Dynamic Optimization of Tunnel Construction Scheduling in a Reverse Construction Scenario by Jianying Wei, Yuming Liu, Xiaochun Lu, Rong Zhao, Gan Wang

“…Tunnel construction, a critical aspect of railway engineering, is a repetitive process with distinct linear characteristics. While the Linear Scheduling Method (LSM) is widely used for scheduling optimization in linear projects, it struggles to accommodate dynamic construction sequences, reverse construction, and flexible team allocation. …”
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Ant Colony Optimization Using Common Social Information and Self-Memory by Yoshiki Tamura, Tomoko Sakiyama, Ikuo Arizono

“…Ant colony optimization (ACO), which is one of the metaheuristics imitating real ant foraging behavior, is an effective method to find a solution for the traveling salesman problem (TSP). …”
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Hybrid MPPT Strategy: Optimizing SEIG Performance in Wind Energy Installation by Fadi Ouafia, Abbou Ahmed, Gaizen Soufiane

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Optimization of Offshore Saline Aquifer CO₂ Storage in Smeaheia Using Surrogate Reservoir Models by Behzad Amiri, Ashkan Jahanbani Ghahfarokhi, Vera Rocca, Cuthbert Shang Wui Ng

“…SRMs showed a runtime improvement of 300 times and an accuracy of 99% compared to the 3D numerical simulator. The genetic algorithm was then employed to determine the optimal rate and duration of CO₂ injection, which maximizes the volume of injected CO₂ while ensuring storage operations’ safety through constraints. …”
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Achieving Faster and Smarter Chest X-Ray Classification With Optimized CNNs by Hassen Louati, Ali Louati, Khalid Mansour, Elham Kariri

“…Finally, model compression through filter pruning, driven by evolutionary algorithms, trims redundant parameters to improve computational efficiency while preserving model accuracy. …”
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Optimizing Cardiovascular Risk Assessment with a Soft Voting Classifier Ensemble by Ammar Oad, Zulfikar Ahmed Maher, Imtiaz Hussain Koondhar, Karishima Kumari, Hammad Bacha

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Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…Experiments conducted on multiple public datasets, including MOT17, MOT20, and VisDrone-MOT, demonstrate that this method remarkably improves tracking accuracy while maintaining real-time performance. On the MOT17 test set, it achieves 63.7% in HOTA, 61.4 FPS in processing speed, and 79.4% in IDF1, outperforming current state-of-the-art tracking algorithms.…”
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Optimized DINO model for accurate object detection of sesame seedlings and weeds by Yong Wang, ShunFa Xu, ZhenYuan Ye, KongHao Cheng

“…However, in environments where the target and the surrounding morphology are highly similar, such as distinguishing sesame seedlings from weeds, the problem essentially becomes one of optimizing edge detection algorithms for similar targets. …”
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Numerical modeling and neural network optimization for advanced solar panel efficiency by Udit Mamodiya, Indra Kishor, Mohammed Amin Almaiah, Monia Hamdi, Rami Shehab, Tayseer Alkhdour

“…Conventionally, such optimization techniques—MPPT (Maximum Power Point Tracking) along with heuristic algorithms—suffer significantly from slow adaptability and track sub optimality under dynamic environments. …”
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Efficient and Composable Masked AES S-Box Designs Using Optimized Inverters by Vedad Hadžic, Roderick Bloem

“…The masking of the AES S-Box is well studied, and most implementations use Canright’s F28 inverter design that decomposes operations in a larger field into a combination of multiplications, additions and inversions in a smaller field. While remarkable, Canright’s inverter design has a sub-optimal multiplicative depth, and can thus not take full advantage of recent developments in low-latency composable masking schemes. …”
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Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? by Mohamed Hassan, Aleksandar Vakanski, Boyu Zhang, Min Xian

“…Other sharpness-based optimizers, however, do not demonstrate consistent results. …”
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Optimizing image capture for low-light widefield quantitative fluorescence microscopy by Zane Peterkovic, Avinash Upadhya, Christopher Perrella, Admir Bajraktarevic, Ramses E. Bautista Gonzalez, Megan Lim, Kylie R. Dunning, Kishan Dholakia

