检索结果-内蒙古大学图书馆

8th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2022

作者： Tang, Zihang Wang, Hao Gao, Weibo Huang, Zhenya Liu, Qi Yu, Jun University of Science and Technology of China School of Data Science China University of Science and Technology of China Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and Technology China IFLYTEK CO. LTD. IFLYTEK Research

ISBN: (纸本)9781665477352

Finding Similar Exercises (FSE) is a tough nut to crack in online education systems, especially among large scale exercise corpus. Given exercises with associated attributes, contents (texts and images) and knowledge concepts, most solutions learn exercise representations in isolation, where only contents or concepts are exploited. Though a few works try to combine concept-exercise associations for capturing long-range similarity among exercises, they just utilize a single relation among concepts but neglect the multiple dependencies. In this paper, we propose a novel Dependency and Association enhanced Finding Similar Exercises framework, namely DAFSE, which can consider both the concept-exercise associations and the multiple dependency relations among concepts, simultaneously. Specifically, we first build a concept-exercise-content multi-layer graph and embed each concept, exercise and content node through an Embedding Layer. Then we introduce Attentive Combination Layer to effectively preserve the long-range similarity as well as rich domain knowledge to exercise representations by propagating on the multi-layer graph. Finally, we use a Similarity Score Layer to assess the similarity of exercise pairs. Extensive experiments on real-world datasets demonstrate the effectiveness of DAFSE. © 2022 IEEE.

关键词： Online systems

来源：评论

学校读者我要写书评

暂无评论

Real-Time Semantic Segmentation Algorithm Based on Tversky Loss Function and Mixed Pooling

Real-Time Semantic Segmentation Algorithm Based on Tversky L...

引用

2023 International Conference on Networking and Network Applications, NaNA 2023

作者： Xu, Peng Zhao, Ziyi Ma, Sugang Xi'an Science and Technology Museum Shaanxi Xi'an710002 China School of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Xi'an710121 China School of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Shaanxi Xi'an710121 China

ISBN: (纸本)9798350327380

In recent years, semantic segmentation methods based on deep learning have made remarkable developments. Despite achieving high segmentation accuracy, the performance of real-time segmentation methods cannot satisfy real-world applications. In order to achieve a balance between segmentation accuracy and speed, a real-time semantic segmentation algorithm based on Tversky loss function and mixed pooling is proposed in this paper. A Short-Term Dense Concatenate network (STDC network) is used to construct the encoder, and a mixed pooling module is used for the final part of the encoder, which uses strip pooling and average pooling to enhance the feature representation while expanding the receptive field. Additionally, a Tversky-based loss function is used for the detail guidance module of the backbone network in the encoder, and a joint loss function is used to supervise the whole network's training. We achieved 76.9% mIoU at 110.7 FPS on the Cityscapes dataset, a 2.4% improvement in accuracy over the benchmark algorithm STDCSeg, and 72.2% mIoU at 177.6 FPS on the Camvid dataset, satisfied the requirements of the real-time segmentation task. © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

DVasMesh: Deep Structured Mesh Reconstruction from Vascular Images for Dynamics Modeling of Vessels 6th

DVasMesh: Deep Structured Mesh Reconstruction from Vascular...

引用

6th International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2024

作者： Jia, Dengqiang Yang, Xinnian Xiong, Xiaosong Huang, Shijie Hou, Feiyu Qin, Li Sun, Kaicong Chan, Kannie Wai Yan Shen, Dinggang Hong Kong Centre for Cerebro-Cardiovascular Health Engineering China School of Data Science City University of Hong Kong China School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai201210 China School of Mechanical and Automotive Engineering Shanghai University of Engineering Science Shanghai201620 China JinFeng Laboratory Chongqing401329 China Department of Biomedical Engineering City University of Hong Kong China Shanghai United Imaging Intelligence Co. Ltd. Shanghai200230 China Shanghai Clinical Research and Trial Center Shanghai201210 China

