ABSTRACT
Amidst Covid-19, identity fraud in exams is becoming more and more advanced. Therefore, identifying these fake candidates accurately has become a difficult problem in exam administration. The novelty of this work is the introduction of optimized Inception ResNetV2 for an ideal online testing system where the system can detect the faces of test-takers and generate a report of the automated monitoring of the candidate. The point of the work is to design a biometric module that is to be implemented as the candidate authentication and identity verification proctoring method for the exams. For research, the suggested method concentrates on a single image. The system integrates various technologies, such as facial imaging, human-computer interaction, data transmission, and communication. Using video proctoring, the system can continuously monitor the examinee's behaviour by live streaming. This is done by using, MediaPipe Face Mesh, MediaPipe Face Detection, Pretrained Inception-ResNet-v2 Convolutional Neural Network, Django Framework, and OpenCV. The proposed work involves two modules: Online Examination Management and Face Recognition Proctor. This research attempts to build automated face recognition and identity features in order to detect fraud. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Background and aims: Optimal management of carotid artery freefloating thrombus (CAFFT) and CAFFT-related strokes remains unclear. We sought to examine the clinical characteristics, treatment strategies and patient outcomes for CAFFT-related ischaemic strokes. Methods: We conducted a single-centre retrospective observational study by extracting data from electronic patient records. We included consecutive patients admitted between 2016-2021 with ischaemic stroke and CAFFT on initial CT/MR angiogram. Results: We included 59 patients (mean age 63, 66% male). Vascular risk factors included hypertension (42%), diabetes (19%), dyslipidaemia (27%), previous stroke (10%), smoking history (56%) and alcohol excess (14%). 6 patients (10%) were COVID-19 positive. Median modified Rankin score was 0 and mean NIHSS was 11. On admission, 42% were taking antiplatelet agents, 10% were on anticoagulant, 34% had CRP >10mg/L, and 14% had eGFR <50 ml/min/1.73m2. On arrival, 27% received IV thrombolysis and 19% underwent mechanical thrombectomy. Acute antithrombotic strategies included IV heparin (49%), low molecular weight heparin (47%), oral anticoagulation (15%), and antiplatelet agents (63%). 24 patients (41%) were referred to vascular surgery, of whom 9 (38%, 15% of total) received emergency carotid endarterectomy. Neurological deterioration (<7 days) occurred in 14%. In-hospital mortality was 8% overall, but 67% for COVID-positive patients. At 6 months, recurrent stroke occurred in 12% and mortality was 3%. Conclusions: CAFFT-related ischaemic stroke is associated with significant mortality and neurological morbidity. The use of different acute antithrombotic strategies and emergency carotid endarterectomy varied significantly between patients. These major treatment options should be subjects of future clinical trials.
ABSTRACT
Background: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is global pandemic. MUMBAI HEART CLINIC is a tertiary care centre in the heart of chembur with more than 60 health care workers and catering more than 500 patients per month for OPD services and almost 100 in door patients with more than 50 Cath lab procedures and almost equal number of surgical cases in a month. Objective: protocols and ‘nine parameter model’ in the prevention of COVID 19, single centre experience. Methods: Core team was established. Internal check points were identified and policies were framed to minimise contact and prevent spread of infection. We followed ‘Nine parameter model’ of hand washing, physical distancing, temperature measurement, saturation measurement, face mask, hand sanitization, prophylaxis of HCQS, symptoms of SARS-CoV-2 and wearing Personal protective equipment’s. Results: It was found that nine parameter model was practically feasible and highly effective in avoiding spread of SARS-CoV-2. Conclusion: The ‘Nine parameter model’ adopted by our hospital is a simple and effective method not only to prevent but also to early detect the presence of SARS-CoV-2 infection. These simple measures along with identifying internal check points were instrumental in preventing spread of SARS-COV-2 infection and at the same time allowing for smooth working of hospital.