Outlier detection with partial information:Application to emergency mapping

This paper, addresses the problem of novelty detection in the case that the observed data is a mixture of a known 'background' process contaminated with an unknown other process, which generates the outliers, or novel observations. The framework we describe here is quite general, employing univariate classification with incomplete information, based on knowledge of the distribution (the 'probability density function', 'pdf') of the data generated by the 'background' process. The relative proportion of this 'background' component (the 'prior' 'background' 'probability), the 'pdf' and the 'prior' probabilities of all other components are all assumed unknown. The main contribution is a new classification scheme that identifies the maximum proportion of observed data following the known 'background' distribution. The method exploits the Kolmogorov-Smirnov test to estimate the proportions, and afterwards data are Bayes optimally separated. Results, demonstrated with synthetic data, show that this approach can produce more reliable results than a standard novelty detection scheme. The classification algorithm is then applied to the problem of identifying outliers in the SIC2004 data set, in order to detect the radioactive release simulated in the 'oker' data set. We propose this method as a reliable means of novelty detection in the emergency situation which can also be used to identify outliers prior to the application of a more general automatic mapping algorithm. © Springer-Verlag 2007.

CEO compensation, option incentives and information disclosure

This paper examines the impact of information disclosure on the valuation of CEO options and the incentives created by those options. Prior executive compensation research in the US has made assumptions about key input variables that can affect the calculation of option values and financial incentives. Accordingly, biases may have ensued due to incomplete information disclosure about noncurrent option grants. Using new data on a sample of UK CEOs, we value executive option holdings and incentives for the first time and estimate the levels of distortion created by the less than complete US-style disclosure requirements. We also investigate the levels of distortion in the UK for the minority of companies that choose to reveal only partial information. Our results suggest that there have to date been few economic biases arising from less than complete information disclosure. Furthermore, we demonstrate that researchers using US data, who made reasonable assumptions about the inputs of noncurrent option grants, are unlikely to have made significant errors when calculating CEO financial incentives or option wealth. However, the recent downturn in the US stock market could result in the same assumptions, producing exaggerated incentive estimates in the future.

BOWL:augmenting the semantic web with beliefs

As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.

Resolving ambiguous descriptions through visual information

The project “Reference in Discourse” deals with the selection of a specific object from a visual scene in a natural language situation. The goal of this research is to explain this everyday discourse reference task in terms of a concept generation process based on subconceptual visual and verbal information. The system OINC (Object Identification in Natural Communicators) aims at solving this problem in a psychologically adequate way. The system’s difficulties occurring with incomplete and deviant descriptions correspond to the data from experiments with human subjects. The results of these experiments are reported.

Statistical distribution, host for encrypted information

The statistical distribution, when determined from an incomplete set of constraints, is shown to be suitable as host for encrypted information. We design an encoding/decoding scheme to embed such a distribution with hidden information. The encryption security is based on the extreme instability of the encoding procedure. The essential feature of the proposed system lies in the fact that the key for retrieving the code is generated by random perturbations of very small value. The security of the proposed encryption relies on the security to interchange the secret key. Hence, it appears as a good complement to the quantum key distribution protocol. © 2005 Elsevier B.V. All rights reserved.

A solution for information management in logistics operations of modern manufacturing chains

One dominant feature of the modern manufacturing chains is the movement of goods. Manufacturing companies would remain an unprofitable investment if the supplies/logistics of raw materials, semi-finished products or final goods are not handled in an effective way. Both levels of a modern manufacturing chain-actual production and logistics-are characterized by continuous data creation at a much faster rate than they can be meaningfully analyzed and acted upon manually. Often, instant and reliable decisions need to be taken based on huge, previously inconceivable amounts of heterogeneous, contradictory or incomplete data. The paper will highlight aspects of information flows related to business process data visibility and observability in modern manufacturing networks. An information management platform developed in the framework of the EU FP7 project ADVANCE will be presented.

Quality of the written information about suicide attempters

INTRODUCTION: The aim of the study was to assess the quality of the clinical records of the patients who are seen in public hospitals in Madrid after a suicide attempt in a blind observation. METHODS: Observational, descriptive cross-sectional study conducted at four general public hospitals in Madrid (Spain). Analyses of the presence of seven indicators of information quality (previous psychiatric treatment, recent suicidal ideation, recent suicide planning behaviour, medical lethality of suicide attempt, previous suicide attempts, attitude towards the attempt, and social or family support) in 993 clinical records of 907 patients (64.5% women), ages ranging from 6 to 92 years (mean 37.1±15), admitted to hospital after a suicide attempt or who committed an attempt whilst in hospital. RESULTS: Of patients who attempted suicide, 94.9% received a psychosocial assessment. All seven indicators were documented in 22.5% of the records, whilst 23.6% recorded four or less than four indicators. Previous suicide attempts and medical lethality of current attempt were the indicators most often missed in the records. The study found no difference between the records of men and women (z=0.296; p=0.767, two tailed Mann-Whitney U test), although clinical records of patients discharged after an emergency unit intervention were more incomplete than the ones from hospitalised patients (z=2.731; p=0.006), and clinical records of repeaters were also more incomplete than the ones from non-repeaters (z=3.511; p<0.001). CONCLUSIONS: Clinical records of patients who have attempted suicide are not complete. The use of semi-structured screening instruments may improve the evaluation of patients who have self- harmed.