Toward edge-computing-enabled collision-free scheduling management for autonomous vehicles at unsignalized intersections by Ziyi Lu, Tianxiong Wu, Jinshan Su, Yunting Xu, Bo Qian, Tianqi Zhang, Haibo Zhou

“…Second, this problem is solved with low complexity by the Edge Intelligence Optimal Entry Time (EI-OET) algorithm based on edge-cloud computing power support. …”
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Study and application of the energy unit cutting theory and punching-blasting synergy permeability enhancement technology in tectonic anomaly areas of coal mines by Jingyu JIANG, Xiaobin DONG, Mintao WEI, Chenghao WANG, Yuanping CHENG, Xiaoning SHI

“…The unit cutting effectively increases the length of the energy-resistant zone in front of the mining work and reduces the risk of operation in the low-high energy transition zone. ④ A numerical model was constructed based on the fluid-solid coupling algorithm to simulate the synergistic effect of controlled directional energy-focused blasting and punching holes. …”
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Initial State Preparation for Quantum Chemistry on Quantum Computers by Stepan Fomichev, Kasra Hejazi, Modjtaba Shokrian Zini, Matthew Kiser, Joana Fraxanet, Pablo Antonio Moreno Casares, Alain Delgado, Joonsuk Huh, Arne-Christian Voigt, Jonathan E. Mueller, Juan Miguel Arrazola

“…Quantum algorithms for ground-state energy estimation of chemical systems require a high-quality initial state. …”
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Stochastic Fractal Search for Bayesian Network Structure Learning Under Soft/Hard Constraints by Yinglong Dang, Xiaoguang Gao, Zidong Wang

“…The combination of the two serves as guidance and constraints to enhance the performance of the proposed SFS algorithm. Extensive experimental analysis reveals that our proposed method is more robust and accurate than other algorithms.…”
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Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder by Lei Tang, Liling Wu, Mengqin Dai, Nian Liu, Lu liu

“…By comparing the enrichment results across the five datasets, we found that the cell-killing signaling pathway was consistently present in the enriched signaling pathways of all datasets, suggesting that this pathway may play a crucial role in the pathogenesis of MDD. The random forest algorithm (AUC = 0.788) was selected as the optimal algorithm from 113 machine learning algorithms, leading to the development of a robust and predictive MDD algorithm, highlighting the important role of NPL in MDD. …”
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YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…To address existing issues in remote sensing image application algorithms such as difficulties in power target feature extraction, low detection accuracy, and false positives/missed detections, this paper proposes the YOLOv9-GDV power tower detection algorithm specifically for power tower detection in high-resolution satellite remote sensing images. …”
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Road Feel Simulation Strategy for Steer-by-Wire System in Electric Vehicles Based on an Improved Nonlinear Second-Order Sliding Mode Observer by Leiyan Yu, Zihua Hu, Hao Zhang, Xinyue Wu, Haijie Huang, Xiaobin Liu

“…Addressing the shortcoming that steer-by-wire (SBW) system cannot directly transmit road feel, this study investigates a SBW system dynamics model, steering angle tracking control, and road feel simulation algorithm design. …”
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A New Parameter-Free Slope Unit Division Method That Integrates Terrain Factors by Ping Li, Junfu Fan, Yujie Du, Kuan Li, Yuke Zhou

“…Despite the significant progress in slope unit division techniques, most existing methods still have certain limitations, such as a strong dependence on manually set thresholds during the division process, resulting in low levels of automation and efficiency. To address this issue, a new parameter-free slope unit extraction algorithm that integrates terrain factors, called Terrain Factor Parameter-Free Slope Unit Division (TFPF-SU), is introduced. …”
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Harnessing greylag goose optimization for efficient MPPT and seven-level inverter in renewable energy systems by K. Rajaram, R. Kannan

“…An inverter is a device that transforms a direct current into a sinusoidal alternating current. …”
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Satellite- and Cache-Assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks by Dinh-Hieu Tran, Symeon Chatzinotas, Bjorn Ottersten