ISBN: (纸本)9783031832420

Vessel dynamics simulation is vital in studying the relationship between geometry and vascular disease progression. Reliable dynamics simulation relies on high-quality vascular meshes. Most of the existing mesh generation methods highly depend on manual annotation, which is time-consuming and laborious, usually facing challenges such as branch merging and vessel disconnection. This will hinder vessel dynamics simulation, especially for the population study. To address this issue, we propose a deep learning-based method, dubbed as DVasMesh to directly generate structured hexahedral vascular meshes from vascular images. Our contributions are threefold. First, we propose to formally formulate each vertex of the vascular graph by a four-element vector, including coordinates of the centerline point and the radius. Second, a vectorized graph template is employed to guide DVasMesh to estimate the vascular graph. Specifically, we introduce a sampling operator, which samples the extracted features of the vascular image (by a segmentation network) according to the vertices in the template graph. Third, we employ a graph convolution network (GCN) and take the sampled features as nodes to estimate the deformation between vertices of the template graph and target graph, and the deformed graph template is used to build the mesh. Taking advantage of end-to-end learning and discarding direct dependency on annotated labels, our DVasMesh demonstrates outstanding performance in generating structured vascular meshes on cardiac and cerebral vascular images. It shows great potential for clinical applications by reducing mesh generation time from 2 h (manual) to 30 s (automatic). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mesh generation

来源：评论

学校读者我要写书评

暂无评论

Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolution 27

Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Xu, Tianyi Zhou, Yijie Hu, Xiaotao Zhang, Kai Zhang, Anran Qiu, Xingye Xu, Jun School of Statistics and Data Science Nankai University Tianjin China College of Computer Science Nankai University Tianjin China School of Intelligence Science and Technology Nanjing University Suzhou China Tencent Data Platform Beijing China Zhejiang University Hangzhou China Systems Engineering Research Institute China State Shipbuilding Corporation Limited Beijing China Guangdong Provincial Key Laboratory of Big Data Computing The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781643685489

Arbitrary-scale super-resolution (ASSR) aims to learn a single model for image super-resolution at arbitrary magnifying scales. Existing ASSR networks typically comprise an off-the-shelf scale-agnostic feature extractor and an arbitrary scale upsampler. These feature extractors often use fixed network architectures to address different ASSR inference tasks, each of which is characterized by an input image and an upsampling scale. However, this overlooks the difficulty variance of super-resolution on different inference scenarios, where simple images or small SR scales could be resolved with less computational effort than difficult images or large SR scales. To tackle this difficulty variability, in this paper, we propose a Task-Aware Dynamic Transformer (TADT) as an input-adaptive feature extractor for efficient image ASSR. Our TADT consists of a multi-scale feature extraction backbone built upon groups of Multi-Scale Transformer Blocks (MSTBs) and a Task-Aware Routing Controller (TARC). The TARC predicts the inference paths within feature extraction backbone, specifically selecting MSTBs based on the input images and SR scales. The prediction of inference path is guided by a new loss function to trade-off the SR accuracy and efficiency. Experiments demonstrate that, when working with three popular arbitrary-scale upsamplers, our TADT achieves state-of-the-art ASSR performance when compared with mainstream feature extractors, but with relatively fewer computational costs. The code is available at https://***/Tillyhere/TADT. © 2024 The Authors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Measurement of Br(n,γ)cross sections up to stellar s-process temperatures at the CSNS Back‑n

引用

Nuclear science and Techniques 2023年第11期34卷 226-241页

作者： Gao‑Le Yang Zhen‑Dong An Wei Jiang Xian‑Kai Li Wei‑Wei Qiu Zheng‑Fa Liao Zi‑Yue Zhuang Xiao‑Ping Zhang Sheng‑Li Chen Chen‑Chen Guo Er‑Xi Xiao Xiao Fang Xin‑Xiang Li Xin‑Rong Hu Bing Jiang Jin‑Cheng Wang Jie Ren Wen Luo Zhi‑Chao Zhu Hao‑Yang Lan Zong‑Wei Cao Xu Ma Ying‑Du Liu Pu‑Sen Wang Yi Yang Ping Su Xian‑Gai Deng Wan‑Bing He Chun‑Wang Ma Yu‑Ting Wang Zhi‑Tao Dai Peng‑Qin He Ren‑Guang Tang Tao Zhou Jing Wang Han Yi Yue Zhang Yong‑Hao Chen Rui‑Rui Fan Ke‑Qing Gao Qiang Li Kang Sun Zhi‑Xin Tan Min‑Hao Gu Han‑Tao Jing Jing‑Yu Tang School of Physics and Astronomy Sun Yat-sen UniversityZhuhai 519082China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China State Key Laboratory of Lunar and Planetary Sciences Macao University of Science and TechnologyMacao 999078China CNSA Macao Center for Space Exploration and Science Macao 999078China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China Spallation Neutron Source Science Center Dongguan 523803China School of Nuclear Science and Technology University of South ChinaHengyang 421001China Sino‑French Institute of Nuclear Engineering and Technology Sun Yat-sen UniversityZhuhai 519082China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China School of Materials Science and Engineering Xiangtan UniversityXiangtan 411100China Key Laboratory of Nuclear Physics and Ion‑beam Application(MOE) Institute of Modern PhysicsDepartment of Nuclear Science and TechnologyFudan UniversityShanghai 200433China Institute of Particle and Nuclear Physics Henan Normal UniversityXinxiang 453007China School of Physics Henan Normal UniversityXinxiang 453007China Shenzhen Center Cancer hospitalChinese Academy of Medical SciencesShenzhen 518100China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230027China

