scholarly journals Complexity and Vulnerability Analysis of Critical Infrastructures: A Methodological Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yongliang Deng ◽  
Liangliang Song ◽  
Zhipeng Zhou ◽  
Ping Liu
Keyword(s):  
Decision Making ◽  
Critical Infrastructure ◽  
Methodological Approach ◽  
Network Models ◽  
Vulnerability Analysis ◽  
Clustering Coefficient ◽  
Near Miss ◽  
System Component ◽  
Emergency Situations ◽  
New Research

Vulnerability analysis of network models has been widely adopted to explore the potential impacts of random disturbances, deliberate attacks, and natural disasters. However, almost all these models are based on a fixed topological structure, in which the physical properties of infrastructure components and their interrelationships are not well captured. In this paper, a new research framework is put forward to quantitatively explore and assess the complexity and vulnerability of critical infrastructure systems. Then, a case study is presented to prove the feasibility and validity of the proposed framework. After constructing metro physical network (MPN), Pajek is employed to analyze its corresponding topological properties, including degree, betweenness, average path length, network diameter, and clustering coefficient. With a comprehensive understanding of the complexity of MPN, it would be beneficial for metro system to restrain original near-miss or accidents and support decision-making in emergency situations. Moreover, through the analysis of two simulation protocols for system component failure, it is found that the MPN turned to be vulnerable under the condition that the high-degree nodes or high-betweenness edges are attacked. These findings will be conductive to offer recommendations and proposals for robust design, risk-based decision-making, and prioritization of risk reduction investment.

scholarly journals Evaluating the Implementation of the “Build-Back-Better” Concept for Critical Infrastructure Systems: Lessons from Saint-Martin’s Island Following Hurricane Irma

2021 ◽  
Vol 13 (6) ◽  
pp. 3133
Author(s):  
Rita Der Sarkissian ◽  
Anas Dabaj ◽  
Youssef Diab ◽  
Marc Vuillet
Keyword(s):  
Decision Making ◽  
Conceptual Analysis ◽  
Scientific Literature ◽  
Critical Infrastructure ◽  
Methodological Approach ◽  
Infrastructure Systems ◽  
Before And After ◽  
Study Offer ◽  
Hurricane Irma ◽  
Operational Aspects

A limited number of studies in the scientific literature discuss the “Build-Back-Better” (BBB) critical infrastructure (CI) concept. Investigations of its operational aspects and its efficient implementation are even rarer. The term “Better” in BBB is often confusing to practitioners and leads to unclear and non-uniform objectives for guiding accurate decision-making. In an attempt to fill these gaps, this study offers a conceptual analysis of BBB’s operational aspects by examining the term “Better”. In its methodological approach, this study evaluates the state of Saint-Martin’s CI before and after Hurricane Irma and, accordingly, reveals the indicators to assess during reconstruction projects. The proposed methods offer practitioners a guidance tool for planning efficient BBB CI projects or for evaluating ongoing programs through the established BBB evaluation grid. Key findings of the study offer insights and a new conceptual equation of the BBB CI by revealing the holistic and interdisciplinary connotations behind the term “Better” CI: “Build-Back-resilient”, “Build-Back-sustainable”, and “Build-Back-accessible to all and upgraded CI”. The proposed explanations can facilitate the efficient application of BBB for CI by operators, stakeholders, and practitioners and can help them to contextualize the term “Better” with respect to their area and its CI systems.

Model for integrated assessment of rescue operations efficiency at group use of robotics for elimination of consequences of large-scale technogenic emergencies

2020 ◽  
pp. 90-101
Author(s):  
Андрей Владимирович Байков ◽  
Константин Валерьевич Александров
Keyword(s):  
Decision Making ◽  
Emergency Response ◽  
Integrated Assessment ◽  
Large Scale ◽  
Methodological Approach ◽  
Scheduling Theory ◽  
Rescue Operation ◽  
Scientific Methods ◽  
Emergency Rescue ◽  
Emergency Situations

Применение одного робототехнического средства (РТС) в зоне чрезвычайной ситуации (ЧС) малоэффективно из-за множества выполняемых задач, что обусловливает необходимость привлечения группы РТС для уменьшения времени ликвидации ЧС. В статье представлена математическая модель выбора группы РТС для ликвидации ЧС. Разработанная модель комплексной оценки эффективности проведения аварийно-спасательных работ при групповом применении РТС в техногенной ЧС является научно-методическим аппаратом по обоснованию состава группировки системы РТС МЧС России, необходимых для выполнения задач в ЧС. The use of one robotic in the emergency zone is not very effective due to the multitude of tasks performed in the emergency zone. This determines the need to use the group of robotics to reduce the time for emergency elimination. The relevance of the work is determined by the scattered scientific and methodological system for substantiating the composition of the robotics grouping of the Ministry of Emergency Situations of Russia, as well as by errors in decision making on the use of robotics in emergencies. The paper presents a mathematical model for choosing a group of robotic equipment for emergency response. The model for integrated assessment of the rescue operation effectiveness with application of group of robotics is based on the “scheduling theory”. The paper proposes scientific methods for the development of quantitatively substantiated recommendations for decision-making, where mathematical models of ordering various purposeful actions in time are constructed and analyzed taking into account the objective function and different restrictions. The developed model for integrated assessment of the effectiveness of emergency rescue operations at group application of robotics during technogenic emergency is a scientific and methodological approach for substantiating the structure of robotics grouping of EMERCOM of Russia required to solve tasks in an emergency.

scholarly journals Preventive Maintenance of a k-out-of-n System with Applications in Subsea Pipeline Monitoring

2021 ◽  
Vol 9 (1) ◽  
pp. 85
Author(s):  
Vladimir Rykov ◽  
Olga Kochueva ◽  
Mais Farkhadov
Keyword(s):  
Decision Making ◽  
Preventive Maintenance ◽  
Environmental Safety ◽  
Transport Systems ◽  
System Component ◽  
Subsea Pipeline ◽  
Safety Issues ◽  
Emergency Situations ◽  
Variational Series ◽  
Pipeline Monitoring

Environmental safety issues are of particular importance when we design and operate underwater transport systems. To ensure the transport systems function safely, special systems to monitor their condition are being created. Underwater pipeline monitoring systems should continuously operate to detect and prevent emergency and pre-emergency situations in a timely manner. The purpose of this article is to demonstrate the possibility of using a mathematical model of a k-out-of-n system to support decision-making in the preventive maintenance of an unmanned underwater vehicle to monitor the condition of a subsea pipeline. The novelty and feature of this study are that we investigate a strategy of preventive maintenance for a model of a k-out-of-n system, where failures depend not only on the number but also on the location of the failed components in the system. The method to solve this problem, based on the distribution of the members of the variational series of the failing components, is also new. Since the distributions of the system component lifetimes are usually known with an accuracy of only one or two moments, we paid special attention to how sensitive the decision making about preventive maintenance is to the shape of the distributions. Numerical examples are conducted in order to support the theoretical investigations of the paper. The results of the study are applied to specific equipment to monitor the state of the outer surface of the pipeline.

THE THE INDIGENOUS IDENTITY INTERPRETED AS A CATEGORY OF ANALYSIS IN POPULATION STUDIES

2017 ◽  
Vol 6 (Especial) ◽  
pp. 105
Author(s):  
Dante Choque-Caseres
Keyword(s):  
Indigenous Peoples ◽  
Methodological Approach ◽  
Indigenous Communities ◽  
Social Contexts ◽  
Indigenous Identity ◽  
Critical Thought ◽  
Northern Border ◽  
The Social ◽  
The Government ◽  
New Research

In Latin America, based on the recognition of Indigenous Peoples, the identification of gaps or disparities between the Indigenous and non-Indigenous population has emerged as a new research interest. To this end, capturing Indigenous identity is key to conducting certain analyses. However, the social contexts where the identity of Indigenous persons are (re)produced has been significantly altered. These changes are generated by the assimilation or integration of Indigenous communities into dominant national cultures. Within this context, limitations emerge in the use of this category, since Indigenous identity has a political and legal component related to the needs of the government. Therefore, critical thought on the use of Indigenous identity is necessary in an epistemological and methodological approach to research. This article argues that research about Indigenous Peoples should evaluate how Indigenous identity is included, for it is socially co-produced through the interaction of the State and its institutions. Thus, it would not necessarily constitute an explicative variable. By analyzing the discourse about Aymara Indigenous communities that has emerged in the northern border of Chile, this paper seeks to expose the logic used to define identity. Therefore, I conclude that the process of self-identification arises in supposed Indigenous people, built and/or reinforced by institutions, which should be reviewed from a decolonizing perspective and included in comparative research.

What do new neuroscience discoveries in children mean for their open future?

2017 ◽  
Author(s):  
Cheryl D. Lew
Keyword(s):  
Decision Making ◽  
Moral Agency ◽  
Structural Changes ◽  
Fetal Life ◽  
Open Future ◽  
Ethical Concerns ◽  
Pediatric Ethics ◽  
Pediatric Decision Making ◽  
New Research ◽  
Pediatric Healthcare

Over the last decade, the number of neuroimaging and other neuroscience studies on the developing brain from fetal life through adolescence has increased exponentially. Children are viewed as particularly vulnerable members of our society and observations of significant neural structural changes associated with behavioral anomalies raise numerous ethical concerns around personal identity, free will, and the possibility of an open future. This chapter provides a review of recent research in the pediatric neuroscience literature, common pediatric decision-making, and social justice models, and discusses the implications of this research for the future of pediatric ethics thinking and policy. New research presents challenges to professional and pediatric bioethicist views of the moral future of children in pediatric healthcare and opportunities to examine anew notions of how to consider the developing moral agency of children.

The configuration model

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Degree Sequence ◽  
Graph Model ◽  
Network Models ◽  
Clustering Coefficient ◽  
Giant Component ◽  
Configuration Model ◽  
Bipartite Networks ◽  
Small Component ◽  
Random Graph Model ◽  
Average Size

A discussion of the most fundamental of network models, the configuration model, which is a random graph model of a network with a specified degree sequence. Following a definition of the model a number of basic properties are derived, including the probability of an edge, the expected number of multiedges, the excess degree distribution, the friendship paradox, and the clustering coefficient. This is followed by derivations of some more advanced properties including the condition for the existence of a giant component, the size of the giant component, the average size of a small component, and the expected diameter. Generating function methods for network models are also introduced and used to perform some more advanced calculations, such as the calculation of the distribution of the number of second neighbors of a node and the complete distribution of sizes of small components. The chapter ends with a brief discussion of extensions of the configuration model to directed networks, bipartite networks, networks with degree correlations, networks with high clustering, and networks with community structure, among other possibilities.

scholarly journals Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys

2021 ◽  
Vol 13 (11) ◽  
pp. 6038
Author(s):  
Sergio Alonso ◽  
Rosana Montes ◽  
Daniel Molina ◽  
Iván Palomares ◽  
Eugenio Martínez-Cámara ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Sustainable Development Goals ◽  
Modern Society ◽  
Agenda 2030 ◽  
Model Based ◽  
Development Goals ◽  
Sustainability Challenges ◽  
New Research ◽  
Decision Making Model

The United Nations Agenda 2030 established 17 Sustainable Development Goals (SDGs) as a guideline to guarantee a sustainable worldwide development. Recent advances in artificial intelligence and other digital technologies have already changed several areas of modern society, and they could be very useful to reach these sustainable goals. In this paper we propose a novel decision making model based on surveys that ranks recommendations on the use of different artificial intelligence and related technologies to achieve the SDGs. According to the surveys, our decision making method is able to determine which of these technologies are worth investing in to lead new research to successfully tackle with sustainability challenges.

scholarly journals Flexible categorization in perceptual decision making

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Genís Prat-Ortega ◽  
Klaus Wimmer ◽  
Alex Roxin ◽  
Jaime de la Rocha
Keyword(s):  
Decision Making ◽  
Network Models ◽  
Drift Diffusion Model ◽  
Perceptual Decision Making ◽  
Drift Diffusion ◽  
Perceptual Decision ◽  
Attractor Dynamics ◽  
Attractor Model ◽  
Sensory Evidence ◽  
Winner Take All

AbstractPerceptual decisions rely on accumulating sensory evidence. This computation has been studied using either drift diffusion models or neurobiological network models exhibiting winner-take-all attractor dynamics. Although both models can account for a large amount of data, it remains unclear whether their dynamics are qualitatively equivalent. Here we show that in the attractor model, but not in the drift diffusion model, an increase in the stimulus fluctuations or the stimulus duration promotes transitions between decision states. The increase in the number of transitions leads to a crossover between weighting mostly early evidence (primacy) to weighting late evidence (recency), a prediction we validate with psychophysical data. Between these two limiting cases, we found a novel flexible categorization regime, in which fluctuations can reverse initially-incorrect categorizations. This reversal asymmetry results in a non-monotonic psychometric curve, a distinctive feature of the attractor model. Our findings point to correcting decision reversals as an important feature of perceptual decision making.

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