A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing by Yang Liu, Yong Li, Wei Cheng, Weiguang Wang, Junhua Yang

“…Finally, we use the greedy method to optimize the user recruitment for each task to select the most suitable users for the tasks. …”
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Integrating Confidence Maps and Visual Servoing for Needle Tracking in Robotic US-Guided Percutaneous Nephrolithotomy by Hoorieh Mazdarani, James Watterson, Rebecca Hibbert, Carlos Rossa

“…Unlike previous methods, where confidence maps were used for probe positioning with static targets, this article introduces the first unified algorithm that optimizes image quality while tracking a moving tool. …”
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Cooperative Downloading in Mobile Ad Hoc Networks: A Cost-Energy Perspective by He Li, Yang Yang, Xuesong Qiu, Zhipeng Gao, Guizhen Ma

“…However, the efficiency, cost, and energy consumption of cooperative downloading are sensitive by content distribution, which is a challenge to get the optimal in mobile ad hoc networks. This paper proposes a cost distribution (OCD) algorithm and a content distribution algorithm based on auction (OCDA) for mobile ad hoc networks based on relative location of nodes and local optimization theory. …”
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Tactical Coordination-Based Decision Making for Unmanned Combat Aerial Vehicles Maneuvering in Within-Visual-Range Air Combat by Yidong Liu, Dali Ding, Mulai Tan, Yuequn Luo, Ning Li, Huan Zhou

“…Finally, an improved particle swarm optimization algorithm (I-PSO) is proposed, which enhances the optimization ability and real-time performance through the design of local social factor iterative components and adaptive adjustment of inertia weights. …”
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Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer by Rui Zhang, Chunfan Jiang, Feng Li, Lin Li, Xiaomin Qin, Jiang Yang, Huabing Lv, Tao Ai, Lei Deng, Chencui Huang, Hui Xing, Feng Wu

“…Various machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression, Random Forest, AdaBoost, and Decision Tree, were used to construct radiomics models based on different ROIs, and diagnostic performances were compared to identify the optimal approach. …”
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Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…While Sequential Minimal Optimization (SMO) has enhanced the efficiency of SVM training, traditional implementations still suffer from high computational cost. …”
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The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…On the contrary, the algorithms applying YOLOv5, YOLOX, YOLOv7 and the paper's improved YOLOv5 achieved the recall rates from 95.26% to 96.28%, while algorithms applying DeepSORT, StrongSORT, Bot-SORT and CombineSORT achieved the MOTA values from 0.887 to 0.901. …”
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Multi-time Scale Voltage-Reactive Power Control for Distribution Network with Distributed Generation by LIU Haotian, ZHENG Chuyu, LENG Yang, LI Qin, ZHANG Hua, CHEN Shidu, LI Jiayong

“…And for the voltage regulation, it can optimize the regulation target according to the voltage sensitivity and the regulation costs of each DG, and thus has better economic performance while adjusting voltages.…”
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A Distributed Resilience Enhancement Strategy for Multi-microgrids Based on System of Systems Architecture by Linxinyan LIN, Junpeng ZHU, Yue YUAN

“…Firstly, the energy exchange process of the multi-microgrid systems is modeled based on the SoS architecture, and the distributed optimization algorithm is used to solve the model, which ensures the privacy of user information. …”
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Load-Balanced Dynamic SFC Migration Based on Resource Demand Prediction by Tian Sun, Hefei Hu, Sirui Zhang

“…Therefore, we propose the Resource Predictive Load Balancing SFC Migration (RP-LBM) algorithm in this paper. The algorithm uses CNN-AT-LSTM to predict VNF resource demands in advance, eliminating the delays associated with dynamic migrations and determining the optimal migration timing. …”
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Electric Bus Charging Schedules Relying on Real Data-Driven Targets Based on Hierarchical Deep Reinforcement Learning by Jiaju Qi, Lei Lei, Thorsteinn Jonsson, Lajos Hanzo

“…As a result, the high-level agent learns an effective policy for prescribing the charging targets for every charging period, while the low-level agent learns an optimal policy for setting the charging power of every time step within a single charging period, with the aim of minimizing the charging costs while meeting the charging target. …”
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A cooperative jamming resource allocation method based on PSO-SSNOA by Wei Liu, You Chen, Xiaohong Zhao, Dejiang Lu, Tianjian Yang

“…This approach innovatively integrates Particle Swarm Optimization (PSO) with the Nutcracker Optimization Algorithm (NOA), while enhancing the nutcracker’s behavioral patterns through seasonal adaptation strategies. …”
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A comparison of tools used for tuberculosis diagnosis in resource-limited settings: a case study at Mubende referral hospital, Uganda. by Adrian Muwonge, Sydney Malama, Barend M de C Bronsvoort, Demelash Biffa, Willy Ssengooba, Eystein Skjerve

“…Clinical variables from a questionnaire and DZM were used to predict TB status in multivariable logistic and Cox proportional hazard models, while optimization and visualization was done with receiver operating characteristics curve and algorithm-charts in Stata, R and Lucid-Charts respectively.…”
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Fractional-Order Adaptive P-Laplace Equation-Based Art Image Edge Detection by Ming Chen

“…The experimental results demonstrate that the algorithm can remove the noise while preserving the texture and details of the image. …”
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Forest cover and canopy health mapping in Australian subalpine landscape: supervised machine learning models for Sentinel-2 and Landsat images by Weerach Charerntantanakul, Marta Yebra, Hilary Rose Dawson, Adrienne Beth Nicotra, Saul Alan Cunningham, Matthew Theodore Brookhouse

“…We tested random-forest (RF), support vector machine (SVM), and multiple linear regression (MLR) to find the algorithm that provides the best accuracy. Cross-validation experiments were undertaken to optimize the model configurations. …”
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Predicting the Attraction and Retention of Customers in Sports Pools in Isfahan City Using a Decision Tree: Presenting a Data Mining-Based Model by Seyed Masoud Mirsaeidi, Davood Nasr Esfahani

“…To evaluate the features, two algorithms—Grasshopper Optimization Algorithm (GOA) and Simulated Annealing (SA)—were used for feature selection, while classification algorithms, specifically Decision Tree (DT) and K-Nearest Neighbors (KNN), were employed to classify and recognize customer behavior. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The optimized algorithm is then used for video skilled movement detection processing to obtain cropped frame images. …”
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Channel-Hopping Using Reinforcement Learning for Rendezvous in Asymmetric Cognitive Radio Networks by Dongsup Jin, Minho Jang, Ji-Woong Jang, Gyuyeol Kong

“…Our proposed RL-based algorithm leverages the actor-critic policy gradient method to learn optimal channel selection strategies by dynamically adapting to the environment and minimizing TTR. …”
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Comparing MEG and EEG measurement set-ups for a brain-computer interface based on selective auditory attention. by Dovilė Kurmanavičiūtė, Hanna Kataja, Lauri Parkkonen

“…Auditory attention modulates auditory evoked responses to target vs. non-target sounds in electro- and magnetoencephalographic (EEG/MEG) recordings. Employing whole-scalp MEG recordings and offline classification algorithms has been shown to enable high accuracy in tracking the target of auditory attention. …”
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Modeling of train flow handling through a limiting single-track section of the route at the organization of high-speed operation using the existing infrastructure by S. V. Karasev, A. D. Kalidova

“…The article examines the problem of studying the process of handling the opposing train flows through a single track section of the route by modeling for the conditions of organizing high-speed operation while minimizing capital investments in infrastructure. …”
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