Risk assessment of E-Commerce projects using evidential reasoning

The purpose of this study is to develop a decision making system to evaluate the risks in E-Commerce (EC) projects. Competitive software businesses have the critical task of assessing the risk in the software system development life cycle. This can be conducted on the basis of conventional probabilities, but limited appropriate information is available and so a complete set of probabilities is not available. In such problems, where the analysis is highly subjective and related to vague, incomplete, uncertain or inexact information, the Dempster-Shafer (DS) theory of evidence offers a potential advantage. We use a direct way of reasoning in a single step (i.e., extended DS theory) to develop a decision making system to evaluate the risk in EC projects. This consists of five stages 1) establishing knowledge base and setting rule strengths, 2) collecting evidence and data, 3) determining evidence and rule strength to a mass distribution for each rule; i.e., the first half of a single step reasoning process, 4) combining prior mass and different rules; i.e., the second half of the single step reasoning process, 5) finally, evaluating the belief interval for the best support decision of EC project. We test the system by using potential risk factors associated with EC development and the results indicate that the system is promising way of assisting an EC project manager in identifying potential risk factors and the corresponding project risks.

Comparison of flavor compounds of potato chips fried in palmolein and silicone fluid

The importance of the frying oil as a heat-transfer medium and as a source of flavor precursors for the formation of potato chip flavor was investigated. Potato slices were fried in palmolein or silicone fluid, and the volatile flavor compounds of the resulting chips were isolated onto Tenax and analyzed by gas chromatography-mass spectrometry. Although the heat-transfer coefficients of the oils did not differ significantly, their temperature profiles during frying were different, probably due to greater turbulence on placing potato slices in palmolein, leading to more efficient heat transfer. Levels of Strecker aldehydes and sulfides in chips fried in the two media were not significantly different, but levels of pyrazines were significantly higher in palmolein-fried chips. Amounts of 2,4-decadienal were also significantly higher in palmolein-fried chips, but there was no significant difference in hexanal levels between the samples.

Comparison between fluid simulations and experiments in inductively coupled argon/chlorine plasmas

Comparisons of 2D fluid simulations with experimental measurements of Ar/Cl-2 plasmas in a low-pressure inductively coupled reactor are reported. Simulations show that the wall recombination coefficient of Cl atom (gamma) is a crucial parameter of the model and that neutral densities are very sensitive to its variations. The best agreement between model and experiment is obtained for gamma = 0.02, which is much lower than the value predicted for stainless steel walls (gamma = 0.6). This is consistent with reactor wall contaminations classically observed in such discharges. The electron density, negative ion fraction and Cl atom density have been investigated under various conditions of chlorine and argon concentrations, gas pressure and applied rf input power. The plasma electronegativity decreases with rf power and increases with chlorine concentration. At high pressure, the power absorption and distribution of charged particles become more localized below the quartz window. Although the experimental trends are well reproduced by the simulations, the calculated charged particle densities are systematically overestimated by a factor of 3-5. The reasons for this discrepancy are discussed in the paper.

The Combination of Multiple Classifiers Using an Evidential Reasoning Approach

In many domains when we have several competing classifiers available we want to synthesize them or some of them to get a more accurate classifier by a combination function. In this paper we propose a ‘class-indifferent’ method for combining classifier decisions represented by evidential structures called triplet and quartet, using Dempster's rule of combination. This method is unique in that it distinguishes important elements from the trivial ones in representing classifier decisions, makes use of more information than others in calculating the support for class labels and provides a practical way to apply the theoretically appealing Dempster–Shafer theory of evidence to the problem of ensemble learning. We present a formalism for modelling classifier decisions as triplet mass functions and we establish a range of formulae for combining these mass functions in order to arrive at a consensus decision. In addition we carry out a comparative study with the alternatives of simplet and dichotomous structure and also compare two combination methods, Dempster's rule and majority voting, over the UCI benchmark data, to demonstrate the advantage our approach offers. (A continuation of the work in this area that was published in IEEE Trans on KDE, and conferences)

An extended framework for evidential reasoning systems.

Use of the Dempster-Shafer (D-S) theory of evidence to deal with uncertainty in knowledge-based systems has been widely addressed. Several AI implementations have been undertaken based on the D-S theory of evidence or the extended theory. But the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is still a major problem. This paper presents an approach to representing such knowledge, in which Yen’s probabilistic multi-set mappings have been extended to evidential mappings, and Shafer’s partition technique is used to get the mass function in a complex evidence space. Then, a new graphic method for describing the knowledge is introduced which is an extension of the graphic model by Lowrance et al. Finally, an extended framework for evidential reasoning systems is specified.

