Assessing the Current State of University-based Business Incubators (UBIS) in Canada and the UAE

There is a dearth of published research that explores UBIs from a comparative dimension across geographical and institutionalised contexts that assesses the current state and scope of UBI activities. This paper explores the current state of University-based Business Incubators (UBIs) both in the United Arab Emirates and Canada underpinned by a comparative case analysis approach. This study utilises both secondary and primary research data that was obtained through desk-based secondary research and qualitative methods of inquiry (semi-structured interviews) with UBI managers, academics, and support staff that were used to develop each case. This informed the development of 18 cases of UBIs in the United Arab Emirates and Canada (9 each, respectively). The data was collected through VoIP (Voice-Over-Internet-Protocol) and telephone during the COVID-19 pandemic from March 2021 to February 2022. The findings of the study illustrate that the Canadian context offers similar provisions of services for business incubators (BIs) but in comparison, the UAE-based university UBIs are much younger and are transitioning towards the development of various business and enterprise initiatives in Higher Education and are also focused on driving student recruitment using this provision. The value of this study is inherent in its comparative approach between two under-studied and represented empirical geographies (i.e., Canada and the UAE), the findings also indicate the divergence and specialisms adopted by institutions in the UAE based on the various provisions for the governmental vision 2030, and the empirical development of showcasing these initiatives to be novel for the efficacy of UBIs. © 2022, Academic Conferences and Publishing International Limited. All right reserved.

An empirical analysis on social responsibility education of college students in four universities in Shandong Province during COVID-19 Response

Since the 18th National Congress of the Communist Party of China, general secretary Xi Jinping has repeatedly stressed the issue of college students shouldering social responsibilities in the new era. He encourages college students to bear the responsibility of the times and learns to assume social responsibility. Based on the literature analysis, using the methods of data investigation and case analysis, the study explores how colleges and universities reasonably use and actively guide students to correctly understand and then agree to translate into action showing social responsibility. At the same time, according to the investigation of college students' sense of social responsibility, this paper analyzes the existing problems in education, so as to put forward objective and accurate feasible strategies and suggestions. © 2022 The Authors. Published by Elsevier B.V.

Study on the Discovery of Personal Information on the Network of People Diagnosed with COVID-19

The arbitrary disclosure of information of people diagnosed with COVID-19on the network will adversely affect personal privacy and even violate the privacy rights of individuals. Through the method of literature analysis and case analysis, the information of the confirmed patients of COVID-19 is studied on the network disclosure. The study found that information disclosure can be divided into disclosable information and non-disclosure information, and make different ways of dealing with sensitive information, sensitive information must be handled with care, personal information processing must take into account the balance between personal interests and public interests. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Well-being Data Origination Using MROCs with Variable Quest: A Case Analysis of Gloom during COVID-19 Pandemic

Technologies using artificial intelligence (AI) have been implemented as services to solve various social problems. However, the contributions of AI to people's mentality and unknown/ unobserved events have not been extensively discussed. In this study, we focus on people's mental changes caused by the COVID-19 pandemic and discuss the origin of data sources for well-being using marketing research online communities (MROCs) and variable quest (VQ). In the experiment, we selected 15 females aged between 20 and 40 who were interested in exploring how daily life has changed since the emergence of COVID-19 using MROCs. The analysis results by VQ revealed that the variable sets of the events differed with the situations, mental states, and attitudes, while not being featured in any of the MROC topics as keywords. The result suggests that ing the features of unobserved events as variable sets, can help us acquire information potentially contributing to unexplored data discovery for human well-being from texts not containing any information related to the data. © 2022 for this paper by its authors.

Research on the Academic Early Warning Model of Distance Education based on Student Behavior Data in the Context of COVID-19

The COVID-19 epidemic has caused great impact on the entire society, and the spread of novel coronavirus has brought a lot of inconvenience to the education industry. To ensure the sustainability of education, distance education plays a significant role. During the process of distance education, it is necessary to examine the learning situation of students. This study proposes an academic early warning model based on long and short-term memory (LSTM), which firstly extracts and classifies students’ behavior data, and then uses the optimized LSTM to establish an academic early warning model. The precision rate of the optimized LSTM algorithm is 0.929, the recall rate is 0.917 and the F value is 0.923, showing a higher degree of convergence than the basic LSTM algorithm. In the actual case analysis, the accuracy rate of the academic early warning system is 92.5%. The LSTM neural network shows high performance after parameter optimization, and the academic early warning model based on LSTM also has high accuracy in the actual case analysis, which proves the feasibility of the established academic early warning model. © 2022,International Journal of Advanced Computer Science and Applications. All Rights Reserved.

A Data Warehouse Schema for Monitoring Regional COVID-19 Case Registration

From all websites in Indonesia, 'variant' is an important aspect that was excluded. Based on that limitation, we deliver an enhancement of a data warehouse design. The research methodology adopted Ralph Kimball's Four Step methodology in designing dimensional model of data warehouse that defined four core elements of data warehouse such as business process, granularity, dimensional table, and fact table. Several dimensional tables with different granularity are combined with a fact table and formed a snowflakes schema as the research outcome. The proposed design included 'variant' as a new dimension to complete date, patients, and health centers dimensions. The proposed design is expected to deliver regional COVID-19 case analysis that covered risk, vaccine, therapeutics, and diagnostic is expected to present when the snowflake schema is implemented. For further development, it is expected to test the acceptance of the proposed a data warehouse schema in operating regional COVID-19 case analysis. © 2022 IEEE.

