Exploring the Realization of Creative Dimensions within the Metaverse: The Case of Tabriz Metropolis by Saied Jaffari namvar, Hossein Nazmfar, Ibrahim Taghav

“…To ascertain the relative importance of research components, 20 experts were consulted using the preferential weighting evaluation ratio algorithm (SOARA). The weights of indicators and sub-indices were determined and ranked utilizing the Aras Gray analytical model. …”
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…A coupled land–atmosphere RT model (RTM) and shuffled complex evolution optimization algorithm were first implemented at globally distributed VIIRS pixels for realistic simulation of land surface reflectance corresponding Landsat spectral bands and FAPAR under various conditions. …”
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Stratified allocation method for water injection based on machine learning: A case study of the Bohai A oil and gas field by Changlong Liu, Pingli Liu, Qiang Wang, Lu Zhang, Zechao Huang, Yuande Xu, Shaojiu Jiang, Le Zhang, Changxiao Cao

“…Fourth, the optimized BP neural network model exhibits enhanced prediction accuracy, improved generalization capabilities, and superior dynamic relationship–capturing abilities. …”
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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…The review highlights the utility of various ML approaches in classifying activity levels and significantly improving the prediction of sedentary behavior, offering a promising approach to address this widespread health issue.ConclusionML algorithms, including supervised and unsupervised models, show great potential in accurately detecting and predicting sedentary behavior. …”
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Deepfake Face Detection and Adversarial Attack Defense Method Based on Multi-Feature Decision Fusion by Shanzhong Lei, Junfang Song, Feiyang Feng, Zhuyang Yan, Aixin Wang

“…The final decisions from both modules were integrated using a voting method, completing the deepfake face detection process. Ultimately, the model’s robustness was validated by generating adversarial samples using the I-FGSM algorithm and optimizing model performance through adversarial training. …”
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Automated design framework for excavation retaining structures: Extending IFC standards and integrating BIM with geotechnical simulation by Qiwei Wan, Yuyuan Zhu, Haibin Ding, Wentao Hu, Changjie Xu

“…Key contributions include: (1) the extension of the IFC standard to support excavation retaining structures with objects like IfcBracedPit and IfcPitWall, improving interoperability between geotechnical models and BIM systems; (2) the integration of heuristic algorithms for automated optimization of deformation control parameters, reducing manual intervention; and (3) the promotion of design methodology that bypasses two-dimensional modeling and directly generates three-dimensional models, enhancing efficiency and allowing engineers to focus on high-level decision-making. …”
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Use Cases of Machine Learning in Queueing Theory Based on a <i>GI</i>/<i>G</i>/<i>K</i> System by Dmitry Efrosinin, Vladimir Vishnevsky, Natalia Stepanova, Janos Sztrik

“…Machine learning (ML) in queueing theory combines the predictive and optimization capabilities of ML with the analytical frameworks of queueing models to improve performance in systems such as telecommunications, manufacturing, and service industries. …”
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Quantum AI: A Cognitive Machine Learning Technique based on Nurturing Food Security Sustainability Predictive Analysis for Life Science - Bioengineering in Healthcare by Senthil G.A., Monica K.M., Prabha R., Prinslin L., Elavarasi R.

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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…To solve this problem, this paper proposes a hybrid method that combines multimodal data-aware attacks with Light Gradient Boosting Machine (LightGBM) and Support Vector Regression (SVR) agent models. By using Particle Swarm Optimization-Genetic Algorithm (PSO-GA) for optimal architecture search and combining the dynamic adaptability of Deep Q-Network (DQN) algorithm, this method can automatically identify the most suitable GNN architecture for power data monitoring, thereby improving the adaptive detection and defense efficiency of the system. …”
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Prediction of formation pressure in underground gas storage based on data-driven method by SUI Gulei, FU Yujiang, ZHU Hongxiang, LI Zunzhao, WANG Xiaolin

“…Introducing the proportion of gas injection-production to screen pressure monitoring wells can improve the predictive performance of the data-driven model. …”
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IMAGE SEGMENTATION AND OBJECT SELECTION BASED ON MULTI-THRESHOLD PROCESSING by Vladimir Yu. Volkov, Oleg A. Markelov, Mikhail I. Bogachev

“…The main advantage of the proposed approach consists in the minimisation of the post-processing shape modification of the selected objects. …”
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Design and performance analysis of wear-resistant micro-groove cutting tool: Numerical simulation and experimental study by Feilong Du, Fukuan Chen, Tao Zhou, Hongfei Yao, Xuefeng Zhao, Dongwei Zhu, Lin He

“…ML algorithms were employed to develop predictive surrogate models, subsequently driving GA optimization of critical geometric parameters. …”
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Data‐sharing strategies in medical consortium based on master‐slave multichain and federated learning by Bohan Kang, Ning Zhang, Jianming Zhu

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Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…Predictive Control optimization often relies on exhaustive enumeration of voltage vectors within the finite control set. …”
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Study on Predicting Blueberry Hardness from Images for Adjusting Mechanical Gripper Force by Hao Yin, Wenxin Li, Han Wang, Yuhuan Li, Jiang Liu, Baogang Li

“…The radial basis network optimized by the chimpanzee optimization algorithm (ChOA-RBF) model was compared with a non-optimized model, and the results showed that the ChOA-RBF prediction model has significant advantages in predicting fruit hardness. …”
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Accurate GRACE terrestrial water storage estimations via a new fusion method by Min Dai, Hao Zhou, Wenjing Ma, Shuyun Zheng, Mingyang Xia, Yaozong Li, Zhicai Luo

“…Urgently addressing this issue by optimizing different products with rigorous algorithms is crucial to enhance the comprehension of global and regional TWS variability. …”
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Analyzing Student Graduation and Dropout Patterns Using Artificial Intelligence and Survival Strategies by Behrouz Alefy, Vahid Babazadeh

“…From the careful investigation of the convergence curves obtained from the improved models, the study showed that the Cat Boost Classifier modified with the Weevil Damage Optimization Algorithm (CAWD) model was the best among all with an amazing accuracy of 0.993 after 140 iterations. …”
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An Integrated Approach to the Determination of Wages of Bank Employees by Alexander S. Artamonov

“…The integrated approach that was used to calculate the wages of employees of the bank employees taking into account the proposed comparison algorithm with market data on wages submitted by the consulting companies, may potentially contribute to improving the competitiveness of HR-brand of the organization and optimize the size of the wage fund.…”
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A Review of Embodied Grasping by Jianghao Sun, Pengjun Mao, Lingju Kong, Jun Wang

“…In reinforcement learning, the pre-trained model is used to obtain the optimal reward function, which improves the learning efficiency and ability of reinforcement learning; (3) embodied agent: The pre-trained model adopts hierarchical or holistic execution to achieve end-to-end robot control. …”
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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…To reduce data complexity and improve model efficiency, the input by selecting specific frequency points based on SHAP values is further optimized. …”
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