检索结果-内蒙古大学图书馆

28th International Conference on database Systems for Advanced Applications, DASFAA 2023

作者： Lin, Leilei Jin, Yumeng Wen, Lijie Chen, Wenlong Di, Ying Xu, Yusong Wang, Jianmin School of Management Capital Normal University Beijing China Information Engineering College Capital Normal University Beijing China School of Software Tsinghua University Beijing China Beijing Key Laboratory of Industrial Big Data System and Application Beijing China

ISBN: (纸本)9783031306778

The only constant is change. Drift detection in process mining is a family of methods to detect changes by analyzing event logs to ensure the accuracy and reliability of business processes in process-aware information systems (e.g., ERP systems). However, artificial feature selection is still a mountain to climb in existing methods, which requires high domain knowledge for users. In this paper, we propose a novel approach by using Graph convolutional networks for Drifts Detection in the event log, we name it GDD. Specifically, 1) we transform event sequences into two directed graphs by using two consecutive time windows, and construct the line graphs for the directed graphs to capture the orders between different activities;2) we use graph convolutional networks to capture the features in these graphs, and augment the original graphs with virtual nodes to represent the latent aspects of the graphs;3) we calculate the distances between virtual nodes, and use the K-means algorithm to find the outliers that are considered as candidate change points. Then, a filter mechanism is used to confirm the actual change points. The experiments on simulated event logs and real-life event logs confirmed the improvements of GDD compared with the baselines. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Real-time stealth transmission via dither-based bias control

Real-time stealth transmission via dither-based bias control

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Wang, Yuanxiang Shao, Weidong Zhong, Linsheng Dai, Xiaoxiao Yang, Qi Deng, Lei Liu, Deming Cheng, Mengfan Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China

We report a real-time 1 kbps stealthy transmission in the 10 Gbps QPSK public communication. The stealth data is embedded in dither signals of bias control. The scheme is compatible with existing optical transmission ... 详细信息

ISBN: (纸本)9781957171258

关键词： Light transmission

来源：评论

学校读者我要写书评

暂无评论

A novel thermally-stable Ca2GaTaO6:Sm3+ phosphor and its application in WLEDs and anti-counterfeit inks

引用

Journal of Rare Earths 2025年第06期 1120-1132页

作者： Yanzhi Zhang Yi Ling Ruirui Cui Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information EngineeringGuizhou University College of Physics Guizhou University State Key Laboratory of Public Big Data Guizhou University

In this study,a novel Ca2GaTaO6:Sm3+phosphor was developed using the conventional hightemperature solid-phase *** phase structure and morphology test results of phosphor indicate that the Ca2GaTaO6material was successfully synthesized and the Sm3+ions were successfully doped into the host *** utilizing 406 nm excitation,the Ca2GaTaO6:xSm3+phosphor has the strongest emission intensity at 599 nm and shows orange-red emission,which is mainly owing to the4G5/2→6H7/2jump of Sm3+*** the performance of different concentrations of Sm3+ions,3 mol%performs the *** this time,concentration quenching occurs,which is most predominantly induced by dipole-dipole（d-d） *** terms of thermal stability,the Ca2GaTaO6:0.03Sm3+phosphor shows good properties,with the luminescence intensity at 423 K exhibiting 88.17% of that at 298 *** white light-emitting diodes（WLEDs） devices prepared using Ca2GaTaO6:0.03Sm3+phosphor shows warm white light with excellent performance in terms of correlated color temperature and color rendering index（CCT=3642 K,CRI,Ra=93.5）.In terms of anticounterfeit inks,the Ca2GaTaO6:0.03Sm3+phosphor also shows good *** research results show that Ca2GaTaO6:Sm3+phosphors have great performance for application in WLEDs and anti-counterfeit inks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

TrustUQA: A Trustful Framework for Unified Structured data Question Answering 39

TrustUQA: A Trustful Framework for Unified Structured Data Q...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhang, Wen Jin, Long Zhu, Yushan Chen, Jiaoyan Huang, Zhiwei Wang, Junjie Hua, Yin Liang, Lei Chen, Huajun Zhejiang University China University of Manchester United Kingdom Ant Group China ZJU-Ant Group Joint Lab of Knowledge Graph China Zhejiang Key Laboratory of Big Data Intelligent Computing China

