Logical Comparison of Inconsistent Perspectives using Scoring Functions

The language for describing inconsistency is underdeveloped. If a database (a set of formulae) is inconsistent, there is usually no qualification of that inconsistency. Yet, it would seem useful to be able to say how inconsistent a database is, or to say whether one database is more inconsistent than another database. In this paper, we provide a more general characterization of inconsistency in terms of a scoring function for each database . A scoring function S is from the power set of into the natural numbers defined so that S() gives the number of minimally inconsistent subsets of that would be eliminated if the subset was removed from . This characterization offers an expressive and succinct means for articulating, in general terms, the nature of inconsistency in a set of formulae. We then compare databases using their scoring functions. This gives an intuitive ordering relation over databases that we can describe as more inconsistent than. These techniques are potentially useful in a wide range of problems including monitoring progress in negotiations between a number of participants, and in comparing heterogeneous sources of information.     

Polynomial calculation of the Shapley value based on sampling

In this paper we develop a polynomial method based on sampling theory that can be used to estimate the Shapley value (or any semivalue) for cooperative games. Besides analyzing the complexity problem, we examine some desirable statistical properties of the proposed approach and provide some computational results.     

On the impact of serializing contention management on STM performance

Transactional memory (TM) is an emerging concurrent programming abstraction. Numerous software-based transactional memory (STM) implementations have been developed in recent years. STM implementations must guarantee transaction atomicity and isolation. In order to ensure progress, an STM implementation must resolve transaction collisions by consulting a contention manager (CM).     

Meta-Learner for Unknown Attribute Values Processing: Dealing with Inconsistency of Meta-Databases

Efficient robust data mining algorithms should comprise some routines for processing unknown (missing) attribute values when acquiring knowledge from real-world databases because these data usually contain a certain percentage of missing values. The paper Bruha and Franek (1996) figures out that each dataset has more or less its own favourite routine for processing unknown attribute values. It evidently depends on the magnitude of noise and source of unknownness in each dataset. One possibility how to choose an efficient routine for processing unknown attribute values for a given database is exhibited in this paper. The covering machine learning algorithm CN4, a large extension of the well-known CN2 algorithm, is used here as an inductive vehicle.Each of the six routines for unknown attribute value processing (which are available in CN4) is used independently in order to process a given database. Afterwards, a meta-learner is used to derive a meta-classifier that makes up the overall (final) decision about the class of input unseen objects. The entire system is called a meta-combiner.The meta-database that is formed for the meta-learner could be inconsistent which could decrease the performance of the entire meta-classifier. Therefore, the existing meta-system (Meta-CN4) has been enhanced by a purification procedure that appropriately solves up the conflict of inconsistent meta-data.The paper first surveys the CN4 algorithms including its six routines for unknown attribute value processing. Afterwards, it introduces the methodology of the meta-learner including its enhancement that solves inconsistent meta-databases. Finally, the results of experiments with various percentages of unknown attribute values on real-world data are presented and performances of the meta-classifier and the six base classifiers are then compared. The paper also explains the difference between the meta-combiner (meta-learner) described here and the cross-validation procedure used for obtaining the classification accuracy.     

Collaborative conceptual design—state of the art and future trends

This paper presents a state of the art review of existing research, projects, and applications in the domain of collaborative conceptual design, based on the Internet and Web technologies. The purpose of the review is to understand the needs for conceptual engineering design, to clarify the current conceptual design practice, to classify the available technologies, and to study the future trend in this area. The emphasis of this paper is to briefly outline the methodologies, architectures, and tools developed for the projects reviewed in this paper. It also uncovers approaches to conflict resolution and team/project management, as they are vital to a successful engineering design in a collaborative environment. More than 80 journal and conference papers and about 20 projects are reviewed based on the primary focus mentioned above. The selected research works are further categorised into several areas based on the application domain, design theory, and the technology used for implementation. The selected research projects and applications are basically for, but not limited to, the collaborative conceptual design.     

