Real time counting method for coal mine drill pipes based on deep learning by Fukai ZHANG, Yiran SUN, Xufeng WU, Aijun LI, Peiyang LI, Dengke WANG, Guan YUAN, Shan ZHAO, Haiyan ZHANG

“…Experiments on the CMDPC dataset show that the improved Drill-YOLOv8 model performs well in mAP@0.5 The mAP @ [0.5:0.95] index has increased by 3.0% and 2.7% respectively, effectively solving the problem of false detection and missed detection of drilling head and drill pipe targets under strong light, water vapor, and occlusion environments, and the detection speed has reached 86 frames per second; At the same time, the weighted average error rate of the counting inference algorithm Pipe Count is 2%, showing good robustness against multi scene data, and the processing speed reaches 40 frames per second, meeting real-time counting requirements.…”
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Estimation of Ultrahigh Resolution PM_2.5 in Urban Areas by Using 30 m Landsat-8 and Sentinel-2 AOD Retrievals by Hao Lin, Siwei Li, Jiqiang Niu, Jie Yang, Qingxin Wang, Wenqiao Li, Shengpeng Liu

“…This study developed an ultrahigh resolution retrieval algorithm to estimate 30 m resolution PM_2.5 mass concentrations over urban areas from Landsat-8 and Sentinel-2A/B satellite measurements. …”
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Estimation of Land Surface Evapotranspiration and Identification of Key Influencing Factors in the Zoige Forest–Grass Transition Zone by Xinzhu Lu, Huaiyong Shao, Yixi Kan, Shibin Liu, Chang Du, Qiufang Shao, Linsen Duan, Huan Xiao

“…The Zoige forest–grass transition zone is a critical water conservation area in the upper reaches of the Yellow River, with high environmental heterogeneity, significant edge effects, and ecological and climatic gradient effects. …”
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Estimation of gas hydrate and free gas saturation using the rock physics model based on constrained least squares and trust region method in the Shenhu Area, South China Sea by Dajiang Meng, Dajiang Meng, Ruwei Zhang, Ruwei Zhang, Yuan Gu, Yuan Gu, Baojin Zhang, Baojin Zhang, Yunqian Lu, Yunqian Lu, Jiangnan Lin, Jiangnan Lin, Lijie Wang, Lijie Wang

“…Additionally, the application results indicate that the trust region algorithm demonstrates favorable global convergence.…”
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A Single-Field Finite Difference Time-Domain Method Verified Using a Novel Antenna Design with an Artificial Magnetic Conductor Enhanced Structure by Yongjun Qi, Weibo Liang, Yilan Hu, Liang Zhang, Cheng You, Yuxiang Zhang, Tianrun Yan, Hongxing Zheng

“…In this work, we develop a variation of the algorithm to accurately calculate antenna, microwave circuit, and target scattering problems. …”
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Improved YOLOv8-Based Method for the Carapace Keypoint Detection and Size Measurement of Chinese Mitten Crabs by Ke Chen, Zhuquan Chen, Changbo Wang, Zhifan Zhou, Maohua Xiao, Hong Zhu, Dongfang Li, Weimin Liu

“…Specifically, we used the YOLOv8 algorithm combined with the pose keypoint detection algorithm to process Chinese mitten crab images to acquire carapace sizes. …”
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Dynamic Path Planning of Unknown Environment Based on Deep Reinforcement Learning by Xiaoyun Lei, Zhian Zhang, Peifang Dong

“…The results show that, after training in different dynamic environments and testing in a new environment, the agent is able to reach the local target position successfully in unknown dynamic environment.…”
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Page-Size Aware Buddy Allocator With Unaligned Range Supports for TLB Coalescing by Tran Dai Duong, Jae Young Hur

“…It is well known that the traditional page-based address translation scheme has limited translation look-aside buffer (TLB) reach and page-table walk overheads. A TLB coalescing scheme reduces these problems by representing an address range in a TLB entry. …”
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Parametric Studies of Laminated Cooling Configurations: Overall Cooling Effectiveness by Chen Wang, Chunhua Wang, Jingzhou Zhang

