Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalizati...Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.展开更多
To improve high quality and/or retain achieved high quality of an academic program, time to time evaluation for quality of each covered course is often an integrated aspect considered in reputed institutions, however,...To improve high quality and/or retain achieved high quality of an academic program, time to time evaluation for quality of each covered course is often an integrated aspect considered in reputed institutions, however, there has been little effort regarding humanities courses. This research article deals with analysis of evaluation data collected regarding humanities course from a College of Commerce & Economics, Mumbai, Maharashtra, India, on Likert type items. Appropriateness of one parametric measure and three non-parametric measures are discussed and used in this regard which could provide useful clues for educational policy planners. Keeping in view of the analytical results using these four measures, regardless of the threshold regarding satisfaction among students, overall performance of almost every subject has been un-satisfactory. There is a need to make a focused approach to take every course at the level of high performance. The inconsistency noticed under every threshold further revealed that under such poorly performing subjects globally, one needs to analyze merely at the global level item. Once the global level analysis reveals high performance of a course, then only item specific analysis may need to be focused to find out the items requiring further improvements.展开更多
Background:Magnetic resonance imaging(MRI)is crucial in modern medical diagnostics,providing detailed insights into soft tissue structures and pathological changes.Traditional grayscale images can sometimes obscure cr...Background:Magnetic resonance imaging(MRI)is crucial in modern medical diagnostics,providing detailed insights into soft tissue structures and pathological changes.Traditional grayscale images can sometimes obscure critical details,complicating accurate interpretations.Automated color coding of the MRI signal intensities may enhance the visualization of various pa-thologies,potentially leading to improved diagnostic accuracy and image quality.This paper aims to explore the effectiveness of color-coded MR image reconstruction in enhancing both diagnostic precision and overall image quality in musculoskeletal MRI.Methods:Two fellowship-trained musculoskeletal radiologists evaluated the images reconstructed with color coding,rating their diagnostic value,image quality,and visual appeal using a five-point Likert scale.To assess interrater reliability,Cohen's Kappa statistical analysis was performed.Additionally,descriptive statistics summarizing the Likert scores for diagnostic value,image quality,and visual appeal of the reconstructed images have been described.Results:Statistical analysis of the data revealed that the diagnostic value,image value,and visual appeal of the color-coded MR images were excellent in almost two-thirds of the data set.The minimum Likert score recorded was 3,signifying a good quality rating.Conclusion:Our study shows positive results,supporting the efficiency of color-coded MR imaging in aiding the conventional gray scale MR imaging to improve its diagnostic efficiency.展开更多
Likert scales are a common methodological tool for data collection used in quantitative or mixed-method approaches in multiple domains.They are often employed in surveys or questionnaires,for benchmarking answers in t...Likert scales are a common methodological tool for data collection used in quantitative or mixed-method approaches in multiple domains.They are often employed in surveys or questionnaires,for benchmarking answers in the fields of disaster risk reduction,business continuity management,and organizational resilience.However,both scholars and practitioners may lack a simple scale of reference to assure consistency across disciplinary fields.This article introduces a simple-to-use rating tool that can be used for benchmarking responses in questionnaires,for example,for assessing disaster risk reduction,gaps in operational capacity,and organizational resilience.We aim,in particular,to support applications in contexts in which the target groups,due to cultural,social,or political reasons,may be unsuitable for in-depth analyses that use,for example,scales from 1 to 7 or from 1 to 10.This methodology is derived from the needs emerged in our recent fieldwork on interdisciplinary projects and from dialogue with the stakeholders involved.The output is a replicable scale from 0 to 3 presented in a table that includes category labels with qualitative attributes and descriptive equivalents to be used in the formulation of model answers.These include examples of levels of resilience,capacity,and gaps.They are connected to other tools that could be used for in-depth analysis.The advantage of our Likert scale-based response model is that it can be applied in a wide variety of disciplines,from social science to engineering.展开更多
基金Supported by the National Natural Science Foundation of China(61473026,61104131)the Fundamental Research Funds for the Central Universities(JD1413)
文摘Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.
