检索结果-内蒙古大学图书馆

Prognostics and system Health Management Conference (PHM-Qingdao)

作者： Pengfei Gou Daiwei Zheng Lei Tang Mengjuan Liu School of Information and Software Engineering University of Electronic Science and Technology of China UESTC Chengdu China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China NPIC Chengdu China

ISBN: (数字)9798350354010

ISBN: (纸本)9798350354027

Prognostics and Health Management (PHM) is currently the mainstream solution for the condition monitoring and maintenance of industrial systems. In PHM, the system condition is monitored by monitoring the operational status parameters of the system to diagnose equipment faults, predict the remaining useful life, etc. Utilizing sequential operational status parameters to complete prediction and classification tasks is usually modeled as a time series processing task. Therefore, a high-performance time series prediction model is crucial for PHM. This paper focuses on the use of time series prediction models to achieve the prediction of key state parameters of the nuclear power system. However, there are still some challenges when directly applying existing time series prediction models to industrial systems. First, obtaining operational data on the nuclear power system is relatively difficult, resulting in a small amount of training data, which causes many models to face the risk of insufficient training or overfitting. Second, most of the existing time series prediction models are composed of high- and low-frequency decoupling modules, while the operational data of nuclear power systems often have fewer high-frequency components, making it difficult for many existing SOTA models to achieve good results. In order to address these challenges, we have developed a Transformer-based time series prediction model with contrastive learning for monitoring the status of nuclear power systems. We evaluated the new model on three nuclear power simulation datasets and four power transformer datasets. The experimental results show that the new model's performance is superior to baseline models. We also proved the effectiveness of our improvement through ablation experiments.

关键词： Training Time series analysis Training data Contrastive learning Predictive models Data models Power systems Power transformers Prognostics and health management Monitoring

来源：评论

学校读者我要写书评

暂无评论

Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion Recognition

arXiv

引用

arXiv 2024年

作者： Wang, Jingyao Qiang, Wenwen Zheng, Changwen Sun, Fuchun University of Chinese Academy of Sciences Beijing China National Key Laboratory of Space Integrated Information System Institute of Software Chinese Academy of Sciences Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

Fine-grained emotion recognition (FER) plays a vital role in various fields, such as disease diagnosis, personalized recommendations, and multimedia mining. However, existing FER methods face three key challenges in real-world applications: (i) they rely on large amounts of continuously annotated data to ensure accuracy since emotions are complex and ambiguous in reality, which is costly and time-consuming;(ii) they cannot capture the temporal heterogeneity caused by changing emotion patterns, because they usually assume that the temporal correlation within sampling periods is the same;(iii) they do not consider the spatial heterogeneity of different FER scenarios, that is, the distribution of emotion information in different data may have bias or interference. To address these challenges, we propose a Spatio-Temporal Fuzzy-oriented Multi-modal Meta-learning framework (ST-F2M). Specifically, ST-F2M first divides the multimodal videos into multiple views, and each view corresponds to one modality of one emotion. Multiple randomly selected views for the same emotion form a meta-training task. Next, ST-F2M uses an integrated module with spatial and temporal convolutions to encode the data of each task, reflecting the spatial and temporal heterogeneity. Then it adds fuzzy semantic information to each task based on generalized fuzzy rules, which helps handle the complexity and ambiguity of emotions. Finally, ST-F2M learns emotion-related general meta-knowledge through meta-recurrent neural networks to achieve fast and robust fine-grained emotion recognition. Extensive experiments show that ST-F2M outperforms various state-of-the-art methods in terms of accuracy and model efficiency. In addition, we construct ablation studies and further analysis to explore why ST-F2M performs well. Copyright © 2024, The Authors. All rights reserved.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Few-shot gearbox fault diagnosed based on meta-learning and time convolution network

Few-shot gearbox fault diagnosed based on meta-learning and ...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Dai, Yuan Ou, Yanghui Hu, Junwei Ping, Zuowei Xu, Xinghua Zhang, Yong Wuhan University of Science and Technology School of Information Science and Engineering Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan China

ISBN: (纸本)9781665465335

In order to resolve the problem that the traditional fault diagnosis methods can not accurately diagnose under complex working conditions and few fault data, a fault diagnosis method based on meta-learning and time convolution network (TCN) is proposed in this paper. Firstly, Ensemble Empirical Mode Decomposition-Independent Component Analysis (EEMDICA) is used to denoise the original signals under different working conditions, and the acquired signals are randomly sampled to form meta tasks according to the meta-learning protocol. Through the TCN model training, the priori knowledge is obtained by optimizing the initialization parameters. The knowledge is used to improve accuracy in unforeseen condition tasks. Finally, simulation experiments are carried out on the gearbox dataset. The results indicate that the method has advantages in solving the fault classification problem of few shot gearbox under complex working conditions. © 2022 IEEE.

