检索结果-内蒙古大学图书馆

2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Long, Yusi Lee, Gary C.F. Li, Lanhua Gong, Shimin Sun, Sumei Niyato, Dusit School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen Campus China Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology China A∗star Singapore College of Computing and Data Science Nanyang Technological University Singapore

ISBN: (纸本)9798350368369

This paper investigates an unmanned aerial vehicle (UAV)-assisted semantic communication network. The energy-limited ground users (GUs) provide semantic services to periodically generated raw data and a UAV relays the extracted semantic information to a base station (BS). Semantic extraction enhances data responsiveness and reduces the age-of-information (AoI) by transmitting only the most essential information. However, more complex semantic extraction increases energy consumption, making it easier for the GUs to deplete their energy. Therefore, we introduce a novel energy-efficient AoI (EAoI) metric to capture both information freshness and energy consumption of the GUs. We formulate a time-averaged EAoI minimization problem by jointly optimizing the GUs' scheduling, pre-extraction strategy, semantic control, computing resource allocation, and the UAV's trajectory. We further propose a semantic-aware joint pre-extraction and trajectory planning (Sem-JPT) algorithm to decompose the complex optimization problem into three subproblems, which are solved by a series of approximation methods. Simulation results demonstrate that semantic communication can reduce the overall EAoI by more than 18% compared with conventional bit-based communication. Moreover, the proposed Sem-JPT algorithm can maintain information freshness and prolong the GUs' lifetimes, outperforming existing baselines. © 2025 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Sequential Indifferentiability of 7-Round Misty Structures

Sequential Indifferentiability of 7-Round Misty Structures

引用

Cryptographers’ Track at the RSA Conference, CT-RSA 2025

作者： Ai, Jiayi Guo, Chun School of Cyber Science and Technology Shandong University Qingdao China The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Key Laboratory of Cryptologic Technology and Information Security of Ministry of Education Shandong University Shandong Qingdao266237 China Shandong Research Institute of Industrial Technology Shandong Jinan250102 China

ISBN: (纸本)9783031886607

We investigate the Misty structure with respect to the security notion of sequential indifferentiability of Mandal et al. (TCC 2012). As our main result, we prove sequential indifferentiability for 7-round Misty structures using seven independent random permutations in the rounds. We also prove insecurity for 5 rounds by exhibiting an attack. Our main result implies known-key security of 7 rounds in the sense of correlation intractability, providing the first known-key security results on Misty structures to our knowledge. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Safe and Reliable Diffusion Models via Subspace Projection

arXiv

引用

arXiv 2025年

作者： Chen, Huiqiang Zhu, Tianqing Wang, Linlin Yu, Xin Gao, Longxiang Zhou, Wanlei Faculty of Data Science City University of Macau China School of Computer Science University of Queensland QLD Australia Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China

Large-scale text-to-image (T2I) diffusion models have revolutionized image generation, enabling the synthesis of highly detailed visuals from textual descriptions. However, these models may inadvertently generate inappropriate content, such as copyrighted works or offensive images. While existing methods attempt to eliminate specific unwanted concepts, they often fail to ensure complete removal—allowing the concept to reappear in subtle forms. For instance, a model may successfully avoid generating images in Van Gogh’s style when explicitly prompted with "Van Gogh", yet still reproduce his signature artwork when given the prompt "Starry Night". In this paper, we propose SAFER, a novel and efficient approach for thoroughly removing target concepts from diffusion models. At a high level, SAFER is inspired by the observed low-dimensional structure of the text embedding space. The method first identifies a concept-specific subspace Sc associated with the target concept c. It then projects the prompt embeddings onto the complementary subspace of Sc, effectively erasing the concept from the generated images. Since concepts can be abstract and difficult to fully capture using natural language alone, we employ textual inversion to learn an optimized embedding of the target concept from a reference image. This enables more precise subspace estimation and enhances removal performance. Furthermore, we introduce a subspace expansion strategy to ensure comprehensive and robust concept erasure. Extensive experiments demonstrate that SAFER consistently and effectively erases unwanted concepts from diffusion models while preserving generation quality. © 2025, CC BY.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Dynamic Searchable Scheme with Forward Privacy for Encrypted Document Similarity 22

Dynamic Searchable Scheme with Forward Privacy for Encrypted...

