检索结果-内蒙古大学图书馆

26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wang, Chundong Li, Yue Tianjin University of Technology Tianjin300384 China National Engineering Laboratory for Virus Prevention and Control Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin China

ISBN: (纸本)9798350331684

Database watermarking plays an irreplaceable role in copyright authentication and data integrity protection, but the robustness of the watermark and the resulting data distortion are a pair of contradictory objects that cannot be ignored. To solve this problem, a reversible database watermarking method, named IGADEW, is proposed to balance the relationship between them. The biggest difference from previous research is that IGADEW synthesizes the optimization objects and obtain various parameters through genetic algorithm (GA). Second, the fitness function considers the weights of robustness and distortion, aiming to find the optimal balance between the two. IGADEW uses the Hash-based Message Authentication Code (HMAC) algorithm to encrypt the experimental parameters and uses the primary key hash algorithm for data grouping, both to ensure robustness. And the data distortion is limited with the help of threshold constraints. Finally, experiments using the UCI dataset demonstrate the effectiveness of IGADEW. Experimental results show that, compared with existing methods, IGADEW is more robust against common attacks, with lower data distortion. © 2023 IEEE.

关键词： Copyrights

来源：评论

学校读者我要写书评

暂无评论

PAIR: Protein-aptamer interaction prediction based on language models and contrastive learning framework

PAIR: Protein-aptamer interaction prediction based on langua...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Jun Yan, Zhiqiang Zeng, Hao Zhu, Zexuan Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Shenzhen University College of Computer Science and Software Engineering Shenzhen China

ISBN: (纸本)9798350386226

Aptamers are single-stranded DNA or RNA oligonucleotides that selectively bind to specific targets, making them valuable for drug design and diagnostic applications. Identifying the interactions between aptamers and target proteins is crucial for these applications. The systematic evolution of ligands by exponential enrichment process, traditionally used for this purpose, is challenging and time-consuming. The resulting aptamers often suffer from limitations in stability and diversity. Computational approaches have shown promise in aiding the discovery of high-performance aptamers, but existing methods are usually constrained by insufficient training data and limited generalizability. Recently, advancements in pre-training large language models have offered a new avenue to mitigate the dependency on large datasets. In this study, we propose a novel method to predict aptamer-protein interactions using large language models within a contrastive learning framework. Experimental results demonstrate that our method exhibits superior generalization and outperforms existing approaches. This method holds promise as a powerful tool for predicting aptamer-protein interactions. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Anti-3CLpro Molecular Design Based on the Model Constrained by Specific DTIs

Anti-3CLpro Molecular Design Based on the Model Constrained ...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Lin, Xiaoli Liu, Xuan Zhang, Xiaolong School of Computer Science and Technology Wuhan University of Science and Technology Hubei Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (纸本)9798350337488

computer-aided drug design and artificial intelligence-driven drug design have accelerated drug discovery. However, how to design effective drugs that have strong interaction ability with target proteins to further improve the efficacy of drugs in treating diseases remains a key issue. This paper proposes a new target-specific drug generative model 3CLpro2mol to generate new drug molecules, which uses features of drug-target interactions (DTIs) to constrain the correlation between the drug and the target protein. To obtain as many drug-target interaction features as possible from a small amount of data, a small molecule extraction strategy is proposed to ensure the diversity of small molecules in the training samples. To improve the efficiency and accuracy of the generative model, a TOP K sampling strategy is used to generate tokens, which can improve the rationality and diversity of the generated molecules. The experimental results show that the proposed model has the potential to generate small molecules that interact better with the target protein. © 2023 IEEE.

关键词： COVID-19 DTIs generative model molecular design molecular docking

来源：评论

学校读者我要写书评

暂无评论

A Coarse to Fine Detection Method for Prohibited Object in X-ray Images Based on Progressive Transformer Decoder 24

A Coarse to Fine Detection Method for Prohibited Object in X...

