A Semantic Safety Check System for Emergency Management

There has been an exponential growth and availability of both structured and unstructured data that can be leveraged to provide better emergency management in case of natural disasters and humanitarian crises. This paper is an extension of a semantics-based web application for safety check, which uses of semantic web technologies to extract different kinds of relevant data about a natural disaster and alerts its users. The goal of this work is to design and develop a knowledge intensive application that identifies those people that may have been affected due to natural disasters or man-made disasters at any geographical location and notify them with safety instructions. This involves extraction of data from various sources for emergency alerts, weather alerts, and contacts data. The extracted data is integrated using a semantic data model and transformed into semantic data. Semantic reasoning is done through rules and queries. This system is built using front-end web development technologies and at the back-end using semantic web technologies such as RDF, OWL, SPARQL, Apache Jena, TDB, and Apache Fuseki server. We present the details of the overall approach, process of data collection and transformation and the system built. This extended version includes a detailed discussion of the semantic reasoning module, research challenges in building this software system, related work in this area, and future research directions including the incorporation of geospatial components and standards

An emergency dispatch model considering the urgency of the requirement for reliefs in different disaster areas

Purpose: Frequent sudden-onset disasters which have threatened the survival of human and the development of society force the public to pay an increasing attention to emergency management. A challenging task in the process of emergency management is emergency dispatch of reliefs. An emergency dispatch model considering the urgency of the requirement for reliefs in different disaster areas is proposed in this paper to dispatch reliefs reasonably and reduce the effect of sudden-onset disasters. Design/methodology/approach: Firstly, quantitative assessment on the urgency of the requirement for reliefs in different disaster areas is done by an evaluation method based on Fuzzy Comprehensive Evaluation and improved Evidence Reasoning which is proposed in this paper. And then based the quantitative results, an emergency dispatch model aiming to minimize the response time, the distribution cost and the unsatisfied rate of the requirement for reliefs is proposed, which reflects the requests of disaster areas under emergency, including the urgency of requirement, the economy of distribution and the equity of allocation. Finally, the Genetic Algorithm is improved based on the adaptive crossover and mutation probability function to solve the emergency dispatch model. Findings: A case that the Y hydraulic power enterprise carries on emergency dispatch of reliefs under continuous sudden-onset heavy rain is given to illustrate the availability of the emergency dispatch model proposed in this paper. The results show that the emergency dispatch model meets the distribution priority requirement of disaster area with the higher urgency, so that reliefs are supplied more timely. Research limitations/implications: The emergency dispatch model faced to large scale sudden-onset disasters is complex. The quantity of reliefs that disaster area requires and the running time of vehicles are viewed as available information, and the problem that how to obtain the information is not considered. Practical implications: The emergency dispatch model considering the urgency of the requirement for reliefs in different disaster areas is applicable to a realistic emergency dispatch of reliefs under sudden-onset disasters and the research results is the foundation of further research on the problem of emergency management. Originality/value: This paper proposes emergency dispatch model considering the urgency of the requirement for reliefs in different disaster areas which can meet the realistic requirement that the disaster area with the higher urgency has an priority to obtain the reliefs and make reliefs be distributed timely.Peer Reviewe

Alternative sweetener from curculigo fruits

This study gives an overview on the advantages of Curculigo Latifolia as an alternative sweetener and a health product. The purpose of this research is to provide another option to the people who suffer from diabetes. In this research, Curculigo Latifolia was chosen, due to its unique properties and widely known species in Malaysia. In order to obtain the sweet protein from the fruit, it must go through a couple of procedures. First we harvested the fruits from the Curculigo trees that grow wildly in the garden. Next, the Curculigo fruits were dried in the oven at 50 0C for 3 days. Finally, the dried fruits were blended in order to get a fine powder. Curculin is a sweet protein with a taste-modifying activity of converting sourness to sweetness. The curculin content from the sample shown are directly proportional to the mass of the Curculigo fine powder. While the FTIR result shows that the sample spectrum at peak 1634 cm–1 contains secondary amines. At peak 3307 cm–1 contains alkynes

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

Semantic reasoning for intelligent emergency response applications

Emergency response applications require the processing of large amounts of data, generated by a diverse set of sensors and devices, in order to provide for an accurate and concise view of the situation at hand. The adoption of semantic technologies allows for the definition of a formal domain model and intelligent data processing and reasoning on this model based on generated device and sensor measurements. This paper presents a novel approach to emergency response applications, such as fire fighting, integrating a formal semantic domain model into an event-based decision support system, which supports reasoning on this model. The developed model consists of several generic ontologies describing concepts and properties which can be applied to diverse context-aware applications. These are extended with emergency response specific ontologies. Additionally, inference on the model performed by a reasoning engine is dynamically synchronized with the rest of the architectural components. This allows to automatically trigger events based on predefined conditions. The proposed ontology and developed reasoning methodology is validated on two scenarios, i.e. (i) the construction of an emergency response incident and corresponding scenario and (ii) monitoring of the state of a fire fighter during an emergency response

Towards Knowledge in the Cloud

Knowledge in the form of semantic data is becoming more and more ubiquitous, and the need for scalable, dynamic systems to support collaborative work with such distributed, heterogeneous knowledge arises. We extend the “data in the cloud” approach that is emerging today to “knowledge in the cloud”, with support for handling semantic information, organizing and finding it efficiently and providing reasoning and quality support. Both the life sciences and emergency response fields are identified as strong potential beneficiaries of having ”knowledge in the cloud”

Deliberate clinical inertia: Using meta-cognition to improve decision-making

Deliberate clinical inertia is the art of doing nothing as a positive response. To be able to apply this concept, individual clinicians need to specifically focus on their clinical decision-making. The skill of solving problems and making optimal clinical decisions requires more attention in medical training and should play a more prominent part of the medical curriculum. This paper provides suggestions on how this may be achieved. Strategies to mitigate common biases are outlined, with an emphasis on reversing a 'more is better' culture towards more temperate, critical thinking. To incorporate such an approach in medical curricula and in clinical practice, institutional endorsement and support is required

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio