检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Bian, Weixin Feng, Luo Xu, Deqin Jie, Biao Huang, Yi The School of Computer and Information Anhui Normal University Wuhu241002 China Anhui Province Key Laboratory of Network and Information Security Wuhu241002 China

Identifying prohibited items in security X-ray images is a challenging task. Since prohibited items may be intentionally concealed, and the background of X-ray images is complex and the image representation ability is limited, it is easy to cause missed detection or false alarms. These questions are critical to ensuring safety. To address these challenges, the Multidimensional Adaptive Perception Module (MAPM) is proposed, and coordinated attention (CA) adaptive learning weights are introduced to make the learning focus of the model more accurate. The MAPM module fuses high semantic information into deep networks through residual connections, while integrating detailed features into shallow networks, allowing the model to obtain deeper and more comprehensive information and improve its ability to understand complex backgrounds. At the same time, we adopt a decoupling head mechanism to accelerate the convergence speed of the network. Experiments have proven that our model significantly improves the detection accuracy of X-ray security inspection images. Compared with the YOLOv5s model, the average accuracy is increased by 7.9mAP. Compared with many current advanced algorithms, our model has higher accuracy and stronger robustness. This research aims to provide an effective and reliable solution to the security inspection field to improve safety and operability. © 2023, The Authors. All rights reserved.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Fast Gumbel-Max Sketch and its Applications

Fast Gumbel-Max Sketch and its Applications

引用

作者： Zhang, Yuanming Wang, Pinghui Qi, Yiyan Cheng, Kuankuan Zhao, Junzhou Tian, Guangjian Guan, Xiaohong Xi'An Jiaotong University MOE Key Laboratory for Intelligent Networks and Network Security Xi'an710049 China Huawei Noah's Ark Lab Hong Kong Tsinghua University Center for Intelligent and Networked Systems Tsinghua National Lab for Information Science and Technology Beijing100084 China

The well-known Gumbel-Max Trick for sampling elements from a categorical distribution (or more generally a non-negative vector) and its variants have been widely used in areas such as machine learning and information retrieval. To sample a random element ii in proportion to its positive weight v_ivi, the Gumbel-Max Trick first computes a Gumbel random variable g_igi for each positive weight element ii, and then samples the element ii with the largest value of g_i+ln v_igi+lnvi. Recently, applications including similarity estimation and weighted cardinality estimation require to generate kk independent Gumbel-Max variables from high dimensional vectors. However, it is computationally expensive for a large kk (e.g., hundreds or even thousands) when using the traditional Gumbel-Max Trick. To solve this problem, we propose a novel algorithm, FastGM, which reduces the time complexity from O(kn^+)O(kn+) to O(k ln k + n^+)O(klnk+n+), where n^+n+ is the number of positive elements in the vector of interest. FastGM stops the procedure of Gumbel random variables computing for many elements, especially for those with small weights. We perform experiments on a variety of real-world datasets and the experimental results demonstrate that FastGM is orders of magnitude faster than state-of-the-art methods without sacrificing accuracy or incurring additional expenses. © 1989-2012 IEEE.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

A Lightening Fine-grained Access Control Scheme Supporting Full Policy Hiding in Cloud Storage 29

A Lightening Fine-grained Access Control Scheme Supporting F...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Shi, Jiaoli Hu, Chao Yao, Shimao Mei, Zhuolin Wu, Bin Li, Hui Jiujiang Univ. School of Computer and Big Data Jiujiang China Jiangxi Univ. of Finance and Economics School of Software IoT Engineering Nanchang China Jiujiang Key Lab. of Network and Information Security Jiujiang China Jiujiang University School of Computer and Big Data Jiujiang China Peking University School of Elec. and Comp. Engineering Shenzhen China

ISBN: (纸本)9798350330717

Efficiency, security, and flexibility are difficult to balance in a full policy hiding CP-ABE scheme. This paper creatively converts the privacy matching problem of access policy and a user's private key to the privacy three-party set computation problem. Then the new privacy set computation problem is resolved by a message driven key generation method. Additionally, the ROBDD (Reduced Ordered Binary Decision Diagrams) is utilized to rich access structure expression and convert access policies into feasible path sets. Each feasible path is composed of attributes and these attributes are bound to the ciphertext using CP-ABE. Based on the innovative ideas mentioned above, we present a Lighten Fine-grained Access Control scheme supporting Full Policy Hidden (LFAC-FPH) that integrates data confidentiality protection, access policy rich expression but complete hiding, fine-grained access control, and lightweight terminal computing. Our scheme has three advantages: 1) High Efficiency. The proposed scheme can achieve fast privacy matching of access policies during user decryption. 2) Full Policy Hiding. The access policy bound by an owner on the ciphertext does not leak any information. Moreover, a user cannot know attributes they do not own. 3) High Flexibility. The decryption process does not require online from owners or KGC, and system attributes can be added at any time. © 2023 IEEE.

关键词： CP-ABE full policy hiding lighten computation Private-Preserving

来源：评论

学校读者我要写书评

暂无评论

TransUKAN:Computing-Efficient Hybrid KAN-Transformer for Enhanced Medical Image Segmentation

arXiv

引用

arXiv 2024年

作者： Wu, Yanlin Li, Tao Wang, Zhihong Kang, Hong He, Along Tianjin Key Laboratory of Network and Data Security Technology College of Computer Science Nankai University Tianjin China Haihe Lab of ITAI China

U-Net is currently the most widely used architecture for medical image segmentation. Benefiting from its unique encoder-decoder architecture and skip connections, it can effectively extract features from input images to segment target regions. The commonly used U-Net is typically based on convolutional operations or Transformers, modeling the dependencies between local or global information to accomplish medical image analysis tasks. However, convolutional layers, fully connected layers, and attention mechanisms used in this process introduce a significant number of parameters, often requiring the stacking of network layers to model complex nonlinear relationships, which can impact the training process. To address these issues, we propose TransUKAN. Specifically, we have improved the KAN to reduce memory usage and computational load. On this basis, we explored an effective combination of KAN, Transformer, and U-Net structures. This approach enhances the model’s capability to capture nonlinear relationships by introducing only a small number of additional parameters and compensates for the Transformer structure’s deficiency in local information extraction. We validated TransUKAN on multiple medical image segmentation tasks. Experimental results demonstrate that TransUKAN achieves excellent performance with significantly reduced parameters. The code will be available athttps://***/wuyanlin-wyl/TransUKAN. Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

CroPrompt: Cross-task Interactive Prompting for Zero-shot Spoken Language Understanding

CroPrompt: Cross-task Interactive Prompting for Zero-shot Sp...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Qin, Libo Wei, Fuxuan Chen, Qiguang Zhou, Jingxuan Huang, Shijue Si, Jiasheng Lu, Wenpeng Che, Wanxiang School of Computer Science and Engineering Central South University China Key Laboratory of Data Intelligence and Advanced Computing in Provincial Universities Soochow University China Research Center for Social Computing and Information Retrieval Harbin Institute of Technology China Harbin Institute of Technology Shenzhen China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology Shandong Academy of Sciences China

ISBN: (纸本)9798350368741

Slot filling and intent detection are two highly correlated tasks in spoken language understanding (SLU). Recent SLU research attempts to explore zero-shot prompting techniques in large language models to alleviate the data scarcity problem. Nevertheless, the existing prompting work ignores the cross-task interaction information for SLU, which leads to sub-optimal performance. To solve this problem, we present the pioneering work of Cross-task Interactive Prompting (CroPrompt) for SLU, which enables the model to interactively leverage the information exchange across the correlated tasks in SLU. Additionally, we further introduce a multi-task self-consistency mechanism to mitigate the error propagation caused by the intent information injection. We conduct extensive experiments on the standard SLU benchmark and the results reveal that CroPrompt consistently outperforms the existing prompting approaches. In addition, the multi-task self-consistency mechanism can effectively ease the error propagation issue, thereby enhancing the performance. We hope this work can inspire more research on cross-task prompting for SLU. © 2025 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Adaptive Multi-Modality Prompt Learning 24

Adaptive Multi-Modality Prompt Learning

引用

32nd ACM International Conference on Multimedia, MM 2024

作者： Wu, Zongqian Liu, Yujing Zhan, Mengmeng Hu, Ping Zhu, Xiaofeng School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Guangxi Key Lab of Multisource Information Mining and Security Guangxi Normal University Guilin China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China

ISBN: (纸本)9798400706868

Although current prompt learning methods have successfully been designed to effectively reuse the large pre-trained models without fine-tuning their large number of parameters, they still have limitations to be addressed, i.e., without considering the adverse impact of meaningless patches in every image and without simultaneously considering in-sample generalization and out-of-sample generalization. In this paper, we propose an adaptive multi-modality prompt learning to address the above issues. To do this, we employ previous text prompt learning and propose a new image prompt learning. The image prompt learning achieves in-sample and out-of-sample generalization, by first masking meaningless patches and then padding them with the learnable parameters and the information from texts. Moreover, each of the prompts provides auxiliary information to each other, further strengthening these two kinds of generalization. Experimental results on real datasets demonstrate that our method outperforms SOTA methods, in terms of different downstream tasks. © 2024 ACM.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Improved Design of des Algorithm Based on Symmetric Encryption Algorithm

Improved Design of des Algorithm Based on Symmetric Encrypti...

