies ◽  
Testing Policies

Research on SARS-CoV-2 and its social implications have become a major focus to interdisciplinary teams worldwide. As interest in more direct solutions, such as mass testing and vaccination grows, several studies appear to be dedicated to the operationalization of those solutions, leveraging both traditional and new methodologies, and, increasingly, the combination of both. This research examines the challenges anticipated for preventative testing of SARS-CoV-2 in schools and proposes an artificial intelligence (AI)-powered agent-based model crafted specifically for school scenarios. This research shows that in the absence of real data, simulation-based data can be used to develop an artificial intelligence model for the application of rapid assessment of school testing policies.

Risk Evaluation by Human Trajectory Simulation Based on Real Data

2011 ◽  
Vol 15 (2) ◽  
pp. 220-225
Author(s):  
Kiyoshi Izumi ◽  
◽  
Yoshifumi Nishida ◽  
Yoichi Motomura ◽  
Keyword(s):  
Risk Evaluation ◽  
Real Data ◽  
Public Spaces ◽  
Layout Design ◽  
Sensor Data ◽  
Agent Based Simulation ◽  
New Approach ◽  
Agent Based ◽  
Trajectory Simulation ◽  
Simulation Based

This paper proposes a new approach integrating the modeling of moving persons from sensor data and agent-based simulation for indoor layout design viewed from preventing children’s accidents. Our model focuses on interaction between indoor objects and children to estimate the risk of indoor accidents. We discuss the agent-based simulation of multiple persons moving in public spaces and its application to evaluating information presentation for guidance.

Social and Group Simulation Based on Real Data Analysis

2011 ◽  
Vol 15 (2) ◽  
pp. 166-172
Author(s):  
Kiyoshi Izumi ◽  
◽  
Keiki Takadama ◽  
Hiromitsu Hattori ◽  
Nariaki Nishino ◽  
...  
Keyword(s):  
Data Analysis ◽  
Financial Marketing ◽  
Real Data ◽  
Social Simulation ◽  
Sustainable Society ◽  
Agent Based Simulation ◽  
Simulation Research ◽  
Agent Based ◽  
Simulation Based ◽  
General Method

Recently, social simulation research based on real data has appeared in various fields. This paper introduces studies of Agent-Based Simulation (ABSs) based on real data, focusing on introducing studies in the fields of financial marketing, traffic, pedestrians, and a sustainable society. We also introduce some approaches to establish a general method and/or theory about linking social simulation to real data. Finally, we categorize ABS research for understanding ABS research features.

Simulation-based analyses of an evacuation from a metropolis during a bombardment

SIMULATION ◽  
2014 ◽  
Vol 90 (11) ◽  
pp. 1244-1267 ◽  
Author(s):  
Jang Won Bae ◽  
SeHoon Lee ◽  
Jeong Hee Hong ◽  
Il-Chul Moon
Keyword(s):  
Initial Conditions ◽  
Real Data ◽  
Agent Based Modeling ◽  
Agent Based Model ◽  
Target Region ◽  
Agent Based ◽  
Virtual Experiments ◽  
The Road ◽  
Simulation Based ◽  
The Military

The bombardment of a metropolis is considered a nightmare scenario. To reduce losses from such an assault, big cities have developed evacuation policies in case of bombardment. However, to build efficient evacuation policies, much footing data is required that considers both military and civilian views. Agent-based modeling and simulation could be utilized as a method to obtain the footing data. In this paper, we develop an evacuation agent-based model that describes a massive evacuation through the road network of a metropolis during a bombardment. In particular, our model took account of bombing strategies (i.e. the military view) as well as the characteristics of roads and evacuation agents (i.e. the civilian view) in order to analyze evacuations from both military and civilian perspectives. Moreover, we applied real data from a target region to calibrate parameters and initial conditions of the evacuation agent-based models, which increased the reliability of simulation results. Using the evacuation agent-based model, we designed and performed virtual experiments with varying military and civilian factors. Through the various analyses on the experiment results, we showed that our model could be a framework that provides footing data to develop efficient evacuation policies and preparations.

Research on the framework of university ideological and political education management system based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Political Theory ◽  
Outlier Detection ◽  
Management System ◽  
Detection Algorithm ◽  
Colleges And Universities ◽  
Ideological And Political Education ◽  
Political Education ◽  
Data Simulation ◽  
Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

An Intelligent Approach to Detect Fake News Using Artificial Intelligence Technique

2021 ◽  
Vol 13 (2) ◽  
pp. 1-12
Author(s):  
Sumit Das ◽  
Manas Kumar Sanyal ◽  
Sarbajyoti Mallik
Keyword(s):  
Artificial Intelligence ◽  
Web Application ◽  
Short Term Memory ◽  
Real Data ◽  
Fake News ◽  
Artificial Intelligence Technique ◽  
News Reports ◽  
Proposed Model ◽  
Long Short Term Memory ◽  
Intelligent Approach