Dynamic Customer Value Management: Asset Values under Demand Uncertainty using Airline Yield Management and Related Techniques

The focus of this paper is to demonstrate the close links between the airline and the manufacturing industry in so far as some of their decision support problems are concerned. We show that the yield management (YM) problem for the airline characterized by perishable and limited resources has counterparts in manufacturing and retail although with some variations. In the process of establishing similarities we highlight the importance of the concept of value of assets/resources, known as bid price in the airline terminology, that ties the two together. Several examples of its calculations and uses are provided. We believe that this new paradigm will open up new avenues for profits for manufacturers in the new era of e-commerce where the businesses shall have to be increasingly customer centric including pricing functions.     

View merging in the presence of incompleteness and inconsistency

View merging, also called view integration, is a key problem in conceptual modeling. Large models are often constructed and accessed by manipulating individual views, but it is important to be able to consolidate a set of views to gain a unified perspective, to understand interactions between views, or to perform various types of analysis. View merging is complicated by incompleteness and inconsistency: Stakeholders often have varying degrees of confidence about their statements. Their views capture different but overlapping aspects of a problem, and may have discrepancies over the terminology being used, the concepts being modeled, or how these concepts should be structured. Once views are merged, it is important to be able to trace the elements of the merged view back to their sources and to the merge assumptions related to them. In this paper, we present a framework for merging incomplete and inconsistent graph-based views. We introduce a formalism, called annotated graphs, with a built-in annotation scheme for modeling incompleteness and inconsistency. We show how structure-preserving maps can be employed to express the relationships between disparate views modeled as annotated graphs, and provide a general algorithm for merging views with arbitrary interconnections. We provide a systematic way to generate and represent the traceability information required for tracing the merged view elements back to their sources, and to the merge assumptions giving rise to the elements.

TROPHI: development of a tool to measure complex,multi-factorial patient handling interventions

Patient handling interventions are complex and multi-factorial. It has been difficult to make comparisons across different strategies due to the lack of a comprehensive outcome measurement method. The Tool for Risk Outstanding in Patient Handling Interventions (TROPHI) was developed to address this gap by measuring outcomes and comparing performance across interventions. Focus groups were held with expert patient handling practitioners (n = 36) in four European countries (Finland, Italy, Portugal and the UK) to identify preferred outcomes to be measured for interventions. A systematic literature review identified 598 outcome measures; these were critically appraised and the most appropriate measurement tool was selected for each outcome. TROPHI was evaluated in the four EU countries (eight sites) and by an expert panel (n = 16) from the European Panel of Patient Handling Ergonomics for usability and practical application. This final stage added external validity to the research by exploring transferability potential and presenting the data and analysis to allow respondent (participant) validation.

Practitioner Summary: Patient handling interventions are complex and multi-factorial and it has been difficult to make comparisons due to the lack of a comprehensive outcome measurement method. The Tool for Risk Outstanding in Patient Handling Interventions (TROPHI) was developed to address this gap by measuring outcomes to compare performance across interventions.     

Computing the Shapley value in allocation problems: approximations and bounds,with an application to the Italian VQR research assessment program

Abstract

In allocation problems with indivisible goods, money compensation is used to distribute worth in a fair way. Coalitional games provide a formal mathematical framework to model such problems, and the Shapley value is a solution concept widely used to realise a fair distribution. To overcome its intractability, we describe how to simplify allocation problems and we propose algorithms for computing lower bounds and upper bounds of the Shapley value that can be combined with approximation algorithms. The proposed techniques have been implemented and tested on a real-world application of allocation problems, namely, the Italian research assessment program known as VQR.     

On the Accuracy of Polynomial Interpolation in Hilbert Space with Disturbed Nodal Values of the Operator

The interpolation accuracy of polynomial operators in a Hilbert space with a measure is estimated when nodal values of these operators are given approximately.