Computerized conferencing for knowledge acquisition from multiple experts

The increasing complecity of many expert system application areas calls for the integration of the knowledge of multiple experts. The use of multiple experts introduces some interesting new problems during the process of knowledge acquisition. The problems are further complicated when the experts are geographically dispersed or unavailable for face-to-face interactions.

This article discusses the motivations for acquiring the knowledge of multiple experts, the problems related to knowledge acquisition, new issues that arise whens multiple experts interact, solutions that can be brought to bear in building multiple expert systems (particularly when experts are geographically dispersed), and new tools for knowledge engineers to use when dealing with multiple experts.     

Review of information extraction technologies and applications

Information extraction (IE) is an important and growing field, in part because of the development of ubiquitous social media networking millions of people and producing huge collections of textual information. Mined information is being used in a wide array of application areas from targeted marketing of products to intelligence gathering for military and security needs. IE has its roots in artificial intelligence fields including machine learning, logic and search algorithms, computational linguistics, and pattern recognition. This review summarizes the history of IE, surveys the various uses of IE, identifies current technological accomplishments and challenges, and explores the role that neural and adaptive computing might play in future research. A goal for this review is also to encourage practitioners of neural and adaptive computing to look for interesting applications in the important emerging area of IE.     

PEOPL: A knowledge-based system for the evaluation of personnel

Abstract: A project is underway to increase the effective use of personnel by creating a knowledge-based assistant for supervisors. The Programmed Evaluation of Personnel (PEOPL) is designed to permit the combination of quantitative and qualitative data to standardize supervisory ratings. The full scope of the project will combine subjective experience with data from psychological research which assesses employee performance. Peopl combines heuristic, subjective experience with experimental data to establish performance standards for use in a comprehensive system for personnel use. In this way, organizations can assess corporate needs, evaluate the current pool of employees, place them where they may be used more efficiently, and determine what jobs remain undone.     

Synthesis and cationic photopolymerization of a new fluorinated oxetane monomer

A new fluorinated oxetane monomer (FOX) was prepared using a fluorinated alcohol by phase transfer catalysis in a Williamson ether synthesis. The new fluorinated monomer was used in cationic photopolymerization as comonomer of 3,3′-[oxydi(methylene)]bis(3-ethyloxetane). The presence of the FOX monomer induces a decrease of the glass transition temperature, thermal stabilization and an increase of the final oxetane group conversion. Completely hydrophobic surfaces were obtained with a selective enrichment of the fluorinated comonomer, as confirmed by contact angle and XPS analysis.     

Introduction to the special issue on deep learning for biomedical and healthcare applications

Neural Computing and Applications -     

Traffic crash involvement: Experiential driving knowledge and stressful contextual antecedents.

Researchers have rarely examined stressful environments and psychological characteristics as predictors of driving behavior in the same study. The authors hypothesized that (a) safer drivers, more accurately assess physical and emotional traffic hazards and (b) stress and emotional states elevate crash risk. The hypotheses were evaluated with procedural and declarative tacit driving knowledge tests requiring assessment of emotional and contextual hazards and with accident reports describing crash antecedents, including stressful events and environmental conditions. Analyses identified separate driving knowledge factors corresponding to emotional and contextual hazards that were significantly related to the crash criteria. Accident report analyses show that stress significantly elevates at-fault crash risk. The results demonstrate the importance of experiential knowledge acquired without instruction (procedural or tacit knowledge) and provide safety recommendations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)