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Earthquake simulations at the urban scale usually focus on estimating the damages to the built environment and the consequent losses without fully taking into account human behavior in crisis. Yet, human behavior is a key element for improving crisis disaster management; therefore, it is important to include it in seismic crisis simulations. In this study, an agent-based model for the simulation of pedestrian evacuation during earthquakes at the city scale is developed following an interdisciplinary approach. The model recreates the urban conditions using Geographic Information System (GIS) and a synthetic population, in addition to the earthquake consequences on the urban fabric. Moreover, the model integrates realistic human behaviors calibrated using quantitative survey results. We simulate pedestrian outdoor mobility with the different constraints that affect it such as the topography and the presence of debris. The simulator is applied to the case of Beirut, Lebanon. A what-if approach is adopted to analyze the population's safety in case of earthquakes in Beirut, particularly the open spaces' capacity to provide shelters and the effect of debris and realistic human behaviors on people's safety. The simulation results show that less than 40% of the population is able to arrive at an open space within 15 min after an earthquake. This number is further reduced when some open spaces are locked. Debris and realistic human behaviors significantly delay the arrivals to safe areas and, therefore, should not be neglected in earthquake simulations. [ABSTRACT FROM AUTHOR]

The estimation of seismic damages and debris at the urban scale—at a building-by-building level- is challenging for several reasons. First, commonly used methodologies for seismic damage estimation rarely take into account the local site effects, precisely at the building-level. Second, the available methods for debris estimation fail to estimate at the same time the quantity of debris generated per building according to its damage level and the distribution of the debris (extent and height) around buildings. Finally, the lack of comprehensive data on the building stock and the relevant building properties and their taxonomy further increases the complexity of assessing possible earthquake consequences at an urban scale. This paper addresses these challenges and proposes improvements to the assessment of seismic damages and debris from building-level simulations, along with the development of a 3D building model based on satellite images and heterogeneous data. These developments, applied to the city of Beirut, Lebanon, highlight the control of the site effects on the seismic damage's spatial distribution throughout the city and the large volume and extent of debris to be expected in the city for a strong earthquake. [ABSTRACT FROM AUTHOR]

Training firefighters is a difficult process in which emotions and nonverbal behaviors play an important role. The authors have developed a mixed reality environment for training a small group of firefighters, which takes into account these aspects. The assessment of the environment was made up of three phases: assessing the virtual agents to gauge their expressiveness, assessing the contextual virtual environment to see if it provides the same decision-making support as that found in the real world, and verifying indexicality to support agent interaction. (Contains 9 figures, 3 tables, and 4 notes.)

As the reallocator of liquidity from banks with excess to banks with a deficit, the interbank money market (IMM) plays a fundamental role in the proper functioning of the banking system and the economy as a whole. The aggregate uncertainty derived from stochasticity of the overall level of the demand for short-term liquidity and the likelihood of domino failures of tightly connected competitors who lend themselves vast amounts of liquidity explains the complexity of decisions in this environment. To identify the most significant factors influencing actors' strategies, we first present the five underlying patterns discovered through a bibliometric analysis of 609 scientific documents in this field: contagion and systemic risk, stability, market structure, relationship and trust, and default and failure. Then, our detailed study findings on 160 recent works indicate elements that affect central banks' strategies in reducing systemic risk and preventing financial contagion, as well as managing the interbank network in a way that makes it more stable and resilient to shocks to conserve market confidence. Furthermore, they address factors that influence banks' strategies to maintain their lending relationships and mitigate default risk. In addition to summarizing potential research directions, this paper provides market participants with a strategy fact-sheet. [ABSTRACT FROM AUTHOR]

This document discusses the use of computational simulation in crisis and disaster management. It highlights the advantages of simulation models in examining alternative strategies and predicting the effects of changes in real-world systems. The document also acknowledges the challenges in incorporating realistic human behavior, increasing acceptability of simulation models, and creating multi-scale models. The special issue focuses on current real-world problems and includes papers on topics such as epidemics, seismic crises, population sheltering management, and mass evacuation. Two companion papers on airport evacuation and the Syrian refugee crisis are also mentioned. [Extracted from the article]

