A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…The CFSD-UAVNet model was evaluated on the publicly available SeaDronesSee maritime dataset and compared with other cutting-edge algorithms. …”
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A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY by Lev Raskin, Yurii Parfeniuk, Larysa Sukhomlyn, Mykhailo Kravtsov, Leonid Surkov

“…Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. …”
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Comprehensive benefits evaluation of low impact development using scenario analysis and fuzzy decision approach by Ting Ni, Xiaohong Zhang, Peng Leng, Mark Pelling, Jiuping Xu

“…The framework’s novelty lies in the integration of the hesitant fuzzy weighted average algorithm to handle subjective uncertainties in expert judgment and the incorporation of multi-return period scenarios to enhance the robustness of the evaluation. …”
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Adaptive Covariance Matrix for UAV-Based Visual–Inertial Navigation Systems Using Gaussian Formulas by Yangzi Cong, Wenbin Su, Nan Jiang, Wenpeng Zong, Long Li, Yan Xu, Tianhe Xu, Paipai Wu

“…Our algorithm has shown significantly higher accuracy compared to the famous VINS-Mono framework, outperforming it by 18.18% on average, as well as the optimization rate of RMS, which reaches 65.66% for the F1 dataset and 41.74% for F2 in the field tests outdoors.…”
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Research on power system transformation based on edge node technology under the background of carbon neutrality by LI Jin, GAO Hongliang, LIU Kemeng, XIE Hu

“…In each island, the improved particle swarm optimization algorithm is used to reasonably distribute the power tasks, forming a novel power system with the coordinated planning of source-network-load-storage as the core. …”
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CT-TDMA:efficient TDMA protocol for underwater sensor networks by Lu HONG, Feng HONG, Zheng-bao LI, Zhong-wen GUO

“…Aimed at underwater acoustic sensor networks(UWSN),a novel sender based conflict model with the schemes of allocating continuous time was presented,including local conflict graph(LCG)and a distribute algorithm to generate LCG.Moreover,CT-TDMA,an efficient TDMA protocol based on the conflict model was also proposed,which used heuristic priority rules to allocate transmitting moments for all nodes.CT-TDMA exploits the diversity of propagation delay of different links in UWSN to decrease the idle time between packets at the same receiving node,which helps in improving the throughput.And a heuristic schedule algorithm is applied to shorten the process of allocating continuous time for each node.Simulation results show that,compared with traditional TDMA protocols such as ST-MAC,network throughput of CT-TDMA has increased 20% and end to end delay has decreased 18%;compared to the theoretically optimal scheme with global knowledge,CT-TDMA has achieved 80% network throughput and the end to end delay is only 12% longer.…”
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CT-TDMA:efficient TDMA protocol for underwater sensor networks by Lu HONG, Feng HONG, Zheng-bao LI, Zhong-wen GUO

“…Aimed at underwater acoustic sensor networks(UWSN),a novel sender based conflict model with the schemes of allocating continuous time was presented,including local conflict graph(LCG)and a distribute algorithm to generate LCG.Moreover,CT-TDMA,an efficient TDMA protocol based on the conflict model was also proposed,which used heuristic priority rules to allocate transmitting moments for all nodes.CT-TDMA exploits the diversity of propagation delay of different links in UWSN to decrease the idle time between packets at the same receiving node,which helps in improving the throughput.And a heuristic schedule algorithm is applied to shorten the process of allocating continuous time for each node.Simulation results show that,compared with traditional TDMA protocols such as ST-MAC,network throughput of CT-TDMA has increased 20% and end to end delay has decreased 18%;compared to the theoretically optimal scheme with global knowledge,CT-TDMA has achieved 80% network throughput and the end to end delay is only 12% longer.…”
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Multi-Level Spectral Attention Network for Hyperspectral BRDF Reconstruction from Multi-Angle Multi-Spectral Images by Liyao Song, Haiwei Li

“…Then, the radiance consistency of BRDF multi-angle data is effectively optimized, the error caused by illumination variation in BRDF modeling is reduced, and the accuracy of BRDF modeling is improved. …”
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Numerical Investigation on Influential Factors for Quality of Smooth Blasting in Rock Tunnels by Baoping Zou, Zhipeng Xu, Jianxiu Wang, Zhanyou Luo, Lisheng Hu