“…This paper considers Low Earth Orbit (LEO) satellite- and cache-assisted unmanned aerial vehicle (UAV) communications for content delivery in terrestrial networks, which shows great potential for next-generation systems to provide ubiquitous connectivity and high capacity. …”
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YOLO-APDM: Improved YOLOv8 for Road Target Detection in Infrared Images by Song Ling, Xianggong Hong, Yongchao Liu

“…A new algorithm called YOLO-APDM is proposed to address low quality and multi-scale target detection issues in infrared road scenes. …”
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Decomposing Imaginary-Time Feynman Diagrams Using Separable Basis Functions: Anderson Impurity Model Strong-Coupling Expansion by Jason Kaye, Zhen Huang, Hugo U. R. Strand, Denis Golež

“…We present a deterministic algorithm for the efficient evaluation of imaginary-time diagrams based on the recently introduced discrete Lehmann representation (DLR) of imaginary-time Green’s functions. …”
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Design and Motion Modeling of a Small-Scale Lunar Jumping Robot by YAN He, ZHU Xingyue, HOU Zhangli, WANG Weijun, ZHANG Zhinan

“…Aiming at the load index of 5 kPa for the lunar surface detector, a new energy storage leg configuration of a jumping robot was proposed to realize low load jump with variable initial velocity and direction during take-off. …”
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Crowd anomaly estimation and detection: A review by A. Hussein, M.W. Raed, A. Al-Shaikhi, M. Mohandes, B. Liu

“…We present a comprehensive literature review on crowd anomaly detection using disruptive technologies such as radio frequency identification, wireless sensor networks, Wi-Fi, and Bluetooth low energy, employing device-free noninvasive algorithms based on received signal strength indicator variations to detect the speed and direction of a moving crowd to predict the onset of a stampede. …”
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Federated learning based intelligent edge computing technique for video surveillance by Yu ZHAO, Jie YANG, Miao LIU, Jinlong SUN, Guan GUI

“…With the explosion of global data,centralized cloud computing cannot provide low-latency,high-efficiency video surveillance services.A distributed edge computing model was proposed,which directly processed video data at the edge node to reduce the transmission pressure of the network,eased the computational burden of the central cloud server,and reduced the processing delay of the video surveillance system.Combined with the federated learning algorithm,a lightweight neural network was used,which trained in different scenarios and deployed on edge devices with limited computing power.Experimental results show that,compared with the general neural network model,the detection accuracy of the proposed method is improved by 18%,and the model training time is reduced.…”
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Group Authentication Key Agreement Protocol Based on Certificateless Cryptography in UAV Network by Yuecheng WANG, Youwen ZHU, Zhiqiang ZHANG

“…However, this key exchange algorithm does not address the issue of a man-in-the-middle attack. …”
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Tumour Budding with Epithelial Mesenchymal Transition Markers – A Novel Prognostic Tool for Breast Carcinoma by Priyadharshini Kumar, Meghashree Vishwanath, Saranyabai Selvaraj

“…The presence and number of TBs are directly proportional to tumor invasion and metastasis. …”
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Clock Glitch Fault Attacks on Deep Neural Networks and Their Countermeasures by Sangwon Lee, Suhyung Kim, Seongwoo Hong, Jaecheol Ha

“…Since these DNNs can be directly implemented on edge devices, they offer advantages such as real-time processing in low-power and low-bandwidth environments. …”
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Efficient and systematic calculation of arbitrary observables for the matrix product state excitation ansatz by Jesse J. Osborne, Ian P. McCulloch

“…While the properties of the low-lying excitations in such systems are often studied in this MPS framework through dynamics by means of time-evolution simulations, we can also look at their statics by directly calculating eigenstates corresponding to these excitations. …”
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Embedding Tangent Space Extreme Learning Machine for EEG Decoding in Brain Computer Interface Systems by Mingwei Zhang, Yao Hou, Rongnian Tang, Youjun Li

“…To improve these problems and enhance the performance of the BCI system, in this study, we propose a novel semisupervised locality-preserving graph embedding model to learn a low-dimensional embedding. This approach enables a low-dimensional embedding to capture more discriminant information for classification by efficiently incorporating information from testing and training data into a Riemannian graph. …”
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