Towards a Digital Twin for Gas Turbines: Thermodynamic Modeling, Critical Parameter Estimation, and Performance Optimization Using PINN and PSO by Jian Tiong Lim, Achnaf Habibullah, Eddie Yin Kwee Ng

“…The results demonstrated that GTPO could be optimized with the application of conformal prediction when the true GTPO is detected to be higher than the upper range of GTPO obtained from the ANN model with a conformal prediction of a 95% confidence level. …”
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Leveraging AI to explore structural contexts of post-translational modifications in drug binding by Kirill E. Medvedev, R. Dustin Schaeffer, Nick V. Grishin

“…Recent advancements in computational power and artificial intelligence, particularly in deep learning algorithms and protein structure prediction tools like AlphaFold3, have opened new possibilities for exploring the structural context of interactions between PTMs and drugs. …”
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Supervised Learning of Depth Estimation From Imperfect Rectified Stereo Laparoscopic Images of Liver Surface by Chongan Zhang, Ziyi Jin, Xiaoyue Liu, Yuelong Liang, Xiao Liang, Peng Wang, Xiujun Cai, Xuesong Ye

“…A dataset is created for laparoscopic liver depth images, and the ACVNet++ algorithm is tested on this dataset. The experiments demonstrate that, compared to non-learning algorithms based on white light image features, the ACVNet++ algorithm reduces the average absolute error (MAE) and endpoint error (EPE) of depth prediction under white light conditions by 51% and 44%, reaching 2.46 mm and 2.56 pixels, respectively. …”
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Advancements in Intelligent Sensing Technologies for Food Safety Detection by Wenhui Jiang, Changhong Liu, Wei Liu, Lei Zheng

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Machine learning assisted estimation of total solids content of drilling fluids by B.T. Gunel, Y.D. Pak, A.Ö. Herekeli, S. Gül, B. Kulga, E. Artun

“…In the final stage, different evaluation metrics were employed to evaluate and compare the performance of different classes of machine learning models. Among all algorithms tested, random forests algorithm was found to be the best predictive model resulting in consistently high accuracy. …”
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Multi-function supported privacy protection data aggregation scheme for V2G network by Baiji HU, Xiaojuan ZHANG, Yuancheng LI, Rongxin LAI

“…In view of the problem that the functions of the current privacy protection data aggregation scheme were insufficient to meet the increasingly rich application requirements, a multi-function supported privacy protection data aggregation (MFPDA) scheme for V2G network was proposed.By using cryptographic algorithms such as BGN, BLS, and Shamir’s secret sharing, as well as fog computing and consortium blockchain technology, multiple security functions like fault tolerance, resistance to internal attacks, batch signature verification, no need for trusted third parties, and multiple aggregation functions were integrated into one privacy protection data aggregation scheme.Security analysis shows that the proposed scheme can protect data aggregation’s security, privacy and reliability.The performance evaluation shows that the introduction of fog computing can significantly reduce the computing overhead of the control center, and the reduction rate can be as high as 66.6%; the improvement of the consortium blockchain can effectively reduce the communication and storage overhead of the system, and the reduction rate can reach 16.7% and 24.9% respectively.…”
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Pengembangan Auto-AI Model Generatif Analisis Kompleksitas Waktu Algoritma Untuk Data Multi-Sensor IoT Pada Node-RED Menggunakan Extreme Learning Machine by Imam Cholissodin, Dahnial Syauqy, Dwi Ady Firmanda, Ibrahim Aji, Edy Rahman, Syazwandy Harahap, Fernando Septino

“…Based on the tests that have been carried out, the difference in value between the actual data and the prediction results in the size of the MAPE average value of 11.90%, which shows a fairly small error value. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

“…When combining PPF and MXF together to develop GSV models, HBA(Site/Type) with double stratification factors (i.e. typical site and forest type) showed similar performance, with only a minor reduction in RMSE by 0.45 m3/ha for PPF and 0.15 m3/ha for MXF. …”
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Aspects of Developing A Methodology for Managing Digital Financial Assets by A. Yu. Proskuryakov

“…The subject of the study is methods, models and algorithms for automated monitoring and management of digital financial assets and cryptocurrencies. …”
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Position Selection and Collision-Free Path Planning for Fruit Picking Robots by Yonghee Cho, Dongwoon Choi, Kwangeun Ko, Jong Hyeon Park

“…Additionally, a method for collision-free path planning in joint space using the model predictive artificial potential field (MPAPF) algorithm is proposed. …”
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AI-Enhanced Criminal Investigations and Ḥudūd Offenses: A Sharīʿah Compliance Framework by Abubakar Muhammad Jibril, Rabiu Abdulmudallib Bello, Abbas Abubakar

“…It takes the legal normative doctrinal approach to examine predictive policing and facial recognition against Qurʾānic evidentiary and confessionary requirements. …”
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Intelligent Integration Method of AI English Teaching Resource Information under Multi-Agent Collaboration by Minjuan Liu

“…In order to improve the intelligent effect of English teaching in the era of intelligent education, this article conducts an intelligent integration system of AI English teaching resources and information on the basis of multi-agent collaboration. …”
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LH-YOLO: A Lightweight and High-Precision SAR Ship Detection Model Based on the Improved YOLOv8n by Qi Cao, Hang Chen, Shang Wang, Yongqiang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…However, detecting multi-scale ship targets in complex backgrounds leads to issues of false positives and missed detections, posing challenges for lightweight and high-precision algorithms. There is an urgent need to improve accuracy of algorithms and their deployability. …”
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Hyperspectral Detection of Pesticide Residues in Black Vegetable Based on Multi-Classifier Entropy Weight Method by Rongchang Jiang, Guoqiang Zhuang, Shijie Xie, Yang Wang, Guoqi Zhang, Dandan Qu, Wanzhi Wen

“…Three dimensionality reduction techniques, competitive adaptive reweighted sampling, random frog leaping, and successive projections algorithm, were compared. …”
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Method and Optimization of Key Parameters of Soil Organic Matter Detection Based on Pyrolysis Coupled with Artificial Olfaction by Mingwei Li, Xiao Li, Xuexun Li, Wenjun Wang, Yulong Chen, Long Zhou, Xiaomeng Xia

“…Finally, the Back-Propagation Neural Network (BPNN) and Partial Least-Squares Regression (PLSR) algorithms were used to establish an SOM prediction model after obtaining soil pyrolysis gases under the optimal combination of pyrolysis parameters. …”
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The State of Artificial Intelligence and its Prospects in Pakistan's Medical Sector by Rohail Akhtar Habib, Yumna Sattar Khan

“…One possible result of AI integration is the early detection of diseases, especially in rural locations where access to expert medical care is limited. Predictive analytics using machine learning algorithms has become more popular in Pakistani healthcare. …”
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Optimization Strategies in Quantum Machine Learning: A Performance Analysis by Nouf Ali AL Ajmi, Muhammad Shoaib

“…The performance of predictive models using these optimizers is rigorously evaluated through key metrics, including accuracy, precision, recall, and F1 score. …”
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The Evolution of Portfolio Theory: Integrating Machine Learning with Markowitz Optimization by Xu Junhao

“…ML increases portfolio flexibility and robustness by aligning predictive modeling with optimization objectives. This evolving methodology lays the foundation for a more responsive, data-informed investment strategy in today’s finance, providing a viable alternative to the limitations of traditional models.…”
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AI-enhanced digital therapeutics for cognitive impairment: integrating mobile applications, virtual reality, and wearable devices by Dian Jiao

“…The integration of artificial intelligence enables dynamic personalization, predictive analytics, and multi-modal data fusion, creating unified therapeutic ecosystems that enhance outcomes despite persistent challenges related to data security, ethics, and algorithmic transparency. …”
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Radiomic nomograms in CT diagnosis of gall bladder carcinoma: a narrative review by Nirupam Konwar Baishya, Kangkana Baishya

“…Abstract Radiomics is a method that extracts many features from medical images using various algorithms. Medical nomograms are graphical representations of statistical predictive models that produce a likelihood of a clinical event for a specific individual based on biological and clinical data. …”
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