关键词： Empirical mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Do Advanced Language Models Eliminate the Need for Prompt Engineering in software Engineering?

arXiv

引用

arXiv 2024年

作者： Wang, Guoqing Sun, Zeyu Gong, Zhihao Ye, Sixiang Chen, Yizhou Zhao, Yifan Liang, Qingyuan Hao, Dan MOE School of Computer Science Peking University Beijing China National Key Laboratory of Space Integrated Information System Institute of Software Chinese Academy of Sciences Beijing China Beijing University of Chemical Technology Beijing China

Large Language Models (LLMs) have significantly advanced software engineering (SE) tasks, with prompt engineering techniques enhancing their performance in code-related areas. However, the rapid development of foundational LLMs such as the non-reasoning model GPT-4o and the reasoning model o1 raises questions about the continued effectiveness of these prompt engineering techniques. This paper presents an extensive empirical study that reevaluates various prompt engineering techniques within the context of these advanced LLMs. Focusing on three representative SE tasks, i.e., code generation, code translation, and code summarization, we assess whether prompt engineering techniques still yield improvements with advanced models, the actual effectiveness of reasoning models compared to non-reasoning models, and whether the benefits of using these advanced models justify their increased costs. Our findings reveal that prompt engineering techniques developed for earlier LLMs may provide diminished benefits or even hinder performance when applied to advanced models. In reasoning LLMs, the ability of sophisticated built-in reasoning reduces the impact of complex prompts, sometimes making simple zero-shot prompting more effective. Furthermore, while reasoning models outperform non-reasoning models in tasks requiring complex reasoning, they offer minimal advantages in tasks that do not need reasoning and may incur unnecessary costs. Based on our study, we provide practical guidance for practitioners on selecting appropriate prompt engineering techniques and foundational LLMs, considering factors such as task requirements, operational costs, and environmental impact. Our work contributes to a deeper understanding of effectively harnessing advanced LLMs in SE tasks, informing future research and application development. © 2024, CC BY.

关键词： Cost engineering

来源：评论

学校读者我要写书评

暂无评论

Long-term and short-term plasticity independently mimicked in highly reliable Ru-doped Ge_(2)Sb_(2)Te_(5) electronic synapses

引用

InfoMat 2024年第8期6卷 85-96页

作者： Qiang Wang Yachuan Wang Yankun Wang Luyue Jiang Jinyan Zhao Zhitang Song Jinshun Bi Libo Zhao Zhuangde Jiang Jutta Schwarzkopf Shengli Wu Bin Zhang Wei Ren Sannian Song Gang Niu State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research LaboratoryKey Laboratory of the Ministry of Education&International Center for Dielectric ResearchSchool of Electronic Science and EngineeringXi'an Jiaotong UniversityXi'anthe People's Republic of China School of Integrated Circuits Peking UniversityBeijingthe People's Republic of China Beijing Microelectronics Technology Institute Beijingthe People's Republic of China National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual information and Applicationsand School of SoftwareXi'an Jiaotong UniversityXi'anthe People's Republic of China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaithe People's Republic of China Key Laboratory of Microelectronics Device and Integrated Technology The Institute of Microelectronics of Chinese Academy of SciencesBeijingthe People's Republic of China University of Chinese Academy of Sciences Beijingthe People's Republic of China The State Key Laboratory for Manufacturing Systems Engineering&The International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong UniversityXi'anthe People's Republic of China Leibniz-Institut für Kristallzüchtung Max-Born-Straße 2BerlinGermany Key Laboratory of Physical Electronics and Devices Ministry of EducationSchool of Electronic Science and EngineeringXi'an Jiaotong UniversityXi'anthe People's Republic of China The International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong UniversityXi'anthe People's Republic of China