ISBN: (纸本)157735897X

Natural language question answering (QA) over structured data sources such as tables and knowledge graphs have been widely investigated, especially with Large Language Models (LLMs) in recent years. The main solutions include question to formal query parsing and retrieval-based answer generation. However, current methods of the former often suffer from weak generalization, failing to dealing with multi-types of sources, while the later is limited in trustfulness. In this paper, we propose TrustUQA, a trustful QA framework that can simultaneously support multiple types of structured data in a unified way. To this end, it adopts an LLM-friendly and unified knowledge representation method called Condition Graph (CG), and uses an LLM and demonstration-based two-level method for CG querying. For enhancement, it is also equipped with dynamic demonstration retrieval. We have evaluated TrustUQA with 5 benchmarks covering 3 types of structured data. It outperforms 2 existing unified structured data QA methods. In comparison with the baselines that are specific to one data type, it achieves state-of-the-art on 2 of the datasets. Further more, we have demonstrated the potential of our method for more general QA tasks, QA over mixed structured data and QA across structured data. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Structured Query Language

来源：评论

学校读者我要写书评

暂无评论

Bidirectional Logits Tree: Pursuing Granularity Reconcilement in Fine-Grained Classification 39

Bidirectional Logits Tree: Pursuing Granularity Reconcilemen...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Lu, Zhiguang Xu, Qianqian Bao, Shilong Yang, Zhiyong Huang, Qingming Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China School of Computer Science and Technology University of Chinese Academy of Sciences China Key Laboratory of Big Data Mining and Knowledge Management University of Chinese Academy of Sciences China

ISBN: (纸本)157735897X

This paper addresses the challenge of Granularity Competition in fine-grained classification tasks, which arises due to the semantic gap between multi-granularity labels. Existing approaches typically develop independent hierarchy-aware models based on shared features extracted from a common base encoder. However, because coarse-grained levels are inherently easier to learn than finer ones, the base encoder tends to prioritize coarse feature abstractions, which impedes the learning of fine-grained features. To overcome this challenge, we propose a novel framework called the Bidirectional Logits Tree (BiLT) for Granularity Reconcilement. The key idea is to develop classifiers sequentially from the finest to the coarsest granularities, rather than parallelly constructing a set of classifiers based on the same input features. In this setup, the outputs of finer-grained classifiers serve as inputs for coarser-grained ones, facilitating the flow of hierarchical semantic information across different granularities. On top of this, we further introduce an Adaptive Intra-Granularity Difference Learning (AIGDL) approach to uncover subtle semantic differences between classes within the same granularity. Extensive experiments demonstrate the effectiveness of our proposed method. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Review-aware Graph Contrastive Learning Framework for Recommendation

arXiv

引用

arXiv 2022年

作者： Shuai, Jie Sun, Peijie Zhang, Kun Hong, Richang Li, Yong Wu, Le Wang, Meng Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Institute of Artificial Intelligence Hefei Comprehensive National Science Center China Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Tsinghua University China

Most modern recommender systems predict users’ preferences with two components: user and item embedding learning, followed by the user-item interaction modeling. By utilizing the auxiliary review information accompanied with user ratings, many of the existing review-based recommendation models enriched user/item embedding learning ability with historical reviews or better modeled user-item interactions with the help of available user-item target reviews. Though significant progress has been made, we argue that current solutions for review-based recommendation suffer from two drawbacks. First, as review-based recommendation can be naturally formed as a user-item bipartite graph with edge features from corresponding user-item reviews, how to better exploit this unique graph structure for recommendation? Second, while most current models suffer from limited user behaviors, can we exploit the unique self-supervised signals in the review-aware graph to guide two recommendation components better? To this end, in this paper, we propose a novel Review-aware Graph Contrastive Learning (RGCL) framework for review-based recommendation. Specifically, we first construct a review-aware user-item graph with feature-enhanced edges from reviews, where each edge feature is composed of both the user-item rating and the corresponding review semantics. This graph with feature-enhanced edges can help attentively learn each neighbor node weight for user and item representation learning. After that, we design two additional contrastive learning tasks (i.e., Node Discrimination and Edge Discrimination) to provide self-supervised signals for the two components in recommendation process. Finally, extensive experiments over five benchmark datasets demonstrate the superiority of our proposed RGCL compared to the state-of-the-art baselines. Copyright © 2022, The Authors. All rights reserved.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Enhancing Event Tagger with Automatic Speech Recognizer for Audio Multi-task Scenarios by Distillation with Pre-Trained Large Models

Enhancing Event Tagger with Automatic Speech Recognizer for ...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Cheng, Jianfeng Liu, Ye Yin, Jian Wang, Liangdao Pan, Yan Lizhi Inc. Artificial Intelligence Department Guangzhou Beijing China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China School of Artificial Intelligence Sun Yat-sen University Zhuhai China

ISBN: (纸本)9781665410205

With the continuous expansion of robotics and digital humans in practical applications, the demand for the auditory system is becoming deeper, usually requiring more efficient speech recognition framework capabilities to handle multiple tasks and use fewer resources. In previous audio processing frameworks, each type of audio processing task typically requires constructing a standalone deep network model for training, which results in more training data and higher training time when constructing models for multi-task audio scenarios simultaneously. The recent improvement of audio models based on transformers have brought about methods that can handle multiple audio tasks concurrently. However, recent related methods still require retraining multi-task targets with an amount of data, and achieve the general effect after training for multi-task scenarios than the simple combination of standalone methods processed separately. In order to better build a model that can handle multiple audio tasks, we propose a novel framework of distillation through pre-trained large models for enhancing event tagger with automatic speech recognizer. Through multiple rounds of experiments on several audio datasets, it has been verified that the proposed framework can achieve better results than the baseline for multitasking, and comparative results with less parameters compared to the baselines for single-task scenarios. © 2024 IEEE.

