A refutation of false statements in propaganda for compulsory health insurance,

Mode of access: Internet.

Report of the Health insurance commission of Pennsylvania.

Mode of access: Internet.

Health insurance coverage : who had a lapse between 1991 and 1993?

Mode of access: Internet.

Health insurance coverage : who had a lapse between 1990 and 1992?

Mode of access: Internet.

Health insurance coverage, 1993.

Mode of access: Internet.

AIDS and health insurance : an OTA survey /

Mode of access: Internet.

Private health insurance to supplement medicare /

Includes bibliographical references.

Background information concerning the Emergency health insurance extension act of 1975 : background information /

At head of title: 94th Congress, 1st session. Committee print.

Fuzzy logic in web data mining for website assessment

This paper proposes a novel application of fuzzy logic to web data mining for two basic problems of a website: popularity and satisfaction. Popularity means that people will visit the website while satisfaction refers to the usefulness of the site. We will illustrate that the popularity of a website is a fuzzy logic problem. It is an important characteristic of a website in order to survive in Internet commerce. The satisfaction of a website is also a fuzzy logic problem that represents the degree of success in the application of information technology to the business. We propose a framework of fuzzy logic for the representation of these two problems based on web data mining techniques to fuzzify the attributes of a website.

Market failure in long-term private health insurance markets: a proposed solution

Recently, private health insurance rates have declined in many countries. In places requiring community rating in their health insurance premiums, a major cause is age-based adverse selection. However, even in countries without community rating, a de facto type of partial community rating tends to occur. In this note, a modified version of Pauly et al.'s guaranteed renewability model, which addresses the problem of age-based adverse selection (Pauly et al., 1995) is presented. Their model is extended from three to 35 periods. Also, probabilities are allowed to increase by age for low-risk types using actual age-based probabilities. This extension of their work shows that private health insurance contracts available stray far from optimal contracts that deal with age-based adverse selection. This suggests that government actions to affect private insurance options are warranted.

Electricity market price spike forecast with data mining techniques

Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

Lifetime Subsidies in Australian Private Health Insurance Markets with Community Rating

This paper considers the problem of inducing low-risk individuals of all ages to buy private health insurance in Australia. Our proposed subsidy scheme improves upon the age-based penalty scheme under the current "Australian Lifetime Cover" (LTC) scheme. We generate an alternative subsidy profile that obviates adverse selection in private health insurance markets with mandated, age-based, community rating. Our proposal is novel in that we generate subsidies that are both risk- and age-specific, based upon actual risk probabilities. The approach we take may prove useful in other jurisdictions where the extant law mandates community rating in private health insurance markets. Furthermore, our approach is useful in jurisdictions that seek to maintain private insurance to complement existing universal public systems.

Data mining and simulation: a grey relationship demonstration

Fuzzy data has grown to be an important factor in data mining. Whenever uncertainty exists, simulation can be used as a model. Simulation is very flexible, although it can involve significant levels of computation. This article discusses fuzzy decision-making using the grey related analysis method. Fuzzy models are expected to better reflect decision-making uncertainty, at some cost in accuracy relative to crisp models. Monte Carlo simulation is used to incorporate experimental levels of uncertainty into the data and to measure the impact of fuzzy decision tree models using categorical data. Results are compared with decision tree models based on crisp continuous data.

IJDWM Special Issue: Advances in Data Mining Applications

This special issue is a collection of the selected papers published on the proceedings of the First International Conference on Advanced Data Mining and Applications (ADMA) held in Wuhan, China in 2005. The articles focus on the innovative applications of data mining approaches to the problems that involve large data sets, incomplete and noise data, or demand optimal solutions.