Information and communication technology for disaster risk management in the Caribbean: subregional solutions to the challenge of limited human resource capacity

This document was adapted from a paper originally presented to the 8th Annual Caribbean Conference of Comprehensive Disaster Management, held in Montego Bay, Jamaica in December, 2013. It summarizes several activities that ECLAC has undertaken to assess the current state of information and communications technology (ICT) in the field of disaster risk management (DRM) as practiced in the Caribbean. These activities included an in-depth study that encompassed a survey of disaster management organizations in the region, an Expert Group Meeting attended by the heads of several national disaster offices, and a training workshop for professionals working in DRM in the Caribbean. One of the notable conclusions of ECLAC’s investigation on this topic is that the lack of human capacity is the single largest constraint that is faced in the implementation of ICT projects for DRM in the Caribbean. In considering strategies to address the challenge of limited human capacity at a regional level, two separate issues are recognized – the need to increase the ICT capabilities of disaster management professionals, and the need to make ICT specialists available to disaster management organizations to advise and assist in the implementation of technology-focused projects. To that end, two models are proposed to engage with this issue at a regional level. The first entails the establishment of a network of ICT trainers in the Caribbean to help DRM staff develop a strategic understanding of how technology can be used to further their organizational goals. The second is the development of “Centres of Excellence” for ICT in the Caribbean, which would enable the deployment of specialized ICT expertise to national disaster management offices on a project-by-project basis.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

Advances in Teaching and Learning 2005 Webcast - Introductions and Expert Panel

Expert Panel: Documenting Teaching Scholarship for Promotion and Tenure Lemuel Moye, School of Public Health Miguel daCunha, School of Nursing William Tate, Dental School Katherine Loveland, Medical School

Early detection of lung cancer: a statement from an expert panel of the Swiss university hospitals on lung cancer screening.

The discussion about setting up a program for lung cancer screening was launched with the publication of the results of the National Lung Screening Trial, which suggested reduced mortality in high-risk subjects undergoing CT screening. However, important questions about the benefit-harm balance and the details of a screening program and its cost-effectiveness remain unanswered. A panel of specialists in chest radiology, respiratory medicine, epidemiology, and thoracic surgery representing all Swiss university hospitals prepared this joint statement following several meetings. The panel argues that premature and uncontrolled introduction of a lung cancer screening program may cause substantial harm that may remain undetected without rigorous quality control. This position paper focuses on the requirements of running such a program with the objective of harmonizing efforts across the involved specialties and institutions and defining quality standards. The underlying statement includes information on current evidence for a reduction in mortality with lung cancer screening and the potential epidemiologic implications of such a program in Switzerland. Furthermore, requirements for lung cancer screening centers are defined, and recommendations for both the CT technique and the algorithm for lung nodule assessment are provided. In addition, related issues such as patient management, registry, and funding are addressed. Based on the current state of the knowledge, the panel concludes that lung cancer screening in Switzerland should be undertaken exclusively within a national observational study in order to provide answers to several critical questions before considering broad population-based screening for lung cancer.

Identifying observable criteria defining a critical situation involving football fans: an expert focus group study

Critical situations (CSs) involving football fans is a well-researched phenomenon with most studies examining factors leading to an escalation of violence (e.g. Braun & Vliegenthart, 2008). However, research so far has fallen short of analysing CSs that do not escalate (e.g. Hylander & Guvå, 2010) as well as establishing observable criteria that constitute such CSs. Granström et al. (2009), for instance, put forward a definition of a CS describing such situations as characterised by a discrepancy between peace and war-making behaviours between police and demonstrators. Still, this definition remains vague and does not provide concrete, defining criteria that can be identified on site. The present study looks beyond fans’ violent acts per se and focuses on these situations with a potentially – but not necessarily - violent outcome. The aim of this preliminary study is to identify observable criteria defining such a CS involving football fans. This focus group comprised of five experts working with football fans in the German-speaking area of Switzerland who discussed observable characteristics of a CS. Inductive content analysis led to the identification of specific criteria such as, “arrest of a fan”, “insufficient distance (<30m) between fans and police” and “fans mask themselves”. These criteria were then assigned to four phases of a CS highlighting the dynamic aspect of this phenomenon: Antecedents, Causes, Reactions, Consequence. Specifically, Causes, Reactions and Consequences are observable on site, while Antecedents include relevant, background information directly influencing a CS. This study puts forward a working definition of a CS that can facilitate the assessment of actual situations in the football context as well as for further research on fan violence prevention and control. These results also highlight similarities with studies investigating fan violence in other European countries while acknowledging unique characteristics of the Swiss German fan culture.

Bird species recorded in an untrained observer survey (UOS) and an expert observer survey (EOS) in 2011 in SE Peru

To evaluate the potential of community-based bird surveys in the tropics, we compared the species richness and abundances of bird functional groups that would be detected by a basic untrained observer (untrained observer survey, UOS) to a comprehensive bird species list compiled by a professional bird guide, in a coffee agroforestry landscape in the Peruvian East Andean foothills and compared functional signatures to global functional signatures of tropical bird assemblages. The submitted data comprises the transect counts of the UOS, the comprehensive bird list, ecological data of the recorded birds and information regarding the conservation status of the recorded birds from the IUCN Red List.

Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd–EOB–DTPA-enhanced MRI

Accurate detection of liver lesions is of great importance in hepatic surgery planning. Recent studies have shown that the detection rate of liver lesions is significantly higher in gadoxetic acid-enhanced magnetic resonance imaging (Gd–EOB–DTPA-enhanced MRI) than in contrast-enhanced portal-phase computed tomography (CT); however, the latter remains essential because of its high specificity, good performance in estimating liver volumes and better vessel visibility. To characterize liver lesions using both the above image modalities, we propose a multimodal nonrigid registration framework using organ-focused mutual information (OF-MI). This proposal tries to improve mutual information (MI) based registration by adding spatial information, benefiting from the availability of expert liver segmentation in clinical protocols. The incorporation of an additional information channel containing liver segmentation information was studied. A dataset of real clinical images and simulated images was used in the validation process. A Gd–EOB–DTPA-enhanced MRI simulation framework is presented. To evaluate results, warping index errors were calculated for the simulated data, and landmark-based and surface-based errors were calculated for the real data. An improvement of the registration accuracy for OF-MI as compared with MI was found for both simulated and real datasets. Statistical significance of the difference was tested and confirmed in the simulated dataset (p < 0.01).

On the dynamic adaptation of language models based on dialogue information

We present an approach to adapt dynamically the language models (LMs) used by a speech recognizer that is part of a spoken dialogue system. We have developed a grammar generation strategy that automatically adapts the LMs using the semantic information that the user provides (represented as dialogue concepts), together with the information regarding the intentions of the speaker (inferred by the dialogue manager, and represented as dialogue goals). We carry out the adaptation as a linear interpolation between a background LM, and one or more of the LMs associated to the dialogue elements (concepts or goals) addressed by the user. The interpolation weights between those models are automatically estimated on each dialogue turn, using measures such as the posterior probabilities of concepts and goals, estimated as part of the inference procedure to determine the actions to be carried out. We propose two approaches to handle the LMs related to concepts and goals. Whereas in the first one we estimate a LM for each one of them, in the second one we apply several clustering strategies to group together those elements that share some common properties, and estimate a LM for each cluster. Our evaluation shows how the system can estimate a dynamic model adapted to each dialogue turn, which helps to improve the performance of the speech recognition (up to a 14.82% of relative improvement), which leads to an improvement in both the language understanding and the dialogue management tasks.

Low-Cost Radar-Based Target Identification Prototype using an Expert System

Smart and green cities are hot topics in current research because people are becoming more conscious about their impact on the environment and the sustainability of their cities as the population increases. Many researchers are searching for mechanisms that can reduce power consumption and pollution in the city environment. This paper addresses the issue of public lighting and how it can be improved in order to achieve a more energy efficient city. This work is focused on making the process of turning the streetlights on and off more intelligent so that they consume less power and cause less light pollution. The proposed solution is comprised of a radar device and an expert system implemented on a low-cost platform based on a DSP. By analyzing the radar echo in both the frequency and time domains, the system is able to detect and identify objects moving in front of it. This information is used to decide whether or not the streetlight should be turned on. Experimental results show that the proposed system can provide hit rates over 80%, promising a good performance. In addition, the proposed solution could be useful in kind of other applications such as intelligent security and surveillance systems and home automation.

Health care, information needs, and outreach: reaching Ohio's rural citizens

As a rural state, Ohio has a vital interest in addressing rural health and information needs. NetWellness is a Web-based consumer health information service that focuses on the needs of the residents of Ohio. Health sciences faculty from the state's three Carnegie Research I universities—University of Cincinnati, Case Western Reserve University, and The Ohio State University—create and evaluate content and provide Ask an Expert service to all visitors. Through partnerships at the state and local levels, involving public, private, commercial, and noncommercial organizations, NetWellness has grown from a regional demonstration project in 1995 to a key statewide service. Collaboration with public libraries, complemented by alliances with kindergarten through twelfth grade agencies, makes NetWellness Ohio's essential health information resource.

Application of Text Summarization techniques to the Geographical Information Retrieval task

Automatic Text Summarization has been shown to be useful for Natural Language Processing tasks such as Question Answering or Text Classification and other related fields of computer science such as Information Retrieval. Since Geographical Information Retrieval can be considered as an extension of the Information Retrieval field, the generation of summaries could be integrated into these systems by acting as an intermediate stage, with the purpose of reducing the document length. In this manner, the access time for information searching will be improved, while at the same time relevant documents will be also retrieved. Therefore, in this paper we propose the generation of two types of summaries (generic and geographical) applying several compression rates in order to evaluate their effectiveness in the Geographical Information Retrieval task. The evaluation has been carried out using GeoCLEF as evaluation framework and following an Information Retrieval perspective without considering the geo-reranking phase commonly used in these systems. Although single-document summarization has not performed well in general, the slight improvements obtained for some types of the proposed summaries, particularly for those based on geographical information, made us believe that the integration of Text Summarization with Geographical Information Retrieval may be beneficial, and consequently, the experimental set-up developed in this research work serves as a basis for further investigations in this field.