Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

The development and evaluation of an incontinence screening questionnaire for female primary care

Although there is a high prevalence of leaking urine among Australian women, there are currently no standardized procedures for screening patients for incontinence in the primary care setting (known in Australia as general practice). In response to this, an incontinence screening questionnaire (ISQ) was developed and evaluated for use in general practice. Eighty-nine women completed an original compilation of 33 items that asked about situations associated with leaking urine, avoidance of leakage, and concern about leakage. Each item was assessed according to its acceptability for the population of female general practice patients, discriminative value, and test-retest reliability. These patients also underwent an objective test of incontinence, the 48-hour pad test, so that the screening items could be validated against an objective classification of incontinence. The study included women who had bladder control problems and those who did not. Eight items on the ISQ were shown to be acceptable to patients, discriminative, reliable, and valid indicators of objective incontinence. Five items were capable of predicting almost 70% of patients who showed objective leakage of urine and misclassified fewer than 15% of these patients. Those five items were selected for inclusion in the (refined) ISQ. (C) 2000 Wiley-Liss, Inc.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Specification and Evaluation of Safety Properties in a Component-Based Software Engineering Process

Over the past years, component-based software engineering has become an established paradigm in the area of complex software intensive systems. However, many techniques for analyzing these systems for critical properties currently do not make use of the component orientation. In particular, safety analysis of component-based systems is an open field of research. In this chapter we investigate the problems arising and define a set of requirements that apply when adapting the analysis of safety properties to a component-based software engineering process. Based on these requirements some important component-oriented safety evaluation approaches are examined and compared.

Adolescents' perceptions of social status: Development and evaluation of a new indicator

Objective. Eliminating health disparities, including those that are a result of socioeconomic status (SES), is one of the overarching goals of Healthy People 2010. This article reports on the development of a new, adolescent-specific measure of subjective social status (SSS) and on initial exploratory analyses of the relationship of SSS to adolescents' physical and psychological health. Methods. A cross-sectional study of 10 843 adolescents and a subsample of 166 paired adolescent/mother dyads who participated in the Growing Up Today Study was conducted. The newly developed MacArthur Scale of Subjective Social Status (10-point scale) was used to measure SSS. Paternal education was the measure of SES. Indicators of psychological and physical health included depressive symptoms and obesity, respectively. Linear regression analyses determined the association of SSS to depressive symptoms, and logistic regression determined the association of SSS to overweight and obesity, controlling for sociodemographic factors and SES. Results. Mean society ladder ranking, a subjective measure of SES, was 7.2 ± 1.3. Mean community ladder ranking, a measure of perceived placement in the school community, was 7.6 ± 1.7. Reliability of the instrument was excellent: the intraclass correlation coefficient was 0.73 for the society ladder and 0.79 for the community ladder. Adolescents had higher society ladder rankings than their mothers (µteen = 7.2 ± 1.3 vs µmom = 6.8 ± 1.2; P = .002). Older adolescents' perceptions of familial placement in society were more closely correlated with maternal subjective perceptions of placement than those of younger adolescents (Spearman's rhoteens

Rational combinatorial chemistry-based selection, synthesis and evaluation of an affinity adsorbent for recombinant human clotting factor VII

The selection, synthesis and chromatographic evaluation of a synthetic affinity adsorbent for human recombinant factor VIIa is described. The requirement for a metal ion-dependent immunoadsorbent step in the purification of the recombinant human clotting factor, FVIIa, has been obviated by using the X-ray crystallographic structure of the complex of tissue factor (TF) and Factor VIIa and has directed our combinatorial approach to select, synthesise and evaluate a rationally-selected affinity adsorbent from a limited library of putative ligands. The selected and optimised ligand comprises a triazine scaffold bis-substituted with 3-aminobenzoic acid and has been shown to bind selectively to FVIIa in a Ca2+-dependent manner. The adsorbent purifies FVIIa to almost identical purity (>99%), yield (99%), activation/degradation profile and impurity content (∼1000 ppm) as the current immunoadsorption process, while displaying a 10-fold higher static capacity and substantially higher reusability and durability. © 2002 Elsevier Science B.V. All rights reserved.

Consensus neuropathological diagnosis of common dementia syndromes: testing and standardising the use of multiple diagnostic criteria

The aim of this study was to assess the variation between neuropathologists in the diagnosis of common dementia syndromes when multiple published protocols are applied. Fourteen out of 18 Australian neuropathologists participated in diagnosing 20 cases (16 cases of dementia, 4 age-matched controls) using consensus diagnostic methods. Diagnostic criteria, clinical synopses and slides from multiple brain regions were sent to participants who were asked for case diagnoses. Diagnostic sensitivity, specificity, predictive value, accuracy and variability were determined using percentage agreement and kappa statistics. Using CERAD criteria, there was a high inter-rater agreement for cases with probable and definite Alzheimer's disease but low agreement for cases with possible Alzheimer's disease. Braak staging and the application of criteria for dementia with Lewy bodies also resulted in high inter-rater agreement. There was poor agreement for the diagnosis of frontotemporal dementia and for identifying small vessel disease. Participants rarely diagnosed more than one disease in any case. To improve efficiency when applying multiple diagnostic criteria, several simplifications were proposed and tested on 5 of the original 210 cases. Inter-rater reliability for the diagnosis of Alzheimer's disease and dementia with Lewy bodies significantly improved. Further development of simple and accurate methods to identify small vessel lesions and diagnose frontotemporal dementia is warranted.