引用

2021 IEEE International Conference on Power Electronics, computer Applications, ICPECA 2021

作者： Yihan, Wang Yongzhen, Li Yanbian University Network Communication and Information Security Lab Dept. of Computer Science and Technology Yanji China

ISBN: (纸本)9781728190037

To address issues in security the threat posed to the DES algorithm by brute force cracking, as well as the low efficiency of the 3DES algorithm, I propose extending the length of the DES algorithm's key. First, change the block length of the DES algorithm from 64 bits to 128 bits and expand the key length of the DES algorithm to double length;secondly, iterative encryption is performed according to the new plaintext grouping and the expanded key length. The two groups are iteratively encrypted, and after every single iteration the two sets of R part data obtained from this round of encryption are exchanged, and then the next round of iteration;finally, the improved DES algorithm is compared with the DES algorithm and the 3DES algorithm by experiment. The results showing that the operating efficiency of the improved DES algorithm is better than 3DES algorithm. Therefore, the improved algorithm is proposed here greatly improves the security of the algorithm under the premise of ensuring operating efficiency and has good application value. © 2021 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Symbiotic Radio: Exploiting Tradeoffs in Hybrid Active-Passive Communications

arXiv

引用

arXiv 2025年

作者： Xu, Rui Ye, Yinghui Sun, Haijian Shi, Liqin Lu, Guangyue Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts & Telecommunications China School of Electrical and Computer Engineering The University of Georgia AthensGA United States

Symbiotic radio (SR), a novel energy- and spectrum-sharing paradigm of backscatter communications (BC), has been deemed a promising solution for ambient Internet of Things (A-IoT), enabling ultra-low power consumption and massive connectivity. However, A-IoT nodes utilizing BC suffer from low transmission rates, which may limit the applications of SR in A-IoT scenarios with data transmission requirements. To address this issue, in this article, we introduce hybrid active-passive communications (HAPC) into SR by exploiting tradeoffs between transmission rate and power consumption. We first present an overview of novel BC paradigms including ambient BC and SR. Then, a novel HAPC-enabled SR is proposed to enhance the transmission rate of A-IoT nodes. Furthermore, within this paradigm, we investigate the resource allocation scheme and present preliminary research results. Simulation results show that the transmission rate of A-IoT nodes in the proposed HAPC-enabled SR surpasses that in traditional SR. Finally, we discuss open issues related to HAPC-enabled SR. Copyright © 2025, The Authors. All rights reserved.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

来源：评论

学校读者我要写书评

暂无评论

Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification 23

Hyperbolic Geometric Graph Representation Learning for Hiera...

引用

2023 World Wide Web Conference, WWW 2023

作者： Fu, Xingcheng Wei, Yuecen Sun, Qingyun Yuan, Haonan Wu, Jia Peng, Hao Li, Jianxin School of Computer Science and Engineering Bdbc Beihang University Beijing China Guangxi Key Lab of Multi-source Information Mining Security Guangxi Normal University Guilin China School of Computing Macquarie University Sydney Australia School of Computer Science and Engineering Beihang University Zhongguancun Lab Beijing China

ISBN: (纸本)9781450394161

Learning unbiased node representations for imbalanced samples in the graph has become a more remarkable and important topic. For the graph, a significant challenge is that the topological properties of the nodes (e.g., locations, roles) are unbalanced (topology-imbalance), other than the number of training labeled nodes (quantity-imbalance). Existing studies on topology-imbalance focus on the location or the local neighborhood structure of nodes, ignoring the global underlying hierarchical properties of the graph, i.e., hierarchy. In the real-world scenario, the hierarchical structure of graph data reveals important topological properties of graphs and is relevant to a wide range of applications. We find that training labeled nodes with different hierarchical properties have a significant impact on the node classification tasks and confirm it in our experiments. It is well known that hyperbolic geometry has a unique advantage in representing the hierarchical structure of graphs. Therefore, we attempt to explore the hierarchy-imbalance issue for node classification of graph neural networks with a novelty perspective of hyperbolic geometry, including its characteristics and causes. Then, we propose a novel hyperbolic geometric hierarchy-imbalance learning framework, named HyperIMBA, to alleviate the hierarchy-imbalance issue caused by uneven hierarchy-levels and cross-hierarchy connectivity patterns of labeled nodes. Extensive experimental results demonstrate the superior effectiveness of HyperIMBA for hierarchy-imbalance node classification tasks. © 2023 ACM.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：