Parallel interval-based reasoning in medical knowledge-based system Clinaid

The paper continues a series of papers and a monograph [33], where we have described the conceptual structures as well as the basic architecture of a knowledge-based systemCunaid.     

RUSHES—an annotation and retrieval engine for multimedia semantic units

Multimedia analysis and reuse of raw un-edited audio visual content known as rushes is gaining acceptance by a large number of research labs and companies. A set of research projects are considering multimedia indexing, annotation, search and retrieval in the context of European funded research, but only the FP6 project RUSHES is focusing on automatic semantic annotation, indexing and retrieval of raw and un-edited audio-visual content. Even professional content creators and providers as well as home-users are dealing with this type of content and therefore novel technologies for semantic search and retrieval are required. In this paper, we present a summary of the most relevant achievements of the RUSHES project, focusing on specific approaches for automatic annotation as well as the main features of the final RUSHES search engine.     

Bayesian networks for enhancement of requirements engineering: a literature review

Requirements analysis is the software engineering stage that is closest to the users’ world. It also involves tasks that are knowledge intensive. Thus, the use of Bayesian networks (BNs) to model this knowledge would be a valuable aid. These probabilistic models could manage the imprecision and ambiguities usually present in requirements engineering (RE). In this work, we conduct a literature review focusing on where and how BNs are applied on subareas of RE in order to identify which gaps remain uncovered and which methods might engineers employ to incorporate this intelligent technique into their own requirements processes. The scarcity of identified studies (there are only 20) suggests that not all RE areas have been properly investigated in the literature. The evidence available for adopting BNs into RE is sufficiently mature yet the methods applied are not easily translatable to other topics. Nonetheless, there are enough studies supporting the applicability of synergistic cooperation between RE and BNs. This work provides a background for understanding the current state of research encompassing RE and BNs. Functional, non-functional and -ilities requirements artifacts are enhanced by the use of BNs. These models were obtained by interacting with experts or by learning from databases. The most common criticism from the point of view of BN experts is that the models lack validation, whereas requirements engineers point to the lack of a clear application method for BNs and the lack of tools for incorporating them as built-in help functions.     

The Great Lakes Region and Bulk Water Exports

Abstract

The article provides an overview of the latest developments in the debate concerning the bulk water export of Great Lakes water. It examines the policy and legal dimensions of this new debate. The policy dimension focuses on the public attention and concern, in Canada, regarding bulk water removals from the Great Lakes basin. This concern has triggered the new Canadian federal legislation banning water exports from the region (Bill C-15). Is this a sign that the Canadian government now embraces a water conservation ethic? Is its position in line with the recent recommendations on the issue of the International Joint Commission (IJC), the joint body created by the United States and Canada to manage its shared waters? The attempt by investors to export water from the Great Lakes basin raises issues regarding Canada's obligations under international and regional trade agreements, most notably the General Agreement on Tariffs and Trade (GATT) and the North American Free Trade Agreement (NAFTA). The article examines the provisions of those two trade agreements in the context of the water export debate in Canada and concludes that increased clarity on Canada/US transboundary water issues is required.     

Differential nanofiller cluster formations in dental adhesive systems

Nanofillers are added to dental adhesives to improve mechanical properties of the hybrid layer. Ethanol or water added to the demineralized dentin to improve adhesive infiltration may produce filler aggregation. OBJECTIVE: To assess the effect of 5 vol% water or ethanol addition on nanoparticles distribution in dental adhesives. METHODS: Six available commercial adhesives systems were selected: Clearfil SE Bond (CSE), Clearfil Protect Bond (CPB), FL‐Bond (FLB), Clearfil S3 (CS3), Bond Force (BF), One Up Bond F plus (OUB), and an experimental adhesive system without filler (EXP). Polymer films were obtained by adding 0 (control) or 5 vol% water or ethanol into the bonding resins. Preparations were light‐cured (40 s). Three specimens were analyzed for each mixture. Three phases and 3D images were taken from each specimen by means of an atomic force microscope in taping mode (TM/AFM). Cluster sizes and surface nanoroughness were assessed. RESULTS: Control specimens from CSE, FLB, OUB, and BF presented clusters. The addition of solvents lead to particles aggregation in tested bonding resins. Ethanol addition produced more aggregates, particularly in adhesives containing fluoraluminosilicate as fillers. CONCLUSIONS: Nanofillers aggregation occurred in all adhesive systems in presence of additional solvents. In general, aggregate sizes were higher after the addition of ethanol. Formed clusters size values are always above the dimensions of the spaces existing between the demineralized collagen fibers. Microsc. Res. Tech. 75:749–757, 2012. © 2011 Wiley Periodicals, Inc.     

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.     

A Mixed Closure-CSP Method for Solving Scheduling Problems

Scheduling problems can be viewed as a set of temporal metric and disjunctive constraints and so they can be formulated in terms of CSP techniques. In the literature, there are CSP-based methods which sequentially interleave search efforts with the application of consistency enforcing mechanisms and variable/ordering heuristics. Therefore, the number of backtrackings needed to obtain a solution is reduced. In this paper, we propose a new method that effectively integrates the CSP process into a limited closure process: not by interleaving them but rather as a part of the same process. Such an integration allows us to define more informed heuristics. These heuristics are used to limit the complete closure process to a maximum number of disjunctions, thereby reducing its complexity while at the same time reducing the search space. Some open disjunctive solutions can be maintained in the CSP process, limiting the number of backtrackings necessary, and avoiding having to know all the problem constraints in advance. Our experiments with flow-shop and job-shop instances show that this approach obtains a feasible solution/optimal solution without having to use backtracking in most cases. We also analyze the behaviour of our algorithm when some constraints are known dynamically and we demonstrate that it can provide better results than a pure CSP process.