Recently, there has been a rapid development in computer technology, which has in turn led to develop the fully robotic welding system using artificial intelligence （AI） technology. However, the robotic welding syst...Recently, there has been a rapid development in computer technology, which has in turn led to develop the fully robotic welding system using artificial intelligence （AI） technology. However, the robotic welding system has not been achieved due to difficulties of the mathematical model and sensor technologies. The possibilities of the fuzzy regression method to predict the bead geometry, such as bead width, bead height, bead penetration and bead area in the robotic GMA （gas metal arc） welding process is presented. The approach, a well-known method to deal with the problems with a high degree of fuzziness, is used to build the relationship between four process variables and the four quality characteristics, respectively. Using these models, the proper prediction of the process variables for obtaining the optimal bead geometry can be determined.展开更多
Objective： Hie （cold sensation） is one of the most well-known health complaints in Japan and elsewhere in East Asia. Those who suffer from severe hie are considered to have hiesho （cold disorder）. This study was ...Objective： Hie （cold sensation） is one of the most well-known health complaints in Japan and elsewhere in East Asia. Those who suffer from severe hie are considered to have hiesho （cold disorder）. This study was conducted to determine symptoms associated with hie in young females using a survey consisting of the hie scale and hie diary. Methods： Two hundred and seventy-one participants were included for the analysis. Survey forms were distributed to the participants. Diagnosis of hiesho was determined by using the hie scale. A discriminant score of over -0.38 was considered hiesho. The Short Form-8 Health Survey Standard Version （SF-8） was used to measure health-related quality of life （QOL）. The participants were also asked to respond to the questionnaire evaluating 14 physical and emotional symptoms, utilizing a six-level Likert scale item. Results： The 1st factor （hie factor） was correlated with hie （r= 0.546）, dry mouth （r= 0.332）, lower- extremity edema （r = 0.450）, headrushes （r=0.470）, shoulder stiffness （r = 0.311 ）, headrushes with chills （r = 0.726）, and fatigue （r= 0.359）. Cronbach＇s α of the 1st factor was 0.748, which indicated reliability between the items. When hie factor was the dependent variable, standardized partial regression coefficient was β=-0.387 for physical component score （P 〈 0.001） and β=-0.243 for mental component score （P 〈 0.001 ）. Conclusion： This study indicated that hiesho symptoms among young female adults were associated with bodily pain and general health perceptions of the SF-8 QOL survey.展开更多
文摘Recently, there has been a rapid development in computer technology, which has in turn led to develop the fully robotic welding system using artificial intelligence （AI） technology. However, the robotic welding system has not been achieved due to difficulties of the mathematical model and sensor technologies. The possibilities of the fuzzy regression method to predict the bead geometry, such as bead width, bead height, bead penetration and bead area in the robotic GMA （gas metal arc） welding process is presented. The approach, a well-known method to deal with the problems with a high degree of fuzziness, is used to build the relationship between four process variables and the four quality characteristics, respectively. Using these models, the proper prediction of the process variables for obtaining the optimal bead geometry can be determined.
基金supported by Tsukuba University of Technology,Promotional Projects for Advanced Education and Research
文摘Objective： Hie （cold sensation） is one of the most well-known health complaints in Japan and elsewhere in East Asia. Those who suffer from severe hie are considered to have hiesho （cold disorder）. This study was conducted to determine symptoms associated with hie in young females using a survey consisting of the hie scale and hie diary. Methods： Two hundred and seventy-one participants were included for the analysis. Survey forms were distributed to the participants. Diagnosis of hiesho was determined by using the hie scale. A discriminant score of over -0.38 was considered hiesho. The Short Form-8 Health Survey Standard Version （SF-8） was used to measure health-related quality of life （QOL）. The participants were also asked to respond to the questionnaire evaluating 14 physical and emotional symptoms, utilizing a six-level Likert scale item. Results： The 1st factor （hie factor） was correlated with hie （r= 0.546）, dry mouth （r= 0.332）, lower- extremity edema （r = 0.450）, headrushes （r=0.470）, shoulder stiffness （r = 0.311 ）, headrushes with chills （r = 0.726）, and fatigue （r= 0.359）. Cronbach＇s α of the 1st factor was 0.748, which indicated reliability between the items. When hie factor was the dependent variable, standardized partial regression coefficient was β=-0.387 for physical component score （P 〈 0.001） and β=-0.243 for mental component score （P 〈 0.001 ）. Conclusion： This study indicated that hiesho symptoms among young female adults were associated with bodily pain and general health perceptions of the SF-8 QOL survey.
