The Measurement of Popularity and Prevalence of Software Vulnerability

Prioritizing bug fixes becomes a daunting task due to the increasing number of vulnerability disclosure programs. When making a decision, not only the Common Vulnerability Scoring System (CVSS) but also the probability of exploitation, the trend of particular security issues should be taken into account. This paper aims to discuss the sources and approaches for measuring degree of interest in a specific vulnerability at a particular point in real-time. This research presents а new metric and estimation model which is based on vulnerability assessment. We compared several techniques to determine the most suitable approach and relevant sources for improving vulnerability management and prioritization problems. We chose the Google Trend analytics tool to gather trend data, distinguish main features and build data set. The result of this study is the regression equation which helps efficiently prioritize vulnerabilities considering the public interest in the particular security issue. The proposed method provides the popularity estimation of Common Vulnerabilities and Exposures (CVE) using public resources.

Defining Causality in Covid-19 and Google Search Trends in Java, Indonesia Cases: A Retrospective Analysis

The Coronavirus disease 2019 (Covid-19) has led all countries around the world to the unpredicted situation. It is such a crucial to investigate novel approaches in predicting the future behaviour of the outbreak. In this paper, Google trend analysis will be employed to analyse the seek pattern of Covid-19 cases. The first method to investigate the seek information behaviour related to Covid-19 outbreak is using lag-correlation between two time series data per regional data. The second method is used to encounter the cause-effect relation between time series data. We apply statistical methods for causal inference in epidemics. Our focus is on predicting the causal-effect relationship between information-seeking patterns and Google search in the Covid-19 pandemic. We propose the using of Granger Causality method to analyse the causal relation between incidence data and Google Trend Data.

Trend Analysis of Pet Plants Before and After COVID-19 Outbreak Using Topic Modeling: Focusing on Big Data of News Articles from 2018 to 2021

Background and objective: The ongoing COVID-19 pandemic restricted daily life, forcing people to spend time indoors. With the growing interest in mental health issues and residential environments, ‘pet plants’ have been receiving attention during the unprecedented social distancing measures. This study aims to analyze the change in trends of pet plants before and during the COVID-19 pandemic and provide basic data for studies related to pet plants and directions of future development.Methods: A total of 2,016 news articles using the keyword ‘pet plants’ were collected on Naver News from January 1, 2018 to August 15, 2019 (609 articles) and January 1, 2020 to August 15, 2021 (1,407 articles). The texts were tokenized into words using KoNLPy package, ultimately coming up with 63,597 words. The analyses included frequency of keywords and topic modeling based on Latent Dirichlet Allocation (LDA) to identify the inherent meanings of related words and each topic.Results: Topic modeling generated three topics in each period (before and during the COVID-19), and the results showed that pet plants in daily life have become the object of ‘emotional support’ and ‘healing’ during social distancing. In particular, pet plants, which had been distributed as a solution to prevent solitary deaths and depression among seniors living alone, are now expanded to help resolve the social isolation of the general public suffering from COVID-19. The new term ‘plant butler’ became a new trend, and there was a change in the trend in which people shared their hobbies and information about pet plants and communicated with others in online.Conclusion: Based on these findings, the trend data of pet plants before and after the outbreak of COVID-19 can provide the basis for activating research on pet plants and setting the direction for development of related industries considering the continuous popularity and trend of indoor gardening and green hobby.

The Role of Leadership in Public Sector Innovation: A Systematic Review and Meta-Analysis of the Management of COVID-19 in Asian Countries

Strong leadership in public sector innovation can empower governments to address community challenges in new ways in light of the challenges posed by the global coronavirus pandemic. Coronavirus management policy, pandemic responses, needs, and options are reflected in various Asian countries in respective published literature, but a summarized synthesis is not available. Using a systematic review approach (PRISMA), this study has analyzed the role of leadership in public sector innovation in COVID-19 management and synthesized 23 articles from 23 different Asian countries. In the light of available data, public sector innovation (PSI) and the role played by the leadership of each country' have been found to be largely inter-dependent. The current review provides a cross-section of the ongoing nature of the pandemic, as management responses and trend data in the countries are still emerging or evolving. Additionally, our study contributes a current state report regarding the barriers facing the leadership of Asian countries in mitigating the global pandemic through PSI. Our study found that a strong political leadership presence combined with a technocratic approach and a highly-skilled public sector workforce, could lead to more tremendous success in managing the outbreak. Furthermore, religious leadership was also found to have a potentially significant role in COVID-19 management strategies.

