In this paper, the mechanism of fabric-evoked prickle is discussed, which indicates that the mechanical stimuli aroused by the fiber ends on the fabric surface to the skin-sensory receptors are responsible for prickle...In this paper, the mechanism of fabric-evoked prickle is discussed, which indicates that the mechanical stimuli aroused by the fiber ends on the fabric surface to the skin-sensory receptors are responsible for prickle. The factors influencing the intensity of prickle are specialized and anatomized. Several means of sense estimate, including the corresponding statistical measures, are described. A few groping objective methods of evaluating prickle are analyzed, including the testing principles, the advantages and the disadvantages. At last, a new concept is proposed on the objective evaluation of prickle.展开更多
Converting between “fuzzy concept” and “numerical value” in computer aided assessment is rather difficult in many applications. This paper presents a LVQ neural network paradigm for sensory evaluation. This intell...Converting between “fuzzy concept” and “numerical value” in computer aided assessment is rather difficult in many applications. This paper presents a LVQ neural network paradigm for sensory evaluation. This intelligent approach utilizes predefined class information for supervised learning in order to solve the converting problem and keep the fuzziness and imprecision of the whole sensory information. The method is validated by the experiment on stimulation evaluation of cigarette sensory.展开更多
文摘In this paper, the mechanism of fabric-evoked prickle is discussed, which indicates that the mechanical stimuli aroused by the fiber ends on the fabric surface to the skin-sensory receptors are responsible for prickle. The factors influencing the intensity of prickle are specialized and anatomized. Several means of sense estimate, including the corresponding statistical measures, are described. A few groping objective methods of evaluating prickle are analyzed, including the testing principles, the advantages and the disadvantages. At last, a new concept is proposed on the objective evaluation of prickle.
文摘Converting between “fuzzy concept” and “numerical value” in computer aided assessment is rather difficult in many applications. This paper presents a LVQ neural network paradigm for sensory evaluation. This intelligent approach utilizes predefined class information for supervised learning in order to solve the converting problem and keep the fuzziness and imprecision of the whole sensory information. The method is validated by the experiment on stimulation evaluation of cigarette sensory.
