In the process of X-ray transmission imaging, the mutual occlusion between structures will lead to the image information overlap, and the computed tomography (CT) method is often required to obtain the structure information at different depths, but with low efficiency. To address these problems, an X-ray focused on imaging algorithm based on multi-line scanning is proposed, which only requires the scene target to pass through the detection area along a straight line to extract multi-view information, and uses the optical field reconstruction theory to achieve the de-obscured reconstruction of the structure at a specified depth with high real-time. The results of multi-line scan and X-ray reconstruction of the target show that the proposed method can reconstruct the information of any specified depth layer, and it can perform fast imaging detection of the mutually occluded target structures and improve the recognition of the occluded targets, which has a good application prospect.

The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.

Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.

Countering cyber extremism is a crucial challenge in the digital age. Social media algorithms, if designed and used properly, have the potential to be a powerful tool in this fight, development of technological solutions that can make social networks a safer and healthier space for all users. this study mainly aims to provide a comprehensive view of the role played by the algorithms of social networking sites in countering electronic extremism, and clarifying the expected ease of use by programmers in limiting the dissemination of extremist data. Additionally, to analyzing the intended benefit in controlling and organizing digital content for users from all societal groups. Through the systematic review tool, a variety of previous literature related to the applications of algorithms in the field of online radicalization reduction was evaluated. Algorithms use machine learning and analysis of text and images to detect content that may be harmful, hateful, or call for violence. Posts, comments, photos and videos are analyzed to detect any signs of extremism. Algorithms also contribute to enhancing content that promotes positive values, tolerance and understanding between individuals, which reduces the impact of extremist content. Algorithms are also constantly updated to be able to discover new methods used by extremists to spread their ideas and avoid detection. The results indicate that it is possible to make the most of these algorithms and use them to enhance electronic security and reduce digital threats.

This paper investigates the evolving clustering and historical progression of “Asian regionalisms” concerning their involvement in multilateral treaties deposited in the United Nations system. We employ criteria such as geographic proximity, historical connections, cultural affinities, and economic interdependencies to identify twenty-eight candidate countries from East Asia, Southeast Asia, South Asia, and Central Asia for this empirical testing. Using a social network analysis approach, we model the network of these twenty-eight Asian state actors alongside 600 major treaties from the United Nations system, identifying clusters among Asian states by assessing similarities in their treaty participation behavior. Specifically, we observe dynamic changes in these clusters across three key historical eras: Post-war reconstruction and transformation (1945–1968), Cold War tensions and global transformations (1969–1989), and post-Cold War era and globalization (1990–present). Employing the Louvain cluster detection algorithm, the results reveal the evolution in cluster numbers and changes in membership status throughout the world timeline. The results also identify the current situation of six distinct Asian clusters based on states’ inclinations to engage or abstain from multilateral treaties across six policy domains. These findings provide a foundation for further research on the trajectories of Asian regionalisms amidst evolving global dynamics and offer insights into potential alliances, cooperation, or conflicts within the region.