AReal-time Detection Method of Vehicle Target Based on Improved YOLOv5s Algorithm by CHEN Xiufeng, WANG Chengxin, WU Yuechen, GU Kexin

“…To improve the detection rate of small target vehicles，an optimization of the YOLOv5s algorithm network structure was established，which added a small target detection layer and spliced the shallow feature map with the deep feature map in the detection. …”
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Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm by Weikang Han, Qihang Gu, Huaning Gu, Rui Xia, Yuan Gao, Zhenbao Zhou, Kangya Luo, Xipeng Fang, Yali Zhang

“…The system’s positioning component integrates pose data from the GNSS and the IMU inertial navigation system, and corrects positioning errors caused by the clutter of LiDAR environmental feature points. To solve the problem of local optimization and excessive collision handling in the TEB algorithm during the path planning phase, the weight parameters are optimized based on environmental characteristics, thereby reducing errors in optimal path determination. …”
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A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…With the popularization of smart terminals and the gradual increase of power grid informatization and digitization, the protection of power monitoring systems from various cybersecurity threads is a current scientific problem that needs to be solved urgently. To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
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A Novel Hybrid Methodology Based on Transfer Learning, Machine Learning, and ReliefF for Chickpea Seed Variety Classification by İbrahim Kılıç, Nesibe Yalçın

“…In this study, a novel hybrid methodology is proposed for the chickpea classification problem. This methodology combines three well-suited and robust components: feature extraction using three pre-trained models, feature selection with the ReliefF algorithm, and classification employing classical machine learning methods to enhance classification accuracy and efficiency. …”
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Research on scene matching positioning technology for large-scale indoor scenes by Chenchen Zhou, Yujin Kuang, Tongfei Hu, Xiaoguo Zhang

“…Firstly, a prior database via the Oriented FAST and Rotated BRIEF feature extraction algorithm, employing a bag-of-words model for efficient feature matching, is proposed. …”
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Research on bearing fault diagnosis based on improved northern goshawk algorithm optimizing SVM by WU Xiaojun, LI Quwei

“…The energy of each frequency band in the 3rd layer was used as the feature vector and input into the fault diagnosis model. …”
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MVHGCN: Predicting circRNA-disease associations with multi-view heterogeneous graph convolutional neural networks. by Yan Miao, Xuan Tang, Chunyu Wang, Zhenyuan Sun, Guohua Wang, Shan Huang

“…MVHGCN first constructs a heterogeneous graph and generates feature descriptors by integrating multiple databases. …”
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Author name disambiguation based on heterogeneous graph neural network. by Ge Wang, Zikai Sun, Weiyang Hu, MengHuan Cai

“…The current mainstream methods for author disambiguation are mainly divided into two methods: feature-based clustering and connection-based clustering, but none of the current mainstream methods can efficiently deal with the author name disambiguation problem, For this reason, this paper proposes the author name ablation method based on the relational graph heterogeneous attention neural network, first extract the semantic and relational information of the paper, use the constructed graph convolutional embedding module to train the splicing to get a better feature representation, and input the constructed network to get the vector representation. …”
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Evaluating the Predictive Power of Software Metrics for Fault Localization by Issar Arab, Kenneth Magel, Mohammed Akour

“…This study investigates the predictive power of various software metrics for fault localization by framing the task as a multi-class classification problem and evaluating it using the Defects4J dataset. …”
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Research on the role of multi-sensor system information fusion in improving hardware control accuracy of intelligent system by Li Xin, Li Yuesong

“…In the process of multi-sensor information fusion, there is not only the problem of information redundancy but also obvious time delay. …”
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High efficiency classification of thyroid cytopathological images based on knowledge distillation and vision transformer by Jiazhe Zhang, Haolin Zhang, Peng Jiang, Qin Huang, Guangya Zhu, Jingjing Chen, Yingling Cheng, Shu Ran, Fusong Jiang

“…To address this practical problem, this paper proposes a knowledge distillation method called Multi-Dimensional Knowledge Distillation, which involves feature-based distillation and response-based distillation.We employ a 12-layer Vision Transformer as the teacher model. …”
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Research on networking troubleshooting method based on software defined network by Jia-wei LI, Zhi-ju YANG, Xi-jun LIN, UHai-peng Q

“…Based on the reaserch status of networking troubleshooting in software defined network,a new net-working troubleshooting method was proposed.A TCP packet marked in head field was sent and detailed forward information in every hop would be written in its data filed once the test packet was matched.Taking advantages of the programmable feature of the controller and OpenFlow extensible match,special flow table was designed for matching test-used packet.The analysis module extracted and split the forward information,and thus printed the suspicious network problem which can be used to track and located the problematic network node.The experiment results indicate that the proposed method is fairy efficient.…”
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Nostalgia and Archival Footage in Contemporary Hungarian Documentary (Gábor Zsigmond Papp: "The Life of an Agent") by Terez Vincze

“…At the end of the article, I use Gábor Zsigmond Papp’s documentary fi lm The Life of an Agent as an example of the nostalgic use of archival material in the representation of a still-unresolved Hungarian historical problem: socialist secret agents.…”
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The role of a nurse in a multidisciplined rehabilitation brigade by N. G. Petrova, S. A. Kalinina, T. I. Mynnullin

“…A feature of a multidisciplinary approach to national health care system is the lack of nursing staff in the brigades, which reduces their clinical and costeffectiveness. …”
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Food Fortification as a Preventive Factor of Micronutrient Deficiency by Mayurnikova L., Koksharov A., Krapiva T., Novoselov S.

“…Yet some aspects of the problem can be solved on state level. The present research featured micronutrient deficit and preventive measures in several countries taking into account local food traditions. …”
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Efficient Reordering of Multiple Memory Operations in a Multithreaded Program by Ilya Andreev, Konstantin Vladimirov

“…The complexity of the problem lies in the fact that even for a set of small size, constructing and checking for any feature of its possible linear orders can lead to the need of enumeration of huge number of options. …”
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Granularity Decision of Microservice Splitting in View of Maintainability and Its Innovation Effect in Government Data Sharing by Yan Li, Chun-Zi Wang, Ying-chao Li, Jia Su

“…However, how to determine the granularity of microservice splitting is a multiparameter and multiobjective decision-making problem, which is also a key basic problem to be solved urgently both in academic research and application. …”
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Performance improvement of data offloading using Krill herd optimization algorithm by Maryam Jawad Kadhim, Rasool Sadeghi, Ahmad Shaker Abdalrada, Behdad Arandian, Reihaneh Khorsand

“…Two optimization algorithms are proposed to solve the problem: the Krill Herd Algorithm (KHA) and the Greedy algorithm. …”
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ACGNet: An Alternating Conjugate Gradient Optimization-Based Neural Network for SAR Image Despeckling by Xin Mao, Ying Liu, Chenghao Qiu, Cong Lin

“…Synthetic aperture radar (SAR) images are characterized by unique speckle noise, and maintaining image details while effectively reducing this noise has always been a challenging problem. Current deep-learning-based denoising methods mainly rely on global noise models or local feature learning, but these methods often fail to achieve a balance between noise suppression and detail preservation. …”
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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…DeepMol rapidly and automatically identifies the most effective data representation, pre-processing methods and model configurations for a specific molecular property/activity prediction problem. On 22 benchmark datasets, DeepMol obtained competitive pipelines compared with those requiring time-consuming feature engineering, model design and selection processes. …”
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