There is a lot of fake news roaming around various mediums, which misleads people. It is a big issue in this advanced intelligent era, and there is a need to find some solution to this kind of situation. This article proposes an approach that analyzes fake and real news. This analysis is focused on sentiment, significance, and novelty, which are a few characteristics of this news. The ability to manipulate daily information mathematically and statistically is allowed by expressing news reports as numbers and metadata. The objective of this article is to analyze and filter out the fake news that makes trouble. The proposed model is amalgamated with the web application; users can get real data and fake data by using this application. The authors have used the AI (artificial intelligence) algorithms, specifically logistic regression and LSTM (long short-term memory), so that the application works well. The results of the proposed model are compared with existing models.

scholarly journals Feedforward Tactical Optimization for Energy-Efficient Operation of Freight Trains: The Swiss Case

2018 ◽  
Vol 2672 (10) ◽  
pp. 278-288 ◽  
Author(s):  
Valerio De Martinis ◽  
Ambra Toletti ◽  
Francesco Corman ◽  
Ulrich A. Weidmann ◽  
Andrew Nash
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Real Data ◽  
Efficient Solutions ◽  
Future Market ◽  
Speed Profile ◽  
Efficient Operation ◽  
The North ◽  
Simulation Based ◽  
Profile Optimization

The optimization of rail operation for improving energy efficiency plays an important role for the current and future market of rail freight services and helps rail compete with other transport modes. This paper presents a feedforward simulation-based model that performs speed profile optimization together with minor rescheduling actions. The model’s purpose is to provide railway operators and infrastructure managers with energy-efficient solutions that are tailored especially for freight trains. This work starts from the assumption that freight train characteristics are completely defined only a few hours before actual departure; therefore, small specific feedforward adjustments that do not affect the surrounding operation can still be considered. The model was tested in a numerical example. The example clearly shows how the optimized solutions can be evaluated with reference to energy saved and robustness within the rail traffic. The evaluation is based on real data from the North–South corridor crossing Switzerland from Germany to Italy.

Analyzing Marketing Strategies in the Emerging Mobile Communications Market

2016 ◽  
Vol 7 (4) ◽  
pp. 40-59
Author(s):  
Weiyang Wang ◽  
Manabu Ichikawa ◽  
Hiroshi Deguchi
Keyword(s):  
Emerging Markets ◽  
Market Share ◽  
Mobile Communications ◽  
Computational Simulation ◽  
Marketing Strategies ◽  
Agent Based Model ◽  
Service Market ◽  
Agent Based ◽  
Simulation Based

As one of the typical emerging markets, China's 3rd generation (3G) mobile communications service is proliferating rapidly recently, and great potentialities are expected in the market. Thus the strategy to improve the share in the emerging 3G service market appears to be an important topic for the mobile communications operators. To study the topic, the authors apply an agent-based model to study the interactions among the individuals and the complex externalities in China's 3G mobile communications market, and analyze several strategies of the operators with computational simulation. Based on the analysis, the efficient strategies for each operator to improve the market share are proposed. Furthermore, the analysis also shows that how the efficiency of the strategies varies depending on the different market environments. Because the emerging markets share some common characteristics, the conclusions can also be applied in other emerging communications markets.

scholarly journals Electrification of Urban Waste Collection: Introducing a Simulation-Based Methodology for Technical Feasibility, Impact and Cost Analysis

2021 ◽  
Vol 12 (3) ◽  
pp. 122 ◽  
Author(s):  
Ricardo Ewert ◽  
Alexander Grahle ◽  
Kai Martins-Turner ◽  
Anne Magdalene Syré ◽  
Kai Nagel ◽  
...  
Keyword(s):  
Open Source ◽  
Waste Collection ◽  
Commercial Vehicles ◽  
Urban Waste ◽  
Technical Feasibility ◽  
Routing Problem ◽  
Agent Based ◽  
Simulation Based ◽  
Multi Agent ◽  
Urban Emissions

Electrification is a potential solution for transport decarbonization and already widely available for individual and public transport. However, the availability of electrified commercial vehicles like waste collection vehicles is still limited, despite their significant contribution to urban emissions. Moreover, there is a lack of clarity whether electric waste collection vehicles can persist in real world conditions and which system design is required. Therefore, we introduce a multi-agent-based simulation methodology to investigate the technical feasibility and evaluate environmental and economic sustainability of an electrified urban waste collection. We present a synthetic model for waste collection demand on a per-link basis, using open available data. The tour planning is solved by an open-source algorithm as a capacitated vehicle routing problem (CVRP). This generates plausible tours which handle the demand. The generated tours are simulated with an open-source transport simulation (MATSim) for both the diesel and the electric waste collection vehicles. To compare the life cycle costs, we analyze the data using total cost of ownership (TCO). Environmental impacts are evaluated based on a Well-to-Wheel approach. We present a comparison of the two propulsion types for the exemplary use case of Berlin. And we are able to generate a suitable planning to handle Berlin’s waste collection demand using battery electric vehicles only. The TCO calculation reveals that the electrification raises the total operator cost by 16–30%, depending on the scenario and the battery size with conservative assumptions. Furthermore, the greenhouse gas emissions (GHG) can be reduced by 60–99%, depending on the carbon footprint of electric power generation.

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