Efficient scheduling of sensor activity for information coverage in wireless sensor networks

In this paper, we are concerned with algorithms for scheduling the sensing activity of sensor nodes that are deployed to sense/measure point-targets in wireless sensor networks using information coverage. Defining a set of sensors which collectively can sense a target accurately as an information cover, we propose an algorithm to obtain Disjoint Set of Information Covers (DSIC), which achieves longer network life compared to the set of covers obtained using an Exhaustive-Greedy-Equalized Heuristic (EGEH) algorithm proposed recently in the literature. We also present a detailed complexity comparison between the DSIC and EGEH algorithms.

Nationwide-US newspaper coverage of handling water contamination : a community structure approach

Resumen: Empleando la teoría de la “estructura comunitaria”, un muestreo de diarios principales en 28 ciudades grandes en Estados Unidos examina la cobertura del tema “El manejo de contaminación de agua y acceso a agua potable”. Mediante el análisis de todos los artículos de más de 250 palabras publicados a través de diez años entre 01/01/2001 y 01/01/2011 (339 artículos), se compararon sistemáticamente características comunitarias y el “Vector Mediático” de Pollock (combinando en un valor dos medidas de contenido: la “prominencia” de un artículo en un periódico con la orientación o tono). Cobertura “favorable”, que apoya la mayor ayuda gubernamental para mejorar el abastecimiento de agua potable, fue vinculada con medidas de “los interesados”, por ejemplo, con el porcentaje de hispanos (r de Pearson = .349, p = .04). El análisis de las medidas y su regresión reveló dos medidas significativas asociadas con apoyo para manejo gubernamental por agua potable: porcentaje de hispanos (12.2% de la varianza), y con porcentaje de ciudadanos de 18-24 años, 16.7%. Inesperadamente, la cobertura de manejo gubernamental para mejorar las existencias de agua potable no fue vinculado ni con medidas de “vulnerabilidad” (pobreza, desempleo) ni con medidas de “estabilidad” (educación, ingreso).

AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients

Background Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network. Results This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.×, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage. Conclusion By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

Using extreme value theory to measure value-at-risk for daily electricity spot prices

The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Benchmarking of performance of Mexican states with effective coverage

Benchmarking of the performance of states, provinces, or districts in a decentralised health system is important for fostering of accountability, monitoring of progress, identification of determinants of success and failure, and creation of a culture of evidence. The Mexican Ministry of Health has, since 2001, used a benchmarking approach based on the World Health Organization (WHO) concept of effective coverage of an intervention, which is defined as the proportion of potential health gain that could be delivered by the health system to that which is actually delivered. Using data collection systems, including state representative examination surveys, vital registration, and hospital discharge registries, we have monitored the delivery of 14 interventions for 2005-06. Overall effective coverage ranges from 54.0% in Chiapas, a poor state, to 65.1% in the Federal District. Effective coverage for maternal and child health interventions is substantially higher than that for interventions that target other health problems. Effective coverage for the lowest wealth quintile is 52% compared with 61% for the highest quintile. Effective coverage is closely related to public-health spending per head across states; this relation is stronger for interventions that are not related to maternal and child health than those for maternal and child health. Considerable variation also exists in effective coverage at similar amounts of spending. We discuss the implications of these issues for the further development of the Mexican health-information system. Benchmarking of performance by measuring effective coverage encourages decision-makers to focus on quality service provision, not only service availability. The effective coverage calculation is an important device for health-system stewardship. In adopting this approach, other countries should select interventions to be measured on the basis of the criteria of affordability, effect on population health, effect on health inequalities, and capacity to measure the effects of the intervention. The national institutions undertaking this benchmarking must have the mandate, skills, resources, and independence to succeed.

The Responsiveness, Content Validity, and Convergent Validity of the Measure Yourself Concerns and Wellbeing (MYCaW) Patient-Reported Outcome Measure

Objective Measure Yourself Concerns and Wellbeing (MYCaW) is a patient-centred questionnaire that allows cancer patients to identify and quantify the severity of their ‘Concerns’ and Wellbeing, as opposed to using a pre-determined list. MYCaW administration is brief and aids in prioritising treatment approaches. Our goal was to assess the convergent validity and responsiveness of MYCaW scores over time, the generalisability of the existing qualitative coding framework in different complementary and integrative healthcare settings and content validity. Methods Baseline and 6-week follow-up data (n=82) from MYCaW and FACIT-SpEx questionnaires were collected for a service evaluation of the ‘Living Well With The Impact of Cancer’ course at Penny Brohn Cancer Care. MYCaW construct validity was determined using Spearman's Rank Correlation test, and responsiveness indices assessed score changes over time. The existing qualitative coding framework was reviewed using a new dataset (n=158) and coverage of concern categories compared to items of existing outcome measures. Results Good correlation between MYCaW and FACIT-SpEx score changes were achieved (r= -0.57, p≥0.01). MYCaW Profile and Concern scores were highly responsive to change: SRM=1.02 and 1.08; effect size=1.26 and 1.22. MYCaW change scores showed the anticipated gradient of change according to clinically relevant degrees of change. Categories including ‘Spirituality’, ‘weight change’ and ‘practical concerns’ were added to the coding framework to improve generalisability. Conclusions MYCaW scores were highly responsive to change, allowing personalized patient outcomes to be quantified; the qualitative coding framework is generalisable across different oncology settings and has broader coverage of patient-identified concerns compared with existing cancer-related patient-reported outcome measures.