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1.
Ieee Transactions on Emerging Topics in Computational Intelligence ; : 10, 2022.
Article in English | Web of Science | ID: covidwho-1886622

ABSTRACT

Coronavirus disease 2019 (COVID-19) generated a global public health emergency since December 2019, causing huge economic losses. To help radiologists strengthen their recognition of COVID-19 cases, we developed a computer-aided diagnosis system based on deep learning to automatically classify chest computed tomography-based COVID-19, Tuberculosis, and healthy control subjects. Our novel classification model AdaD-FNN sequentially transfers the trained knowledge of an FNN estimator to the next FNN estimator while updating the weights of the samples in the training set with a decaying learning rate. This model inhibits the network from remembering the noisy information and improves the learning of complex patterns in the hard-to-identify samples. Moreover, we designed a novel image preprocessing model F-U2MNet-C by enhancing the image features using fuzzy stacking and eliminating the interference factors using U2MNet segmentation. Extensive experiments are conducted on four publicly available datasets namely, TLDCA, UCSD-Al4H, SARS-CoV-2, TCIA, and the obtained classification accuracies are 99.52%, 92.96%, 97.86%, 91.97%. Our novel system gives out compelling performance for assisting COVID-19 detection when compared with 22 state-of-the-art methods. We hope to help link together biomedical research and artificial intelligence and to assist the diagnosis of doctors, radiologists, and inspectors at each epidemic prevention site in the real world.

2.
Kybernetes ; ahead-of-print(ahead-of-print):24, 2021.
Article in English | Web of Science | ID: covidwho-1550698

ABSTRACT

Purpose This study aims to investigate the impact of skills and knowledge of employees, economic situations of the company, current IT infrastructure, payment fashion, cloud availability, and cloud privacy and security on the productivity of the human resources in the COVID-19 era. Design/methodology/approach Over the past few years, the advent of cloud-assisted technologies has dramatically advanced the Information Technology (IT)-based industries by providing everything as a service. Cloud computing is recognized as a growing technology among companies around the world. One of the most critical cloud applications is deploying systems and organizational resources, especially systems whose deployment costs are high. Manpower is one of the basic and vital resources of the organization, and organizations need an efficient workforce to achieve their goals. But, in the COVID-19 era, human resources' productivity can be reduced due to stress, high labor force, reduced organizational performance and profits, unfavorable organizational conditions, inability to manage and lack of training. Therefore, this study tries to investigate the productivity of human resources in the COVID-19 era. Data were collected from the medium-sized companies through a questionnaire. Distributed questionnaires were conducted on the Likert scale. The model is assessed using the structural equation modeling technique to examine its reliability and validity. The study is a library method and literature review. A case study was conducted through a questionnaire and statistical analysis by SPSS 25 and SMART-PLS. Findings Based on the findings, the skills and knowledge of employees, the economic situations of the company, payment fashion, cloud availability and the current IT infrastructures of the company have a positive impact on human resource efficiency in the COVID-19 era. But cloud privacy and security have a negative effect on the productivity of human resources. The findings can be the basis for companies and organizations in the COVID-19 era. Research limitations/implications This study has some restrictions that need to be considered in evaluating the obtained results. First, due to the prevalence of Coronavirus, access to information from the companies under study was limited. Second, this research may have overlooked other variables that affect human resource productivity in the COVID-19 era. Prospective researchers can examine the impact of Customer Relationship Management (CRM) and Supply Chain Management (SCM) on the human resource's productivity in the COVID-19 era. Practical implications The results of this research are applicable for all companies, their departments and human resources in the COVID-19 era. Originality/value In this paper, human resources' productivity in the COVID-19 era is pointed out. The presented new model provides a complete framework for investigating cloud-based enterprise resource planning systems affect the productivity of human resources in the COVID-19 era.

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