Real-Time Machine Learning Based Open Switch Fault Detection and Isolation for Multilevel Multiphase Drives

Due to the rapid proliferation interest of the multiphase machines and their combination with multilevel inverters technology, the demand for high reliability and resilient in the multiphase multilevel drives is increased. High reliability can be achieved by deploying systematic preventive real-time monitoring, robust control, and efficient fault diagnosis strategies. Fault diagnosis, as an indispensable methodology to preserve the seamless post-fault operation, is carried out in consecutive steps; monitoring the observable signals to generate the residuals, evaluating the observations to make a binary decision if any abnormality has occurred, and identifying the characteristics of the abnormalities to locate and isolate the failed components. It is followed by applying an appropriate reconfiguration strategy to ensure that the system can tolerate the failure. The primary focus of presented dissertation was to address employing computational and machine learning techniques to construct a proficient fault diagnosis scheme in multilevel multiphase drives. First, the data-driven nonlinear model identification/prediction methods are used to form a hybrid fault detection framework, which combines module-level and system-level methods in power converters, to enhance the performance and obtain a rapid real-time detection. Applying suggested nonlinear model predictors along with different systems (conventional two-level inverter and three-level neutral point clamped inverter) result in reducing the detection time to 1% of stator current fundamental period without deploying component-level monitoring equipment. Further, two methods using semi-supervised learning and analytical data mining concepts are presented to isolate the failed component. The semi-supervised fuzzy algorithm is engaged in building the clustering model because the deficient labeled datasets (prior knowledge of the system) leads to degraded performance in supervised clustering. Also, an analytical data mining procedure is presented based on data interpretability that yields two criteria to isolate the failure. A key part of this work also dealt with the discrimination between the post-fault characteristics, which are supposed to carry the data reflecting the fault influence, and the output responses, which are compensated by controllers under closed-loop control strategy. The performance of all designed schemes is evaluated through experiments

Real-Time Machine Learning Based Open Switch Fault Detection and Isolation for Multilevel Multiphase Drives

Due to the rapid proliferation interest of the multiphase machines and their combination with multilevel inverters technology, the demand for high reliability and resilient in the multiphase multilevel drives is increased. High reliability can be achieved by deploying systematic preventive real-time monitoring, robust control, and efficient fault diagnosis strategies. Fault diagnosis, as an indispensable methodology to preserve the seamless post-fault operation, is carried out in consecutive steps; monitoring the observable signals to generate the residuals, evaluating the observations to make a binary decision if any abnormality has occurred, and identifying the characteristics of the abnormalities to locate and isolate the failed components. It is followed by applying an appropriate reconfiguration strategy to ensure that the system can tolerate the failure. The primary focus of presented dissertation was to address employing computational and machine learning techniques to construct a proficient fault diagnosis scheme in multilevel multiphase drives. First, the data-driven nonlinear model identification/prediction methods are used to form a hybrid fault detection framework, which combines module-level and system-level methods in power converters, to enhance the performance and obtain a rapid real-time detection. Applying suggested nonlinear model predictors along with different systems (conventional two-level inverter and three-level neutral point clamped inverter) result in reducing the detection time to 1% of stator current fundamental period without deploying component-level monitoring equipment. Further, two methods using semi-supervised learning and analytical data mining concepts are presented to isolate the failed component. The semi-supervised fuzzy algorithm is engaged in building the clustering model because the deficient labeled datasets (prior knowledge of the system) leads to degraded performance in supervised clustering. Also, an analytical data mining procedure is presented based on data interpretability that yields two criteria to isolate the failure. A key part of this work also dealt with the discrimination between the post-fault characteristics, which are supposed to carry the data reflecting the fault influence, and the output responses, which are compensated by controllers under closed-loop control strategy. The performance of all designed schemes is evaluated through experiments

Educational Quality and Facilities Assessment in the Department of Restorative Dentistry from the Viewpoint of Dentistry Students of Kerman University of Medical Sciences, Iran, in 2014

Background & Objective: Restorative dentistry is a fundamental field in dentistry and students’ opinions about its education can be helpful in finding its deficiencies and solving them. The aim of this study was to evaluate dentistry students’ attitudes toward restorative dentistry education, and its facilities and physical environment. Methods: This descriptive, cross-sectional study was performed on fourth, fifth, and sixth year students of the School of Dentistry of Kerman University of Medical Sciences, Iran. The data collection tool was a two-part questionnaire consisting of demographic characteristics form and 38 questions about environment, facilities, and educational and exam methods, and 1 open question scored based on a Likert scale (very appropriate to inappropriate). Data were analyzes using t-test, ANOVA, and linear regression in SPSS software. The significant level was considered as 0.05 in all tests. Results: Among the 110 participates, 61.8% were women and 38.2% were men. The average attitude score (from 26 to 130) was 84.86 ± 11.30. Overall attitude score was not significantly different between genders, academic years, and different restorative scores. However, in the education field, the fifth and sixth year students had significantly higher attitude scores than the fourth year students. Conclusion: Satisfaction with the clinical and theoretical education of restorative dentistry in the School of Dentistry of Kerman University of Medical Sciences is acceptable, but its physical environment and facilities must be improved. Key Words: Restorative dentistry, Education, Students, Attitude, Kerman (Iran

Global prevalence of nosocomial infection: A systematic review and meta-analysis

Objectives: Hospital-acquired infections (HAIs) are significant problems as public health issues which need attention. Such infections are significant problems for society and healthcare organizations. This study aimed to carry out a systematic review and a meta-analysis to analyze the prevalence of HAIs globally.   Methods: We conducted a comprehensive search of electronic databases including EMBASE, Scopus, PubMed and Web of Science between 2000 and June 2021. We found 7031 articles. After removing the duplicates, 5430 studies were screened based on the titles/abstracts. Then, we systematically evaluated the full texts of the 1909 remaining studies and selected 400 records with 29,159,630 participants for meta-analysis. Random-effects model was used for the analysis, and heterogeneity analysis and publication bias test were conducted.   Results: The rate of universal HAIs was 0.14 percent. The rate of HAIs is increasing by 0.06 percent annually. The highest rate of HAIs was in the AFR, while the lowest prevalence were in AMR and WPR. Besides, AFR prevalence in central Africa is higher than in other parts of the world by 0.27 (95% CI, 0.22-0.34). Besides, E. coli infected patients more than other micro-organisms such as Coagulase-negative staphylococci, Staphylococcus spp. and Pseudomonas aeruginosa. In hospital wards, Transplant, and Neonatal wards and ICU had the highest rates. The prevalence of HAIs was higher in men than in women.   Conclusion: We identified several essential details about the rate of HAIs in various parts of the world. The HAIs rate and the most common micro-organism were different in various contexts. However, several essential gaps were also identified. The study findings can help hospital managers and health policy makers identify the reason for HAIs and apply effective control programs to implement different plans to reduce the HAIs rate and the financial costs of such infections and save resources

Water and Wastewater Treatment Systems by Novel Integrated Membrane Distillation (MD)

The scarcity of freshwater has been recognized as one of the main challenges people must overcome in the 21st century. The adoption of an environmentally friendly, cost-effective, and energy-efficient membrane distillation (MD) process can mitigate the pollution caused by industrial and domestic wastes. MD is a thermally driven process based on vapor–liquid equilibrium, in which the separation process takes place throughout a microporous hydrophobic membrane. The present paper offers a comprehensive review of the state-of-the-art MD technology covering the MD applications in wastewater treatment. In addition, the important and sophisticated recent advances in MD technology from the perspectives of membrane characteristics and preparation, membrane configurations, membrane wetting, fouling, and renewable heat sources have been presented and discussed

Assessing the viewpoint of faculty members of medical record departments in Iran about the impact of Information Technology on health system 2004

Background: Understanding the potential impact of information technology on health system can be used as a basis for health promotion based on information technology (IT). Undoubtedly, faculty members of medical record departments in Iranian medical universities have a significant role in knowledge gain of college students about the effectiveness of information technology on health system. Methods: In order to assess the impact of IT on health system in the viewpoint of faculty members of medical record departments in Iranian medical universities, a cross sectional survey was conducted and questionnaires were sent to 17 universities with medical records departments. The questionnaire had three sections: The effect of IT on health information management (including: quantitative and qualitative promotion of documentations, follow up and referral, demand management and income and cost system), medical research and medical education. To investigate the correlations between variables of the study, X2 and exact fisher tests were used. Result: From 64 distributed questionnaires, a total of 49 were completed. The majority of faculty members (%40.81) believed that the use of IT enhances the utilization of paper documents. %26.53 believed that the use of IT has high impact on increase of medical errors. The majority of members (%36.75) considered IT to have a medium impact on self-therapy. The impact of information technology on medical research and medical education was believed to be very high by 83.67% and 79.59% of respondents, respectively. We did not find any correlation between the impact of IT on the studied variables and demographic data of participants such as age, gender and the years of teaching. Discussion: Most of faculty members of medical record departments have a high knowledge about the impact of IT on promotion of the management of health, research and education in medical sciences, but their knowledge about effectiveness of IT on quality of health services and its adverse effect was not proper. Therefore, the knowledge of faculty members of medical record departments in Iranian medical universities about the impact of IT on the quality of health services should be increased by educational programs