关键词： Continuous speech recognition

来源：评论

学校读者我要写书评

暂无评论

A Color Image Encryption Scheme Based on Block Compressive Sensing and Chaotic Systems 2

A Color Image Encryption Scheme Based on Block Compressive S...

引用

2nd International Conference on Applied Statistics, Computational Mathematics, and Software engineering, ASCMSE 2023

作者： Tian, Junfeng Chen, Keke Key Laboratory of Big Data Analysis and Processing of Henan Province Henan University Kaifeng475004 China College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Province Engineering Research Center of Spatial Information Processing Henan University Kaifeng475004 China

ISBN: (数字)9781510668195

ISBN: (纸本)9781510668188

The traditional compressive sensing theory does not take full advantage of the differences in image block information features for sampling, and the measurement matrix does not adequately measure the image based on the image information features. To solve these problems, we design a color image encryption scheme based on block compressive perception and chaotic systems. First, the color image is divided into three channels of RGB and into 8*8 blocks respectively. Then, a zigzag transform is applied to each block so that each pixel value is evenly distributed. Each block is sparsified by the discrete cosine transform, and the measurement matrix generated by the Chen chaotic system is sampled to compress the image blocks to CR times the original block size according to different compression ratios (CR). The resulting chunked compressed samples are further distributed across the pixel values of the image using a cross-channel confusion dislocation method. Finally, the size of the pixel values is changed by a dissimilarity operation. The experimental results show that the scheme can balance the security of image information transmission and the integrity of reception, and has good resistance to various attacks. © 2023 SPIE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Visible Thermal Person Re-Identification Via Multi-Branch Modality Residual Complementary Learning

SSRN

引用

SSRN 2024年

作者： Chen, Long Sun, Rui Yu, Yiheng Du, Yun Zhang, Xudong Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer and Information Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei University of Technology Hefei230009 China The School of Computer and Information Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei University of Technology Hefei230009 China

Visible-thermal Person Re-identification (VT Re-ID) is a challenging task in all-weather surveillance system. Existing methods focus on extracting the modality-shared features, ignoring the discriminative inter-modality complementary features. To tackle this issue, we propose the multi-branch modality residual complementary learning method consisting of modality residual complementary learning (MRCL) module and multi-branch feature learning (MBFL) module. The MRCL module can be easily integrated into existing CNN and Transformer baselines and drive the network to focus on both intra-modality and inter-modality information simultaneously. On one hand, we adopt the basic two-stream network to obtain the intra-modality features, on the other hand, we feed the residual image acquired by cross-modality correlation saliency erasing operation to another two-stream network to capture the inter-modality complementary features. Moreover, we employ the MBFL module to capture local spatial features and local channel features and integrate them with global features to increase the discriminability and robustness of the ultimate representations for handling intra-modality variations. The extensive experiments on RegDB and SYSU-MM01 datasets demonstrate the superiority of our proposed method compared with state-of-the-art methods. © 2024, The Authors. All rights reserved.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

COVID-19 Impact on Global Electricity Generation Structure-Based on Sustainable Development Perspective 9th

COVID-19 Impact on Global Electricity Generation Structure-B...

引用

9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Peng, Shuyang Yang, Xian Lu, Haibo Guo, Kun School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

This paper has sorted out the general logic of the impact of COVID-19 on energy consumption. In the short term, the epidemic has forced governments to adopt different levels of lockdown measures. The total electricity consumption decreased and the share of renewable energy has increased. Based on the International Energy Agency's (IEA) data on electricity production and consumption, this paper analyzes the long-term effects: The COVID-19 pandemic does affect overall electricity demand and market structure in the short term, but in the long term, the impact of the pandemic is detrimental to the proportion of electricity generated from renewable sources. Increased, especially in hard-hit countries. The impact on countries with different levels of development is different, and countries with higher levels of economic development are better able to resist such exogenous shocks. The pandemic is still ongoing, how to steadily promote sustainable development? In this paper we suggest that to cope with climate change, to accomplish energy transformation and upgrading or even sustainable development, we should not only rely on reducing human activities, but give more support to countries with low development levels in realizing sustainable development. © 2022 The Authors. Published by Elsevier B.V.

关键词： COVID-19

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：