Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…To address the challenges of significant scale variations and difficulty in extracting discriminative features for small targets in airborne remote sensing object detection, while considering the constraints and efficiency requirements of onboard systems, this article proposes a lightweight detection algorithm. …”
Get full text

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. …”
Get full text

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.…”
Get full text

Predicting the subclinical carotid atherosclerosis in overweight and obese patients using a machine learning model by D. V. Gavrilov, T. Yu. Kuznetsova, M. A. Druzhilov, I. N. Korsakov, A. V. Gusev

“…The introduction of such risk stratification algorithms into practice will increase the accuracy and quality of CVR prediction and optimize the system of preventive measures.…”
Get full text

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. …”
Get full text

Dense Matching with Low Computational Complexity for Disparity Estimation in the Radargrammetric Approach of SAR Intensity Images by Hamid Jannati, Mohammad Javad Valadan Zoej, Ebrahim Ghaderpour, Paolo Mazzanti

“…Notably, unlike traditional local and global models, the computational complexity of the proposed approach remains stable as the input size or kernel dimensions increase while memory consumption stays low. Compared to a pyramid-based local normalized cross-correlation (NCC) algorithm and adaptive semi-global matching (SGM) models, the proposed method maintains good accuracy comparable to adaptive SGM while reducing processing time by up to 50% relative to pyramid SGM and achieving a 35-fold speedup over the local NCC algorithm with an optimal kernel size. …”
Get full text

Beamforming design for energy-constrained full-duplex two-way relaying system by Wei WANG, Liyuan AN, Guoan ZHANG, Shibing ZHANG

“…A beamforming design was proposed under simultaneous wireless information and power transfer (SWIPT) protocol.A utility optimization problem was considered aiming to maximize the harvested energy by jointly optimizing the beamforming matrix,the power splitting ratio at the relay and the transmit powers at the sources.Since the formulated joint optimization problem was nonconvex,it was difficult or even intractable to obtain the global optimal solution.To overcome this issue,the objective problem into three subproblems was decoupled which could be solved by the proposed semidefinite relaxation technique and the derived constraints activation solution,respectively.The solution was finally obtained with the proposed convergent iterative algorithm.Simulation results show that the proposed joint optimization scheme achieves the optimal performance.Compared with the traditional half-duplex (HD) algorithm,the proposed algorithm can obtain 2~3 times energy harvesting (EH) efficiency improvement,while the computational complexity increases slightly.…”
Get full text

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. …”
Get full text

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. …”
Get full text

Research on pedestrian detection technology for mining unmanned vehicles by ZHOU Libing, YU Zhengqian, WEI Jianjian, JIANG Xueli, YE Baisong, ZHAO Yexin, YANG Siliang

“…YOLOv3 and a coal mine key position personnel unsafe behavior recognition method based on improved YOLOv7 and ByteTrack experienced missed detections and false positives based on enhanced images, while the proposed pedestrian detection algorithm effectively mitigated these issues.…”
Get full text

Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications by Shaobo Ma, Yongkang Chen, Zhefan Li, Junlin Chen, Xiaolan Zhong

“…While cylinder fitting algorithms provide a three-dimensional (3D) solution for trunk detection, their performance in complex forest environments remains limited due to sensitivity to parameters like distance thresholds. …”
Get full text

Subcortical Brain Segmentation Based on a Novel Discriminative Dictionary Learning Method and Sparse Coding by Xiang Li, Ying Wei, Yunlong Zhou, Bin Hong

“…For the shared dictionary, a regularization term is used to minimize the between-class scatter of corresponding shared coefficients so that they can learn shared image patterns. The optimization algorithms are developed to solve the problems in the learning step. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Obstacle Avoidance of Surface Agent Formation Based on Streamline Traction at Fixed-Time by Yiping Liu, Yameng Niu, Jianqiang Zhang, Weihao Tao

“…The optimal guiding angular velocity signal is obtained through quadratic programming, ensuring that the SA steers towards the designated position while avoiding obstacles. …”
Get full text

Hybrid precoding method for mmWave massive MIMO systems based on LFM by Haoyi CHEN, Yifan DING, Ying CHENG

“…Analog-digital hybrid precoding is a key technology for millimeter wave massive MIMO systems that reduce hardware costs while balancing system performance.However,the traditional hybrid precoding scheme often needed to find a suitable codebook for precoding,and some codebooks were not easy to obtain or had deviations in actual situations.An analog-digital hybrid precoding method based on latent factor model (LFM) in machine learning without codebook was proposed for this problem.The LFM decomposition and stochastic gradient descent method were used to approximate the designed precoding matrix to the optimal full digital precoding matrix for good performance.The simulation results show that compared with the hybrid precoding design method based on orthogonal matching pursuit (OMP) algorithm,this method not only does not need a codebook,but also has better performance than the hybrid precoding algorithm based on OMP algorithm,which is closer to optimal full digital precoding method.…”
Get full text

Methodological aspects of inventory management in logistics under modern conditions by A. G. Sakharov, A. E. Trubin, O. P. Kultygin, A. Yu. Anisimov

“…The article aims to design optimal inventory management algorithms in logistics in the current environment. …”
Get full text

Classification-based point cloud denoising and 3D reconstruction of roadways by Denghong CHEN, Ning PANG, Wen NIE, Juqiang FENG, Jiliang KAN, Jinjing ZHANG

“…The reconstruction algorithm could reduce holes effectively while maintaining the accuracy and smoothness of the roadway model. …”
Get full text

Enhancing Spreading Factor Assignment in LoRaWAN with a Geometric Distribution Approach for Practical Node Distributions by Phanupong Tempiem, Rardchawadee Silapunt

“…While the GD algorithm consistently demonstrated superior DER values across varying coverage areas and payload sizes, it incurred a slight increase in energy consumption due to node allocations to higher SFs. …”
Get full text

Indoor Positioning System based on SSA-ELM Neural Network for Visible Light by JIA Kejun, NIU Zhen, YU Kai, ZHANG Zhicong, PENG Duo, CAO Minghua

“…【Objective】The Extreme Learning Machine (ELM) neural network algorithm in the traditional indoor Visible Light Positioning (VLP) system suffers from unstable convergence and a tendency to get stuck in local optimal states, resulting in decreased positioning accuracy. …”
Get full text