Vol 3 No 1 (2025)

• Application of Digital Radiographic Imaging Technology in Metal Wall Thickness Measurement

  Hai-Bo Niu, Jing Yang, Peng-Chong Zhang

  Digital radiographic imaging technology applied in metal wall thickness measurement mainly addresses the non-contact thickness measurement for online inspection of high-temperature operating equipment and devices. This technology utilizes the penetrating and attenuation principles of rays, combined with the precise capture of digital detectors and image software analysis and processing, to achieve estimation and measurement of changes in metal wall thickness. The study reveals the unique advantages of digital radiographic imaging in metal wall thickness measurement, facilitating the detection of thickness changes caused by corrosion and thinning, thus providing reliable data support for the safety assessment and maintenance decisions of metal structures.

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• Application of Artificial Intelligence in Computer Vision and Networking

  Yi-Xuan Tang

  As the core driving force behind today's technological advancements, artificial intelligence (AI) is profoundly reshaping the technological landscape of computer vision and networking fields. This paper systematically explores the current application status, technological principles, and future development trends of AI in these two domains. In the field of computer vision, the paper focuses on deep learning-based technologies such as object detection, image recognition, facial recognition, and video analysis, and demonstrates their practical application value through real-world cases in medical imaging and autonomous driving. In the networking field, the paper elaborates on AI's innovative applications in network security, network optimization, and intelligent network management. The article also proposes strategic recommendations for promoting AI development, from the perspectives of technological integration and data privacy. By synthesizing authoritative data and the latest research results, this paper provides an important reference for technological development and practical applications in these fields.

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• Innovative research on building energy consumption and comfort optimization based on BIM-BECS-AI collaboration

  Chun Yik Jenny Li, Yan Li

  Against the backdrop of the continuous growth of global building energy consumption, achieving a balance between building energy conservation and indoor comfort has become a research hotspot. Traditional optimization methods mostly rely on a single simulation tool or empirical formula, which makes it difficult to deal with the nonlinear relationships and multi-objective conflicts of complex building systems. This study aims to provide a scientific and reasonable decision-making basis for building design and operation management by integrating domain knowledge enhancement technology and using the Pareto optimal solution of energy consumption intensity (EUI) and thermal comfort (PPD) based on the NSGA-II genetic algorithm and the hybrid superposition model (FNN XGB), so as to achieve the goal of energy saving while ensuring indoor thermal comfort. Artificial intelligence algorithms have significantly improved the scientific nature of green building design and the iterative efficiency of energy-saving solutions. Empirical studies based on public data sets (such as the London building data set) have verified the advantages of artificial intelligence algorithms in key indicators such as energy optimization efficiency.

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• Application Analysis of Artificial Intelligence Technology in the Education Industry

  Wen-Hua Zhang

  With the rapid advancement of artificial intelligence (AI) technology, its application in the field of education has gradually deepened, exerting a profound impact on teaching models, learning support, educational management, and resource allocation. This paper examines the current state of AI application across four dimensions: instructional assistance, personalized learning, educational administration, and resource development. It analyzes practical challenges in areas such as technological compatibility, conceptual transformation, and ethical risks. The study highlights that the integration of AI and education must overcome limitations in data collection, algorithmic opacity, and system silos, while also addressing issues such as conflicts with traditional educational values, disparities in teachers’ digital literacy, and outdated evaluation systems. Based on these insights, the paper proposes coordinated strategies across technological development, educational practice, and social ethics, aiming to provide guidance for building an education ecosystem that balances technological empowerment with humanistic care, and to promote the rational application and deep integration of AI technology in educational settings.