引用

22nd IEEE International Conference on Trust, Security and Privacy in computing and Communications, TrustCom 2023

作者： Al Sibahee, Mustafa A. Luo, Chengwen Zhang, Jin Huang, Yijing Abduljabbar, Zaid Ameen Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Iraq University College Computer Technology Engineering Department Basrah61004 Iraq University of Basrah College of Education for Pure Sciences Department of Computer Science Basrah61004 Iraq Huazhong University of Science and Technology Shenzhen Institute Shenzhen518000 China

ISBN: (纸本)9798350381993

Document retrieval plays an essential role in many real-world applications especially when the data storage is outsourced. Due to the great advantages offered by cloud computing, clients tend to outsource their personal data to remote servers maintained by external service providers. This raises serious privacy concerns about outsourced data because such providers are usually considered untrusted entities. The majority of previous schemes of document similarity search share the same limitation: they focus mainly on static collections. Dynamic searchable schemes (DSE) allow adding or removing documents at the expense of more leakage than static schemes. To thwart certain attacks, DSE schemes should support forward privacy property, which ensures that newly added documents cannot be related to previously issued search queries. We design and implement dynamic secure similarity search schemes with forward privacy for textual documents utilizing simhash method for hamming similarity. Our scheme provides an efficient search time and a sufficient level of privacy. To show the practicality of our proposed scheme, we performed excremental results with large document collections. © 2023 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Inverse Quadratic Transform for Minimizing A Sum of Ratios

Inverse Quadratic Transform for Minimizing A Sum of Ratios

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yannan Chen Licheng Zhao Yaowen Zhang Kaiming Shen School of Science and Engineering The Chinese University of Hong Kong (Shenzhen) China Shenzhen Research Institute of Big Data China

A major challenge with the multi-ratio Fractional Program (FP) is that the existing methods for the maximization problem typically do not work for the minimization case. We propose a novel technique called inverse quadratic transform for the sum-of-ratios minimization problem. Its main idea is to reformulate the min-FP problem in a form amenable to efficient iterative optimization. Furthermore, this transform can be readily extended to a general cost-function-of-multiple-ratios minimization problem. We also give a Majorization-Minimization (MM) interpretation of the inverse quadratic transform, showing that all those desirable properties of MM can be carried over to the new technique. Moreover, we demonstrate the application of inverse quadratic transform in minimizing the Age-of-Information (AoI) of data networks.

关键词： Transforms Signal processing Minimization Information age Cost function Acoustics Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Uncovering meanings of embeddings via partial orthogonality 23

Uncovering meanings of embeddings via partial orthogonality

引用

Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Yibo Jiang Bryon Aragam Victor Veitch Department of Computer Science University of Chicago Booth School of Business University of Chicago Department of Statistics University of Chicago and Data Science Institute University of Chicago

Machine learning tools often rely on embedding text as vectors of real numbers. In this paper, we study how the semantic structure of language is encoded in the algebraic structure of such embeddings. Specifically, we look at a notion of "semantic independence" capturing the idea that, e.g., "eggplant" and "tomato" are independent given "vegetable". Although such examples are intuitive, it is difficult to formalize such a notion of semantic independence. The key observation here is that any sensible formalization should obey a set of so-called independence axioms, and thus any algebraic encoding of this structure should also obey these axioms. This leads us naturally to use partial orthogonality as the relevant algebraic structure. We develop theory and methods that allow us to demonstrate that partial orthogonality does indeed capture semantic independence. Complementary to this, we also introduce the concept of independence preserving embeddings where embeddings preserve the conditional independence structures of a distribution, and we prove the existence of such embeddings and approximations to them.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detection of Plant Disease Using Machine Learning and Deep Learning Algorithms

Detection of Plant Disease Using Machine Learning and Deep L...

