Dietary patterns analysis using data mining method. An application to data from the CYKIDS study

Data mining is a computational method that permits the extraction of patterns from large databases. We applied the data mining approach in data from 1140 children (9-13years), in order to derive dietary habits related to children's obesity status. Rules emerged via data mining approach revealed the detrimental influence of the increased consumption of soft dinks, delicatessen meat, sweets, fried and junk food. For example, frequent (3-5times/week) consumption of all these foods increases the risk for being obese by 75%, whereas in children who have a similar dietary pattern, but eat >2times/week fish and seafood the risk for obesity is reduced by 33%. In conclusion patterns revealed from data mining technique refer to specific groups of children and demonstrate the effect on the risk associated with obesity status when a single dietary habit might be modified. Thus, a more individualized approach when translating public health messages could be achieved.     

Describing Network Traffic Using the Index of Variability

Commonly used measures of traffic burstiness do not capture the fluctuation of traffic variability over the entire range of time-scales. In this paper, we present a measure of variability, called the Index of Variability (Hv(tau)), that depicts the degree of variability (burstiness) of a typical network traffic process at each time-scale and is analytically tractable for many traffic models. As an illustration, we derive the closed-form expressions of Hv(tau) for two traditional traffic models and generate a variety of two-dimensional (2D) and three-dimensional (3D) Index-of-Variability curves. These curves demonstrate that the Index of Variability can help in determining the complexities of the network traffic variability over the network performance relevant time-scales. We then introduce a practical method for estimating the Index-of-Variability curve from a given traffic trace. Using this method, we estimate the Index-of-Variability curves for 12 long NLANR network traffic traces. The results indicate that the variability of real network traffic varies with time-scales and that the Index of Variability has the ability to discern qualitative differences between traffic traces obtained from different networks. Thus, the Index of Variability offers the potential to gain insights into the dynamics of network traffic that existing tools do not offer.     

CO2 benefit from the increasing percentage of diesel passenger cars in Sweden

Control of CO₂ emissions is a major environmental issue in most countries. The Swedish car market shows remarkably low new Diesel passenger car registrations compared to the average European Union car market. Therefore, a simple way to decrease CO₂ emissions from the transport sector in Sweden would be the replacement of gasoline by Diesel passenger cars, which emit less CO₂. The combined effects of probable changes in Diesel and gasoline future fuel consumption, new passenger car sales and market segmentation have been evaluated for different Diesel passenger cars penetrations. The results show a benefit in CO₂ emissions of about 2.8% with 30% Diesel penetration; if Diesel penetration reaches 50%, the benefit attains 7.5%. Future rises of CO₂ emissions caused by higher new passenger car registrations or unfavourable market segmentation could be at least partially counterbalanced by the introduction of more Diesel passenger cars. Copyright © 2006 John Wiley & Sons, Ltd.     

An integrated mechatronic approach for the systematic design of force fields and programming of microactuator arrays for micropart manipulation

Micromanipulation is a hot topic in the rapidly emerging area of micromechatronics and particularly in the manufacturing and assembling of micromechatronic products. This paper introduces an integrated mechatronic approach for the systematic design and operation of flexible, sensorless, automated micromanipulation for a variety of microparts on microactuation arrays. This approach is a mechatronic synthesis of methods from different engineering areas such as solid modeling, electronics design, software for control and programming of mechanical actuation. It involves designing of programmable force fields for manipulation of convex or non-convex polygonal microparts on an array, hardware programmable circuitry for the activation of the array and a software algorithmic procedure for the programming. A detailed analysis is given, as well as several simulated experiments performed using the introduced approach on a cilia microactuator array for a variety of polygonal asymmetric and non-convex microparts and the results are presented and discussed. Finally, the advantages and limitations of this approach are analyzed and points for further research are raised.     

Electrocardiographic appearance of a non-Q wave acute myocardial infarction in a patient with thyrotoxicosis. A case history

A patient with severe thyrotoxicosis developed the typical electrocardiographic (ECG) evolution of a non-q myocardial infarction. This occurred without evidence of myocardial necrosis and in the absence of coronary artery disease. Treatment with beta blockers resolved the ECG changes despite the persistence of the thyrotoxic state.     

