The Experts below are selected from a list of 228 Experts worldwide ranked by ideXlab platform
Carol Smidts - One of the best experts on this subject based on the ideXlab platform.
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causal mechanism graph a new notation for capturing cause effect knowledge in software dependability
Reliability Engineering & System Safety, 2017Co-Authors: Fuqun Huang, Carol SmidtsAbstract:Abstract Understanding cause-effect relations between concepts in software dependability engineering is fundamental to various research or industrial activities. Cognitive maps are traditionally used to elicit and represent such knowledge; however they seem incapable of accurately representing complex causal mechanisms in dependability engineering. This paper proposes a new notation called Causal Mechanism Graph (CMG) to elicit and represent the cause-effect domain knowledge embedded in experts’ minds or described in the literature. CMG contains a new set of symbols elicited from domain experts to capture the recurring interaction mechanisms between multiple concepts in software dependability engineering. Furthermore, compared to major existing Graphic Methods, CMG is particularly robust and suitable for mental knowledge elicitation: it allows one to represent the full range of cause-effect knowledge, accurately or fuzzily as one sees fit depending on the depth of knowledge he/she has. This feature combined with excellent reliability and validity poses CMG as a promising method that has the potential to be used in various areas, such as software dependability requirement elicitation, software dependability assessment and dependability risk control.
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Causal Mechanism Graph ─ A new notation for capturing cause-effect knowledge in software dependability
Reliability Engineering & System Safety, 2017Co-Authors: Fuqun Huang, Carol SmidtsAbstract:Abstract Understanding cause-effect relations between concepts in software dependability engineering is fundamental to various research or industrial activities. Cognitive maps are traditionally used to elicit and represent such knowledge; however they seem incapable of accurately representing complex causal mechanisms in dependability engineering. This paper proposes a new notation called Causal Mechanism Graph (CMG) to elicit and represent the cause-effect domain knowledge embedded in experts’ minds or described in the literature. CMG contains a new set of symbols elicited from domain experts to capture the recurring interaction mechanisms between multiple concepts in software dependability engineering. Furthermore, compared to major existing Graphic Methods, CMG is particularly robust and suitable for mental knowledge elicitation: it allows one to represent the full range of cause-effect knowledge, accurately or fuzzily as one sees fit depending on the depth of knowledge he/she has. This feature combined with excellent reliability and validity poses CMG as a promising method that has the potential to be used in various areas, such as software dependability requirement elicitation, software dependability assessment and dependability risk control.
Fuqun Huang - One of the best experts on this subject based on the ideXlab platform.
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causal mechanism graph a new notation for capturing cause effect knowledge in software dependability
Reliability Engineering & System Safety, 2017Co-Authors: Fuqun Huang, Carol SmidtsAbstract:Abstract Understanding cause-effect relations between concepts in software dependability engineering is fundamental to various research or industrial activities. Cognitive maps are traditionally used to elicit and represent such knowledge; however they seem incapable of accurately representing complex causal mechanisms in dependability engineering. This paper proposes a new notation called Causal Mechanism Graph (CMG) to elicit and represent the cause-effect domain knowledge embedded in experts’ minds or described in the literature. CMG contains a new set of symbols elicited from domain experts to capture the recurring interaction mechanisms between multiple concepts in software dependability engineering. Furthermore, compared to major existing Graphic Methods, CMG is particularly robust and suitable for mental knowledge elicitation: it allows one to represent the full range of cause-effect knowledge, accurately or fuzzily as one sees fit depending on the depth of knowledge he/she has. This feature combined with excellent reliability and validity poses CMG as a promising method that has the potential to be used in various areas, such as software dependability requirement elicitation, software dependability assessment and dependability risk control.
