LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…A Focal-EIoU loss function is also integrated to optimize the model’s training process. Experimental results show that compared to YOLOv8, the LCDDN-YOLO model reduces the number of parameters by 12.9% and the floating-point operations (FLOPs) by 9.9%, while precision, mAP@50, and recall improve by 4.6%, 6.5%, and 7.8%, respectively, reaching 89.5%, 85.4%, and 80.2%. …”
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Protein structural domain-disease association prediction based on heterogeneous networks by Jingpu Zhang, Lianping Deng, Lei Deng

“…Moreover, representing domains and diseases through integrating more multi-omic data will further optimize predictive performance.…”
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Intelligent building design based on green and low-carbon concept by Qian Lv

“…Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. …”
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ApproximateSecret Sharing in Field of Real Numbers by Jiaqi Wan, Ziyue Wang, Yongqiang Yu, Xuehu Yan

“…To address these issues, this paper proposes an innovative algorithm to optimize SSS via type-specific coding for real numbers. …”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning by Yaoyao Ding, Fengming Wang, Yuanwei Mu, Hongfei Sun

“…To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. …”
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Integrating distributed photovoltaic and energy storage in 5G networks for sustainable IoT applications by Yi Zhong, Yiting Wu, Yi Zheng, Xiaohu Ge

“…This paper explores the integration of distributed photovoltaic (PV) systems and energy storage solutions to optimize energy management in 5G base stations. By utilizing IoT characteristics, we propose a dual-layer modeling algorithm that maximizes carbon efficiency and return on investment while ensuring service quality. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Secondly, as the model requires target recognition and segmentation of different types of tasks, an efficient layer aggregation network (RepGFPN) with skip layer connection structure is adopted to optimize the feature fusion part, greatly improving the detection accuracy of the model for different detection tasks while controlling the number of model parameters and inference speed; Finally, to address the detection tasks of three different label shapes, the Inner CIOU loss function is introduced to compensate for the weak generalization ability of the CIoU loss function in different detection tasks. …”
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FEXGBIDS: Federated XGBoost-Based Intrusion Detection System for In-Vehicle Network by Jie Li, Yuanyuan Song, Ming-Gang Zheng, Shuo Zhang, Han Liang

“…Additionally, we employ BLS aggregate signatures to achieve efficient and verifiable parameter aggregation, and leverage the DDSketch distributed quantile estimation algorithm to optimize the feature bucketing process. …”
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Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface by Zhouzheng Shi, Leiyang Guo, Jingde Li, Ni Cao, Xiansheng Qin, Zhanxi Wang

“…Finally, with total cleaning time as the optimization objective, a genetic algorithm is employed to optimize the path combination across sub-facets. …”
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Multivisit Drone-Vehicle Routing Problem with Simultaneous Pickup and Delivery considering No-Fly Zones by Yan-Qiu Liu, Jing Han, Ying Zhang, Yan Li, Tao Jiang

“…These prescribed no-fly zones cause significant challenges when attempting to optimize the routing of truck-drone operations. Thus, this study constructs a mixed integer linear programming (MILP) model for the path optimization problem of joint service of trucks and drones considering no-fly zones and simultaneous pickup and delivery. …”
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On-Board Content Caching With Dynamic Cache Reconfiguration in Multi-Layer Satellite Edge Networks by Haftay Gebreslasie Abreha, Ilora Maity, Houcine Chougrani, Christos Politis, Symeon Chatzinotas

“…To address these challenges, in this paper, we propose an on-board dynamic cache reconfiguration strategy that maximizes the cache hit rate while minimizing reconfiguration overhead. We design a proximity-based content popularity model and an Age of Information (AoI)-aware caching strategy to optimize on-board satellite resources, enhancing the cache hit rate and ensuring content freshness. …”
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Automated Detection of Tailing Impoundments in Multi-Sensor High-Resolution Satellite Images Through Advanced Deep Learning Architectures by Lin Qin, Wenyue Song

“…Accurate spatial mapping of Tailing Impoundments (TIs) is vital for environmental sustainability in mining ecosystems. While remote sensing enables large-scale monitoring, conventional methods relying on single-sensor data and traditional machine learning-based algorithm suffer from reduced accuracy in cluttered environments. …”
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Real-time motion detection using dynamic mode decomposition by Marco Mignacca, Simone Brugiapaglia, Jason J. Bramburger

“…Effectiveness is analyzed using receiver operating characteristic curves, while we use cross-validation to optimize the threshold parameter that identifies movement.…”
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The Effectiveness of Peyton’s 4-Step Approach to Teach Resuscitation Skills: A Randomized Controlled Clarification Study by Denisa Cenaj, Leonie Schulte-Uentrop, Leonie Fee Laura Kröger, Josephine Küllmei, Jan-Marcus Haus, Parisa Moll-Khosrawi

“…While the method shows limited benefit for teaching discrete tactile skills in earlier stages, its strategic inclusion in later phases can optimize curriculum design by aligning advanced teaching methods with learners’ developmental needs. …”
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A cartographic generalization method for 3D visualization of trajectories in space–time cubes: case study of epidemic spread by Fei Yang, Jie Shen, Fengzhen Zhu, Junrui Zhang

“…The proposed method incorporates a 3D generalization algorithm that mitigates visual stickiness, while leveraging a 3D line field visualization technique to optimize opacity, thereby minimizing visual occlusion and spatial clutter. …”
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Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage by Yongqiang Zhang, Haijie Pang, Jinlong Ma, Guilei Ma, Xiaoming Zhang, Menghua Man

“…Background: With the development of artificial intelligence, memristors have become an ideal choice to optimize new neural network architectures and improve computing efficiency and energy efficiency due to their combination of storage and computing power. …”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…Methods:To reduce inter-user interference,an improved K-means algorithm is proposed to group users and select a cluster head for each group of users, which maximizes the correlation of user channels in the same cluster and reduces the correlation between users in different clusters as much as possible;Then,a low-complexity analog precoding is designed to maximize the array gain of the antenna based on the relevant user channel matrix composed of the cluster head set, followed by a digital precoding designed to eliminate inter-user interference with the maximum equivalent channel gain between beams using a forced-zero technique; Finally, an EE maximization problem is formed to optimize the transmit power under users'quality of services and total transmit power constraints,and a two-layer iterative algorithm is proposed for the resulting non-convex optimization problem. …”
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Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

“…Our goal is to maximize secure EE, where the secure EE is defined as the secrecy rate over the power consumption of the user. We aim to jointly optimize phase-shift of IRS, transmit power of jammer and user, to maximize the objective function while ensuring that the secrecy rate is greater than the predefined threshold while allowing the eavesdroppers to harvest energy using SWIPT. …”
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Jumping knowledge graph attention network for resource allocation in wireless cellular system by Qiushi Sun, Zhou Fang, Yin Li, Ovanes Petrosian

“…The realization of these features hinges on the development of rational resource allocation strategies to optimize the utilization of radio resources. This study addresses the beamforming design problem for downlink transmission in multi-cell cellular networks, with a focus on maximizing user data rates while adhering to stringent power constraints. …”
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Deep Reinforcement Learning-Based Multi-Agent System with Advanced Actor–Critic Framework for Complex Environment by Zihao Cui, Kailian Deng, Hongtao Zhang, Zhongyi Zha, Sayed Jobaer

“…We introduce an advanced multi-agent deep reinforcement learning (DRL) framework, specifically a Multi-Agent Proximal Policy Optimization (MA-PPO), designed to optimize target acquisition while operating within defined ammunition and time constraints. …”
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