ATM WAN performance tools, experiments, and results

Practical experiments in a wide-area ATM network environment are essential to gain a better understanding of the factors affecting ATM performance. This article summarizes the main lessons learned through the authors' practical experiences with ATM and how these can be applied to performance tuning. In order to achieve maximum performance from an ATM WAN, factors ranging from the transport protocol to the equipment used and the network conditions must be carefully taken into consideration. The authors also discuss some of the software-based throughput measurement tools available for the evaluation of high speed network performance, with particular emphasis on NetSpec     

Using Cultural‐Historical Activity Theory to design and evaluate an educational game in science education

The aim of this paper is to describe a methodology for using Cultural‐Historical Activity Theory (CHAT) at the initial stages of the design process of an educational game, by exploring how the theory can be used as a framework for producing not only usable but also useful computer tools. The research also aimed to investigate how the theory could be used for designing computer tools for learning science. Although CHAT and specifically the concepts of ‘activity system’ and ‘contradictions’ were used as the basis for the design and development of the educational game, subsidiary design guidelines also contributed significantly to this process. These derived from the research fields of Human Computer Interaction and Science Education and from students' everyday experiences when playing video games at home. The educational game produced was concerned with the teaching and learning of ‘Expansion and Contraction of Air’ in primary science, a subject that existing research suggests is conceptually difficult for students. As far as the main outcomes of the study are concerned, it was revealed through the implementation of the game that contradictions could be adequately resolved, while stakeholders' needs and motives could be appropriately addressed.     

Continuous speech recognition using linear dynamic models

Hidden Markov models (HMMs) with Gaussian mixture distributions rely on an assumption that speech features are temporally uncorrelated, and often assume a diagonal covariance matrix where correlations between feature vectors for adjacent frames are ignored. A Linear Dynamic Model (LDM) is a Markovian state-space model that also relies on hidden state modeling, but explicitly models the evolution of these hidden states using an autoregressive process. An LDM is capable of modeling higher order statistics and can exploit correlations of features in an efficient and parsimonious manner. In this paper, we present a hybrid LDM/HMM decoder architecture that postprocesses segmentations derived from the first pass of an HMM-based recognition. This smoothed trajectory model is complementary to existing HMM systems. An Expectation-Maximization (EM) approach for parameter estimation is presented. We demonstrate a 13 % relative WER reduction on the Aurora-4 clean evaluation set, and a 13 % relative WER reduction on the babble noise condition.     

Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies

OBJECTIVE: To estimate the incidence of serious and fatal adverse drug reactions (ADR) in hospital patients. DATA SOURCES: Four electronic databases were searched from 1966 to 1996. STUDY SELECTION: Of 153, we selected 39 prospective studies from US hospitals. DATA EXTRACTION: Data extracted independently by 2 investigators were analyzed by a random-effects model. To obtain the overall incidence of ADRs in hospitalized patients, we combined the incidence of ADRs occurring while in the hospital plus the incidence of ADRs causing admission to hospital. We excluded errors in drug administration, noncompliance, overdose, drug abuse, therapeutic failures, and possible ADRs. Serious ADRs were defined as those that required hospitalization, were permanently disabling, or resulted in death. DATA SYNTHESIS: The overall incidence of serious ADRs was 6.7% (95% confidence interval [CI], 5.2%-8.2%) and of fatal ADRs was 0.32% (95% CI, 0.23%-0.41%) of hospitalized patients. We estimated that in 1994 overall 2216000 (1721000-2711000) hospitalized patients had serious ADRs and 106000 (76000-137000) had fatal ADRs, making these reactions between the fourth and sixth leading cause of death. CONCLUSIONS: The incidence of serious and fatal ADRs in US hospitals was found to be extremely high. While our results must be viewed with circumspection because of heterogeneity among studies and small biases in the samples, these data nevertheless suggest that ADRs represent an important clinical issue.