“…In all such cases, it is critical for researchers to optimize the selection and application of scientific cameras to their microscopes, but few resources discuss performance in the low-light regime. …”
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Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…The study had limitations, such as the absence of advanced optimization or dimensionality reduction. In conclusion, it demonstrated that an ensemble model with optimized hyperparameters could classify river water quality more effectively than individual models, contributing to the advancement of sustainable development goals (SGD) related to water access.…”
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Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management by Mahmoud Badee Rokaya Mahmoud, Dalia Ismaeil Ibrahim Hemdan, Samah Hazzaa Alajmani, Raneem Yousif Alyami, Ghada Elmarhomy, Hassan Hashim, El-Sayed Atlam

“…Moreover, ontology-based feature structuring enhances interpretability, while hyperparameter tuning (GridSearchCV, Bayesian Optimization) and model compression techniques (pruning, quantization, knowledge distillation) ensure computational efficiency. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…As a result of this transition, individual customer service visit rates increased by 30%, while corporate customer visits rose by 37%. This study contributes to ongoing research on AI-driven workforce planning and service optimization, particularly within the scope of the AI4LABOUR project.…”
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Simulation and Optimization of Multi-Phase Terminal Trajectory for Three-Dimensional Anti-Ship Missiles Based on Hybrid MOPSO by Jiandong Sun, Shixun You, Di Hua, Zhiwei Xu, Peiyao Wang, Zihang Yang

“…To overcome these challenges, this research introduces a three-dimensional (3D) multi-stage trajectory optimization approach based on the hybrid multi-objective particle swarm optimization algorithm (MOPSO-h). …”
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Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy by Xuemei Li, Xuemei Li, Xuemei Li, Xuemei Li, Xuemei Li, Chao Xiong, Chao Xiong, Chao Xiong, Chao Xiong, Chao Xiong, Siyi Wang, Siyi Wang, Siyi Wang, Zhangjun Ren, Zhangjun Ren, Zhangjun Ren, Qi Jin, Qi Jin, Qi Jin, Jinhai Yu, Jinhai Yu, Jinhai Yu, Jinhai Yu, Jinhai Yu, Yunxiu Chen, Yunxiu Chen, Yunxiu Chen, Puying Gan, Puying Gan, Puying Gan, Puying Gan, Qihua Xu, Qihua Xu, Qihua Xu, Qihua Xu, Qihua Xu, Yaohua Wang, Yaohua Wang, Yaohua Wang, Yaohua Wang, Yaohua Wang, Hongfei Liao, Hongfei Liao, Hongfei Liao, Hongfei Liao, Hongfei Liao

“…Validation results showed that, in addition to MMD, the expression of ACO1 and HCAR1 in orbital adipose tissue of TAO patients was significantly down-regulated, while M2-type macrophages might be involved in regulating the expression of ACO1 in orbital adipose-derived OFs. …”
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AI-based routing algorithms improve energy efficiency, latency, and data reliability in wireless sensor networks by Rahul Priyadarshi, Ravi Ranjan Kumar, Rakesh Ranjan, Padarti Vijaya Kumar

“…Each AI module plays a distinct role-RL handles local routing decisions, while GA and PSO are invoked for global optimization under resource constraints. …”
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Solving the Electric Share-A-Ride Problem Using a Hybrid Variable Neighborhood Search Algorithm by Vincent F. Yu, Sy Hoang Do, Pham Tuan Anh, Cheng-Ta Yeh

“…The MIP model provides optimal solutions for small E-SARP instances using the CPLEX solver, while the HVNS algorithm is designed to solve larger E-SARP instances. …”
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Time-varying MVAR algorithms for directed connectivity analysis: Critical comparison in simulations and benchmark EEG data. by Mattia F Pagnotta, Gijs Plomp

“…Here, we critically compare four recursive tvMVAR algorithms and assess their performance while systematically varying adaptation coefficients, model order, and signal sampling rate. …”
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