TRANSFORMATION OF THE TOURISM SYSTEM IN THE CONTEXT OF DIGITALIZATION

The tourism system through its multiplication effect can provide the development of the related branches and become the background cause of the positive socio-eco-economic processes. The significant impact on the tourism system made the global COVID-19 pandemic, which incurred a number of downturns in the functioning of this economic sector. The necessity of the solution of the strategic problems in the development of the tourism system determines the necessity of research of transformation changes, which take place in it. The socio-economic transformations in the tourism systems are proved, the essential actions concerning reinforcement of the positive impact and evening-out the negative impact of the external environment in the context of new reality and digitalization are proposed. Based on the analysis of the tourism sector and hospitality sector subjects’ activities trend data as the main components of the tourism system the asymmetries of the development are detected and restricted into three groups: functional, structural, and temporal. The structural and temporal factors of transitivity are shown and its aspects are proved through the progressive and regressive trends of the Ukrainian tourism system development processes. The stages of tourism system evolution are specified (adaptive, knowledge-minded, integrative) and the new one is proved (digital and mobile). The promotion of the innovative dominants in the tourism system of Ukraine as the drivers of the strategical development is proposed. Referred innovative dominants are concentrated towards digital, communicative, partner, ecological, and financial directions. The emphasis is put on the influence of digital changes on the transformation of the tourism system of Ukraine and its individual components. Actualization of the innovative dominants in the tourism system of Ukraine shows global trends of society and corrected by institutional surroundings and domestic mindset entities on the one hand and the building up of the new tourism system development surroundings on the other hand.

Disability Trends Among Community-Dwelling Older Adults and Related Determinants of Disability

The growing aging population with disabilities poses challenges to caregiving and health care services but there is little recent data on disability trends. Some studies have shown that disability is decreasing while others have shown it increasing. Understanding these trends among community-dwelling older adults is critical for communities to allocate resources and develop policies. This study updates disability trend data among community-dwelling older adults using nationally representative National Health & Aging Trends Study data. Results revealed that about 30% of Medicare beneficiaries had at least one limitation of the activity of daily living (ADL) from 2011 to 2019. Age 75-79 (IRR=1.55), 80-84 (IRR= to 4.60), 85-89 (IRR=2.99), 90+ (IRR=4.60), female, (IRR=1.18), not a house owner (IRR=1.51), financial strain (IRR=1.71), and receiving Medicaid (IRR=1.84) are associated with a higher likelihood of becoming ADL limited or having more ADL limitations. We will discuss potential policy, intervention, and research implications.

High Order Spatial Weighting Matrix Using Google Trends

This research aimed to form a high-order spatial weighting matrix based on various simulations. The simulation was the determination of the center of the country based on the capital and google trend data. The keywords that have been used in the Google Trends data are "gold price" and "deposit". These keywords have been translated into 6 official languages of the United Nation including Arabic, Chinese, English, French, Russian, and Spanish. Each language has been represented by 1 country. The determination of the country center that has been used based on the capital as well as keywords and time influenced the form of the high-order spatial weighting matrix. In simulations 1, 2, 4, and 5 the highest spatial order formed was 6. It was different with simulations 3, 6, and 7 the highest spatial order formed was 5. Keywords: language, simulation, gold price, deposit.

Spatio-temporal Analysis of Land Cover Changes in Al-Hubail Wetland (Kingdom of Saudi Arabia)

Land cover dynamics were analyzed temporally and spatially in Al-Hubail wetland (Al-Ahsa, Kingdom of Saudi Arabia) to determine the evolution of the environmental status of this biologically and ecologically interesting area in Saudi Arabia. Land cover changes were estimated for the next 41 years (1980-2021) using remote sensing data. For this analysis, three images from 1985 (Landsat 5 MSS) 2000 (Landsat 7 ETM+) and 2021 (Sentinel-2) were used to classify and detect changes. A machine learning algorithm was used and the images were classified into four main land cover classes: Water bodies, hydromorphic areas, vegetation and open ground. Change detection was performed for the year pairs 1985 to 2000 and 2000 to 2021. The results of this classification show that there was a significant increase in the area of hydromorphic areas and vegetation. The results were checked with a confusion matrix indicating an overall accuracy between 89.3 and 92.8%. The qualitative trend data show that the Al-Hubail wetland has changed significantly during the study period. Thus, a significant expansion of the wetland was observed in conjunction with an increase in agricultural drainage towards the wetland. This analysis shows the strong anthropogenic pressure on the area and highlights the need to strengthen the existing laws in order to preserve the local biodiversity in the long term. It suggests that more efforts should be made to effectively manage the water resources of the region.

Forecasting COVID-19 Cases in Indonesia Using Hybrid Double Exponential Smoothing

The COVID-19 epidemic has spread throughout countries around the world. In Indonesia, this case was detected in early March 2020, and until now, there is still an increase in positive cases of COVID-19. The purpose of this paper is to predict COVID-19 cases in Indonesia using a time series approach. The method used is H-WEMA method because this method can capture trend data patterns following the conditions of COVID-19 cases in Indonesia. Based on the analysis results, H-WEMA can predict COVID-19 cases very well. The forecasted results of the COVID-19 cases in Indonesia still have an upward trend, so it needs the cooperation of all elements of community to reduce the spread of COVID-19. Received September 8, 2021Revised October 15, 2021Accepted November 3, 2021