The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.

Since the Reform and Opening up, GDP of the cities on eastern bank of the Pearl River Estuary in Guangdong Province were higher than the eastern bank cities. Therefore, this article aims to modify the urban gravity model combines it with the entropy weight method to calculate urban quality and applies it to measure the degree of connectivity between cities over the past decades. The research aims to explore whether cities with higher economic output have a greater attraction for surrounding cities, and whether the eastern bank cities can also promote the development of the west. Through detailed data collection and analysis, this essay reveals the dynamic changes of the gravity among cities and its influence factors such as economic, transportation and urban development. The research results indicate that the strongest gravitational force between cities on the east and west banks is between Dongguan and Zhongshan, rather than between Shenzhen and cities on the west bank. This demonstrates that the connection between cities on the east and west banks is primarily constrained by geographical factors, and the geographical location of a city influences on surrounding cities significantly. In particular, Dongguan and Zhongshan play a key role in connecting the eastern and western bank of the Pearl River Estuary, rather than Shenzhen, which is traditionally considered to have the highest economic aggregate. In addition, the study also found that the COVID-19 epidemic has had a significant impact on inter-city communication, resulting in a decline in inter-city gravity in recent years.

The principal objective of this article is to gain insight into the biases that shape decision-making in contexts of risk and uncertainty, with a particular focus on the prospect theory and its relationship with individual confidence. A sample of 376 responses to a questionnaire that is a replication of the one originally devised by Kahneman and Tversky was subjected to analysis. Firstly, the aim is to compare the results obtained with the original study. Furthermore, the Cognitive Reflection Test (CRT) will be employed to ascertain whether behavioural biases are associated with cognitive abilities. Finally, in light of the significance and contemporary relevance of the concept of overconfidence, we propose a series of questions designed to assess it, with a view to comparing the various segments of respondents and gaining insight into the profile that reflects it. The sample of respondents is divided according to gender, age group, student status, professional status as a trader, status as an occasional investor, and status as a behavioural finance expert. It can be concluded that the majority of individuals display a profile of underconfidence, and that the hypotheses formulated by Kahneman and Tversky are generally corroborated. The low frequency of overconfident individuals suggests that the results are consistent with prospect theory in all segments, despite the opposite characteristics, given the choice of the less risk-averse alternative. These findings are useful for regulators to understand how biases affect financial decision making, and for the development of financial literacy policies in the education sector.

This study examines innovative teaching approaches’ effect on the quality of education for prospective primary teachers. A mixed-methods approach combining qualitative and quantitative data collection techniques was employed. Initially, the two data sets were analyzed separately—qualitative data through thematic analysis and quantitative data through statistical methods. The themes emerging from the qualitative analysis were then cross-referenced with the quantitative findings to evaluate whether the trends supported each other. For instance, if a qualitative theme indicated that teachers felt more confident using innovative methods, this was supported by quantitative data showing improvements in teacher performance scores or student outcomes. The study had 200 participants, and the study findings revealed a significant positive impact of innovative teaching approaches on the quality of education for future primary teachers. Participants reported increased engagement, improved critical thinking, and enhanced adaptability in classroom settings. The study findings reveal that innovative approaches significantly improve the quality of education for prospective primary teachers by fostering more interactive, technology-enhanced, and student-centered learning environments. To maintain these improvements, it is essential to invest in infrastructure, provide ongoing support for teacher educators, and continuously update curricula to reflect emerging educational technologies and practices. These findings emphasize the importance of innovation in teacher training to meet the evolving demands of primary education.

Regions rich in natural resources often exhibit a high dependency on revenue from Revenue Sharing Funds (DBH). This dependency can pose long-term challenges, especially when commodity prices experience significant fluctuations. This study examines the role of Revenue Sharing Funds from Natural Resources (DBH SDA) on economic growth in 491 regencies/cities in Indonesia during the 2010–2012 period. The analysis employs panel data regression. The selection of this period was based on the occurrence of a resource boom characterized by a surge in global demand for natural resource commodities, accompanied by an increase in commodity prices. This condition positively impacted the revenues of both the nation and resource-rich regions. The results of the study show that economic growth is not influenced by DBH SDA but rather by General Allocation Funds (DAU). This indicates that the central government still plays a significant role in determining economic growth at the regency/city level in Indonesia. Regions need to prioritize economic diversification to reduce reliance on DBH SDA and DAU. Investment in productive sectors, such as infrastructure, education, and technology, can be a strategic approach to accelerating regional economic growth.

This study investigates the critical skills required for new entrants to succeed in today’s workforce, focusing on both soft and hard skills. Through a comprehensive systematic review of existing literature using the PRISMA method, we analyzed 12 selected journals from an initial pool of 870, sourced from major databases such as Scopus, Science Direct, and Emerald Insight. Our research uncovers four key insights. First, we provide a clear and precise definition of employability skills, establishing the foundation for what competencies are essential for workforce readiness. Second, our analysis identifies a distinct separation between soft and hard skills, with soft skills such as communication, problem-solving, teamwork, ethics, and leadership being universally critical across all industries. Third, while soft skills have broad applicability, hard skills are highly specialized, varying significantly depending on industry and job role. To simplify their understanding and application, we categorized these hard skills into specific groups. Finally, the study highlights the urgent need for further empirical research to validate these findings in real-world settings, as the current conclusions are drawn solely from literature. This potential gap between academic preparation and industry expectations underscores the necessity for ongoing collaboration between educational institutions and employers, which will be a primary focus of our future research.

This research aims to build an appropriate leadership model for regional heads in mitigating disasters due to climate change that is occurring in Papua. Papua Island is one of the islands that is included in disaster-prone areas, namely earthquakes, flash floods, tidal floods and landslides. This disaster occurred due to Papua’s geological conditions in the form of activity on the Indo-Australian plate (southern part) and the Pacific plate (north-eastern part). Exploitation of nature carried out by companies and communities themselves in a particular area has an impact on the balance of the natural ecosystem. So far, disaster management has only focused on emergency response. Aid movements coordinated by ordinary people also focus more on raising aid for emergency situations. In fact, comprehensive disaster management includes before, during and after a disaster occurs. So a combination of leadership styles is needed that must be carried out at each phase of a disaster so that the right model can be produced. The results of this research found that the leadership model of regional heads in mitigating climate change in Papua is in accordance with the disaster management cycle with leadership styles, and traditional Papuan leadership styles. This combination is called a collaborative leadership model for disaster management in Papua. It is hoped that by implementing this model, climate change disaster mitigation can be effective.

The aim of this paper is to develop a methodology for determining the size of the unified land tax in agriculture based on the results of the economic assessment of agricultural land to form the foundation of a new effective system of macroeconomic instruments for state regulation of the innovative development of the agro-industrial complex of the Republic of Kazakhstan. There were used gatherings of facts and summaries, induction and deduction, analysis and synthesis, historical and logical, normative, comparison, index and modeling methods in the research. The article provides an overview of various scholarly perspectives on the challenges and strategies for improving the tax system. The base rates of the unified land tax per hectare of arable land have been calculated to establish equal conditions for all land users. This unified land tax rate is expected to encourage the efficient utilization of land resources and enable the optimization of production structure. The article addresses avenues for improving water management relations in agriculture, aimed at fostering a shared interest and creating incentives for adopting innovative technologies in both agriculture and the water management sector. An essential condition for achieving the effective functioning of Kazakhstan’s agro-industrial complex is its transformation to an innovative development model. This necessitates the development and application of a new system of macroeconomic tools for its implementation, aimed at creating a favorable environment for entrepreneurial development.