The proposed research work encompasses implications for infrastructure particularly the cybersecurity as an essential in soft infrastructure, and policy making particularly on secure access management of infrastructure governance. In this study, we introduce a novel parameter focusing on the timestamp duration of password entry, enhancing the algorithm titled EPSBalgorithmv01 with seven parameters. The proposed parameter incorporates an analysis of the historical time spent by users entering their passwords, employing ARIMA for processing. To assess the efficacy of the updated algorithm, we developed a simulator and employed a multi-experimental approach. The evaluation utilized a test dataset comprising 617 authentic records from 111 individuals within a selected company spanning from 2017 to 2022. Our findings reveal significant advancements in EPSBalgorithmv01 compared to its predecessor namely EPSBalgorithmv00. While EPSBalgorithmv00 struggled with a recognition rate of 28.00% and a precision of 71.171, EPSBalgorithmv01 exhibited a recognition rate of 17% with a precision of 82.882%. Despite a decrease in recognition rate, EPSBalgorithmv01 demonstrates a notable improvement of approximately 14% over EPSBalgorithmv00.

Exploring the development path of badminton with Chinese characteristics is a key area in advancing the reform of China’s sports system and a crucial theoretical support for transitioning from a sports power to a sports powerhouse. This article reviews the overall situation of the development of badminton in China since the founding of the People’s Republic of China, and based on this, puts forward the basic connotations and directions of the development path of badminton with Chinese characteristics. It discusses the opportunities and challenges faced in aspects such as badminton management system and mechanism, accelerated optimization and upgrading of sports industry and brands, substantial breakthroughs in competitive level, cultivation of reserve talents, and diversified development of sports culture. It explores the future direction of the development path of badminton with Chinese characteristics from five aspects: system, management, talent, industry, and culture.

Use of technologies and online presence is now almost inevitable in language learning. The practice of virtual exchanges (VEs) has been receiving a lot of attention among educators at all levels over the past years. This research paper sheds light on 13 VEs carried out in pre-service teacher education in the last six years and proposes its own VE design based on recommendations from the literature with the future perspective of designing a specific VE for the research. The aim of the systematic review was at first to determine the exchange and interaction set-ups and the potential gains in the terms of pre-service teachers’ skills development. Afterwards, we identified areas for improvement and proposed our design of a VE between pre-service teachers of English in Slovakia and Turkey. Some of the expected contributions of the proposed VE design are development of a linguistic and intercultural communicative competence, digital literacy, and other competences relevant for development of VEs.

Blockchain technology is poised to significantly transform the corporate world, heralding a new era of innovation and efficiency. Over the past few years, its impact has been noted by leaders, academics, and government representatives around the globe this growing interest underscores businesses’ need to evolve and reconsider traditional operational models. To remain competitive, organizations must embrace this change. Before introducing such ground-breaking technology, it is crucial to assess the motivations of primary stakeholders concerning its implementation. This study looks into what influences the use of Blockchain technology in the oil and gas sector, primarily using a quantitative survey of Iraqi oil and gas companies. A questionnaire was distributed among 250 top-level managers, senior executives, project managers, and IT managers for analyzing the data, the study employs the Structural Equation Modelling-Partial Least Squares (SEM-PLS) technique, with Smart PLS for data processing. The findings suggest that the intention to utilise blockchain technology is influenced by one’s attitude towards it. Competitive pressure (environmental factors), functional benefit, and privacy/security (technological factors) significantly affect blockchain adoption intention. Nevertheless, there was no discernible correlation between regulatory backing and the desire to use Blockchain. Additionally, cost concern and perceived risk (organizational factors) two factors contribute negatively to the perception of blockchain technology. Besides the direct relationship, the findings revealed that attitude toward blockchain technology mediate the relationship between cost concern, perceived risk, and intention to adopt Blockchain. Built upon the Technology-Organization-Environment (TOE) model and the Theory of Reasoned Action, this research offers a comprehensive framework for investigating the intention to adopt blockchain technology. The results enhance both theoretical understanding and practical implementation by providing valuable insights into the emerging area of blockchain adoption intentions.

Managing business development related to the innovation of intelligent supply chains is an important task for many companies in the modern world. The study of management mechanisms, their content and interrelations of elements contributes to the optimization of business processes and improvement of efficiency. This article examines the experience of China in the context of the implementation of intelligent supply chains. The study uses the methods of thematic search and systematic literature review. The purpose of the article is to analyze current views on intelligent supply chain management and identify effective business management practices in this area. The analysis included publications devoted to various aspects of supply chain management, innovation, and the implementation of digital technologies. The main findings of the article are as follows: Firstly, the key elements of intelligent supply chain management mechanisms are identified, secondly, successful experiences are summarized and the main challenges that companies face in their implementation are identified. In addition, the article focuses on the gaps in research related to the analysis of successful experiences and the reasons for achieving them.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.