In order to fulfill the complex cognitive behaviors in neuromorphic systems with reduced peripheral circuits,the reliable electronic synapses mimicked by single device that achieves diverse long-term and short-term plasticity are *** change random access memory(PCRAM)is of great potential for artificial synapses,which faces,however,difficulty to realize short-term plasticity due to the long-lasting resistance *** work reports the ruthenium-doped Ge_(2)Sb_(2)Te_(5)(RuGST)based PCRAM,demonstrating a series of synaptic behaviors of short-term potentiation,pair-pulse facilitation,longterm depression,and short-term plasticity in the same single *** optimized RuGST electronic synapse with the high transformation temperature of hexagonal phase>380C,the outstanding endurance>108 cycles,the low resistance drift factor of 0.092,as well as the extremely high linearity with correlation coefficients of 0.999 and 0.976 in parts of potentiation and *** investigations also go insight to mechanisms of Ru doping according to thorough microstructure characterization,revealing that Ru dopant is able to enter GST lattices thus changing and stabilizing atomic arrangement of *** leads to the short-term plasticity realized by RuGST ***,the proposed RuGST electronic synapses performs a high accuracy of94.1%in a task of image recognition of CIFAR-100 database using ResNet *** work promotes the development of PCRAM platforms for large-scale neuromorphic systems.

关键词： electronic synapses neuromorphic computing PCRAM Ru-doped Ge_(2)Sb_(2)Te_(5)

来源：评论

学校读者我要写书评

暂无评论

BI-based Reasoning about Quantum Programs with Heap Manipulations

arXiv

引用

arXiv 2024年

作者： Su, Bonan Zhou, Li Feng, Yuan Ying, Mingsheng Department of Computer Science and Technology Tsinghua University Beijing China Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Centre for Quantum Software and Information University of Technology Sydney Ultimo Australia

We provide well-founded semantics for a quantum programming language Qwhile-hp with heap manipulations, where allocation statements follow a dirty pattern, meaning that newly allocated qubits can nondeterministically assume arbitrary initial states. To thoroughly characterize heap manipulations in the quantum setting, we develop a quantum BI-style logic that includes interpretations for separating implication (−∗) and separating conjunction (∗). We then adopt this quantum BI-style logic as an assertion language to reason about heap-manipulated quantum programs and present a quantum separation logic which is sound and relatively complete. Finally, we apply our framework to verify the correctness of various practical quantum programs and to prove the correct usage of dirty ancilla qubits. Copyright © 2024, The Authors. All rights reserved.

关键词： Qubits

来源：评论

学校读者我要写书评

暂无评论

Rethinking Causal Relationships Learning in Graph Neural Networks

arXiv

引用

arXiv 2023年

作者： Gao, Hang Yao, Chengyu Li, Jiangmeng Si, Lingyu Jin, Yifan Wu, Fengge Zheng, Changwen Liu, Huaping Science and Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences China University of Chinese Academy of Sciences China State Key Laboratory of Intelligent Game China Department of Computer Science and Technology Tsinghua University China

Graph Neural Networks (GNNs) demonstrate their significance by effectively modeling complex interrelationships within graph-structured data. To enhance the credibility and robustness of GNNs, it becomes exceptionally crucial to bolster their ability to capture causal relationships. However, despite recent advancements that have indeed strengthened GNNs from a causal learning perspective, conducting an in-depth analysis specifically targeting the causal modeling prowess of GNNs remains an unresolved issue. In order to comprehensively analyze various GNN models from a causal learning perspective, we constructed an artificially synthesized dataset with known and controllable causal relationships between data and labels. The rationality of the generated data is further ensured through theoretical foundations. Drawing insights from analyses conducted using our dataset, we introduce a lightweight and highly adaptable GNN module designed to strengthen GNNs' causal learning capabilities across a diverse range of tasks. Through a series of experiments conducted on both synthetic datasets and other real-world datasets, we empirically validate the effectiveness of the proposed module. The codes are available at https://***/yaoyao-yaoyao-cell/CRCG. © 2023, CC BY.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Measurement-based Verification of Quantum Markov Chains

arXiv

引用

arXiv 2024年

作者： Guan, Ji Feng, Yuan Turrini, Andrea Ying, Mingsheng Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Beijing100190 China Department of Computer Science and Technology Tsinghua University Beijing100084 China Institute of Intelligent Software Guangzhou511458 China The Centre for Quantum Software and Information University of Technology SydneyNSW2007 Australia

