A Secure Grid Medical Data Manager Interfaced to the gLite Middleware

The medical community is producing and manipulating a tremendous volume of digital data for which computerized archiving, processing and analysis is needed. Grid infrastructures are promising for dealing with challenges arising in computerized medicine but the manipulation of medical data on such infrastructures faces both the problem of interconnecting medical information systems to Grid middlewares and of preserving patients’ privacy in a wide and distributed multi-user system. These constraints are often limiting the use of Grids for manipulating sensitive medical data. This paper describes our design of a medical data management system taking advantage of the advanced gLite data management services, developed in the context of the EGEE project, to fulfill the stringent needs of the medical community. It ensures medical data protection through strict data access control, anonymization and encryption. The multi-level access control provides the flexibility needed for implementing complex medical use-cases. Data anonymization prevents the exposure of most sensitive data to unauthorized users, and data encryption guarantees data protection even when it is stored at remote sites. Moreover, the developed prototype provides a Grid storage resource manager (SRM) interface to standard medical DICOM servers thereby enabling transparent access to medical data without interfering with medical practice.     

Simple multichannel system for the measurement of the net water flux across biological tissues

This paper describes the development of a simple system for measurement of net water movement through biological membrane barriers. The system is based on the detection of a water meniscus inside a polyethylene tube, which reflects the water movement inside one hemichamber of a modified Ussing chamber containing a membrane barrier. The detection device consists of a commercial computer-controlled flat bed scanner and specifically developed software. This system allows one to perform a relatively high number of individual experiments per physical unit. It is a flexible and affordable device, which allows comparatively more information per unit to be obtained than previously described methods.     

A wavelet-VQ system for real-time video compression

This paper presents a scheme and its Field Programmable Gate Array (FPGA) implementation for a system based on combining the bi-dimensional discrete wavelet transformation (2D-DWT) and vector quantization (VQ) for image compression. The 2D-DWT works in a non-separable fashion using a parallel filter structure with distributed control to compute two resolution levels. The wavelet coefficients of the higher frequency sub-bands are vector quantized using multi-resolution codebook and those of the lower frequency sub-band at level two are scalar quantized and entropy encoded. VQ is carried out by self organizing feature map (SOFM) neural nets working at the recall phase. Codebooks are quickly generated off-line using the same nets functioning at the training phase. The complete system, including the 2D-DWT, the multi-resolution codebook VQ, and the statistical encoder, was implemented on a Xilinx Virtex 4 FPGA and is capable of performing real-time compression for digital video when dealing with grayscale 512 × 512 pixels images. It offers high compression quality (PSNR values around 35 dB) and acceptable compression rate values (0.62 bpp).

Decision support system to divide a large network into suitable District Metered Areas

This paper presents a new approach to divide large Water Distribution Networks (WDN) into suitable District Metered Areas (DMAs). It uses a hydraulic simulator and two operational models to identify the optimal number of DMAs, their entry points and boundary valves, and the network reinforcement/replacement needs throughout the project plan. The first model divides the WDN into suitable DMAs based on graph theory concepts and some user-defined criteria. The second model uses a simulated annealing algorithm to identify the optimal number and location of entry points and boundary valves, and the pipes reinforcement/replacement, necessary to meet the velocity and pressure requirements. The objective function is the difference between the economic benefits in terms of water loss reduction (arising from the average pressure reduction) and the cost of implementing the DMAs. To illustrate the proposed methodology, the results from a hypothetical case study are presented and discussed.     

Cell formation in group technology using constraint programming and Boolean satisfiability

Cell formation consists in organizing a plant as a set of cells, each of them containing machines that process similar types or families of parts. The idea is to minimize the part flow among cells in order to reduce costs and increase productivity. The literature presents different approaches devoted to solve this problem, which are mainly based on mathematical programming and on evolutionary computing. Mathematical programming can guarantee a global optimal solution, however at a higher computational cost than an evolutionary algorithm, which can assure a good enough optimum in a fixed amount of time. In this paper, we model and solve this problem by using state-of-the-art constraint programming (CP) techniques and Boolean satisfiability (SAT) technology. We present different experimental results that demonstrate the efficiency of the proposed optimization models. Indeed, CP and SAT implementations are able to reach the global optima in all tested instances and in competitive runtime.     

Satellite-Based Energy Balance to Assess Within-Population Variance of Crop Coefficient Curves

Quantifying evapotranspiration (ET) from agricultural fields is important for field water management, water resources planning, and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage. Recent development of satellite remote sensing ET models has enabled us to estimate ET and Kc for large populations of fields. This study evaluated the distribution of Kc over space and time for a large number of individual fields by crop type using ET maps created by a satellite based energy balance (EB) model. Variation of Kc curves was found to be substantially larger than that for the normalized difference vegetation index because of the impacts of random wetting events on Kc, especially during initial and development growth stages. Two traditional Kc curves that are widely used in Idaho for crop management and water rights regulation were compared against the satellite-derived Kc curves. Simple adjustment of the traditional Kc curves by shifting dates for emergence, effective full cover, and termination enabled the traditional curves to better fit Kc curves as determined by the EB model. Applicability of the presented techniques in humid regions having higher chances of cloudy dates was discussed.     

Relative hazard rate estimation for right censored and left truncated data

In medical research differences among treatment groups are a common focus of study. The concept of relative hazard rate is a tool for comparing two groups in terms of their difference in risk rates. A kernel estimator is proposed in the case where both samples are subject to left truncation and right censoring and an iid representation is obtained in this setup. The asymptotic distribution and the asymptotic mean squared error of the estimator are obtained. An application to the famous Channing House data set illustrates the theory. Research supported in part by MCyT Grants PB98-0182-C02-01 and BFM2002-00265 (ERDF support included) and XUGA Grant PGIDT00PX110501 PN for the first author and by the Ministry of the Flemish Community (Project BIL00/28, International Scientific and Technological Cooperation) and by the IAP research network nr P5/24 of the Belgian State (Federal Office for Scientific, Technical and Cultural Affairs) for the last two authors.     

Benchmarking System for Evaluating Management Practices in the Construction Industry

This paper presents the results obtained for the initial application of a management evaluation system whose objective is to provide a continuous improvement tool for construction companies through benchmarking management practices. The outlined system seeks to support a benchmarking system that has been recently established in the Chilean construction industry by incorporating qualitative management aspects in addition to performance indicators. Different analyses were made to determine trends in the sector and to establish correlations between qualitative aspects coming from surveys and quantitative aspects coming from performance indicators. Thirteen construction companies participated in the initial application of the benchmarking system. A correlation analysis found that safety performance was strongly related to companies having superior planning and control, quality management, cost control, and subcontractor management policies. A factor analysis found that central office priorities focus on strategic management policies having longer-term competitive impact, while site management emphasizes tactical management dimensions having short-term impact. There is scope to elevate the profile of continuous improvement initiatives to strategic significance at the central office level.