A Human-Centric Approach to Data Fusion in Post-Disaster Managment: The Development of a Fuzzy Set Theory Based Model

It is critical to provide an efficient and accurate information system in the post-disaster phase for individuals\u27 in order to access and obtain the necessary resources in a timely manner; but current map based post-disaster management systems provide all emergency resource lists without filtering them which usually leads to high levels of energy consumed in calculation. Also an effective post-disaster management system (PDMS) will result in distribution of all emergency resources such as, hospital, storage and transportation much more reasonably and be more beneficial to the individuals in the post disaster period. In this Dissertation, firstly, semi-supervised learning (SSL) based graph systems was constructed for PDMS. A Graph-based PDMS\u27 resource map was converted to a directed graph that presented by adjacent matrix and then the decision information will be conducted from the PDMS by two ways, one is clustering operation, and another is graph-based semi-supervised optimization process. In this study, PDMS was applied for emergency resource distribution in post-disaster (responses phase), a path optimization algorithm based ant colony optimization (ACO) was used for minimizing the cost in post-disaster, simulation results show the effectiveness of the proposed methodology. This analysis was done by comparing it with clustering based algorithms under improvement ACO of tour improvement algorithm (TIA) and Min-Max Ant System (MMAS) and the results also show that the SSL based graph will be more effective for calculating the optimization path in PDMS. This research improved the map by combining the disaster map with the initial GIS based map which located the target area considering the influence of disaster. First, all initial map and disaster map will be under Gaussian transformation while we acquired the histogram of all map pictures. And then all pictures will be under discrete wavelet transform (DWT), a Gaussian fusion algorithm was applied in the DWT pictures. Second, inverse DWT (iDWT) was applied to generate a new map for a post-disaster management system. Finally, simulation works were proposed and the results showed the effectiveness of the proposed method by comparing it to other fusion algorithms, such as mean-mean fusion and max-UD fusion through the evaluation indices including entropy, spatial frequency (SF) and image quality index (IQI). Fuzzy set model were proposed to improve the presentation capacity of nodes in this GIS based PDMS

Disaster management and its economic implications

Das Ziel dieser Arbeit ist es, aktuelle Forschungsschwerpunkte im Bereich des Katastrophenmanagements in der Operational Research Literatur aufzuzeigen. Katastrophenmanagement umfasst in diesem Zusammenhang einerseits Naturkatastrophen wie geophysikalische und hydro-meteorologische Katastrophen, technologische Katastrophen wie industrielle Unfälle, Transportunfälle und sonstige Unfälle, und andererseits die verschiedenen Formen des Terrorismus, allgemeinen Terrorismus sowie Bioterrorismus. Da die Anzahl und das Ausmaß von Katastrophen immer weiter zunehmen ist auch eine immer größere Notwendigkeit für die Entwicklung, den Einsatz und die wirtschaftliche Beurteilung der jeweiligen Strategien gegeben. Der erste Teil dieser Arbeit gibt einen Überblick über die Literatur im Bereich des Katastrophenmanagements und umfasst Simulation, Katastrophenmanagement in Krankenhäusern und die Rolle von Versicherungen im Katastrophenmanagementprozess. Im zweiten Teil wird eine Taxonomie entwickelt, deren Kategorien auf den Modellen und Ergebnissen der Literatur beruhen. Einerseits werden allgemeine Modelleigenschaften wie die Ebene im Katastrophenmanagementprozess, der Modelltyp und die Anwendungsgebiete der Modelle untersucht. Andererseits stellen die Art der Intervention und die Anwendbarkeit für die unterschiedlichen Katastrophenklassen weitere Kategorien der Taxonomie dar. Es wurden 90 Artikel, die beispielhaft für die Forschungsrichtungen im Bereich des Katastrophenmanagements der letzten 25 Jahre stehen, ausgewählt, und entsprechend den jeweiligen Kategorien der Taxonomie zugeordnet. Das Hauptaugenmerk der Taxonomie liegt auf der wirtschaftlichen Analyse, die wirksamkeitsbezogene, ressourcenbezogene und kostenbezogene Parameter umfasst. Es wird gezeigt ob und welche wirtschaftliche Analyse wie beispielsweise die Kosten-Nutzwert- Analyse, die Kosten-Wirksamkeits-Analyse und die Kosten-Nutzen-Analyse angewendet wird um die in den Artikeln beschriebenen Interventionen zu evaluieren. Es wird gezeigt, dass erhebliche Verbesserungen für die verschiedenen Katastrophentypen und in den verschiedenen Situationen erzielt werden können. Eingeschränkte Datenverfügbarkeit schränkt in vielen Fällen die Einsetzbarkeit der Modelle in realen Situationen ein. Im Allgemeinen ist erkennbar, dass Kooperation und Koordination zwischen den beteiligten Einheiten ausschlaggebend für den zeitgerechten und effizienten Einsatz der knappen Ressourcen sind. Oftmals erzielt der gemeinsame Einsatz mehrerer Maßnahme ein deutlich besseres Ergebnis als der Einsatz von lediglich einem einzigen Instrument. Die Taxonomie unterstreicht dass trotz der großen Fülle an Literatur im Bereich des Katastrophenmanagements nur wenige Autoren auf die Kosten-Nutzwert-Analyse, die Kosten-Wirksamkeits-Analyse und die Kosten-Nutzen-Analyse als Hilfsmittel zur wirtschaftlichen Analyse zurückgreifen. In Zukunft, um Interventionen erfolgreich evaluieren zu können oder die beste aus mehreren Interventionen bestimmen zu können wird es immer wichtiger werden, diese Art von wirtschaftlichen Analysen anzuwenden.This thesis intends to demonstrate current research directions in the field of disaster management in the Operational Research literature. Disaster management in this context comprises the management of natural, such as geophysical and hydro-meteorological, and technological disasters, such as industrial accidents, transportation accidents, and miscellaneous accidents, as well as the management of the different terrorism forms, general terrorism and bioterrorism. As the occurrence of disasters is getting more and more frequent and the accumulated loss of these events is getting higher and higher, there is a strong need for the development, implication and economic evaluation of strategies to counter these disasters. In the first part of the thesis, a general overview of the literature is given, including a focus on simulation, disaster management in hospitals, and the role of insurances in the disaster management process. The second part encompasses the taxonomy which focuses on models and outcomes presented in the literature. As a result of the review of the literature, appropriate categories for the disaster management taxonomy are derived. On the one hand, an overview of general model features, i.e., the level of disaster management, model type and methods of application is given. On the other hand, the type of intervention used and the practicability for different disaster types are discussed. 90 papers, illustrative main examples of the research directions of the last 25 years, were selected for deeper investigation and classified according to the main criteria analyzed in the articles. The main focus of the taxonomy lies on the economic analysis, which encompasses effectiveness-related, resource-related, and cost-related parameters and shows the type of economic analysis used in the literature. We analyze whether economic analysis, i.e., costutility, cost-effectiveness, and cost-benefit are used to investigate different interventions and what type of analysis has been chosen by the authors. Policy implications and results show that considerable improvements can be achieved for different disastrous events and in different situations. Limited data availability constrains the outcomes of the models and their applicability to real-world situations. In general, cooperation and coordination of the entities involved are crucial to guarantee timely and efficient assignment of scarce resources. Furthermore, different authors confirm that a combination of various measures often achieves a better outcome than if tools are used autonomously. The taxonomy has underlined that although there exists a vast disaster management literature dealing with various problems related to mitigation, preparedness, response and recovery from disasters, there are only a few authors evaluating the actions taken through economic analyses such cost-utility, cost-effectiveness, or cost-benefit analysis. In the future, to be able to evaluate interventions, or to figure out the most effective intervention among several interventions, it is crucial to stronger rely on the abovementioned economic analyses

