Enhanced SVM-based model for predicting cyberspace vulnerabilities: Analyzing the role of user group dynamics and capital influx. by Yicheng Long

“…To address the limited adaptability of traditional support vector machine (SVM) models in identifying nonlinear attacks, this study introduces a distribution-driven, dynamically adaptive kernel optimization approach. This method adjusts kernel parameters or switches kernel functions in real time according to the statistical characteristics of input data, thereby improving the model's generalization capability and responsiveness in complex attack scenarios. …”
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Narrowing the semantic gap in virtual machine introspection by Chao-yuan CUI, Yun WU, Ping LI, Xiao-ming ZHANG

“…Virtual machine introspection(VMI)has been widely used in areas such as intrusion detection and malware analysis.However,due to the existence of semantic gap,the generality and the efficiency of VMI were partly influenced while getting internal information of a virtual machine.By analyzing the deficiencies of existing technology of semantic gap restoration,a method called ModSG was proposed to bridge the semantic gap.ModSG was a modularity system,it divided semantic restoration into two parts.One was online phase that interact directly with user to construct semantic views,the other was offline phase that only interact with operating system to parse high-level semantic knowledge.Both were implemented via independent module,and the latter provided the former with necessary kernel information during semantic view construction.Experiments on different virtual machine states and different kernel versions show that the ModSG is accurate and efficient in narrowing semantic gap.The modular design and deployment also make ModSG easily to be extended to other operating systems and virtualization platforms.…”
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Uji Parameter dan Arsitektur Convolutional Neural Network untuk Mendeteksi Citra Wajah Bermasker by Dewi Novita Sari, Muh. Arif Rahman, Randy Cahya Wihandika

“…Based on these results, it is concluded that the kernel size parameter and the number of kernels have a relationship in producing the best CNN architectural performance value for masked face image detection. …”
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Highway subgrade stability prediction model based on depth separation convolutional fusion network by Yubian Wang

“…The method can quickly and effectively identify the adjacent supervoxels in the convolution kernel, effectively reduce the number of parameters of the network, and alleviate the problems of overfitting and long training time to improve computational efficiency. …”
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Coverage problem in camera-based sensor networks using the CUDA platform by Jae-Hyun Seo, Yourim Yoon, Yong-Hyuk Kim

“…The efficiency of a CUDA kernel function using the NVIDIA GeForce GTX 970 graphic card was analyzed.…”
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MRP-YOLO: An Improved YOLOv8 Algorithm for Steel Surface Defects by Shuxian Zhu, Yajie Zhou

“…This issue is particularly evident in the context of surface defect detection in industrial parts, where low contrast, small target features, difficult feature extraction, and low real-time detection efficiency are prominent challenges. …”
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A machine vision approach for classification and dimensional design of furniture panels using GMM-SVM by Yuan Tian, Li Zhao, Haoxin Li

“…The findings of this study reveal that the use of various feature parameters and kernel functions affects the support vector machine’s recognition accuracy. …”
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GCF-DeepLabv3+: An Improved Segmentation Network for Maize Straw Plot Classification by Yuanyuan Liu, Jiaxin Zhang, Yueyong Wang, Yang Luo, Pengxiang Sui, Ying Ren, Xiaodan Liu, Jun Wang

“…These findings indicate that the proposed GCF-DeepLabv3+-based rapid detection method offers robust support for straw return detection.…”
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HP-YOLO: A Lightweight Real-Time Human Pose Estimation Method by Haiyan Tu, Zhengkun Qiu, Kang Yang, Xiaoyue Tan, Xiujuan Zheng

“…We designed an Enhanced Large Separated Kernel Attention (ELSKA) mechanism and integrated it into the backbone network, thereby improving the model’s effective receptive field and feature separation capabilities, which enhances keypoint detection accuracy in challenging environments. …”
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Innovative segmentation technique for aerial power lines via amplitude stretching transform by Pengfei Xu, Nor Anis Asma Sulaiman, Yafei Ding, Jiangwei Zhao

“…For this reason, this paper designs a pure amplitude stretching kernel function to form a Fourier amplitude vector field and uses this amplitude vector field to implement the stretching transformation of the amplitude field of the aerial power line image, so that the angular field after the Fourier inverse transformation can better react to the spatial domain line targets, and finally, after the Relative Total Variation (RTV) processing, the power line can be well detected. …”
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Aspect-Based Sentiment Analysis on User Perceptions of OVO using Latent Dirichlet Allocation and Support Vector Machine by Eka Fahira Aprilia, Amalia Anjani Arifiyanti, Nambi Sembilu

“…These results demonstrate the model’s effectiveness in handling multi-label classification under imbalanced data conditions, particularly for well-distributed aspects such as Transaction Efficiency and User Experience, while highlighting challenges in minority-class detection for aspects such as Account Access and Registration and Balance and Charges.…”
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Failure State Identification and Fault Diagnosis Method of Vibrating Screen Bolt Under Multiple Excitation of Combine Harvester by Jiaojiao Xu, Tiantian Jing, Meng Fang, Pengcheng Li, Zhong Tang

“…The demanding operational conditions of combine harvesters induce substantial vibrations and component degradation, significantly impacting harvesting efficiency, safety, and overall machine reliability. …”
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Hybrid Gradient Descent Grey Wolf Optimizer for Machine Learning Performance Enhancement by Sri Rossa Aisyah Puteri Baharie, Sugiyarto Surono, Aris Thobirin

“…Still, its performance depends significantly on selecting appropriate hyperparameters such as regularization (C), kernel coefficient (γ), and polynomial kernel degree (d). …”
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Research on Long-Distance Snow Depth Measurement Method Based on Improved YOLOv8 by Jia-Wen Wang, Yu Cao, Zong-Kai Guo, Cheng Xu

“…With the development of deep learning, the YOLO model has become widely used for automated snow depth detection due to its efficient and accurate instance segmentation. …”
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Wheat Powdery Mildew Severity Classification Based on an Improved ResNet34 Model by Meilin Li, Yufeng Guo, Wei Guo, Hongbo Qiao, Lei Shi, Yang Liu, Guang Zheng, Hui Zhang, Qiang Wang

“…Further refinements included embedding a Squeeze-and-Excitation (SE) block to strengthen feature representation while maintaining computational efficiency. The model architecture was also optimized by modifying the first convolutional layer (conv1)—replacing the original 7 × 7 kernel with a 3 × 3 kernel, adjusting the stride to 1, and setting padding to 1—to better capture fine-grained leaf textures and edge features. …”
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Genomic approaches for almond traceability from nursery and along the food chain by Alessandra Gentile, Ilaria Inzirillo, Stefania Bennici, Francesco Scollo, Giuseppina Las Casas, Mario Di Guardo, Stefano La Malfa, Gaetano Distefano

“…Almond is widely cultivated in the world thanks to the quality and healthy features of the kernel. Almond kernel is consumed fresh or employed in the food industry. …”
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Red-KPLS Feature Reduction with 1D-ResNet50: Deep Learning Approach for Multiclass Alzheimer’s Staging by Syrine Neffati, Ameni Filali, Kawther Mekki, Kais Bouzrara

“…The early detection of Alzheimer’s disease (AD) is essential for improving patient outcomes, enabling timely intervention, and slowing disease progression. …”
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Application of OCR in Locomotive Maintenance Record Sheet Electrification by YAN Jiayun, ZHANG Huiyuan, LI Chen, PENG Liantie

“…Requirements of accuracy and efficiency are satisfied with batch computation.Compared with origin PaddlePaddle-OCR, the method proposed in this paper performs better in text inclination scene.The influences on text detector and recognizer caused by ratio of convolution kernel in backbones are also researched in this paper.…”
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YOLO-DLHS-P: A Lightweight Behavior Recognition Algorithm for Captive Pigs by Changhua Zhong, Hao Wu, Junzhuo Jiang, Chaowen Zheng, Hong Song

“…Firstly, the C2f-DRB structure is introduced at the Backbone position, and the sizeable convolutional kernel is used to extend the receptive field to enhance the spatial perception ability of the model, and to enhance the network’s ability to capture spatial information while maintaining the number of learnable parameters and computational efficiency; The LSKA attention mechanism is then introduced to be integrated into the SPPF module to construct the SPPF-LSKA structure, which significantly improves the ability of the SPPF module to aggregate features at multiple scales; Then, the downsampling at the Neck position is optimised to the HWD algorithm, which reduces the spatial resolution of the feature map while retaining more useful information and reduces the uncertainty of the information compared with the downsampling method of the baseline model; finally, the Shape-IoU is used to replace the original CIoU, which significantly improves the detection efficiency and accuracy of the model without increasing the extra computational burden. …”
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Blind Infrared Remote-Sensing Image Deblurring Algorithm via Edge Composite-Gradient Feature Prior and Detail Maintenance by Xiaohang Zhao, Mingxuan Li, Ting Nie, Chengshan Han, Liang Huang

“…The problem of blind image deblurring remains a challenging inverse problem, due to the ill-posed nature of estimating unknown blur kernels and latent images within the Maximum A Posteriori (MAP) framework. …”
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