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• Slope Stability Analysis of the Mining Pit in an Open-Pit Nonmetallic Mine

  Qi Liu, Yong-Qiang Ren, Xiang-Yang Wu, Jia-Yao Chen, Xiang-Mei Chen

  The scale of high and steep slopes formed in open-pit mining differs significantly from that in other engineering fields. Due to the extensive range of potential mining sites, the geological conditions of slopes often fail to meet ideal standards, making slope stability analysis critically important. This study examines the slope of an open-pit nonmetallic mine, discussing the primary influencing factors on slope stability, including external factors (stratigraphic lithology and slope geometry) and internal factors (groundwater, blasting vibrations, and natural climate). The finite element strength reduction method was employed to analyze and calculate slope stability, followed by evaluations and recommendations based on the computational results.

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• Study on the Mechanical Properties of Recycled Concrete

  Chi-Yu Sun

  This paper focuses on recycled concrete, a building material that aligns with the concept of sustainable development, and primarily investigates its mechanical properties, such as compressive strength and flexural strength. Through experimental analysis, the effects of various factors on its performance are examined, and measures to improve its properties are discussed. The aim is to provide a theoretical basis and reference for the rational application of recycled concrete in practical engineering, contributing to the green development of the construction industry.

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• Exploring the Application of Machine Learning in Carbon Capture, Utilization, and Storage Technologies

  Bo Zhang, Chuan Zhang

  Carbon capture, utilization, and storage (CCUS) technologies are key solutions to mitigating climate change. In recent years, with the advancement of technology, the application of machine learning (ML) in optimizing various stages of CCUS technologies has garnered increasing attention. This paper summarizes the current status of ML applications in CO₂ capture, CO₂ enhanced oil recovery, CO₂ storage, underground sequestration, as well as in the evaluation of the CCUS technologies chain and source-sink matching. It explores the use of ML theory to optimize processes such as data collection, model prediction and recognition, model parameter adjustment, and result comparison in relation to CCUS technologies. Additionally, a full-chain model for CCUS technologies is constructed, and the future directions of ML in CCUS are envisioned. The research provides insights to fully harness the potential of machine learning in the CCUS field.

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• Sustainability in Pharmaceutical Formulation and Processing: Case Studies on Eco-Friendly Micronisation and Nanonisation Approaches This Article Belongs To The Special Issue: Sustainable Process Engineering: Collaborations between Industry and Academia

  Hien V. Nguyen, Thuy Thi-Nhu Huynh, Linh Nguyen-Ngoc Pham, Tung Minh Ta

  The pharmaceutical industry faces growing pressure to adopt sustainable practices throughout the entire product lifecycle, encompassing the design and synthesis of active pharmaceutical ingredients (APIs), manufacturing, distribution, usage, and disposal of pharmaceutical products. Addressing these challenges demands innovative strategies that balance environmental responsibility with economic and operational feasibility. This paper examines key approaches to achieving sustainability in pharmaceutical formulation and processing, including the use of biodegradable materials, minimizing organic solvent consumption, and implementing energy-efficient continuous manufacturing technologies. Through detailed case studies from our research group, we demonstrate the successful application of these principles to develop eco-friendly formulations and optimize manufacturing processes for pharmaceutical micronisation and nanonisation. This work aims to guide further advancements in sustainable pharmaceutical development.

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• Exploring the Role of the Internet of Things (IoT) on Economic Growth in Nigeria: Challenges and Opportunities

  Fadele Ayotunde Alaba, Muhammad Amina, Umar Ibrahim, Hakeem Sulaimon Adewale, Zainab Adamu Aliyu

  This study explores the role of IoT in driving economic growth in Nigeria, identifying both challenges and opportunities within the IoT network. Using a framework grounded in human capital and endogenous growth theories, the research examines how IoT indicators—such as literacy rates, enrolment ratios, and government spending on IoT—affect economic outcomes. Findings indicate that while IoT can significantly contribute to Nigeria’s GDP growth and labour productivity, various constraints, such as inadequate funding, regional disparities, and infrastructural deficiencies, hinder its full potential. The study underscores the importance of targeted investment in STEM IoT, digital literacy, and vocational training to enhance workforce skills and support economic diversification. The results emphasize the need for structural reforms and stronger institutional support to maximize the economic benefits of the IoT.

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