Development and application of a generalized fatigue driving monitoring system for open-pit mining vehicles: A case study in a myanmar copper mine by Tao Li, Baomeng Chang, Yan Sun, Yaodong Zhou, Bin Zhou, Lubin Zhang

“…Engineering practices yielding the following outcomes: (1) The Beidou positioning antenna demonstrated superior performance in the S&K mine, ensuring accurate vehicle tracking and minimal signal blind spots in challenging open-pit mining environments. (2) The GFDMS effectively identifies unsafe driving behaviors, including speeding, fatigue driving and irregular operations, providing real-time alerts to enhance safety. (3) A comprehensive analysis of system performance demonstrated its effectiveness, reducing traffic incident rates by over 70 % for mining dump trucks and auxiliary vehicles within a year while improving vehicle utilization and operational reliability. (4) Challenges in improving the GFDMS persist in areas such as environmental adaptability, algorithm generalization, and scalability. …”
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Differential Diagnosis of Peripheral Lung Lesions: Capabilities and Limitations of Current Methods by R. N. Islamov, R. A. Sharipov, M. A. Bagirov, R. K. Tukfatullin, G. V. Chitorelidze, E. V. Pavlova, R. K. Yagafarova

“…VATS proves effective for lesions below 3 cm, while thoracotomy is applied to large lesions. An individualized approach remains essential for optimal diagnosis. …”
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A reversible and robust hybrid image steganography framework using radon transform and integer lifting wavelet transform by B. M. El-den, Walid Raslan

“…Data embedding is performed in the middle bit planes of high-frequency sub-bands (LH, HL, HH) using Arithmetic Coding, optimizing space utilization while preserving visual quality. …”
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Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach. by Josh L Espinoza, Chris L Dupont, Aubrie O'Rourke, Sinem Beyhan, Pavel Morales, Amy Spoering, Kirsten J Meyer, Agnes P Chan, Yongwook Choi, William C Nierman, Kim Lewis, Karen E Nelson

“…Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. …”
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From Pixels to Diagnosis: Early Detection of Diabetic Retinopathy Using Optical Images and Deep Neural Networks by Amira J. Zaylaa, Sylva Kourtian

“…The ROC curves of both ResNet-50 and GoogleNet yielded optimal results, followed by SqueezeNet. MobileNet-v2 showed the weakest performance in terms of the ROC, while all networks showed negligible errors in diagnosis and detection. …”
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Integrated impact of urban mixed land use on TOD ridership: A multi-radius comparative analysis by Xinyue Gu, Siyan Lin, Chengfang Wang

“… The global trend toward urbanization has spurred the widespread adoption of transit-oriented development (TOD). While previous research has extensively explored the relationship between land use and TOD ridership, much of it has focused on linear associations at a singular scale. …”
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Prioritising explainable AI-driven recommendations with knowledge graphs and reinforcement learning by Neeraj Tiwary, Shahrul Azman Mohd Noah, Fariza Fauzi

“…By applying optimisation techniques that consider rewards, probabilities, information values, and affinity scores while minimising traversal hops within KG paths, XAIRec learns user preferences from historical data, determines optimal reasoning paths, and enhances recommendation quality by prioritising products with higher relevance. …”
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Force-Driven Model for Automated Clear Aligner Staging Design Based on Stepwise Tooth Displacement and Rotation in 3D Space by Sensen Yang, Yumin Cheng

“…An optimal path was generated by iteratively moving teeth from their initial to target positions and subsequently divided into stages based on a predefined step size. …”
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Improving Portfolio Management Using Clustering and Particle Swarm Optimisation by Vivek Bulani, Marija Bezbradica, Martin Crane

“…Particularly, this research examines different approaches for handling missing values and volatility, while examining their effects on optimal portfolios. …”
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Spatiotemporal Analysis of Eco-Geological Environment Using the RAGA-PP Model in Zigui County, China by Xueling Wu, Jiaxin Lu, Chaojie Lv, Liuting Qin, Rongrui Liu, Yanjuan Zheng