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

Ετοιμότητα του ιατρονοσηλευτικού προσωπικού για την αντιμετώπιση μαζικών καταστροφών

Εισαγωγή: Μαζική καταστροφή, όσον αφορά στον τομέα υγείας, θεωρείται η απότομη ή βαθμιαία έκπτωση στη συνολική κατάσταση υγείας μιας κοινότητας η οποία είναι αδύνατο να αντιμετωπισθεί επαρκώς χωρίς εξωτερική βοήθεια. Σκοπός: Η διερεύνηση της ετοιμότητας του ιατρονοσηλευτικού προσωπικού για την αντιμετώπιση μαζικών καταστροφών. Υλικό και Μέθοδος: Το δείγμα της μελέτης αποτέλεσαν 364 επαγγελματίες υγείας. Η στατιστική ανάλυση έγινε με το στατιστικό πακέτο SPSS 17 και την εφαρμογή της δοκιμασίας Χ2. Αποτελέσματα: Από την περιγραφική ανάλυση, βρέθηκε ότι το μεγαλύτερο ποσοστό του ιατρονοσηλευτικού προσωπικού (61%) αντιλαμβάνονταν τον εαυτό του ως απροετοίμαστο για την αντιμετώπιση καταστροφών. Ποσοστό 64,6% ανέφερε ότι η πιο άμεση ενέργειά του σε ενδεχόμενο μαζικής καταστροφής στον χώρο εργασίας του θα ήταν η τήρηση του σχεδίου έκτακτης ανάγκης, ενώ ποσοστό 55,7% δεν γνώριζε αν υπάρχει σχέδιο έκτακτης ανάγκης στον χώρο εργασίας του. Από την στατιστική ανάλυση των δεδομένων, βρέθηκε ότι πιο συχνά ως προετοιμασμένο για την αντιμετώπιση καταστροφών αντιλαμβάνονταν τον εαυτό τους οι ασκούντες διοικητικό έργο νοσηλευτές (p=0,002) και οι έχοντες μεταπτυχιακές σπουδές (p=0,047). Συμπεράσματα: Ο παράγοντας εκπαίδευση επηρεάζει στον μεγαλύτερο βαθμό τις γνώσεις για τις μαζικές καταστροφές και την ετοιμότητα αντιμετώπισής τους. Ως εκ τούτου, είναι αναγκαίο οι επαγγελματίες υγείας σε προπτυχιακό επίπεδο να παρακολουθήσουν περισσότερα σχετικά μαθήματα.Background: Disasters, as regards the health sector, are considered a sudden or gradual disease of an entire community, which is impossible to confront adequately without external assistance. Aim: The aim of the study was to explore the disaster preparedness among medical and nursing personnel. Methods: The statistical sample of this study consisted of 364 health care professionals. Statistical analysis was produced using SPSS 17 and the performance of the chi-square test. Results: By the descriptive analysis it was detected that the biggest percentage of the medical and nursing personnel (61%) considered themselves not adequately prepared for disasters. Of the study participants, 64,6% stated that if a disaster happen in their workplace they would follow the hospital disaster plan to manage the situation, while 55,7% they did not know if there is a disaster plan in their workplace. By the statistical analysis it was detected that the administrative nurses perceived themselves more frequently as prepared for disaster management (p=0,002) as well those who have done postgraduate studies (p=0,047). Conclusions: Education affects positively the knowledge on disasters as well the health-related disaster preparedness, therefore, it is necessary for the health care professionals, when in an undergraduate level, to attend more relevant courses

Applied Methuerstic computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC