Fuzzy logic-based hybrid knowledge systems for the detection and diagnosis of childhood autism

2021 ◽  
pp. 55-69
Author(s):  
Sahar Qazi ◽  
Khalid Raza
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Systems ◽  
Childhood Autism ◽  
Hybrid Knowledge ◽  
Detection And Diagnosis

A Review of Vibration Monitoring as a Diagnostic Tool for Turbine Blade Faults

2012 ◽  
Vol 229-231 ◽  
pp. 1459-1463 ◽  
Author(s):  
Ahmed M. Abdelrhman ◽  
M. Salman Leong ◽  
Somia Alfatih M. Saeed ◽  
Salah M. Ali Al-Obiadi Al Obiadi
Keyword(s):  
Neural Networks ◽  
Signal Processing ◽  
Fuzzy Logic ◽  
Turbine Blade ◽  
Gas Turbines ◽  
Processing Method ◽  
Vibration Monitoring ◽  
Signal Processing Method ◽  
Detection And Diagnosis ◽  
Model Based Analysis

Vibration monitoring is widely recognized as an effective tool for the detection and diagnosis of incipient failures of gas turbines. This paper presents a review of vibration based methods for turbine blade faults. Methods typically involved analysis of blade passing frequencies, and extraction of dynamic signals from the measured vibration response. This includes frequency analysis, wavelet analysis, neural networks and fuzzy logic and model based analysis. The literature reviewed showed that vibration could detect most types of blade faults on the basis that dynamic signals are correctly extracted using the most appropriate signal processing method.

scholarly journals The Role of Leadership and Local Ownership in Research 4 Development (R4D) Projects

Proceedings ◽  
2019 ◽  
Vol 36 (1) ◽  
pp. 2
Author(s):  
Kim Alexander
Keyword(s):  
New Technologies ◽  
Production Systems ◽  
Lao Pdr ◽  
Knowledge Systems ◽  
Local Ownership ◽  
Project Leadership ◽  
Management Interventions ◽  
Geographical Regions ◽  
Hybrid Knowledge ◽  
Stakeholder Interactions

All researchers for development struggle to achieve lasting results on the ground. Regardless of the introduced technology, the fundamental basis for achieving lasting results involves: 1) strategic project leadership, 2) local ownership of research objectives, research design, outputs and overall results, and 3) local leadership and management of activities and finances. To support lasting results, research tools can assist in communicating the complexities of an introduced technology and can guide stakeholder interactions to bridge knowledge systems and create common understandings and new hybrid knowledge systems. We highlight a transdisciplinary process used to co-create a Research Discussion Tool and identification of 9 thematic areas which, in combination, enabled obstacles to technology uptake to be overcome and farmers to benefit from research-based innovations. The process involved assisting local researchers and extension agents to co-develop solutions, strategies and methods to improve technology uptake by farmers in Lao PDR, using a series of change management interventions. A complex ecology of factors involving farmers’ decision drivers and farmers’ decision enablers within farmers’ production systems influence technology uptake. The relative importance of each factor is dependent on the specific technology that is being introduced. Hence, projects that introduce new technologies grapple to address all relevant factors and often do not have the ability to deal with the complex array of factors that are at play. Co-constructed knowledge embeds local knowledge that becomes accessible to projects. The approach also has the potential to harness collaborative exchanges with other projects in similar geographical regions.

A Genetic Fuzzy Semantic Web Search Agent Using Granular Semantic Trees for Ambiguous Queries

2010 ◽  
pp. 426-438
Author(s):  
Yan Chen ◽  
Yan-Qing Zhang
Keyword(s):  
Fuzzy Logic ◽  
Web Search ◽  
Word Sense Disambiguation ◽  
Knowledge Systems ◽  
Web Pages ◽  
Word Sense ◽  
Web Searching ◽  
Search Results ◽  
Sense Disambiguation ◽  
Semantic Tree

For most Web searching applications, queries are commonly ambiguous because words or phrases have different linguistic meanings for different Web users. The conventional keyword-based search engines cannot disambiguate queries to provide relevant results matching Web users’ intents. Traditional Word Sense Disambiguation (WSD) methods use statistic models or ontology-based knowledge systems to measure associations among words. The contexts of queries are used for disambiguation in these methods. However, due to the fact that numerous combinations of words may appear in queries and documents, it is difficult to extract concepts’ relations for all possible combinations. Moreover, queries are usually short, so contexts in queries do not always provide enough information to disambiguate queries. Therefore, the traditional WSD methods are not sufficient to provide accurate search results for ambiguous queries. In this chapter, a new model, Granular Semantic Tree (GST), is introduced for more conveniently representing associations among concepts than the traditional WSD methods. Additionally, users’ preferences are used to provide personalized search results that better adapt to users’ unique intents. Fuzzy logic is used to determine the most appropriate concepts related to queries based on contexts and users’ preferences. Finally, Web pages are analyzed by the GST model. The concepts of pages for the queries are evaluated, and the pages are re-ranked according to similarities of concepts between pages and queries.

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