Effectiveness of ChAdOx1 nCoV-19 coronavius vaccine in preventing severe disease and mortality during the second wave of pandemic: A case-case analysis from a tertiary care center in South India

Objective: To determine the real-world effectiveness of the ChAdOx1 nCoV-19 coronavirus vaccine in preventing severe disease and mortality due to COVID-19. Methods: A case-case design was used to estimate the effect of the ChAdOx1 nCoV-19 coronavirus vaccine on severe SARS-CoV-2 outcomes in individuals aged 40 years and above. Cases (n=200) were COVID-19 patients admitted to intensive care unit (ICU) or who died. Controls (n=223) were those with mild COVID-19, fit for home isolation. The logistic regression model was used to estimate adjusted vaccine effectiveness for full vaccination (two doses >= 14 d) and partial vaccination status (one dose >= 14 d or two doses < 14 d). Results: The proportion of fully vaccinated individuals was significantly lower among cases (12, 6.0%) compared to controls (30, 13.5%). The adjusted effectiveness of a full dose of ChAdOx1 nCoV-19 coronavirus vaccine in preventing ICU admission or death was 81.9% (95% CI: 61.3%-91.6%, P=0.001). Subgroup analysis restricted to age group, sex, and comorbidities found that ChAdOx1 nCoV-19 coronavirus vaccine had a significant positive effect in all subgroups and categories. Conclusion: COVID-19 vaccination reduces ICU admissions or death. Therefore, increased vaccine uptake may reduce the severity of the pandemic, more so in the elderly and those with comorbidities.

Developing valid test bank of surveillance case study scenarios for inter-rater reliability.

Case studies are utilized for training on National Healthcare Safety Network (NHSN) healthcare associated infection surveillance definitions. Item discrimination and item analysis were applied to case studies to identify questions that most accurately assess infection preventionists (IPs) application of surveillance definitions.

Study on the Dilemma and Countermeasures of Rural Emergency Management Under COVID-19—A Case Analysis Based on the Rural Areas Around Chengdu

The COVID-19 broke out and spread rapidly, posing a great challenge to the emergency management capacity of various regions in China, especially in rural areas. This paper takes three communities in ShiYang town, Dujiangyan City, Sichuan Province as cases, to analyze the specific practice of rural response to public health emergencies, summarize different stages in epidemic prevention and control, and explore the difficulties and solutions in rural emergency management. Through the case analysis, it is found that the rural epidemic prevention and control in ShiYang Town have experienced four stages including exploration period, development period, improvement period, and maturity period. At the same time, there are some dilemmas in rural emergency management, such as the imperfect emergency management mechanism, insufficient resources guarantee, and villagers’ weak awareness of health and epidemic prevention. Therefore, the paper proposes such countermeasures suggestions as improving the emergency management mechanism of rural public health, optimizing the resources guarantee system for rural emergency management, strengthening the popularization of health education, providing theoretical and practical guidance for improving the level of rural emergency management, and then promoting the modernization of rural emergency management system and capacity. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Growing Process of Communities on Data Platforms: Case Analysis of a COVID-19 Dataset

In recent years, there have been growing expectations for the creation of new businesses and the improvement of the value of existing services by exchanging data in different fields. Data stored in-house within organizations have become a new source of innovation. While there is a high need for the value creation of data, determining the data value is not an easy task, as there is a wide range of factors to be considered, such as data pricing, acquisition cost, usage value, and update frequency. In this study, we observe communication, such as the sharing of know-hows in data exchange and analysis, and discuss the growing process of a community on the data platform. For the experiment, we focused on the data community in the COVID-19 disaster and used a unique dataset from the data platform Kaggle, which is the data analysis competition service. The results suggest that user actions differ in the discussion of the dataset and analysis. Moreover, providing topics, user participation, and activating actions in the early stages after the dataset is released are essential for forming a data community. We argue that the actions on the data analysis, such as comments and votes, are also crucial for fostering a common understanding of the data value. © 2021 IEEE.

How offline education institutions cope with the impact of epidemic

The outbreak of the novel coronavirus pneumonia has brought serious impacts on the educational institutions under the line. Therefore, how to survive and achieve developments is an important problem that these training institutions need to solve urgently. Taking offline education institutions as an example, this paper uses multi case analysis to explore how to achieve entrepreneurial survival and development through the patchwork of existing resources in the context of resource constraints. The results show that the objects of offline education institutions are mainly the patchwork of material, human, skill and network;in the initial stage, the organization is mainly composed of patchwork of materials and skills;while in the growth stage, it is mainly composed of human and network;Patchwork orientation can be divided into opportunity orientation and customer orientation;the key features of patchwork are existing resources, resource reconstruction and improvisation;the main performance of patchwork is parallel patchwork and selective patchwork. The entrepreneurial patchwork skills mainly involve the use of relationship building, publicity and promotion, financing and team integration skills. From the perspective of entrepreneurial patchwork, this study constructs a patchwork element model of educational institutions under resource constraints, which has a certain reference value for educational institutions to get out of the epidemic crisis, carry out self-help, and achieve survival and development. © 2021 ACM.