引用

32nd ACM International Conference on Multimedia, MM 2024

作者： Ma, Chunjie Du, Lina Gao, Zan Zhuo, Li Wang, Meng Shandong Jinan China School of Computer Science and Technology Shandong Jianzhu University Shandong Jinan China Faculty of Information Technology Beijing University Of Technology Beijing China School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798400706868

Currently, Transformer-based prohibited object detection methods in X-ray images appear constantly, but there are still some shortcomings such as poor performance and high computational complexity for prohibited object detection with heavily occlusion. Therefore, a coarse to fine detection method for prohibited object in X-ray images based on progressive Transformer decoder is proposed in this paper. Firstly, a coarse to fine framework is proposed, which includes two stages: coarse detection and fine detection. Through adaptive inference in stages, the computational efficiency of the model is effectively improved. Then, a position and class object queries method is proposed, which improves the convergence speed and detection accuracy of the model by fusing the position and class information of prohibited object with object queries. Finally, a progressive Transformer decoder is proposed, which distinguishes high and low score queries by decreasing confidence thresholds, so that high-score queries are not affected by low-score queries in the decoding stage, and the model can focus more on decoding low-score queries, which usually correspond to prohibited object with severe occlusion. The experimental results on three public benchmark datasets (SIXray, OPIXray, HiXray) demonstrate that compared with the baseline DETR, the proposed method achieves the state-of-the-art detection accuracy with a 21.6% reduction in model computational complexity. Especially for prohibited objects with heavily occlusion, accurate detection can be carried out. © 2024 ACM.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

Tailoring Highly Confined Electric-field Based Optical Skyrmions

Tailoring Highly Confined Electric-field Based Optical Skyrm...

引用

2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Chen, J. Shen, X. Zeng, Y. Zhan, Q. University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China University of Shanghai for Science and Technology Shanghai Key Laboratory of Modern Optical System Shanghai200093 China

ISBN: (纸本)9798350375909

Optical skyrmions are quasi-particles with nontrivial topological textures, which hold potential applications in optical information processing, transmission, and storage. There are various three-dimensional physical vectors to construct the optical skyrmions, such as spin skyrmions, Stokes skyrmions, Poynting vector skyrmions, and so on. Here, we present a method to construct tightly focused electric-field skyrmions based on the array antenna radiation theory. A multiple concentric-ring array of dipoles (MCAD) is placed at the focal region of the high numerical aperture (NA) lens to mimic the topological structure of the desired electric field skyrmion, and the radiation pattern of the MCAD is derived to form the incident fields at the pupil planes of the high NA lenses in a 4π focusing setup. The characteristics of the generated focal field are quantitatively evaluated by using the Debye diffraction integral theory. The results demonstrate that two types of electric field vector topologies, i.e., skyrmion and meron, can be created with adjustable polarity, vorticity, and helicity. Additionally, the normal direction of the plane containing the skyrmion or meron can also be customized, increasing the degrees of freedom in tailoring optical skyrmions. © 2024 IEEE.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Competitive and Cooperative-Based Strength Pareto Evolutionary Algorithm for Green Distributed Heterogeneous Flow Shop Scheduling

引用

Intelligent Automation & Soft Computing 2023年第8期37卷 2077-2101页

作者： Kuihua Huang Rui Li Wenyin Gong Weiwei Bian Rui Wang College of System Engineering National University of Defense TechnologyChangsha410073China School of Computer Science China University of GeosciencesWuhan430074China Equipment General Technology Laboratory Beijing Mechanical Equipment Research InstituteBeijing100854China

This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm(CCSPEA)which contains the following features:1)An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence.2)A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution.3)A competitive selection is designed which divides the population into a winner and a loser swarms based on the comprehensive metric.4)A cooperative evolutionary schema is proposed for winner and loser swarms to accelerate the convergence of global search.5)Five local search strategies based on problem knowledge are designed to improve convergence.6)Aproblem-based energy-saving strategy is presented to reduce ***,to evaluate the performance of CCSPEA,it is compared to four state-of-art and run on 22 instances based on the Taillard *** numerical experiment results demonstrate that 1)the proposed comprehensive metric can efficiently represent the heuristic information of each solution to help the later step divide the population.2)The global search based on the competitive and cooperative schema can accelerate loser solutions convergence and further improve the winner’s exploration.3)The problembased initialization,local search,and energy-saving strategies can efficiently reduce the makespan and TEC.4)The proposed CCSPEA is superior to the state-of-art for solving DHPFSP.

