We argue that employers subject workers to time theft by controlling workers’ time—both on and off the clock. Time theft considers employer control of workers’ time without the promise of pay through unstable scheduling practices as well as beyond their scheduled work hours. We develop a typology of time theft through a discussion of survey and workshop data with retail workers in Los Angeles. We underscore how federal labor law is inadequate to address unstable scheduling and we discuss retail worker organizing and the implications of time theft for labor policy and worker movements.
One of the most significant pandemics has been raised in the form of Coronavirus disease 2019 . Many researchers have faced various types of challenges for finding the accurate model which can automatically detect the COVID-19 using Computed pulmonary Tomography (CT) scans of the chest. This paper has also focused on the same area, and a fully automatic model has been developed which can predict the COVID-19 using the chest CT scans. The performance of the proposed method has been evaluated by classifying the CT scans of community-acquired pneumonia (CAP) and other non-pneumonia. The proposed deep learning model is based on ResNet 50, named CORNet for the detection of COVID-19, and also performed the retrospective and multicenter analysis for the extraction of visual characteristics from volumetric chest CT scans during COVID-19 detection. Between August 2016 and May 2020, the datasets were obtained from six hospitals. Results are evaluated on the image dataset consisting of a total of 10,052 CT scan images generated from 7,850 patients, and the average age of the patients was 50 years. The implemented model has achieved the sensitivity and specificity of 90% and 96%, per scanned image with an AUC of 0. 95.
The Internet has been welcomed by educators as a great tool for use in the classroom or to create virtual classrooms. It can be used to connect students in disparate countries as well as an increase in student comfort with technology. This paper highlights some of the unplanned and unanticipated consequences that might be encountered as the use of the Internet in education increases. These consequences are discussed as potential problems, categorised as problems of judgement, distance, and ethics. Implications for educators and administrators are addressed by suggesting course design, pedagogical, and student activity solutions.
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