Optical precursors and Beer's law violations; non-exponential propagation losses in water

We develop a model for exponential decay of broadband pulses, and examine its implications for experiments on optical precursors. One of the signature features of Brillouin precursors is attenuation with a less rapid decay than that predicted by Beer's Law. Depending on the pulse parameters and the model that is adopted for the dielectric properties of the medium, the limiting z-dependence of the loss has been described as z(-1/2), z(-1/3), exponential, or, in more detailed descriptions, some combination of the above. Experimental results in the search for precursors are examined in light of the different models, and a stringent test for sub-exponential decay is applied to data on propagation of 500 femtosecond pulses through 1-5 meters of water. (C) 2005 Optical Society of America.

Modeling the economic losses from pressure ulcers among hospitalized patients in Australia

The objective of this study was to predict the number of cases of pressure ulcer, the bed days lost, and the economic value of these losses at Australian public hospitals. All adults (>= 18 years of age) with a minimum stay of 1 night and discharged from selected clinical units from all Australian public hospitals in 2001-02 were included in the study. The main outcome measures were the number of cases of pressure ulcer, bed days lost to pressure ulcer, and economic value of these losses. We predict a median of 95,695 cases of pressure ulcer with a median of 398,432 bed days lost, incurring median opportunity costs of AU$285 M. The number of cases, and so costs, were greatest in New South Wales and lowest in Australian Capitol Territory. We conclude that pressure ulcers represent a serious clinical and economic problem for a resource-constrained public hospital system. The most cost-effective, risk-reducing interventions should be pursued up to a point where the marginal benefit of prevention is equalized with marginal cost. By preventing pressure ulcers, public hospitals can improve efficiency and the quality of the patient's experience and health outcome.

Examining TCP parallelization related methods for various packet losses

The diversity of the networks (wired/wireless) prefers a TCP solution robust across a wide range of networks rather than fine-tuned for a particular one at the cost of another. TCP parallelization uses multiple virtual TCP connections to transfer data for an application process and opens a way to improve TCP performance across a wide range of environments - high bandwidth-delay product (BDP), wireless as well as conventional networks. In particular, it can significantly benefit the emerging high-speed wireless networks. Despite its potential to work well over a wide range of networks, it is not fully understood how TCP parallelization performs when experiencing various packet losses in the heterogeneous environment. This paper examines the current TCP parallelization related methods under various packet losses and shows how to improve the performance of TCP parallelization.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.