Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

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Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment by Mohammad Saleem, Abigail E. Watson, Aisha Anwaar, Ahmad Omar Jasser, Nabiha Yusuf

“…Key findings highlight the efficacy of AI in improving ICI outcomes. Machine learning models successfully identified prognostic cytokine signatures linked to nivolumab clearance. …”
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A trajectory planning and tracking method based on deep hierarchical reinforcement learning by Jiajie Zhang, Bao-Lin Ye, Xin Wang, Lingxi Li, Bo Song

“…First, we present a hierarchical control framework for vehicle trajectory tracking that is based on deep reinforcement learning (DRL) and model predictive control (MPC). We design an upper-level decision model based on the trust region policy optimization algorithm integrated with long short-term memory to obtain more accurate strategies. …”
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Enhanced Community Detection via Convolutional Neural Network: A Modified Approach Based on MRFasGCN Algorithm by Puneet Kumar, Dalwinder Singh, Mamoona Humayun, Ali Alqazzaz, Arun Malik, Ibrahim Alrashdi, Isha Batra, Ghadah Naif Alwakid

“…In this algorithm, researchers have integrated the technique of Graph Convolutional Neural Network (GCN) with the statistical model Markov Random Field (MRF) to get better results and after implementing it on large datasets comparison is done on its results with other state-of-the-art algorithms and got to know its performance is far better than any other algorithm. …”
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Optimal Trajectory Planning for Minimizing Base Disturbance of a Redundant Space Robot with IQPSO by Jianxia Zhang, Fuchao Yang, Guanghua Nie, Jianxin Zhang

“…At last, the proposed improved quantum particle swarm optimization (IQPSO) algorithm was presented. …”
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Enhanced Artificial Rabbit Optimization with attention-based deep learning for leukemia cancer classification by Sabita Rani Behera, Bibudhendu Pati, Devee Sivaprasad Dulam

“…Then the EARO algorithm is designed by using the Levy flight (LF) model for hyperparameter tuning. …”
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Nonlinear Stability Analysis of Shallow-Buried Bias Tunnel Based on Failure Mode Improvement by Wei Luo, Gequan Xiao, Zhi Tao, Jingyu Chen, Xi Lu, Haifeng Wang

“…The SQP algorithm in MATLAB (R2022a) software was used to optimize the solution, and the influence of slope top load, buried depth ratio, cohesion, and axial tensile stress on the surrounding rock pressure and the failure mode of shallow-buried tunnel was analyzed through examples. …”
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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory by Bagher Khalvati, Kaveh Kavousi, Amir Hosein Keyhanipour, Masoud Arabfard

“…To identify robust biomarkers, we applied eight metaheuristic algorithms for feature selection, combined with four classification methods and two data fusion techniques to optimize performance. …”
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Coal-rock interface real-time recognition based on the improved YOLO detection and bilateral segmentation network by Shuzhan Xu, Wanming Jiang, Quansheng Liu, Hongsheng Wang, Jun Zhang, Jinlong Li, Xing Huang, Yin Bo

“…To improve the accuracy and efficiency of coal-rock interface recognition, this study proposes a model built on the real-time detection algorithm, you only look once (YOLO), and the lightweight bilateral segmentation network. …”
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Post-Anesthesia Care Unit (PACU) readiness predictions using machine learning: a comparative study of algorithms by Shahnam Sedigh Maroufi, Maryam Soleimani Movahed, Azar Ejmalian, Maryam Sarkhosh, Ali Behmanesh

“…Machine learning algorithms offer a promising solution by leveraging large amounts of patient data to predict optimal discharge times. …”
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Enhancing flood susceptibility mapping in Sana’a, Yemen with random forest and eXtreme gradient boosting algorithms by Yahia Alwathaf, Ahmed M. Al-Areeq, Yousef A. Al-Masnay, Ali R. Al-Aizari, Nabil M. Al-Areeq

“…The study’s methodology involved optimizing the algorithms through grid search and cross-validation techniques, followed by validation using historical flood data. …”
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Application of a generative adversarial network algorithm to filling blank strips of fractures in formation microresistivity imaging images by Zhengming KANG, Chensheng WU, Guodong YANG, Disheng WU, Ruifei WANG, Xiangyu YANG, Wei GAN

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Optimal Scheduling Strategy of Newly-Built Microgrid in Small Sample Data-Driven Mode by CHEN Shi, YANG Linsen, LIU Yihong, LUO Huan, ZANG Tianlei, ZHOU Buxiang

“…Additionally, the optimal scheduling model is transformed into a Markov decision process and solved using double-delay deep deterministic policy gradient algorithm. …”
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An explainable federated blockchain framework with privacy-preserving AI optimization for securing healthcare data by Tanisha Bhardwaj, K. Sumangali

“…PPFBXAIO employs Secure Hash Algorithm 256 (SHA-256) for blockchain-backed secure model updates, Min-Max normalization for feature scaling, and the Levy Grasshopper Optimization Algorithm (LGOA) for optimal feature selection and federated model tuning. …”
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Performance Evaluation and Optimization of 3D Gaussian Splatting in Indoor Scene Generation and Rendering by Xinjian Fang, Yingdan Zhang, Hao Tan, Chao Liu, Xu Yang

“…The results demonstrate significant performance improvements in the optimized 3DGS algorithm: the PSNR metric increases by 4.3%, and the SSIM metric improves by 0.2%. …”
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A study on improved random forest-based anomaly detection of regional tariff data under distributed photovoltaic access by Shujun Ji, Kai Liu, Bo Ling, Jiadong Li, Jinteng Wang, Xun Ma

“…To ensure the reliability of the measurement and calculation results for electric energy and electricity charges, it is necessary to accurately determine the anomalous data in the regional electricity pricing datasets and consequently propose an anomaly detection method for regional electricity price data based on an improved random forest algorithm under distributed photovoltaic access. …”
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Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance by Qi Tang, Huan Wang

“…To solve the model, we design an improved particle swarm algorithm combining genetic operators, crossover operators and elite retention operator. …”
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Coordinated Optimal Control of Secondary Cooling and Final Electromagnetic Stirring for Continuous Casting Billets by Dongsheng Wu, Zhenping Ji, Jian Yang, Hongwei Gao, Jiahui Yu, Zhaojie Ju

“…The solidification and heat transfer model are developed for the computation of billet temperature and the solidification, and the adaptive grid method is used to improve the diversity and robustness of optimal solutions. …”
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Optimization of Central Pattern Generator-Based Torque-Stiffness-Controlled Dynamic Bipedal Walking by William Suliman, Chadi Albitar, Lama Hassan

“…This reduction enables the employment of the particle swarm algorithm to find the optimal values of these parameters which lead to different solutions with different performance criteria. …”
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Multi-objective optimization placement strategy for SDN security controller considering Byzantine attributes by Tao WANG, Hongchang CHEN

“…By giving the software defined network distributed control plane Byzantine attributes, its security can be effectively improved.In the process of realizing Byzantine attributes, the number and location of controllers, and the connection relationship between switches and controllers can directly affect the key network performance.Therefore, a controller multi-objective optimization placement strategy for SDN security controllers considering Byzantine attributes was proposed.Firstly, a Byzantine controller placement problem (MOSBCPP) model that comprehensively considered interaction delay, synchronization delay, load difference and the number of controllers was constructed.Then, a solution algorithm based on NASG-II was designed for this model, which included the initialization function, the mutation function, the fast non-dominated sorting function and the elite strategy selection function.Simulation results show that this strategy can effectively reduce interaction delay, synchronization delay, load difference and the number of controllers, while improving control plane security.…”
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