The neutron capture cross sections(n,γ)of bromine were obtained using the time-of-flight technique at the Back-n facility of the China Spallation Neutron ***γ-rays originating from neutron-induced capture events were detected using four C_(6)D_(6) *** pulse-height weighting technique and double-bunch unfolding method based on Bayesian theory were used in the data *** deductions,normalization,and corrections were carefully considered to obtain reliable measurement *** multilevel R-matrix Bayesian code SAMMY was used to extract the resonance parameters in the resolved resonance region(RRR).The average cross sections in the unresolved resonance region(URR)were obtained from 10 to 400 *** experimental results were compared with data from several evaluated libraries and previous experi-ments in the RRR and *** TALYS code was used to describe the average cross sections in the *** astrophysical Maxwell average cross sections(MACSs)of ^(79,81)Br from kT=5 to 100 keV were calculated over a sufficiently wide range of neutron *** a thermal energy of kT=30 keV,the MACS value for ^(79)Br 682±68 mb was in good agreement with the KADoNiS v1.0 recommended *** contrast,the value of 293±29 mb for ^(81)Br was substantially higher than that of the evaluated database and the KADoNiS v1.0 recommended value.

关键词： Time-of-flight technique Neutron capture cross sections Maxwell average cross sections

来源：评论

学校读者我要写书评

暂无评论

Tensor Graph Convolutional Network for Dynamic Graph Representation Learning 7

Tensor Graph Convolutional Network for Dynamic Graph Represe...

引用

7th International Symposium on Autonomous Systems, ISAS 2024

作者： Wang, Ling Yuan, Ye The School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China The Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Engineering Research Center of Big Data Application For Smart Cities Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China College of Computer and Information Science Southwest University Chongqing400715 China

ISBN: (纸本)9798350363173

Dynamic graphs (DG) represent evolving interactions between entities in various real-world scenarios. Many existing DG representation learning models employ a combination of graph convolutional networks and sequence neural networks to capture spatial-temporal dependencies. However, this hybrid approach often fails to effectively capture the spatial-temporal continuity inherent in DGs. In this paper, we propose a novel approach called the Tensor Graph Convolutional Network (TGCN) to learn DG representations within a unified convolution framework based on tensor products. Our approach is founded on two key principles: (a) representing DG information in tensor form, and (b) leveraging tensor product operations to design a graph convolutional network that simultaneously models spatial and temporal features. Experimental results on three real-world DG datasets demonstrate that our proposed model achieves state-of-the-art performance. © 2024 IEEE.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

Exploiting Multiple Features for Hash Codes Learning with Semantic-Alignment-Promoting Variational Auto-encoder 12th

Exploiting Multiple Features for Hash Codes Learning with Se...

引用

12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023

作者： Chen, Jiayang Su, Qinliang School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Beijing China

ISBN: (纸本)9783031446924

Semantic hashing is an effective technique to empower information retrieval. Currently, considerable efforts have been dedicated to generating high-quality hash codes by modeling document features using generative models and other approaches. However, most of these methods rely solely on a single type of feature, such as TFIDF features, BERT embeddings, etc. As different types of features have distinct but complementary information of documents, e.g. TFIDF mainly contains the keywords information and BERT focuses on the semantics, hash codes generated solely from either may not capture the full essence of the documents. To overcome this challenge, we propose a semantic-alignment-promoting variational auto-encoder to generate hash codes from multiple document features. Specifically, a VAE-based generative model is first developed to model the multiple features. Then, we propose a semantic-alignment-promoting inference network to estimate the parameters of the variational posterior from multiple features. Additionally, the quality of hash codes is further improved by promoting the semantic alignment between the hash codes of connected documents in a constructed connection graph. The results of extensive experiments on three public datasets demonstrate that our proposed model significantly outperforms current state-of-the-art models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

SQLStateGuard: Statement-Level SQL Injection Defense Based on Learning-Driven Middleware 15

SQLStateGuard: Statement-Level SQL Injection Defense Based o...