“…As prerequisite for the evaluation of the blasting quality, effective identification of the influential factors affecting smooth blasting usually plays a significant role in the improvement of smooth blasting design. Compared to the expensive and time-consuming experiments including physical modelling and field tests, numerical modelling, as a cost-efficient approach, offers an attractive alternative to investigate the influential factors in terms of weight, which might be more applicable and reliable for the optimization of smooth blasting parameters. …”
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Design and Implementation of Local Threshold Segmentation Based on FPGA by Shangshang Gao, Yuanyuan Wang, Zhaofeng Chen, Feng Zhou, Rugang Wang, Naihong Guo

“…Finally, the design algorithm is verified by ModelSim simulation software and QT5 software. …”
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Linkage and Connectivity Control in Wireless Sensor Network: A New Mechanism by Pouya Derakhshan-Barjoei, Ahmad Yousofi

“…The outcomes of the proposed algorithm on the selected model show 56% improvement in the remaining battery charge. …”
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Support vector neural network based fuzzy hybrid filter for impulse noise identification and removal from gray-scale image by Sagenela Vijaya Kumar, C. Nagaraju

“…The SVNN classifier is trained based on the Genetic Algorithm (GA) for identifying the optimal weights and the bias. …”
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Enhancing climate action evaluation using artificial neural networks: An analysis of SDG 13 by Cosimo Magazzino, Zakaria Zoundi

“…It examines seven critical 2023 SDG Global Index indexes to model and predict environmental performance. The innovative use of ANNs allows for capturing complex and non-linear interactions among sustainability indicators, surpassing traditional linear models. …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

“…The Back Propagation Nondominated Sorting Genetic Algorithm-II (BP-NGA) model consistently yielded positive results for most WQI. (2) Water quality in Dianchi varied significantly by region and season. (3) It was recommended to build wetlands and ecological parks on the southwest side of Dianchi and improve sewage interception pipelines on the northeast side to lessen the risk of eutrophication by reducing the inflow of nitrogen and phosphorus.…”
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H∞ Consensus Design and Online Scheduling for Multiagent Systems with Switching Topologies via Deep Reinforcement Learning by Haoyu Cheng, Ruijia Song, Linpeng Xu, Di Zhang, Shengli Xu

“…Moreover, the online scheduling is formulated as a Markov decision process, and the deep deterministic policy gradient (DDPG) algorithm in the framework of actor-critic is proposed for the compensation of disturbance to explore optimal control policy. …”
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An Optimised Method for Fetching and Transforming Survey Data based on SQL and R Programming Language by Hasan et al.

“…This method demonstrated improved accuracy of data collected, reduced data processing time and arranged data to the willing model.…”
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Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting by Xinpeng Liu, Kanyu Xu, Risa Shinoda, Hiroaki Santo, Fumio Okura

“…Furthermore, we use a minimum spanning tree (MST) algorithm during the optimization loop to regularize the graph to a tree structure. …”
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Hyperspectral imaging combined with residual-attention-net for spectral-spatial feature fusion in liver disease diagnosis by Yunze Li, Jingjing Wang, Miaoqing Zhao, Jinlin Deng, Chongxuan Tian, Qize Lv, Yifei Liu, Kun Ru, Wei Li

“…We incorporated band selection techniques, including the Norris derivative and the Successive Projections Algorithm (SPA), and optimized the data processing workflow. …”
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Prediction of cutting depth in abrasive water jet machining of Ti-6AL-4V alloy using back propagation neural networks by Yakub Iqbal Mogul, Ibtisam Mogul, Jaimon Dennis Quadros, Ma Mohin, Abdul Aabid, Muneer Baig, Mohammad Abdul Malik

“…The results showed that as the depth of cut was small, i.e., ranging from 3 mm to 5 mm, the algorithm was unable to predict the optimized parameters, however, the prediction improved as the depth of cut increased. …”
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Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…By establishing coherent relationships between node representations and community structures, we optimize both the Convex-NMF-based representation learning model and the evolutionary clustering-based TCD model within a unified framework. …”
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