Antibacterial properties of nanoporous graphene oxide/cobalt metal organic framework

Metal-organic framework (MOF) based graphene oxide (GO) recently merits of attention because of the relative correspondence of GO with metal ions and organic binding linkers. Furthermore, introducing the GO to the Co-MOF to make a new nanoporous hybrid have are improved the selectivity and stability of the Co-MOF. Here the graphene oxide/cobalt metal organic framework (GO/Co-MOF) was synthesized by a solvothermal process using cobalt salt and terephthalic acid and used for biocidal activity, against the growth of the Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus bacteria. X-ray diffraction, Fourier transform infrared spectroscopy and Raman spectroscopy were confirmed the successful synthesize of metal organic framework and incorporation of Co-MOF in to GO sheets. Scanning electron microscopy was showed the cornflower structure of GO/Co-MOF, and transmission electron microscopy was confirmed, the Co-MOF are decorated on GO. Cytotoxicity study of GO/Co-MOF using 3-[4,5-dimethylthiazol-2yl]-2,5-diphenyltetrazolium bromide (MTT) cell viability assay showed the biocompatibility to human fibroblasts cell over 72 h. The growth inhibition of the Escherichia coli and Staphylococcus aureus bacteria are reached over 99% for bacteria concentration of 100 mu g/mL. The excellent antibacterial activity of GO based Co-MOF is linked to synergistic effect of sharp edges of the GO sheets and the toxic effect of cobalt ions (Co2+) which are released from their surfaces. The GO/Co-MOF radical scavenging assay was measured using 1,1-diphenyl-2-picrylhydrazyl (DPPH) antioxidant assay for samples incubated with cells which confirmed the minimum radicals' toxicity on bacteria. This novel graphene oxide based MOF with its intrinsic superior porous structure, highly active metal coordination, and commercial linker, is an excellent promising candidate to use in biological and pharmaceutical applications as high potential sustained bactericidal materials

Global prevalence of nosocomial infection: A systematic review and meta-analysis.

ObjectivesHospital-acquired infections (HAIs) are significant problems as public health issues which need attention. Such infections are significant problems for society and healthcare organizations. This study aimed to carry out a systematic review and a meta-analysis to analyze the prevalence of HAIs globally.MethodsWe conducted a comprehensive search of electronic databases including EMBASE, Scopus, PubMed and Web of Science between 2000 and June 2021. We found 7031 articles. After removing the duplicates, 5430 studies were screened based on the titles/ abstracts. Then, we systematically evaluated the full texts of the 1909 remaining studies and selected 400 records with 29,159,630 participants for meta-analysis. Random-effects model was used for the analysis, and heterogeneity analysis and publication bias test were conducted.ResultsThe rate of universal HAIs was 0.14 percent. The rate of HAIs is increasing by 0.06 percent annually. The highest rate of HAIs was in the AFR, while the lowest prevalence were in AMR and WPR. Besides, AFR prevalence in central Africa is higher than in other parts of the world by 0.27 (95% CI, 0.22-0.34). Besides, E. coli infected patients more than other micro-organisms such as Coagulase-negative staphylococci, Staphylococcus spp. and Pseudomonas aeruginosa. In hospital wards, Transplant, and Neonatal wards and ICU had the highest rates. The prevalence of HAIs was higher in men than in women.ConclusionWe identified several essential details about the rate of HAIs in various parts of the world. The HAIs rate and the most common micro-organism were different in various contexts. However, several essential gaps were also identified. The study findings can help hospital managers and health policy makers identify the reason for HAIs and apply effective control programs to implement different plans to reduce the HAIs rate and the financial costs of such infections and save resources

Meta-regression based on age and length of saty.

Meta-regression based on age and length of saty.</p