Energy production and consumption are one of the largest sources of greenhouse gases (GHG), along with industry, and is one of the highest causes of global warming. Forecasting the environmental cost of energy production is necessary for better decision making and easing the switch to cleaner energy systems in order to reduce air pollution. This paper describes a hybrid approach based on Artificial Neural Networks (ANN) and an agent-based architecture for forecasting carbon dioxide (CO2) issued from different energy sources in the city of Annaba using real data. The system consists of multiple autonomous agents, divided into two types: firstly, forecasting agents, which forecast the production of a particular type of energy using the ANN models; secondly, core agents that perform other essential functionalities such as calculating the equivalent CO2 emissions and controlling the simulation. The development is based on Algerian gas and electricity data provided by the national energy company. The simulation consists firstly of forecasting energy production using the forecasting agents and calculating the equivalent emitted CO2. Secondly, a dedicated agent calculates the total CO2 emitted from all the available sources. It then computes the benefits of using renewable energy sources as an alternative way to meet the electric load in terms of emission mitigation and economizing natural gas consumption. The forecasting models showed satisfying results, and the simulation scenario showed that using renewable energy can help reduce the emissions by 369 tons of CO2 (3%) per day. [ABSTRACT FROM AUTHOR]

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This article presents an interdisciplinary vision for large-scale integrated emergency management that has been inspired by the transition from platform centric to integrated operations in the oil and gas fields, which uses remote emergency control centres collaborating virtually with local responders. The article discusses some of the most salient research challenges for integrated emergency management, including the role of mobile technology, human-centred sensing, citizen participation and social media, and the socio-cultural determinants of disaster management. The purpose of this article is to frame an integrated emergency management approach that adopts a multi-disciplinary approach, including human computer interaction, information systems, computer science, development studies and organization science employing different methodologies. Most importantly, we need to better understand the socio-cultural determinants of how people prepare to, respond and perceive disasters, in order to evaluate whether and what kind of information and communication technology (ICT) support is appropriate. There is need for more research as to why in some regions local people ignore official orders to evacuate, and rather follow the advice of local leaders, elders or religious leaders. In other instances, disasters are seen as 'acts of God' thus shaping disaster preparedness and response. [ABSTRACT FROM AUTHOR]

Energy waste due to inhabitants' behavior in residential buildings has emerged as a potential research area due to the increasing worldwide population and growing energy needs. However, existing approaches for simulating energy consumption are mainly limited to office buildings and are based on static profiles. In this paper we propose a 4-step co-simulation methodology to assess how inhabitants' interactions with household appliances affect energy consumption. The approach is validated using a case study showing how human activities influence the energy consumption patterns of a refrigerator. The fridge was specifically chosen because it is a high energy-consuming appliance that is strongly affected by inhabitants' behaviors. In addition, modeling the fridge is nontrivial, and in choosing this appliance we show that it is possible to apply the approach to less complex appliances. A co-simulation approach is adopted with the fridge being physically modeled in Matlab and with human behavior being modeled in the Brahms language and simulation environment. The consumption distribution from the simulated scenario is compared with the actual distribution (using data from a consumption database), to find optimum values of tuning parameters with less than 10% variation. This methodology enables us to simulate how human behaviors affect energy appliance consumption. [ABSTRACT FROM AUTHOR]

Abstract: Inhabitant''s decisions and actions have a strong impact on the energy consumption and are an important factor in reducing energy consumption and in modeling future energy trends. Energy simulations that take into account inhabitants’ behaviour are benchmarked at office buildings using controlled activity profiles and predefined scenarios. In this paper we have proposed a co-simulation environment for energy smart homes that takes into account inhabitants’ dynamic and social behaviour. Based on this kind of complex behaviour, the setpoints for different controllers are adjusted in the physical simulator. In this platform, human behaviour is modeled using the Brahms environment and the thermal model and controllers for different appliances are modeled as a physical simulator. The thermal model computes the temperature decrease/increase in a room based on the contextual information resulting from the behaviour simulator. This information is then given to the controller to act upon. [Copyright &y& Elsevier]