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Noman Ullah,Faisal Khan,Wasiq Ullah,Abdul Basit,Muhammad Umair,Zeeshan Khattak 한국자기학회 2018 Journal of Magnetics Vol.23 No.2
Magnetic saturation and complex stator structure of Switched Flux Permanent Magnet Machine (SFPMM) compels designers to adopt universally accepted numerical method of analysis i.e. Finite Element Analysis (FEA). FEA is not preferred for initial design due to its computational complexity and is time consuming process because of repeated iterations. This paper presents an accurate analytical approach for initial design of proposed twelve-stator-slot and ten-rotor-tooth (12/10) with trapezoidal slot structure SFPMM. Air-gap Magnetic Equivalent Circuit (MEC) models with Global Reluctance Network (GRN) methodology is utilized for calculation of open-circuit flux linkage. Fourier Analysis (FA) for cogging torque, and Maxwell Stress Tensor (MST) method for electromagnetic torque where radial and tangential components of the air-gap flux density are produced by the currents flowing in three phase armature winding. Analytical predictions are validated by FEA utilizing JMAG software and shows errors less than ~2% for open-circuit flux linkage, ~4.2% for cogging torque, and ~2% for average electromagnetic torque.
The Assessment of Occupational Injuries of Workers in Pakistan
Noman Muhammad,Mujahid Nooreen,Fatima Ambreen 한국산업안전보건공단 산업안전보건연구원 2021 Safety and health at work Vol.12 No.4
Background: The prevailing global work scenario and deteriorating health facilities in economies indulge the risk perspective in the labor market model. This is the reason that the risk factor is cautiously attributed to wages and labor market efficiencies specifically in developing and emerging economies. In this respect, Occupational Injuries of Workers (OIW) is considered essential to demonstrate the risk and Occupational Health and Safety (OHS) setups given the constraints of the labor. Intuitively, the prime objective of this study is to make an assessment of the labor market considering the OIW through the indicators of industry division, employment status, occupational distribution, adopted treatment, gender and regionality. Methods: The assessment strategy of the study has been categorized into trend analysis and Index Value Calculation (IVC) segments employing the data from 2001 to 2018. Results: The pattern of the selected indicators of the OIW has been observed in the available data while the IVC estimations are considered through time and reference categories. The findings of both exercises revealed absolute and relative heterogeneities at both industry and occupational levels. Conclusion: The consistency for gender and regional distribution of both assessments points out the need for effective policy initiatives. The study suggests separate analyses of industry and occupations for a better understanding of the OHS setups and up-gradation in Pakistan.
Noman Naseer,Keum-Shik Hong,M. Jawad Khan,M. Raheel Bhutta 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
In this paper we analyze and compare the performance of support vector machine (SVM) and artificial neural network (ANN) for classification of fNIRS signals. fNIRS signals due to mental arithmetic and mental counting are acquired from the prefrontal cortex of ten healthy subjects. After preprocessing and filtering, SVM and ANN classification is performed on the same feature set ? mean and slope of the changes in concentration of oxy-hemoglobin. Although no significant difference in the average classification accuracies, obtained using SVM and ANN, is observed (p = 0.2); it is noted that the standard deviation of classification accuracies using ANN is significantly higher than that of SVM. Furthermore, the computational speed of SVM is significantly higher than that of ANN. It is concluded that SVM offers stable classification accuracies and fast computation as compared to ANN.
Trends in Stroke Presentations before and during the COVID-19 Pandemic: A Meta-Analysis
Noman Ishaque,Asif Javed Butt,Joseph Kamtchum-Tatuene,Ali Zohair Nomani,Sarah Razzaq,Nida Fatima,Chetan Vekhande,Radhika Nair,Naveed Akhtar,Khurshid Khan,Maher Saqqur,Ashfaq Shuaib 대한뇌졸중학회 2022 Journal of stroke Vol.24 No.1
Background and Purpose There are reports of decline in the rates of acute emergency presentations during coronavirus disease 2019 (COVID-19) pandemic including stroke. We performed a meta-analysis of the impact of COVID-19 pandemic on rates of stroke presentations and on rates of reperfusion therapy. Methods Following the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines, we systematically searched the literature for studies reporting changes in stroke presentations and treatment rates before and during the COVID-19 pandemic. Aggregated data were pooled using meta-analysis with random-effect models. Results We identified 37 observational studies (n=375,657). Pooled analysis showed decline in rates of all strokes (26.0%; 95% confidence interval [CI], 22.4 to 29.7) and its subtypes; ischemic (25.3%; 95% CI, 21.0 to 30.0), hemorrhagic (27.6%; 95% CI, 20.4 to 35.5), transient ischemic attacks (41.9%; 95% CI, 34.8 to 49.3), and stroke mimics (45.6%; 95% CI, 33.5 to 58.0)during months of pandemic compared with the pre-pandemic period. The decline was most evident for mild symptoms (40% mild vs. 25%–29% moderate/severe). Although rates of intravenous thrombolytic (IVT) and endovascular thrombectomy (EVT) decreased during pandemic, the likelihood of being treated with IVT and EVT did not differ between the two periods, both in primary and in comprehensive stroke centers (odds ratio [OR], 1.08; 95% CI, 0.94 to 1.24 and OR,0.95; 95% CI, 0.83 to 1.09, respectively). Conclusions Rates of all strokes types decreased significantly during pandemic. It is of paramount importance that general population should be educated to seek medical care immediately for stroke-like symptoms during COVID-19 pandemic. Whether delay in initiation of secondary prevention would affect eventual stroke outcomes in the long run needs further study.