Model-checking techniques have been extended to analyze quantum programs and communication protocols represented as quantum Markov chains, an extension of classical Markov chains. To specify qualitative temporal properties, a subspace-based quantum temporal logic is used, which is built on Birkhoff–von Neumann atomic propositions. These propositions determine whether a quantum state is within a subspace of the entire state space. In this paper, we propose the measurement-based linear-time temporal logic MLTL to check quantitative properties. MLTL builds upon classical linear-time temporal logic (LTL) but introduces quantum atomic propositions that reason about the probability distribution after measuring a quantum state. To facilitate verification, we extend the symbolic dynamics-based techniques for stochastic matrices described by Agrawal et al. (JACM 2015) to handle more general quantum linear operators (super-operators) through eigenvalue analysis. This extension enables the development of an efficient algorithm for approximately model checking a quantum Markov chain against an MLTL formula. To demonstrate the utility of our model-checking algorithm, we use it to simultaneously verify linear-time properties of both quantum and classical random walks. Through this verification, we confirm the previously established advantages discovered by Ambainis et al. (STOC 2001) of quantum walks over classical random walks and discover new phenomena unique to quantum walks. © 2024, CC BY.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

SCPatcher: Mining Crowd Security Discussions to Enrich Secure Coding Practices 23

SCPatcher: Mining Crowd Security Discussions to Enrich Secur...

引用

Proceedings of the 38th IEEE/ACM International Conference on Automated software Engineering

作者： Ziyou Jiang Lin Shi Guowei Yang Qing Wang State Key Laboratory of Intelligent Game Beijing China and Science and Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China and University of Chinese Academy of Sciences Beijing China School of Software Beihang University Beijing China The University of Queensland Brisbane Australia

ISBN: (纸本)9798350329964

Secure coding practices (SCPs) have been proposed to guide software developers to write code securely to prevent potential security vulnerabilities. Yet, they are typically one-sentence principles without detailed specifications, e.g., "Properly free allocated memory upon the completion of functions and at all exit points.", which makes them difficult to follow in practice, especially for software developers who are not yet experienced in secure programming. To address this problem, this paper proposes SCPatcher, an automated approach to enrich secure coding practices by mining crowd security discussions on online knowledge-sharing platforms, such as Stack Overflow. In particular, for each security post, SCPatcher first extracts the area of coding examples and coding explanations with a fix-prompt tuned Large Language Model (LLM) via Prompt Learning. Then, it hierarchically slices the lengthy code into coding examples and summarizes the coding explanations with the areas. Finally, SCPatcher matches the CWE and Public SCP, integrating them with extracted coding examples and explanations to form the SCP specifications, which are the wild SCPs with details, proposed by the developers. To evaluate the performance of SCPatcher, we conduct experiments on 3,907 security posts from Stack Overflow. The experimental results show that SCPatcher outperforms all baselines in extracting the coding examples with 2.73% MLine on average, as well as coding explanations with 3.97% F1 on average. Moreover, we apply SCPatcher on 447 new security posts to further evaluate its practicality, and the extracted SCP specifications enrich the public SCPs with 3,074 lines of code and 1,967 sentences.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Study on Gateway Station Deployment for Large Scale LEO Satellite Constellation Networks

Study on Gateway Station Deployment for Large Scale LEO Sate...

引用

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Lei Cheng Shuaijun Liu Lixaing Liu Hailong Hu Jingyi Chen Xiandong Mneg PengCheng Ding Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences & University of Chinese Academy of Sciences Beijing China Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China Tianlong Communication Co. Ltd Yibiin China

In the past few years, the large scale satellite constellation project represented by Starlink, oneweb, etc. has promoted a new round of large scale low earth orbit (LEO) satellite constellation networks (LS-LEOSCN) development wave. In LS-LEOSCN, multiple gateway stations need to be deployed to meet user needs, and their location greatly affects system capacity and other performance. Most of the factors considered are delay, hop count or capacity, but most of them do not consider the interference between the feeding links under the giant constellation. In this paper, a capacity evaluation method considering the interference between feeder links is proposed, and based on this capacity evaluation mechanism, a gateway station deployment optimization method based on genetic algorithm is proposed to maximize the system capacity in the case of considering the interference between feeder links. Compared with the randomly generated scheme, the capacity is increased by 6.9% in average.

关键词： Satellite constellations Privacy Urban areas Low earth orbit satellites Optimization methods Interference Logic gates

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：