引用

International Conference on science Technology Engineering and Management (ICONSTEM)

作者： Kalyani Gollapudi Preethi Varigonda S. Jancy S. PushpaLatha Viji Amutha Mary.A Suji Helen Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Department of Data Analytics Saveetha School of Engineering SIMATS Chennai

Agriculture performs an critical position in India's economic system. Early detection of plant illnesses is critical to save you crop damage and similarly spread of diseases. Most plants, along with apple, tomato, cherry, grape, show symptoms of leaf ailment. These visible patterns may be found to correctly predict the disorder and take early movement to save you it. This can be triumph over with system getting to know and deep getting to know algorithms. We therefore recommend a method that determines tomato plant disease from pix of leaves. This method is performed with aid vector device (SVM), random woodland gadget studying algorithm, and look at algorithms Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and ResNet that is one of the switch learning techniques. Snoring. After the facts set is processed by way of the algorithms, the accuracy of the algorithms is compared and the snapshots are categorized.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multivariate Time Series Imputation Based on Masked Autoencoding with Transformer 24

Multivariate Time Series Imputation Based on Masked Autoenco...

引用

24th IEEE International Conference on High Performance computing and Communications, 8th IEEE International Conference on data science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Wang, Yongsheng Xu, Hao Xu, Zhiwei Gao, Jing Wu, Yuhao Zhang, Zhe Inner Mongolia University of Technology College of Data Science and Application Hohhot China Chinese Academy of Sciences Institute of Computing Technology Beijing China Inner Mongolia Agricultural University College of Computer and Information Engineering Hohhot China

ISBN: (纸本)9798350319934

In this work, we propose a self-supervised learning model based on the transformer framework, using it to impute missing data in multivariate time series. Unlike selfsupervised learning models in NLP and CV fields, it always trains a huge pre-trained model, which can fine-tune the model well in other datasets in the same field. Our Multivariate Time Series Based on the Maksed AutoEncoding model (MTAE) uses the position encoding and mask matrix that are more suitable for missing time series while keeping the general framework of the transformer model unchanged, which can take standard time series information into account. Also, our change can note the change in time delay caused by missing data. Finally, we validate the imputation results of MTAE on two different time series datasets and obtain better evaluations than other machine learning models with a missing dataset rate of 90%. © 2022 IEEE.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Empowering Wireless Networks with Artificial Intelligence Generated Graph

arXiv

引用

arXiv 2024年

作者： Wang, Jiacheng Liu, Yinqiu Du, Hongyang Niyato, Dusit Kang, Jiawen Zhou, Haibo Kim, Dong In The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The School of Electronic Science and Engineering Nanjing University Nanjing China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

In wireless communications, transforming network into graphs and processing them using deep learning models, such as Graph Neural Networks (GNNs), is one of the mainstream network optimization approaches. While effective, the generative AI (GAI) shows stronger capabilities in graph analysis, processing, and generation, than conventional methods such as GNN, offering a broader exploration space for graph-based network optimization. Therefore, this article proposes to use GAI-based graph generation to support wireless networks. Specifically, we first explore applications of graphs in wireless networks. Then, we introduce and analyse common GAI models from the perspective of graph generation. On this basis, we propose a framework that incorporates the conditional diffusion model and an evaluation network, which can be trained with reward functions and conditions customized by network designers and users. Once trained, the proposed framework can create graphs based on new conditions, helping to tackle problems specified by the user in wireless networks. Finally, using the link selection in an integrated sensing and communication (ISAC) as an example, the effectiveness of the proposed framework is validated. © 2024, CC BY.

关键词： Wireless networks

来源：评论

学校读者我要写书评

暂无评论

Automatic Identification Fingerprint Based on Machine Learning Method

引用

Journal of the Operations Research Society of China 2022年第4期10卷 849-860页

作者： Long The Nguyen Huong Thu Nguyen Alexander Diomidovich Afanasiev Tao Van Nguyen Laboratory of Artificial Intelligence and Machine Learning Institute of Information Technology and Data ScienceIrkutsk National Research Technical UniversityIrkutskRussia Baikal School of BRICS Irkutsk National Research Technical UniversityIrkutskRussia University of Information and Communication Technology Thai Nguyen UniversityThai NguyenViet Nam

The fingerprint identification technology has been developed and applied effectively to security systems in financial transactions,personal information security,national security,and other *** this paper,we proposed the development of a fingerprint identification system based on image processing methods that clarify fingerprint contours,using machine learning methods to increase processing speed and increase the accuracy of the fingerprint identification *** identification system consists of the following main steps:improving image quality and image segmentation to identify the fingerprint area,extracting features,and matching the *** accuracy of the system reached 97.75%on the mixed high-and low-quality fingerprint database.

关键词： Fingerprint identification Feature extraction Image segmentation Wavelet transform Neural network algorithm Machine learning

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：