A crack detection and quantification method using matched filter and photograph reconstruction by Liu Zhen-liang, Zhou An, Ran Xin-ru, Wu Yun-peng, Zhao Wei-gang, Zhang Hao

“…This 3D model, annotated with detected cracks, provides an intuitive and comprehensive representation of bridge damage, facilitating informed decision making in maintenance planning and resource allocation. …”
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Optimal allocation of renewable energy resources in a smart grid under neutrosophic credibility-based uncertainty by Muhammad Zafar Abbas, Rukhshanda Anjum, Muhammad Umar Mirza, Abdulrahman A. Almehizia, Amir Hussain

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A retina-inspired pathway to real-time motion prediction inside image sensors for extreme-edge intelligence by Subhradip Chakraborty, Shay Snyder, Md Abdullah-Al Kaiser, Maryam Parsa, Gregory Schwartz, Akhilesh R Jaiswal

“…Additionally, integrating the sensor and MP compute die using a 3D Cu–Cu hybrid bonding approach improves design compactness by minimizing area usage and simplifying routing complexity. …”
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Evaluation of Modified Reflection Symmetry Decomposition Polarization Features for Sea Ice Classification by Tianlang Lan, Chengfei Jiang, Xiaofan Luo, Wentao An

“…In this research, backscattering coefficients were combined with FD, H/A/α, and MRSD polarization features to create eight feature combinations for comparative analysis. Three machine learning algorithms, Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machines (SVM), were also used for the comparative analysis. …”
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Advanced Machine Learning Methodology for Earthquake Magnitude Forecasting Using Comprehensive Seismic Data by Subhieh El-Salhi, Bashar Igried, Sari Awwad

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QUANTUM INFORMATICS: OVERVIEW OF THE MAIN ACHIEVEMENTS by A. Sigov, E. Andrianova, D. Zhukov, S. Zykov, I. E. Tarasov

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An integrated strategy based on radiomics and quantum machine learning: diagnosis and clinical interpretation of pulmonary ground-glass nodules by Xianzhi Huang, Fangyi Xu, Wenchao Zhu, Lin Yao, Jiahuan He, Junhao Su, Wending Zhao, Hongjie Hu

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A Survey on Anti-Money Laundering Techniques in Blockchain Systems by Leyuan Liu, Xiangye Li, Tian Lan, Yakun Cheng, Wei Chen, Zhixin Li, Sheng Cao, Weili Han, Xiaosong Zhang, Hongfeng Chai

“…It categorizes existing AML techniques into three primary approaches: rule-based methods, such as transaction parameter threshold setting, address-entity association analysis, and cross-chain association analysis; machine learning-based approaches, including support vector machines, logistic regression, decision trees, random forests, k-means clustering, and combining off-chain information; and deep learning-based methodologies, encompassing convolutional neural networks, recurrent neural networks, graph neural networks, and transformer-based models. …”
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Simplifying Field Traversing Efficiency Estimation Using Machine Learning and Geometric Field Indices by Gavriela Asiminari, Lefteris Benos, Dimitrios Kateris, Patrizia Busato, Charisios Achillas, Claus Grøn Sørensen, Simon Pearson, Dionysis Bochtis

“…This can be particularly valuable for farmers who need to make informed decisions about resource allocation and operational planning.…”
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Optimizing Transportation Costs: Enhancing Logistics Efficiency and Resource Utilization in Dynamic Environments by Cao Ngoc Anh, Tran Bich Thao, Tran Ba Hung, Trinh Thu Huong, Nguyen Viet Hung

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Ethical Aspects of the Influence of Neural Networks on the Lives of Students in the Context of a Sociological Approach (using the Example of Students of the IT Department of ETU) by A. S. Kurapova, S. V. Kurapov, A. D. Derzhavina, N. V. Shatilo

“…A significant portion of the respondents expressed concerns about ethical issues related to the use of neural networks, including loss of autonomy in decision-making and lack of human interaction. The analysis of the responses of the ChatGPT-3.5 neural network to questions related to solving ethical dilemmas was carried out, which confirmed the ability of the neural network to emotionally analyze and take into account ethical aspects.Conclusion. …”
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Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma by Qiang Liu, Huiguo Chen, Dongfang Tang, Huibiao Zhang, Shaogeng Chen, Yiran Meng, Boying Zheng, Fei Liu, Jing Zhou, Wen Zhang

“…The TCGA‐LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. …”
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Association between red blood cell distribution width-to-albumin ratio and in-hospital mortality in patients with congestive heart failure combined with chronic kidney disease by Lie-jun Qian, Lu-xi Hong

“…Correlation analysis and machine learning algorithms were used to screen the clinical features associated with RAR. …”
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A Practical Methodology for Accuracy and Quality Evaluation of Structured Light Systems in Automotive Inspection by Antonio Lagudi, Umberto Severino, Loris Barbieri, Fabio Bruno

“…In the integration of structured light systems (SLSs) into automotive manufacturing pipelines, achieving reliable 3D reconstruction under industrial conditions remains a critical challenge. …”
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BRIDGING THE GAP: OPPORTUNITIES, CHALLENGES AND STRATEGIES FOR AI DEPLOYMENT IN PUBLIC SERVICE DELIVERY by Richard Douglas Kamara

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High-resolution energy consumption forecasting of a university campus power plant based on advanced machine learning techniques by Saad A. Alsamraee, Sanjeev Khanna

“…The dataset uniquely integrates energy demand data from the university's Combined Heat and Power Plant (CHPP) alongside critical environmental parameters, such as air temperature, humidity, wind speed/direction, atmospheric pressure, and solar intensity, capturing distinctive consumption patterns across pre-pandemic, pandemic, and post-pandemic periods. Several ML algorithms – Decision Tree (DT), Random Forest (RF), Support Vector Regressor (SVR), K-Nearest Neighbor (KNN), and eXtreme Gradient Boosting (XGBoost) – were rigorously trained, validated, and benchmarked. …”
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An Assessment of Land Use Land Cover Using Machine Learning Technique by V. Pushpalatha, H. N. Mahendra, A. M. Prasad, N. Sharmila, D. Mahesh Kumar, N. M. Basavaraju, G. S. Pavithra and S. Mallikarjunaswamy

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Research on short-term traffic flow prediction based on the PCC-IGA-LSTM model by Junxi Zhang, Shiru Qu, Yang Bi, Lijing Ma

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Structural organization of a fuzzy system for monitoring the condition of equipment and control of a gas distribution station by A. I. Magomedov, I. A. Magomedov, M. Sh. Usmanov

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Multi-Static Radar System Deployment Within a Non-Connected Region Utilising Particle Swarm Optimization by Yi Han, Xueting Li, Tianxian Zhang, Xiaobo Yang

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