关键词： Distributed heterogeneous flow shop scheduling green scheduling SPEA2 competitive and cooperative

来源：评论

学校读者我要写书评

暂无评论

An Image Semantic Communication system Based on GAN and Relative Position-Encoding

引用

IEEE Communications Letters 2025年第6期29卷 1280-1284页

作者： Zhang, Ziqi Tan, Weijie Li, Chunguo Guizhou University College of Big Data and Information Engineering Guiyang550025 China Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610025 China Ministry of Industry and Information Technology Laboratory of Cryptography Application Technology Innovation and Testing Verification Beijing100015 China Southeast University School of Information Science and Engineering Nanjing210096 China

In image semantic communication, the complex wireless channel environment leads to the loss of image details and performance degradation during transmission. To address this issue, we propose an image semantic communication system based on Generative Adversarial Networks (GAN) and Relative Position-Encoding (RPE), named GAN-RpeSC. Specifically, in the system design, we introduce the GAN network at the output of the semantic communication framework to enhance the image restoration. We integrate the RPE module into the Visual Transformer (ViT) module, adding the RPE module to its Multihead Self Attention (MHSA), so that the model can better capture the spatial location information of the image. Experimental results show that the proposed GAN-RpeSC has significant advantages in improving image transmission quality, with a 0.3 dB improvement in peak signal-to-noise ratio (PSNR) compared to the ViT module alone. © 1997-2012 IEEE.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

Fine-Grained Software Vulnerability Detection via Neural Architecture Search 28th

Fine-Grained Software Vulnerability Detection via Neural Ar...

引用

28th International Conference on Database systems for Advanced Applications, DASFAA 2023

作者： Du, Qianjin Kuang, Xiaohui Li, Xiang Zhao, Gang The Department of Computer Science and Technology Tsinghua University Beijing100084 China National Key Laboratory of Science and Technology on Information System Security Beijing100084 China

ISBN: (纸本)9783031306778

Vulnerability detection methods based on the deep learning have achieved remarkable performance improvements compared to traditional methods. Current deep learning-based detectors mostly use a single RNN or its variants (i.e., LSTM or GRU) to detect vulnerabilities. However, vulnerability detection is a multi-domain problem. Different types of vulnerabilities have different characteristics. Using a single neural network cannot perform well in all types of vulnerability detection tasks. Manually designing a matching neural network for each type of vulnerability detection task not only requires a lot of trials and computational resources but also highly relies on the knowledge and design experience of experts. To address this issue, in this paper, we propose a novel fine-grained vulnerability detection framework named A-DARTS, which is capable of searching for well-performed neural network architectures for different vulnerability detection tasks by introducing neural network architecture search (NAS) techniques. Specifically, we design a more efficient search space to ensure superior neural network architectures can be found by the search algorithm. Besides, we propose an adaptive differentiable search algorithm to search for superior neural network architectures. Experimental results show that searched models consistently outperform all baseline models and achieve significant performance improvements. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Generating Molecules Conditional on 3D Protein Pockets with HGAF

Generating Molecules Conditional on 3D Protein Pockets with ...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhu, Qinglian Lin, Xiaoli Zhang, Xiaolong Wuhan University of Science and Technology Hubei Key Laboratory of Intelligent Information Processing and Real-Time Industrial System School of Computer Science and Technology Wuhan China

ISBN: (纸本)9798350337488

Most current representations of protein pockets are the atom-pair graph, which ignore the global structural information of amino acids. Therefore, we propose a new molecular generation model, which uses the hypergraph to represent protein pocket structure, and combines the structural features obtained by atom-pair graph representation. These two levels of graphs are more capable of representing the complex structural information of protein pockets. Then, the graphs of the two levels of the protein pockets are input into the improved network model, which is named Hypergraph Graph Attention Fusion (HGAF), to obtain the embedding representation of the protein pockets, which is used as a condition to constrain the molecule generation. The molecules sampled by HGAF are subjected to quality assessment and docking targeting validation. Experimental results show that the molecules generated by proposed method can achieve better results in both of these assessment approaches. © 2023 IEEE.

关键词： 3D Protein Pockets Drug Design Graph Attention Networks

来源：评论

学校读者我要写书评

暂无评论

Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

引用

2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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：