Enhanced medical image segmentation using novel level set evolution and efficient optimization by Samad Wali, Adil Jhangeer, Ariana Abdul Rahimzai, Samina Samina, Mudassar Imran

“…Unlike prior edge-based algorithms, which frequently fail with noisy images and have large computing costs, our method incorporates an improved edge indicator term into the level set architecture, considerably improving performance on degraded images. …”
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Optimization of the Canopy Three-Dimensional Reconstruction Method for Intercropped Soybeans and Early Yield Prediction by Xiuni Li, Menggen Chen, Shuyuan He, Xiangyao Xu, Panxia Shao, Yahan Su, Lingxiao He, Jia Qiao, Mei Xu, Yao Zhao, Wenyu Yang, Wouter H. Maes, Weiguo Liu

“…With these improvements, a high-precision 3D canopy point-cloud model of soybeans covering the entire growth period was successfully constructed. …”
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Optimal Allocation of SVG Considering Voltage Mitigation of DG Grid-connected Inverter and APF by Jing XU, Shuya TIAN, Tiejun ZHAO, Xiaogang GAO, Ju YE, Lingyan BU, Wenmiao LIU

“…A multi-objective SVG optimal allocation model is established with minimum total cost of SVG and optimal mitigation effect of system voltage deviation, and the improved genetic algorithm is used to solve the allocation model. …”
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A power-distribution joint optimization arrangement for multi-point source jamming system by Zhihao Cai, Shiqi Xing, Sinong Quan, Xinyuan Su, Junpeng Wang

“…Third, a multi-objective time-varying mapping particle swarm optimization (MOTPSO) algorithm is adopted to solve the model, thereby achieving the optimal arrangement. …”
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BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches by Pinakshi Panda, Sukant Kishoro Bisoy, Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Zheshan Guo, Haipeng Liu, Prince Jain

“…Microarray data are high dimensional, which can degrade the performance of the ML-based models. For this, feature selection becomes essential.MethodsSwarm Optimization Algorithm (SSA), Improved Maximum Relevance and Minimum Redundancy (IMRMR), and Boruta form the basis of this work’s ML-based model BIMSSA. …”
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Diverse solitons wave structures for coupled NLSEs in birefringent fibers with higher nonlinearities using the modified extended mapping algorithm by Karim K. Ahmed, Njah A. Alsahafi, Hamdy M. Ahmed, Salah Boulaaras, M. S. Osman

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Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings by Agis M. Papadopoulos, Konstantinos Polychronakis, Elli Kyriaki, Effrosyni Giama

“…This paper investigates the optimization of insulation thickness with respect to the integration of renewable energy systems in residential buildings in order to improve energy efficiency, maximize the contribution of renewables and reduce life cycle costs. …”
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Optimizing urban energy flows: Integrative vehicle-to-building strategies and renewable energy management by Jian Hern Yeoh, Kai-Yun Lo, I-Yun Lisa Hsieh

“…This study introduces a scalable, multi-objective optimization model that utilizes Vehicle-to-Building (V2B) interactions to mitigate grid load by leveraging EVs as mobile energy storage units. …”
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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…Significance: Furthermore, the study highlights the potential of AI to transform traditional farming practices, reduce labor-intensive processes, and improve decision-making accuracy. The proposed approach serves as a blueprint for agricultural enterprises aiming to adopt AI technologies while ensuring optimal utilization of human and technological resources. …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…The preprocessing process includes imputing missing values and normalizing numerical features so that the model can learn optimally. Performance evaluation shows that the use of SMOTE increases classification accuracy from 95% to 97%, as well as improving precision, recall, and F1-score metrics at almost all anxiety levels. …”
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UCA-YOLOv8n: a real-time and efficient fruit chunks detection algorithm for meal-assistance robot by Fei Liu, Mingyue Hu

“…Methods We propose an improved YOLOv8n algorithm optimized for real-time, high-accuracy fruit chunk detection. …”
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Comprehensive Utilization and Optimal Allocation of Environmental Protection Building Materials in the Construction of Civil Engineering by Li Ren, Huasha Ru, Ruiya Xiao, Yao Ju

“…The research methodology includes a multi-criteria decision-making approach, integrating material selection criteria such as mechanical properties, sustainability, cost, and environmental impact. An optimization model, using genetic algorithms and life cycle assessment, was employed to achieve the best material distribution for specific project needs. …”
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An Opportunistic Array Beamforming Technique Based on Binary Multiobjective Wind Driven Optimization Method by Zhenkai Zhang, Sana Salous, Hailin Li, Yubo Tian

“…Firstly, the emitted signal model and objective functions of optimization are presented. …”
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Aerodynamic Parameter Identification of Projectile Based on Improved Extreme Learning Machine and Ensemble Learning Theory by Tianyi Wang, Wenjun Yi, Youran Xia

“…The improved particle swarm optimization algorithm (IPSO) with an adaptive update strategy is used to optimize the weight and threshold of ELM. …”
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DS-HPPO Deep Reinforcement Learning for Optimal DVFS Control on an Image Signal Processor by Yang Du, Wenhong Li, Xiaoyang Zeng

“…We apply the Parameterized Action Markov Decision Process (PAMDP) to model the above optimization problem and solve the PAMDP with the proposed DS-HPPO deep reinforcement learning algorithm. …”
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Speed and Path Planning Optimization of Autonomous Vehicle to Minimize Lap Time in Racing Track by Young-Jin Roh, Ji-Ung Im, Jong-Hoon Won

“…This method addresses the challenges inherent in high-speed racing environments, where tire friction and vehicle dynamics are critical for achieving optimal lap times. A friction circle model was used to determine the friction coefficient, which is subsequently applied to calculate the maximum feasible speed and acceleration constraints for different track segments. …”
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Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…This paper presents a reinforcement learning-based approach to automate the tuning of a 6thorder combline bandpass filter, operating at 941 MHz, using a Q-learning algorithm. To reduce complexity, only two tuning screws are considered in the optimization. …”
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Hybrid Attention-Enhanced Xception and Dynamic Chaotic Whale Optimization for Brain Tumor Diagnosis by Aliyu Tetengi Ibrahim, Ibrahim Hayatu Hassan, Mohammed Abdullahi, Armand Florentin Donfack Kana, Amina Hassan Abubakar, Mohammed Tukur Mohammed, Lubna A. Gabralla, Mohamad Khoiru Rusydi, Haruna Chiroma

“…The methodology is built on a combination of preprocessing techniques, transfer learning architecture reconstruction, and dynamic fine-tuning strategies. To optimize key hyper-parameters, this study employed the Dynamic Chaotic Whale Optimization Algorithm. …”
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Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma by Bingxin Zhang, Dong Zheng, Shuxia Zhu, Xinyi Zhang, Quanqiang Wang, Zhili Lin, Ziwei Zheng, Shujuan Zhou, Zixing Chen, Sisi Zheng, Enqing Lan, Luning Cui, Hansen Ying, Yu Zhang, Xuanru Lin, Qiang Zhuang, Honglan Qian, Xudong Hu, Yan Zhuang, Qianying Zhang, Zhouxiang Jin, Songfu Jiang, Yongyong Ma, Yongyong Ma, Yongyong Ma

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Intelligent control method of robot based on angle of attack feedback for energy efficiency optimization by WANG Tianzhu, LIU Jiayin, HAN Song, CHE Honglei, SHI Congling

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