Key Factors Affecting User Adoption of Open-Access Data Repositories in Intelligence and Security Informatics: An Affordance Perspective

Rich, diverse cybersecurity data are critical for efforts by the intelligence and security informatics (ISI) community. Although open-access data repositories (OADRs) provide tremendous benefits for ISI researchers and practitioners, determinants of their adoption remain understudied. Drawing on affordance theory and extant ISI literature, this study proposes a factor model to explain how the essential and unique affordances of an OADR (i.e., relevance, accessibility, and integration) affect individual professionals' intentions to use and collaborate with AZSecure, a major OADR. A survey study designed to test the model and hypotheses reveals that the effects of affordances on ISI professionals' intentions to use and collaborate are mediated by perceived usefulness and ease of use, which then jointly determine their perceived value. This study advances ISI research by specifying three important affordances of OADRs; it also contributes to extant technology adoption literature by scrutinizing and affirming the interplay of essential user acceptance and value perceptions to explain ISI professionals' adoptions of OADRs.

A Connection Access Mechanism of Distributed Network based on Block Chain

Cross-border payment optimization technology based on block chain has become a hot spot in the industry. The traditional method mainly includes the block feature detection method, the fuzzy access method, the adaptive scheduling method, which perform related feature extraction and quantitative regression analysis on the collected distributed network connection access data, and combine the fuzzy clustering method to optimize the data access design, and realize the group detection and identification of data in the block chain. However, the traditional method has a large computational overhead for distributed network connection access, and the packet detection capability is not good. This paper constructs a statistical sequence model of adaptive connection access data to extract the descriptive statistical features of the distributed network block chain adaptive connection access data similarity. The performance of the strategy retrieval efficiency in the experiment is tested based on the strategy management method. The experiment performs matching query tests on the test sets of different query sizes. The different parameters for error rate and search delay test are set to evaluate the impact of different parameters on retrieval performance. The calculation method of single delay is the total delay or the total number of matches. The optimization effect is mainly measured by the retrieval delay of the strategy in the strategy management contract; the smaller the delay, the higher the execution efficiency, and the better the retrieval optimization effect.

Identifying Innovations in Human Resources

HR is evolving into a more technology-based profession because organizations needs to streamline HR processes and reduce administrative burden, reducing administrative cost; compete more effectively with global talent; improve services and access data to the employees and managers; provide real-time metrics in order tom on spot decisions for the decision makers; and manage the workforce more effectively and enable the HR to transform so it can play more strategic role in the business and operations. The purpose of this chapter is to develop a meaningful debate on the innovations in human resource in terms of new ideas, methods, and technology to better meet the evolving requirement of the organization and workforce. Anticipating and exploring the future needs and circumstances rather than simply finding some responses to the situation, this chapter highlights challenges and prospects related to innovations in HR.

Global Perspective of COVID-19 Vaccine Nationalism

This study aimed to explore the global perspective of the association between GDP of various countries and progress of COVID-19 vaccinations; to explore how the global pattern holds in the continents, and investigate the spatial distribution pattern of COVID-19 vaccination progress for all countries. We have used consolidated data on COVID-19 vaccination and GDP from Our World in Data, an open-access data source. Data analysis and visualization were performed in R-Studio. There was a strong linear association between per capita income and the proportion of people vaccinated in countries with one million or more populations. GDP per capita accounts for a 50% variation in the vaccination rate across the nations. Our assessments revealed that the global pattern holds in every continent. Rich European and North-American countries are most protected against COVID-19. Less developed African countries barely initiated the vaccination program. There is a significant disparity among Asian countries. The security of wealthier nations (vac-cinated their citizens) cannot be guaranteed unless adequate vaccination covers the less-endowed countries. Therefore, the global community should take initiatives to speed up the COVID-19 vaccination program in all countries of the world, irrespective of their wealth. Keywords: COVID-19 vaccination; GDP; public health, high-income countries, developing coun-tries

The Role of Education and Awareness in Tackling Insider Threats

Insider threats present a major concern for organizations worldwide. As organizations need to provide employees with authority to access data to enable them to complete their daily tasks, they leave themselves open to insider attacks. This chapter looks at those who fall into the category which can be referred to as insiders and highlights the activity of outsourcing which is employed by many organizations and defines the term insider threat while pointing out what differentiates an accidental threat from a malicious threat. The discussion also considers various methods of dealing with insider threats before highlighting the role education and awareness plays in the process, the importance of tailoring awareness programs, and what the future holds for insider threats within organizations.