“…Compared with the numerical results, the mean prediction error (relative value) of the correlation can reach 8.3%.…”
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Road Roughness Level Identification Based on BiGRU Network by Shuang Chen, Junjun Xue

“…The results show that the accuracy of the road roughness level identification model based on the BiGRU network reaches 95.83%, and the recognition result is reliable. …”
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Research on quality and safety risk identification of import and export toys based on the WOA-BP model by Qiong He, Pengzhao Li

“…The WOA-BP model, optimizing BP with the Whale Optimization Algorithm, achieves 95.71% accuracy—5.71% points higher than unoptimized BP and outperforming PSO-BP and GA-BP. …”
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Rumor Situation Discrimination Based on Empirical Mode Decomposition Correlation Dimension by Yanwen Xin, Fengming Liu

“…Finally, the correlation dimensions of the principal components IMF1–IMF6 as obtained by the Grassberger-Procaccia algorithm are used as feature parameters and are imported into the KNN model for rumor recognition. …”
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Track line status detection system for subway based on lightweight convolutional network by LIN Jun, YUAN Hao, LIU Yue, KANG Gaoqiang, TONG Hao

“…Combined with the hard sample mining based on cloud-edge collaboration and model acceleration technologies, the algorithm can meet the detection performance of high accuracy and real-time. …”
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Intelligent Recognition Technology for the Segmentation of Traffic Indication Images Concerning Different Pavement Materials by Juanhong Xie, Guojian Shi, Weizhi Zhu

“…For example, the proposed method reaches a higher sensitivity performance of 96%.…”
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Modelling of Green function in a rectangular room based upon the geometrical-filtration model by R. Marczuk, L. Majkut

“…To this end it is necessary to work out an impulse response calculating algorithm for a digital room model. The Green's function is the solution of wave equation then give consideration to source and receiver positions. …”
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Construction of advanced persistent threat attack detection model based on provenance graph and attention mechanism by Yuancheng LI, Hao LUO, Xinyu WANG, Jiexuan YUAN

“…In response to the difficulty of existing attack detection methods in dealing with advanced persistent threat (APT) with longer durations, complex and covert attack methods, a model for APT attack detection based on attention mechanisms and provenance graphs was proposed.Firstly, provenance graphs that described system behavior based on system audit logs were constructed.Then, an optimization algorithm was designed to reduce the scale of provenance graphs without sacrificing key semantics.Afterward, a deep neural network (DNN) was utilized to convert the original attack sequence into a semantically enhanced feature vector sequence.Finally, an APT attack detection model named DAGCN was designed.An attention mechanism was applied to the traceback graph sequence.By allocating different weights to different positions in the input sequence and performing weight calculations, sequence feature information of sustained attacks could be extracted over a longer period of time, which effectively identified malicious nodes and reconstructs the attack process.The proposed model outperforms existing models in terms of recognition accuracy and other metrics.Experimental results on public APT attack datasets show that, compared with existing APT attack detection models, the accuracy of the proposed model in APT attack detection reaches 93.18%.…”
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Stability and Complexity of a Novel Three-Dimensional Environmental Quality Dynamic Evolution System by LiuWei Zhao, Charles Oduro Acheampong Otoo

“…But if the peak value of pollution emissions reaches too early, it will pose a certain threat to the environment. …”
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Comparison between MDDV and VADD routing protocols in VANET (Case Study) by Ahmed Ghassan Hameed, Mahmoud Shuker Mahmoud

“… Routing is the process of delivering a packet from a source to a destination in the network using a routing algorithm that tries to create an efficient path. The path should be created with minimum overhead and bandwidth consumption. …”
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Improving Wireless Sensor Network Security Using Quantum Key Distribution by Laith H. Alhasnawy, Ameer K. AL-Mashanji

“…Great emphasis is placed on the concepts of using the BB84 protocol with the AES algorithm in WSN security. The results of analysis indicated a high level of security between the data by depending on the generation of secure keys, and reached an accuracy rate of about (80-95) % based on using NIST statistical. …”
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Anomaly Detection Approach Based on Deep Neural Network and Dropout by Zaid Hussien et al.

“…The proposed DNN classifier implemented with feature selection algorithm, and obtained on accuracy reached to 99.27%.…”
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