“…It utilized the Analytic Hierarchy Process (AHP), coefficient of variation (CV), and the Real-Coded Accelerating Genetic Algorithm-Projection Pursuit (RAGA-PP) model for evaluation, the latter of which optimizes the projection direction and utilizes PP to transform high-dimensional data into a low-dimensional space, thereby obtaining the values of the projection indices. …”
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Analyzing Momentum Shifts in Tennis: A Machine-Learning Approach to Predicting Match Outcomes by Yuean Xia, Changfeng Li, Tanran Zhang

“…Factor analysis identified key independent variables, while a decision-tree model optimized through random-forest and genetic algorithm techniques was employed to predict match outcomes. …”
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GeoAT: Geometry-Aware Attention Feature Matching Network by Yan Li, Yingdan Wu, Yang Ming, Yong Zhang, Zhesheng Cheng

“…In the future, GeoAT will focus on further optimizing computational efficiency and enhancing robustness.…”
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Efficient deep learning based rail fastener screw detection method for fastener screw maintenance robot under complex lighting conditions by Yijie Cai, Ming He, Bin Chen

“…These complex lighting conditions (CLCs) interfere with the fastener recognition ability of the fastener screw detection algorithm since it can hardly maintain fixed and optimized lighting conditions of the fastener screw. …”
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Rolling Bearing Fault Diagnosis Based on VMD-DWT and HADS-CNN-BiLSTM Hybrid Model by Luchuan Shao, Bing Zhao, Xutao Kang

“…The vibration signals are first reconstructed using a genetic algorithm (GA)-optimized VMD and particle swarm optimization (PSO)-optimized DWT for noise suppression. …”
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A Robust Hybrid MRAPID Controller Design for an Underactuated Nonlinear System With Parametric Uncertainty by Ahmed Abduljabbar Mahmood, Mohamed Abderrahim

“…The hybrid controller design is developed by combining the MRAPIDC design with controller gains applied to each output and incorporating the system adaptation error in a specific configuration. Optimal performance is achieved through parameter tuning via the social spider optimization (SSO) algorithm, and MIT (Massachusetts Institute of Technology) rule criteria are employed to ensure system stability. …”
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Consumer-Centered Collaborative Governance of Regional Business Environment by Tingting Xiang, Hongzhi Lin

“…The experimental results confirm the effectiveness and practicality of the proposed algorithm. The findings reveal that the bi-level programming model, integrating simulated annealing and projection algorithms, provides support for governments in accurately determining investment allocation strategies, enabling the simultaneous maximization of consumer welfare and optimization of the business environment. …”
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Model Predictive Control of Nonlinear System Based on GA-RBP Neural Network and Improved Gradient Descent Method by Youming Wang, Didi Qing

“…The incorporation of GA into RBP can reduce the possibility of the BP neural network falling into a local optimum instead of reaching global optimization. In the online optimizing stage, a multistep-ahead GA-RBP neural network predictor and an improved gradient descent method (IGDM) are proposed to efficiently solve the online optimization problem of nonlinear MPC by minimizing a modified quadratic criterion. …”
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Policy Efforts to Promote the Adoption of Autonomous Vehicles: Subsidy and AV Lanes by Chao Liu, Hongfei Jia, Yu Lin, Guanfeng Wang, Jingjing Tian, Ruiyi Wu, Heyao Gao

“…The first and second stage models are solved using the simulation-optimization and genetic-algorithm-based approaches, respectively. …”
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Automation of reversible steganographic coding with nonlinear discrete optimisation by Ching-Chun Chang

“…Experimental results validate the near-optimality of the proposed optimisation algorithm when benchmarked against a brute-force method.…”
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Time-adaptive phase estimation by Brennan de Neeve, Andrey V. Lebedev, Vlad Negnevitsky, Jonathan P. Home

“…Phase estimation is known to be a robust method for single-qubit gate calibration in quantum computers, while Bayesian estimation is widely used in devising optimal methods for learning in quantum systems. …”
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