引用

15th Annual ACM Symposium on Cloud Computing, SoCC 2024

作者： Liu, Xin Huang, Yuanyuan Wang, Tianyi Li, Song Niu, Weina Shen, Jun Zhou, Qingguo Zhou, Xiaokang School of Information Science and Engineering Lanzhou University Gansu Lanzhou China The State Key Laboratory of Blockchain and Data Security Zhejiang University Zhejiang Hangzhou China School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China School of Computing and Information Technology University of Wollongong WollongongNSW Australia Kansai University Osaka Suita Japan

ISBN: (纸本)9798400712869

SQL injection is a significant and persistent threat to web services. Most existing protections against SQL injections rely on traffic-level anomaly detection, which often results in high false-positive rates and can be easily bypassed by attackers. This paper introduces SQLStateGuard, the world's first middleware-driven statement-level SQL injection defense approach, to address these issues. The SQLStateGuard uses a custom SQL middleware based on the idea of Runtime Application Self-Protection to capture raw SQL statements. These statements are then analyzed by SQLSG-Net, a database-oriented detection network based on gated linear units. If SQLSG-Net detects malicious SQL statements, the SQL middleware will block them. Experiments show that the detection accuracy of SQLStateGuard exceeds 99%, outperforming existing approaches, and it can identify the type of a specific SQL injection. Additionally, SQLStateGuard has no fingerprint and does not respond to SQL syntax errors, making it more challenging for attackers to gather information. This paper also presents a novel dataset generation process for SQLStateGuard and shares two statement-level SQL injection datasets with the research community, including over 145,000 malicious SQL statements categorized by the type of SQL injection. © 2024 ACM.

关键词： Middleware

来源：评论

学校读者我要写书评

暂无评论

An integrative profiling of metabolome and transcriptome in the plasma and skeletal muscle following an exercise intervention in diet-induced obese mice

引用

Journal of Molecular Cell Biology 2023年第3期15卷 18-31页

作者： Shuang Han Qingqian Wu Mengying Wang Miqi Yang Chen Sun Jiaqi Liang Xiaozhen Guo Zheyu Zhang Jingya Xu Xinyuan Qiu Cen Xie Siyu Chen Yue Gao Zhuo-Xian Meng Department of Pathology and Pathophysiology and Department of Cardiology of the Second Affiliated Hospital Zhejiang University School of MedicineHangzhou 310058China Department of Geriatrics Affiliated Hangzhou First People’s HospitalZhejiang University School of MedicineHangzhou 310006China Key Laboratory of Disease Proteomics of Zhejiang Province Zhejiang University School of MedicineHangzhou 310058China Department of Big Data in Health Science School of Public Health Zhejiang University School of MedicineHangzhou 310003China State Key Laboratory of Natural Medicines and School of Life Science and Technology China Pharmaceutical UniversityNanjing 211198China State Key Laboratory of Drug Research Shanghai Institute of Material MedicalChinese Academy of SciencesShanghai 201203China Department of Biology and Chemistry College of Liberal Arts and SciencesNational University of Defense TechnologyChangsha 410073China

Exercise intervention at the early stage of type 2 diabetes mellitus(T2DM)can aid in the maintenance of blood glucose homeostasis and prevent the development of macrovascular and microvascular ***,the exercise-regulated pathways that prevent the development of T2DM remain largely *** this study,two forms of exercise intervention,treadmill training and voluntary wheel running,were conducted for high-fat diet(HFD)-induced obese *** observed that both forms of exercise intervention alleviated HFD-induced insulin resistance and glucose *** muscle is recognized as the primary site for postprandial glucose uptake and for responsive alteration beyond exercise *** profiling of the plasma and skeletal muscle in Chow,HFD,and HFD-exercise groups revealed robust alterations in metabolic pathways by exercise intervention in both *** analysis identified nine metabolites,including beta-alanine,leucine,valine,and tryptophan,which were reversed by exercise treatment in both the plasma and skeletal *** analysis of gene expression profiles in the skeletal muscle revealed several key pathways involved in the beneficial effects of exercise on metabolic *** addition,integrative transcriptomic and metabolomic analyses uncovered strong correlations between the concentrations of bioactive metabolites and the expression levels of genes involved in energy metabolism,insulin sensitivity,and immune response in the skeletal *** work established two models of exercise intervention in obese mice and provided mechanistic insights into the beneficial effects of exercise intervention on systemic energy homeostasis.

关键词： type 2 diabetes exercise intervention metabolomics transcriptomics

来源：评论

学校读者我要写书评

暂无评论

Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

引用

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

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：