The Role of Municipalities in Achieving Water Security

The world has realized the fact that the limited resources can't be sustainable for a long time. Sustainable transformation is a key issue to save the current resources and natural environment for the next generation. 2030 Sustainable Development Goals (SDGs) can help governments to focus on main issues to achieve a balance between social, environmental, and economic development. At this point, Goal 6 points out the importance of saving clean and safe freshwater resources. This chapter aims to present the link between municipalities and water security in Turkey. Turkey case was selected according to its risky position in the level of water stress. This study used recent reports and statistical data on environmental indicators related with freshwater resources and the implications of municipalities in Turkey. Environmental Indicators 2020 Report guided the authors to determine water indicators in Turkey. In addition, the available open access data from TURKSTAT is used to determine water supply services of municipalities.

Exploring the Potential Distribution of Relic Trochodendron aralioides: An Approach Using Open-Access Resources and Free Software

Trochodendron aralioides Siebold & Zucc. is a relic tree that is discontinuously scattered across the mountainous areas of Japan, Taiwan, and South Korea, but the origin of T. aralioides in South Korea is still unclear and debated. To confirm its distribution and explore its origins, we constructed a streamlined framework to examine potential species distribution using multiple open access data and free and open-source software, as well as employing maximum entropy principles to predict the potential distribution of T. aralioides. The results showed reasonably good discrimination and were used to examine and discuss the explicit distribution of T. aralioides. The potential distribution of T. aralioides in Japan extended from Iriomote Island to approximately 37° N in Honshu on the Pacific Ocean side. In Taiwan, the potential distribution of T. aralioides was more common than in Japan. It occurred at 1500–3000 m a.s.l. across the Central Mountain Range and decreased toward the northern and southern tips, correlating to the descending pattern of the cloud belt. Thermal and moisture conditions were important factors to determine the distribution of T. aralioides. The potential distribution indicated that Jeju island had high potential as a habitat for T. aralioides, and that may indirectly imply its existence and origins in South Korea, as some researchers have noted.

Open-Access Data and Toolbox for Tracking COVID-19 Impact on Power Systems

Intervention policies against COVID-19 have caused large-scale disruptions globally, and led to a series of pattern changes in the power system operation. Analyzing these pandemic-induced patterns is imperative to identify the potential risks and impacts of this extreme event. With this purpose, we developed an open-access data hub (COVID-EMDA+), an open-source toolbox (CoVEMDA), and a few evaluation methods to explore what the U.S. power systems are experiencing during COVID-19. These resources could be broadly used for research, policy making, or educational purposes. Technically, our data hub harmonizes a variety of raw data such as generation mix, demand profiles, electricity price, weather observations, mobility, confirmed cases and deaths. Several support methods and metrics are then implemented in our toolbox, including baseline estimation, regression analysis, and scientific visualization. Based on these, we conduct three empirical studies on the U.S. power systems and markets to introduce some new solutions and unexpected findings. This conveys a more complete picture of the pandemic's impacts, and also opens up several attractive topics for future work. Python, Matlab source codes, and user manuals are all publicly shared on a Github repository.

Open-Access Data and Toolbox for Tracking COVID-19 Impact on Power Systems

Intervention policies against COVID-19 have caused large-scale disruptions globally, and led to a series of pattern changes in the power system operation. Analyzing these pandemic-induced patterns is imperative to identify the potential risks and impacts of this extreme event. With this purpose, we developed an open-access data hub (COVID-EMDA+), an open-source toolbox (CoVEMDA), and a few evaluation methods to explore what the U.S. power systems are experiencing during COVID-19. These resources could be broadly used for research, policy making, or educational purposes. Technically, our data hub harmonizes a variety of raw data such as generation mix, demand profiles, electricity price, weather observations, mobility, confirmed cases and deaths. Several support methods and metrics are then implemented in our toolbox, including baseline estimation, regression analysis, and scientific visualization. Based on these, we conduct three empirical studies on the U.S. power systems and markets to introduce some new solutions and unexpected findings. This conveys a more complete picture of the pandemic's impacts, and also opens up several attractive topics for future work. Python, Matlab source codes, and user manuals are all publicly shared on a Github repository.