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

“…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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IMPROVEMENT OF PASSENGER SERVICE PROCESSES OF DEPARTING FLIGHT BASED ON PROJECT MANAGEMENT METHODS by S. A. Kropiventseva

“…The article considers the formalization of the service technology of departing passengers into network model, which is a good basis for improving the service technology, monitoring the performance that determines the process duration and service optimization in cost and resources. …”
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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

“…This study presents an artificial intelligence-based optimization framework that improves forecasting accuracy, computational speed, and real-time adaptability. …”
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PdYOLO: A Lightweight Algorithm for Detecting Peach Fruits Against a Peach Tree Background by Jiajun Zhang, Jialin Zhang, Kazuki Kobayashi

“…To address these challenges, this study introduces PdYOLO (Peach detection based on YOLOv8s), an innovative peach detection model optimized within the YOLOv8s framework. This model enhances recognition accuracy, reduces algorithm complexity, and satisfies lightweight requirements. …”
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An efficient algorithm for pedestrian fall detection in various image degradation scenarios based on YOLOv8n by Jianhui Xun, Xuefeng Wang, Xiufang Wang, Xiaoliang Fan, Peishuai Yang, Zhifei Zhang

“…Additionally, the Cross Stage Partial Bottleneck with 2 Convolution Block (C2f) was optimized to reduce computational load and parameter count without compromising performance, while the Inner Extended Intersection over Union (Inner-EIoU) loss function was employed to improve bounding box regression accuracy and speed. …”
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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

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LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…After a series of improvements, LBT-YOLO outperforms YOLOv8n and other detection algorithms on the Autonomous Driving BDD100K dataset, with an average accuracy improvement of 2.4% while reducing the number of model parameters by 48.2%.…”
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Voltage Support Capacity Improvement for Wind Farms with Reactive Power Substitution Control by Yuegong Li, Guorong Zhu, Jianghua Lu, Hua Geng

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A study on an efficient citrus Huanglong disease detection algorithm based on three-channel aggregated attention by Yizong Wang, Zhengrong Xiao, Hong Wang, Fei Li, Jiya Tian

“…Background Aiming at the problems of complex and diverse field symptoms of citrus Huanglong disease (HLB), low efficiency and insufficient recognition accuracy of traditional detection methods, this study proposes an efficient detection algorithm based on improved You Only Look Once (YOLO)v8. …”
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Improving energy efficiency and network performance in IaaS cloud with virtual machine placement by Jian-kang DONG, Hong-bo WANG, Yang-yang LI, Shi-duan CHENG

“…The existing virtual machine(VM) placement schemes mostly reduce energy consumption by optimizing utilization of physical server or network element.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,a VM placement scheme was proposed to achieve two objectives.One is to minimize the number of activating physical machines and network elements to reduce the energy consumption,and the other is to minimize the maximum link utilization to improve the network performance.This scheme is able to reduce the energy consumption caused by physical servers and network equipment while optimizing the network performance,making a trade off between energy efficiency and network performance.A novel two-stage heuristic algorithm for a solution was designed.Firstly,the hierarchical clustering algorithm based on minimum cut and best fit algorithm was used to optimize energy efficiency,and then,local search algorithm was used to minimize the maximum link utilization.The simulations show that this solution achieves good results.…”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). …”
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A Prescriptive Approach Based on Fuzzy Cognitive Maps and Genetic Algorithms for Disease Management in Beef Production by Rodrigo Garcia, Jose Aguilar, Angel Pinto, William Hoyos

“…The FCM captures expert knowledge through causal relationships between symptoms, treatments, and diagnoses, while the GA optimizes treatment actions to achieve desired health outcomes. …”
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Improved RRT*-Connect Manipulator Path Planning in a Multi-Obstacle Narrow Environment by Xueyi He, Yimin Zhou, Haonan Liu, Wanfeng Shang

“…This paper proposes an improved RRT*-Connect algorithm (IRRT*-Connect) for robotic arm path planning in narrow environments with multiple obstacles. …”
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Algorithm for Managing Patients Hospitalized in the Surgical Wards Due to COVID-19-Related Acute Abdominal Pathology by D. G. Buribayev, D. B. Tulyaganov, Kh. E. Anvarov

“…The application of the developed algorithm will optimize the management of patients with COVID-19-related acute surgical pathology, guarantee rapid decision-making while minimizing the risk of infection, reduce the risk of complications and adverse outcomes.…”
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Emerging technologies in airway management: a narrative review of intubation robotics and anatomical structure recognition algorithms by Weixiong Chen, Yu Tian, Yingjie Wang, Lili Feng, Mannan Abdul, Shuangshuang Li, Wenxian Li, Yuan Han

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A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

“…This article addresses the issues of missed and false detections in existing aircraft target fine-grained recognition algorithms for remote sensing images by proposing an improved algorithm based on YOLOv8, called FD-YOLOv8 (Focus Detail-YOLOv8). …”
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Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach by Khalid Alnajim, Ahmed A. Abokifa

“…The optimization framework aims to balance the conflicting objectives of minimizing response time while maximizing water quality metrics after contamination events. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. The core of the research lies in enhancing the feature extraction capability of the model, optimizing the feature expression of the model by introducing the CBAM attention mechanism, and improving the original structure of the neck component. …”
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Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…Experimental results demonstrate that compared with classical UNet, the optimized network achieves 2.05% and 2.58% improvements in F1-Score and IoU, respectively, while reducing the parameter count to 57.25% of the original model. …”
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