文摘To improve high quality and/or retain achieved high quality of an academic program, time to time evaluation for quality of each covered course is often an integrated aspect considered in reputed institutions, however, there has been little effort regarding humanities courses. This research article deals with analysis of evaluation data collected regarding humanities course from a College of Commerce & Economics, Mumbai, Maharashtra, India, on Likert type items. Appropriateness of one parametric measure and three non-parametric measures are discussed and used in this regard which could provide useful clues for educational policy planners. Keeping in view of the analytical results using these four measures, regardless of the threshold regarding satisfaction among students, overall performance of almost every subject has been un-satisfactory. There is a need to make a focused approach to take every course at the level of high performance. The inconsistency noticed under every threshold further revealed that under such poorly performing subjects globally, one needs to analyze merely at the global level item. Once the global level analysis reveals high performance of a course, then only item specific analysis may need to be focused to find out the items requiring further improvements.
文摘Background:Magnetic resonance imaging(MRI)is crucial in modern medical diagnostics,providing detailed insights into soft tissue structures and pathological changes.Traditional grayscale images can sometimes obscure critical details,complicating accurate interpretations.Automated color coding of the MRI signal intensities may enhance the visualization of various pa-thologies,potentially leading to improved diagnostic accuracy and image quality.This paper aims to explore the effectiveness of color-coded MR image reconstruction in enhancing both diagnostic precision and overall image quality in musculoskeletal MRI.Methods:Two fellowship-trained musculoskeletal radiologists evaluated the images reconstructed with color coding,rating their diagnostic value,image quality,and visual appeal using a five-point Likert scale.To assess interrater reliability,Cohen's Kappa statistical analysis was performed.Additionally,descriptive statistics summarizing the Likert scores for diagnostic value,image quality,and visual appeal of the reconstructed images have been described.Results:Statistical analysis of the data revealed that the diagnostic value,image value,and visual appeal of the color-coded MR images were excellent in almost two-thirds of the data set.The minimum Likert score recorded was 3,signifying a good quality rating.Conclusion:Our study shows positive results,supporting the efficiency of color-coded MR imaging in aiding the conventional gray scale MR imaging to improve its diagnostic efficiency.
基金BA/Leverhulme Small Research Grant Award 2019 supported by the United Kingdom’s Department for Business,Energy and Industrial Strategy(Grant Reference:SRG19/191797)the Earthquake Engineering Field Investigation Team Award 2019 by the Institution of Structural Engineers in the UK+2 种基金the Mexican Consejo Nacional de Ciencia y Tecnología(Grant Reference:398485)the European Union’s Horizon 2020 Research and Innovation Programme(Grant Agreement:821046)the TURNkey(Towards more Earthquakeresilient Urban Societies through a Multi-sensor-based Information System enabling Earthquake Forecasting,Early Warning and Rapid Response actions)Project。
文摘Likert scales are a common methodological tool for data collection used in quantitative or mixed-method approaches in multiple domains.They are often employed in surveys or questionnaires,for benchmarking answers in the fields of disaster risk reduction,business continuity management,and organizational resilience.However,both scholars and practitioners may lack a simple scale of reference to assure consistency across disciplinary fields.This article introduces a simple-to-use rating tool that can be used for benchmarking responses in questionnaires,for example,for assessing disaster risk reduction,gaps in operational capacity,and organizational resilience.We aim,in particular,to support applications in contexts in which the target groups,due to cultural,social,or political reasons,may be unsuitable for in-depth analyses that use,for example,scales from 1 to 7 or from 1 to 10.This methodology is derived from the needs emerged in our recent fieldwork on interdisciplinary projects and from dialogue with the stakeholders involved.The output is a replicable scale from 0 to 3 presented in a table that includes category labels with qualitative attributes and descriptive equivalents to be used in the formulation of model answers.These include examples of levels of resilience,capacity,and gaps.They are connected to other tools that could be used for in-depth analysis.The advantage of our Likert scale-based response model is that it can be applied in a wide variety of disciplines,from social science to engineering.
