Campus risk detection using the S-YOLOv10-SIC network and a self-calibrated illumination algorithm by Qiang Zhao, Sha Liu, Shihao Zhang, Baijuan Wang

“…Abstract In order to realize intelligent and accurate campus risk detection, this paper proposes an improved YOLOv10 algorithm that integrates self-calibrated illumination algorithm. The algorithm optimizes the loss function by introducing an auxiliary bounding box, and accelerates model convergence. …”
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Dual-Streams Edge Driven Encoder-Decoder Network for Image Super-Resolution by Feng Li, Huihui Bai, Lijun Zhao, Yao Zhao

“…To reconstruct HR images with better visual quality, a total loss function combining edge loss and color loss is designed to make an optimal tradeoff between the image fidelity and texture details. …”
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End-to-End Mandarin Speech Reconstruction Based on Ultrasound Tongue Images Using Deep Learning by Fengji Li, Fei Shen, Ding Ma, Jie Zhou, Shaochuan Zhang, Li Wang, Fan Fan, Tao Liu, Xiaohong Chen, Tomoki Toda, Haijun Niu

“…The loss of speech function following a laryngectomy usually leads to severe physiological and psychological distress for laryngectomees. …”
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Challenges and solutions in diagnosis and treatment of obesity by FANG Ping, HAN Junfeng

“…Emerging strategies, such as developing small molecule oral drugs, combination therapies, and peptide-drug conjugates, may offer novel solutions to improve tolerability, optimize weight loss experience, and achieve long-term weight maintenance.…”
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GuidedBox: a segmentation-guided box teacher-student approach for weakly supervised road segmentation by Teerapong Panboonyuen, Chaiyut Charoenphon, Chalermchon Satirapod

“…Additionally, we introduce noise-aware pixel loss and noise-reduced affinity loss functions to optimize the student model with pseudo masks dynamically. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Several innovations were introduced to the YOLOv8n framework: (1) An ALKBlock-based C2f module incorporating DACov structure to enhance spatial perception; (2) An EffQA-FPN feature pyramid network inspired by QARepVGG to mitigate precision loss during quantization and reparameterization; (3) A DynamicHead attention mechanism with multi dimensional perception capabilities; and (4) EIoU and Adaptive Wing Loss functions to optimize bounding box and key point regression. …”
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AHG-YOLO: multi-category detection for occluded pear fruits in complex orchard scenes by Na Ma, Na Ma, Na Ma, Yile Sun, Yile Sun, Chenfei Li, Chenfei Li, Zonglin Liu, Zonglin Liu, Haiyan Song, Haiyan Song

“…Finally, the boundary box loss function is changed to Generalized Intersection over Union (GIoU), improving the model’s convergence speed and further enhancing detection performance.ResultsExperimental results show that the AHG-YOLO model achieves 93.5% (FCC), 95.3% (NO), and 93.4% (OBL) in AP, with an mAP@0.5 of 94.1% across all categories. …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…The algorithm innovatively constructs a lightweight depthwise separable network (LDSNet) as backbone, balancing computational efficiency and accuracy through channel re-parameterization strategy; incorporates an Efficient Local Attention (ELA) module to build feature enhancement networks, and employs dual-path feature fusion mechanisms to strengthen edge texture responses, significantly improving discrimination of overlapping spikes and complex backgrounds. Further optimizes the loss function system by replacing traditional IoU with Scylla Intersection over Union (SIoU) metric, enhancing bounding box regression through dynamic focus factors, and adding high-resolution small-object detection layers to mitigate dense spikelet feature loss. …”
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BESW-YOLO: A Lightweight SAR Image Detection Model Based on YOLOv8n for Complex Scenarios by Xiao Tang, Kun Cao, Yunzhi Xia, Enkun Cui, Weining Zhao, Qiong Chen

“…Finally, the innerwise intersection over union loss function is introduced, which accelerates the model’s convergence speed and enhances its generalization capability. …”
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Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network by Xiaorong Li, Lijun Zhang, Dongchen Li, Dan Guo

“…Improving the level of human resource management can make fuller use of human resources and realize the strategic goals of the enterprise. A strategy for optimizing the training of hybrid convolutional neural networks is proposed, using an exponential linear unit activation function to solve the problem of neuron dead zones, a hybrid pooling strategy is used to improve the problem of feature information loss in maximum pooling processing, and an improved cross-entropy loss function is used to solve the problem of insufficient learning of difficult classification samples. …”
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An analysis of the I/O semantic gaps of HPC storage stacks by Sebastian Oeste, Patrick Höhn, Michael Kluge, Julian Kunkel