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Causal Mechanism Graph ─ A new notation for capturing cause-effect knowledge in software dependability
Reliability Engineering & System Safety, 2017Co-Authors: Fuqun Huang, Carol SmidtsAbstract:Abstract Understanding cause-effect relations between concepts in software dependability engineering is fundamental to various research or industrial activities. Cognitive maps are traditionally used to elicit and represent such knowledge; however they seem incapable of accurately representing complex causal mechanisms in dependability engineering. This paper proposes a new notation called Causal Mechanism Graph (CMG) to elicit and represent the cause-effect domain knowledge embedded in experts’ minds or described in the literature. CMG contains a new set of symbols elicited from domain experts to capture the recurring interaction mechanisms between multiple concepts in software dependability engineering. Furthermore, compared to major existing Graphic Methods, CMG is particularly robust and suitable for mental knowledge elicitation: it allows one to represent the full range of cause-effect knowledge, accurately or fuzzily as one sees fit depending on the depth of knowledge he/she has. This feature combined with excellent reliability and validity poses CMG as a promising method that has the potential to be used in various areas, such as software dependability requirement elicitation, software dependability assessment and dependability risk control.
J. T. Fan - One of the best experts on this subject based on the ideXlab platform.
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Characterizing the transplanar and in-plane water transport properties of fabrics under different sweat rate: Forced Flow Water Transport Tester
Scientific Reports, 2015Co-Authors: K. P. M. Tang, K. H. Chau, C. W. Kan, J. T. FanAbstract:The water absorption and transport properties of fabrics are critical to wear comfort, especially for sportswear and protective clothing. A new testing apparatus, namely Forced Flow Water Transport Tester (FFWTT), was developed for characterizing the transplanar and in-plane wicking properties of fabrics based on gravimetric and image analysis technique. The uniqueness of this instrument is that the rate of water supply is adjustable to simulate varying sweat rates with reference to the specific end-use conditions ranging from sitting, walking, running to other strenuous activities. This instrument is versatile in terms of the types of fabrics that can be tested. Twenty four types of fabrics with varying constructions and surface finishes were tested. The results showed that FFWTT was highly sensitive and reproducible in differentiating these fabrics and it suggests that water absorption and transport properties of fabrics are sweat rate-dependent. Additionally, two Graphic Methods were proposed to map the direction of liquid transport and its relation to skin wetness, which provides easy and direct comparison among different fabrics. Correlation analysis showed that FFWTT results have strong correlation with subjective wetness sensation, implying validity and usefulness of the instrument.
K. P. M. Tang - One of the best experts on this subject based on the ideXlab platform.
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Characterizing the transplanar and in-plane water transport properties of fabrics under different sweat rate: Forced Flow Water Transport Tester
Scientific Reports, 2015Co-Authors: K. P. M. Tang, K. H. Chau, C. W. Kan, J. T. FanAbstract:The water absorption and transport properties of fabrics are critical to wear comfort, especially for sportswear and protective clothing. A new testing apparatus, namely Forced Flow Water Transport Tester (FFWTT), was developed for characterizing the transplanar and in-plane wicking properties of fabrics based on gravimetric and image analysis technique. The uniqueness of this instrument is that the rate of water supply is adjustable to simulate varying sweat rates with reference to the specific end-use conditions ranging from sitting, walking, running to other strenuous activities. This instrument is versatile in terms of the types of fabrics that can be tested. Twenty four types of fabrics with varying constructions and surface finishes were tested. The results showed that FFWTT was highly sensitive and reproducible in differentiating these fabrics and it suggests that water absorption and transport properties of fabrics are sweat rate-dependent. Additionally, two Graphic Methods were proposed to map the direction of liquid transport and its relation to skin wetness, which provides easy and direct comparison among different fabrics. Correlation analysis showed that FFWTT results have strong correlation with subjective wetness sensation, implying validity and usefulness of the instrument.
Dong Pei-bei - One of the best experts on this subject based on the ideXlab platform.
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Spherical Triangle Graphic Methods Based on the Relation of Spherical Triangle and Triangular Pyramid
Journal of Engineering Graphics, 2001Co-Authors: Dong Pei-beiAbstract:In this paper the relation of spherical triangle with triangalar pyramid is expounded.At this new viewpoint the Graphic method to solute spherical triangle problems by descriptive geometry is found .
