Genome-wide analyses reveal intricate genetic mechanisms underlying egg production efficiency in chickens by Lizhi Tan, Xinyu Cai, Yuan Kong, Zexuan Liu, Zilong Wen, Lina Bu, Yuzhan Wang, Xiaojun Liu, Zhiwu Zhang, Jianlin Han, Dandan Wang, Yiqiang Zhao

“…Furthermore, our results identified the CNNM2 gene, known for its role in magnesium homeostasis, plays a dual role in egg production variance, promoting variability during the up-stage while reducing it during the sustained-stage to optimize egg production efficiency. Conclusions Collectively, our multiple genome analyses reveal a complex genetic mechanism underlying more efficient and stable egg production, and establish chicken genetics as a model for studying reproductive efficiency across species.…”
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Ship detection optimization method in SAR imagery based on multi-feature weighting by Quanhua ZHAO, Xiao WANG, Yu LI, Guanghui WANG

“…Aiming at the problem that the accuracy of traditional ship detection algorithms is not satisfying in complex scene with many false alarm targets,a ship detection optimization method in SAR imagery based on multi-feature weighting was proposed.Firstly,the marker-based watershed algorithm was employed to remove land from SAR amplitude image.Then,the CFAR algorithm based on log-normal distribution was used to obtain candidate targets from no land image.Furthermore,the length to width ratio,the ship area and the contrast ratio of the candidate targets were extracted.Finally,a variance coefficient method was proposed to distribute the weight of the three features,and the confidence levels were calculated by combining the normalized feature vectors of the candidate targets with the feature weight.By determining the best confidence level,false alarm targets among the candidate targets were removed to optimize ship detection results.In order to verify the proposed method,experiments were carried on with the GF-3 SAR images of different complex scenes.The experimental results show that the proposed method is feasible and effective.…”
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Study of conveyor belt deviation detection based on improved YOLOv8 algorithm by Yunfeng Ni, Haixin Cheng, Ying Hou, Ping Guo

“…Abstract Conveyor belt deviation is a commmon and severe type of fault in belt conveyor systems, often resulting in significant economic losses and potential environment pollution. Traditional detection methods have obvious limitations in fault localization precision and analysis accuracy, unable to meet the demands of efficient and real-time fault detection in complex industrial scenarios. …”
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CIDNet: A Maritime Ship Detection Model Based on ISAR Remote Sensing by Fei Liu, Boyang Liu, Hang Zhou, Song Han, Kunlin Zou, Wenjie Lv, Chang Liu

“…The model is based on the Boundary Box Efficient Transformer (BETR) architecture, which combines super-resolution preprocessing, a deep feature extraction network, a feature fusion technique, and a coordinate maintenance mechanism to improve the detection accuracy and real-time performance of ship targets in complex settings. …”
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Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

“…In order to enhance the accuracy of rice leaf disease detection in complex farmland environments, and facilitate the deployment of the deep learning model onto mobile terminals for rapid real-time inference, this paper introduces a disease detection network titled YOLOv11 Multi-scale Dynamic Feature Fusion for Rice Disease Detection (YOLOv11-MSDFF-RiceD). …”
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IMPLEMENTATION OF K-MEDOIDS AND K-PROTOTYPES CLUSTERING FOR EARLY DETECTION OF HYPERTENSION DISEASE by Hardianti Hafid, Selvi Annisa

“…The clustering results show K-Medoids' superiority in grouping data with higher Silhouette Coefficient values ​​compared to K-Prototypes. Overall, the K-Medoids and K-Prototypes algorithms can detect early hypertension risk by dividing patients into different risk groups. …”
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Mode Selection Model for Rail Crack Detection Based on Ultrasonic Guided Waves by Bo Xing, Zujun Yu, Xining Xu, Liqiang Zhu, Hongmei Shi

“…By setting a reasonable vibration coefficient and orthogonal coefficient, the mode with the highest sensitivity to cracks is selected for crack detection. …”
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Quantifying the impact of external and internal factors and their interactions on thermal load behaviour of a building by Christoph Matschi, Isabell Nemeth

“…Due to the high effort required for transient calculations, a less complex method is needed at the neighborhood level. …”
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An image processing technique for optimizing industrial defect detection using dehazing algorithms. by Xuanyi Zhao, Xiaohan Dou, Gengpei Zhang

“…In recent years, the demand for efficient and accurate defect detection algorithms in industrial production has been increasing. …”
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Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks by Rafiq Fajar Ramadhan, Wahid Miftahul Ashari

“…Despite the small difference in accuracy, Decision Tree demonstrated faster prediction times, making it more efficient for time-sensitive applications. This research concludes that while Random Forest provides higher accuracy for complex datasets, Decision Tree offers a more time-efficient solution with comparable accuracy.…”
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Off-target sequence variations driven by the intrinsic properties of the Cas-sgRNA-DNA complex in genome editing. by Celine Kurniawan, Takeshi Itoh

“…Computational approaches are anticipated to streamline the detection of off-target mutations; however, the performance of current prediction tools is limited, likely owing to insufficient knowledge of off-target mutation characteristics. …”
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Complex PM2.5 Pollution and Hospital Admission for Respiratory Diseases over Big Data in Cloud Environment by Yi Zhou, Lianshui Li

“…Cloud computing may be an efficient and low-cost way to solve this problem. This paper investigates a problem of a complex system: the impact of PM2.5 on hospitalization for respiratory diseases. …”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…Existing models have high false and missed detection rates in complex weather and multi-scale equipment scenarios. …”
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Graph-contrast ransomware detection (GCRD) with advanced feature selection and deep learning by Suneeta Satpathy, Pratik Kumar Swain

“…The present study proposes an efficient and scalable early-stage ransomware detection solution with further potential for improvement through dynamic runtime behaviour analysis of future cyber threats.…”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. Second, an efficient attention module search strategy is proposed to replace traditional fully connected layer structures, which not only increases detection accuracy but also reduces computational overhead. …”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…For practical implementation and validation, a PMSM simulation model is constructed in MATLAB/Simulink, serving as an interactive training platform for the DRL agent and facilitating efficient, robust training. The simulation results validate the effectiveness and superiority of the proposed optimization strategy, demonstrating its applicability and potential for precise and robust control in complex nonlinear defect detection systems.…”
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Audio copy-move forgery detection with decreasing convolutional kernel neural network and spectrogram fusion by Canghong Shi, Xin Qiu, Min Wu, Xianhua Niu, Xiaojie Li, Sani M. Abdullahi

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Subsea Nodule Recognition and Deployment Detection Method Based on Improved YOLOv8s by Jixin Li, Junchao Li, Bin Su, Yuxin Cui

“…An improved small-target detection model based on YOLOv8s is proposed to address the challenges associated with deep-sea polymetallic nodule detection, such as complex target shapes, small sizes, and strong environmental interference. …”
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A Rapid Concrete Crack Detection Method Based on Improved YOLOv8 by Yongzhen Wang, Jiacong He

“…An improved YOLOv8 (You Only Look Once version 8) model is proposed to tackle the challenges of low detection accuracy and slow speed resulting from the complex background and shape diversity of concrete cracks. …”
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YOLOv-MA: A High-Precision Foreign Object Detection Algorithm for Rice by Jiahui Wang, Mengdie Jiang, Tauseef Abbas, Hao Chen, Yuying Jiang

“…Additionally, the adaptive spatial feature fusion (ASFF) module is employed to improve multi-scale feature fusion in rice foreign object detection, significantly boosting YOLOv8’s object detection capability in complex scenarios. …”
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