7 research outputs found
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