Managing Knowledge in Crisis Scenarios: The Use of Pervasive Technologies

Author(s):  
Rajeev K. Bali ◽  
Vikraman Baskaran ◽  
Aapo Immonen ◽  
Alan C. Richards ◽  
Ian M. Marshall ◽  
...  
Keyword(s):  
Author(s):  
Sergio Salvatore ◽  
Terri Mannarini ◽  
Evrinomy Avdi ◽  
Fiorella Battaglia ◽  
Marco Cremaschi ◽  
...  
Keyword(s):  

Author(s):  
Christopher Garcia ◽  
Ghaith Rabadi ◽  
Femida Handy

Purpose Every year volunteers play a crucial role in disaster responses around the world. Volunteer management is known to be more complex than managing a paid workforce, and this is only made worse by the uncertainty of rapidly changing conditions of crisis scenarios. The purpose of this paper is to address the critical problem of assigning tasks to volunteers and other renewable and non-renewable resources simultaneously, particularly under high-load conditions. These conditions are described by a significant mismatch between available volunteer resources and demands or by frequent changes in requirements. Design/methodology/approach Through a combination of literature reviews and interviews with managers from several major volunteer organizations, six key characteristics of crisis volunteer resource allocation problems are identified. These characteristics are then used to develop a general mixed integer programming framework for modeling these problems. Rather than relying on probabilistic resource or demand characterizations, this framework addresses the constantly changing conditions inherent to this class of problems through a dynamic resource reallocation-based approach that minimizes the undesirable impacts of changes while meeting the desired and changing objectives. The viability of this approach for solving problems of realistic size and scale is demonstrated through a large set of computational experiments. Findings Using a common commercial solver, optimal solutions to the allocation and reallocation problems were consistently obtained in short timespans for a wide variety of problems that have realistic sizes and characteristics. Originality/value The proposed approach has not been previously addressed in the literature and represents a computationally tractable method to allocate volunteer, renewable and non-renewable resources to tasks in highly volatile crisis scenarios without requiring probabilistic resource or demand characterizations.


Drones ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 79
Author(s):  
Dimitrios Chatziparaschis ◽  
Michail G. Lagoudakis ◽  
Panagiotis Partsinevelos

Humanitarian Crisis scenarios typically require immediate rescue intervention. In many cases, the conditions at a scene may be prohibitive for human rescuers to provide instant aid, because of hazardous, unexpected, and human threatening situations. These scenarios are ideal for autonomous mobile robot systems to assist in searching and even rescuing individuals. In this study, we present a synchronous ground-aerial robot collaboration approach, under which an Unmanned Aerial Vehicle (UAV) and a humanoid robot solve a Search and Rescue scenario locally, without the aid of a commonly used Global Navigation Satellite System (GNSS). Specifically, the UAV uses a combination of Simultaneous Localization and Mapping and OctoMap approaches to extract a 2.5D occupancy grid map of the unknown area in relation to the humanoid robot. The humanoid robot receives a goal position in the created map and executes a path planning algorithm in order to estimate the FootStep navigation trajectory for reaching the goal. As the humanoid robot navigates, it localizes itself in the map while using an adaptive Monte-Carlo Localization algorithm by combining local odometry data with sensor observations from the UAV. Finally, the humanoid robot performs visual human body detection while using camera data through a Darknet pre-trained neural network. The proposed robot collaboration scheme has been tested under a proof of concept setting in an exterior GNSS-denied environment.


Politics ◽  
2020 ◽  
Vol 40 (4) ◽  
pp. 494-509
Author(s):  
Laura Levick ◽  
Mauricio Olavarria-Gambi

Expert surveys provide a standardized way to access and synthesize specialized knowledge, thereby, enabling the analysis of a diverse range of concepts and contexts that might otherwise be difficult to approach systematically. However, while studies of public opinion have long argued that cognitive biases represent potential problems when it comes to the general population, less attention has been paid to similar issues among expert respondents. This study examines one form of cognitive bias, hindsight bias. Hindsight bias refers to the tendency to retrospectively exaggerate one’s foresight of a particular event. We argue that hindsight bias is a potential problem when it comes to retrospective evaluation due to the difficulty involved in separating our assessments of the pre-crisis period from the knowledge that a crisis occurred. Using disaggregated data from the Varieties of Democracy Project, we look for evidence of hindsight bias in coders’ evaluations of the periods that preceded major crises of democracy. We find that coder disagreement is significantly higher in pre-crisis scenarios than in our control group. Concerningly, despite this disagreement, coders remain similarly confident in their assessments. This represents a potential problem for those who seek to use these data to study democratic breakdowns and transitions.


Author(s):  
Moeed Yusuf

This chapter addresses the general applicability of brokered bargaining beyond South Asia, focusing on four prototypes of rivalries: between countries that are considered friends of the unipole (futuristic crisis scenarios involving Israel versus a nuclear Saudi Arabia, Turkey, or Egypt); between a friend and foe of the unipole (Israel versus a nuclear Iran); between a foe of the unipole and an ally with formally extended deterrence guarantees (Korean peninsula); and between a friend and a presumptive great power rival of the unipole (India versus China). The discussion establishes the similarities and differences of these prototypes with the South Asian cases. While each presents a somewhat distinct set of challenges for third-party actors, the fundamental crisis dynamic whereby the third party works to secure de-escalation without seeking to alienate either conflicting party completely and the antagonists feel compelled not to defy it outright remains valid in each case.


2017 ◽  
Vol 42 ◽  
pp. 1196-1207 ◽  
Author(s):  
Chrysostomos E. Stoforos ◽  
Stavros Degiannakis ◽  
Theodosios B. Palaskas

Author(s):  
Barbara S. Tint ◽  
Viv McWaters ◽  
Raymond van Driel

Purpose – The purpose of this paper is to introduce applied improvisation (AI) as a tool for training humanitarian aid workers. AI incorporates principles and practices from improvisational theatre into facilitation and training. It is an excellent modality for training aid workers to deal with crisis and disaster scenarios where decision-making and collaboration under pressure are critical. Design/methodology/approach – This paper provides a theoretical base for understanding skills needed in disaster response and provides a case for innovative training that goes beyond the current standard. AI principles, activities and case examples are provided. Interviews with development experts who have participated in AI training are excerpted to reveal the impact and promise of this methodology. Findings – Different from typical training and games, which simulate potential crisis scenarios, AI works with participants in developing the skills necessary for success in disaster situations. The benefit is that workers are better prepared for the unexpected and unknown when they encounter it. Research limitations/implications – The current paper is based on author observation, experience and participant interviews. While AI is consistently transformative and successful, it would benefit from more rigorous and structured research to ground the findings more deeply in larger evidence based processes. Practical implications – The authors offer specific activities, resources for many others and practical application of this modality for training purposes. Social implications – Its application has tremendous benefits in training for specific skills, in creating greater cohesion and satisfaction in work units and breaking down culture and language barriers. Originality/value – This work is original in introducing these training methods to humanitarian aid contexts in general, and disaster preparedness and response in particular.


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