Comparative analysis of synovial fluid and plasma proteomes in juvenile arthritis - Proteomic patterns of joint inflammation in early stage disease

Synovial fluid is a potential source of novel biomarkers for many arthritic disorders involving joint inflammation, including juvenile idiopathic arthritis. We first compared the distinctive protein ‘fingerprints’ of local inflammation in synovial fluid with systemic profiles within matched plasma samples. The synovial fluid proteome at the time of joint inflammation was then evaluated across clinical subgroups to identify early disease associated proteins. We measured the synovial fluid and plasma proteomes using the two-dimensional fluorescence difference gel electrophoresis approach. Image analysis software was used to highlight the expression levels of joint and subgroup associated proteins across the study cohort (n = 32). A defined subset of 30 proteins had statistically significant differences (p < 0.05) between sample types such that synovial fluid could be differentiated from plasma. Furthermore distinctive synovial proteome expression patterns segregate patient subgroups. Protein expression patterns localized in the chronically inflamed joint therefore have the potential to identify patients more likely to suffer disease which will spread from a single joint to multiple joints. The proteins identified could act as criteria to prevent disease extension by more aggressive therapeutic intervention directed at an earlier stage than is currently possible.

The human synovial fluid proteome: A key factor in the pathology of joint disease

This review aims to summarise our knowledge to date on the protein complement of the synovial fluid (S F). The tissues, structure and pathophysiology of the synovial joint are briefly described. The salient features of the S F proteome, how it is composed and the influence of arthritic disease are highlighted and discussed. The concentrations of proteins that have been detected and quantified in SF are drawn together from the literature on osteoarthritis, rheumatoid arthritis and juvenile idiopathic arthritis. The measurements are plotted to give a perspective on the dynamic range of protein levels within the SF. Approaches to proteomic analysis of SF to date are discussed along with their findings. From the recent literature reviewed within, it is becoming increasingly clear that analysis of the SF proteome as a whole, could deliver the most valuable differential diagnostic fingerprints of a number of arthritic disorders. Further development of proteomic platforms could characterise prognostic profiles to improve the cliniciads ability to resolve unremitting disease by existing and novel therapeutics.

Inductive reasoning and semantic cognition: More than just different names for the same thing?

We describe evidence that certain inductive phenomena are associated with IQ, that different inductive phenomena emerge at different ages, and that the effects of causal knowledge on induction are decreased under conditions of memory load. On the basis of this evidence we argue that there is more to inductive reasoning than semantic cognition.

Deciding between theories of how reasoning develops is hard

Although Sloutsky agrees with our interpretation of our data, he argues that the totality of the evidence supports his claim that children make inductive generalisations on the basis of similarity. Here we take issue with his characterisation of the alternative hypotheses in his informal analysis of the data, and suggest that a thorough Bayesian analysis, although practically very difficult, is likely to result in a more finely balanced outcome than he suggests. (c) 2008 Elsevier B.V. All rights reserved.

Rarity, pseudodiagnosticity and Bayesian reasoning

Three experiments investigated the effect of rarity on people's selection and interpretation of data in a variant of the pseudodiagnosticity task. For familiar (Experiment 1) but not for arbitrary (Experiment 3) materials, participants were more likely to select evidence so as to complete a likelihood ratio when the initial evidence they received was a single likelihood concerning a rare feature. This rarity effect with familiar materials was replicated in Experiment 2 where it was shown that participants were relatively insensitive to explicit manipulations of the likely diagnosticity of rare evidence. In contrast to the effects for data selection, there was an effect of rarity on confidence ratings after receipt of a single likelihood for arbitrary but not for familiar materials. It is suggested that selecting diagnostic evidence necessitates explicit consideration of the alternative hypothesis and that consideration of the possible consequences of the evidence for the alternative weakens the rarity effect in confidence ratings. Paradoxically, although rarity effects in evidence selection and confidence ratings are in the spirit of Bayesian reasoning, the effect on confidence ratings appears to rely on participants thinking less about the alternative hypothesis.

Searching and planning: Young children's reasoning about past and future event sequences

Six experiments examined children's ability to make inferences using temporal order information. Children completed versions of a task involving a toy zoo; one version required reasoning about past events (search task) and the other required reasoning about future events (planning task). Children younger than 5 years failed both the search and the planning tasks, whereas 5-year-olds passed both (Experiments 1 and 2). However, when the number of events in the sequence was reduced (Experiment 3), 4-year-olds were successful on the search task but not the planning task. Planning difficulties persisted even when relevant cues were provided (Experiments 4 and 5). Experiment 6 showed that improved performance on the search task found in Experiment 3 was not due to the removal of response ambiguity.

Young children's reasoning about the order of past events

Four studies are reported that employed an object location task to assess temporal-causal reasoning. In Experiments 1-3, successfully locating the object required a retrospective consideration of the order in which two events had occurred. In Experiment 1, 5- but not 4-year-olds were successful; 4-year-olds also failed to perform at above-chance levels in modified versions of the task in Experiments 2 and 3. However, in Experiment 4, 3-year-olds were successful when they were able to see the object being placed first in one location and then in the other, rather than having to consider retrospectively the sequence in which two events had happened. The results suggest that reasoning about the causal significance of the temporal order of events may not be fully developed before 5 years. (C) 2007 Elsevier Inc. All rights reserved.