“…Ideally, no semantics of an I/O operation should be lost while passing through the I/O stack, allowing lower layers to optimize performance. Unfortunately, there is a lack of general definition and unified taxonomy of I/O semantics. …”
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Foreign object detection for mining conveyor belts based on YOLOv5n-CND by SUN Aoran, ZHAO Peipei, YANG Di, ZHANG Junyi, YU Hongjian

“…Second, the normalized Gaussian Wasserstein distance (NWD) regression loss function was used to replace CIoU, improving the performance of multi-scale foreign object detection and accurately predicting the detection of adhering small objects. …”
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EF yolov8s: A Human–Computer Collaborative Sugarcane Disease Detection Model in Complex Environment by Jihong Sun, Zhaowen Li, Fusheng Li, Yingming Shen, Ye Qian, Tong Li

“…Building upon the YOLOv8 framework, the EMA attention mechanism and Focal loss function were added to optimize the model, addressing the complex backgrounds and imbalanced positive and negative samples present in the sugarcane data set. …”
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DTC-m6Am: A Framework for Recognizing N6,2′-O-dimethyladenosine Sites in Unbalanced Classification Patterns Based on DenseNet and Attention Mechanisms by Hui Huang, Fenglin Zhou, Jianhua Jia, Huachun Zhang

“…For the data imbalance problem, we use the focal loss function to balance the learning effect of positive and negative samples and improve the performance of the model on imbalanced data. …”
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Research on a Target Detection Algorithm for Common Pests Based on an Improved YOLOv7-Tiny Model by He Gong, Xiaodan Ma, Ying Guo

“…Feature Sharing Enhancement: The introduction of a Cross-layer Feature Sharing Network (CotNet Transformer) strengthens feature fusion and extraction capabilities. 3. Activation Function Optimization: The traditional ReLU activation function is replaced with the Gaussian Error Linear Unit (GELU) to improve nonlinear expression and classification performance. …”
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Exploring Quality of Life in Adults Living With Late-onset Pompe Disease: A Combined Quantitative and Qualitative Analysis of Patient Perceptions from Australia, France, Italy, and... by Holly Lumgair, Lisa Bashorum, Alasdair MacCulloch, Elizabeth Minas, George Timmins, Drago Bratkovic, Richard Perry, Medi Stone, Vasileios Blazos, Elisabetta Conti, Raymond Saich

“…A holistic approach to assessing the individual can help ensure relevant factors are investigated and held in balance, supporting optimized care.…”
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Research on the Combined Load-Bearing Mechanism of Deeply Buried Pressure Pipelines Under High Internal Water Pressure by LIU Yijie, ZHANG Xuhui, HUANG Bensheng, YANG Fengjie, YUAN Mingdao, XU Yunqian

“…Therefore, in engineering design, if the surrounding rock was structurally sound, stable, and the quality of concrete filling can be assured, the thickness of the steel lining may be appropriately reduced to optimize construction costs. 2) When cracks developed in the concrete layer, leading to the loss of its circumferential load-bearing capacity, the corresponding internal water pressure was redistributed between the steel lining and surrounding rock according to their respective stiffness characteristics. …”
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An Intelligent Energy Management System for Educational Buildings by Ahmad Al-Daraiseh, Nazaraf Shah, Eyas El-Qawasmeh

“…Our preliminary results show that up to 17% of energy consumption can be reduced by simply dealing with standby energy loss of labs’ computers. The novelty of this research comes from the use of a functional database approach to deal with high volume of data and query performance and the incorporation of a timetabling system in energy management system.…”
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Role of diet, physical activity and new drugs in the primary management of cancer cachexia in gastrointestinal tumors – a comprehensive review by Ester Oneda, Alessandra Manno, Silvia Noventa, Michela Libertini, Sara Cherri, Alberto Zaniboni

“…Targeted dietary strategies, such as a high-protein diet enriched with omega-3 and branched-chain amino acids (BCAAs), have proven effective in counteracting muscle loss and modulating inflammatory metabolism. Physical activity, particularly resistance training, contributes to preserving lean mass and improving physical function. …”
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Advancements in lamb wave high-frequency devices using diamond-like carbon (DLC) coatings by Jatinder Pal Singh, Ajay Kumar Sao, Babita Sharma, Satyam Garg, Anjali Sharma, Reema Gupta, Lokesh Rana, Mallika Verma, Akhilesh Pandey, Archibald Theodore Nimal, Upendra Mittal, Amit Kumar Vishwakarma, Monika Tomar, Arijit Chowdhuri

“…The outcomes of this research underscore the potential of DLC coatings to optimize the Lamb wave device functionalities, promising enhanced performance and broader applications. …”
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