检索结果-内蒙古大学图书馆

7th IEEE information technology and Mechatronics Engineering Conference, ITOEC 2023

作者： Hao, Xingyu Yu, Bo He, Yuzhuang Shenyang Ligong University School of Information Science and Engineering Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350334197

Casting products are widely used in many industrial fields. Castings are prone to defects in the production process. Due to the high utilization rate of castings, the quality of castings has become the focus of industrial production. Therefore, casting defect detection is very important in the production process. This paper proposes a casting defect detection method based on improved DETR to improve detection accuracy. Firstly, multi-scale feature fusion is added in the feature extraction stage;then, the ECA-NET attention mechanism module is introduced to improve the backbone network;secondly, the attention mechanism in the Transformer module is improved by using relative position encoding;finally, in the casting data, the improved algorithm is trained and tested on the set. The experimental results show that the accuracy of the improved DETR model proposed in this paper can reach 49.6%, which is 6.3% higher than the original DETR algorithm. Compared with other mainstream target detection algorithms, the casting defect detection model proposed in this paper can effectively identify Casting defects and achieve high detection accuracy. © 2023 IEEE.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Event-triggered Anti-disturbance Anti-Saturation Tracking Control for Systems with Nonlinearity:Application to Helicopter Elevation Angle Model 41

Event-triggered Anti-disturbance Anti-Saturation Tracking Co...

引用

第41届中国控制会议

作者： Jiangtong Wang Yang Yi Yunkai Wu Weixing Zheng College of Information Engineering Yangzhou University School of Electronics and Information Jiangsu University of Science and Technology School of Computing Engineering and MathematicsUniversity of Western Sydney

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This article concerns a disturbance observer-based(DOB) event-triggered anti-disturbance tracking control strategy for CE150 Helicopter *** the same time,actuator saturation is introduced compulsively,which is expressed by convex *** the one hand,it is to verify the performance of the system in the saturated state,and on the other hand,the actuator can be avoided from being damaged by excessive ***,the purpose of introducing the event-triggered mechanism is to save communication resources and the function of DOB proportional-integral(PI) controller is to suppress the disturbance and track the trajectory of the reference ***,the feasible gain can be obtained by utilizing the convex optimization and linear matrix inequation(LMI) ***,simulation is provided to demonstrate the feasibility and validity of the proposed control method.

关键词： Disturbance-observer-based control(BOBC) disturbance rejection convex optimization event-triggered control tracking control

来源：评论

学校读者我要写书评

暂无评论

Performance Assessment of Multi-Controller in Software Defined Network 4

Performance Assessment of Multi-Controller in Software Defin...

引用

4th IEEE International Conference on computing, Communication, and Intelligent Systems, ICCCIS 2023

作者： Jaiswal, Ankita Patra, Sudhansu Shekhar Dash, Bibhuti Bhusan Barik, Lalbihari Pandey, Trilok Nath Mishra, Manoj Ranjan School of Computer Engineering KIlT Deemed to Be University Bhubaneswar India King Abdulaziz University Faculty of Computing and Information Technology in Rabigh Department of Information Systems Saudi Arabia School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350306118

In a network design, the control plane and the data plane are separated by the architectural concept of software defined networking (SDN). A centralised controller that serves as the only point of control for the whole network is introduced by the SDN architecture. The controller serves as a logically centralized entity in charge of communicating the appropriate rules to a switch's flow table. Using a single controller to handle a lot of flows becomes insufficient. A lot of large-scale networks have employed multi-controller SDN to meet their objectives. In this research, we use a multi-controller infinite buffer waiting queue model to analyze the system performance metrics. Both numerical and simulated assessments are used to illustrate the proposed model. © 2023 IEEE.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

XRL-SHAP-Cache:an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

引用

science China(information sciences) 2024年第7期67卷 46-71页

作者： Xiaolong XU Fan WU Muhammad BILAL Xiaoyu XIA Wanchun DOU Lina YAO Weiyi ZHONG School of Software Nanjing University of Information Science and Technology School of Computing and Communications Lancaster University School of Computing Technologies Royal Melbourne Institute of Technology State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering University of New South Wales Data 61 Commonwealth Scientific and Industrial Research Organization School of Computer Science Qufu Normal University

Content delivery networks(CDNs) play a pivotal role in the modern internet infrastructure by enabling efficient content delivery across diverse geographical regions. As an essential component of CDNs, the edge caching scheme directly influences the user experience by determining the caching and eviction of content on edge servers. With the emergence of 5G technology, traditional caching schemes have faced challenges in adapting to increasingly complex and dynamic network environments. Consequently, deep reinforcement learning(DRL) offers a promising solution for intelligent zero-touch network governance. However, the blackbox nature of DRL models poses challenges in understanding and making trusting decisions. In this paper,we propose an explainable reinforcement learning(XRL)-based intelligent edge service caching approach,namely XRL-SHAP-Cache, which combines DRL with an explainable artificial intelligence(XAI) technique for cache management in CDNs. Instead of focusing solely on achieving performance gains, this study introduces a novel paradigm for providing interpretable caching strategies, thereby establishing a foundation for future transparent and trustworthy edge caching solutions. Specifically, a multi-level cache scheduling framework for CDNs was formulated theoretically, with the D3QN-based caching scheme serving as the targeted interpretable model. Subsequently, by integrating Deep-SHAP into our framework, the contribution of each state input feature to the agent's Q-value output was calculated, thereby providing valuable insights into the decision-making process. The proposed XRL-SHAP-Cache approach was evaluated through extensive experiments to demonstrate the behavior of the scheduling agent in the face of different environmental *** results demonstrate its strong explainability under various real-life scenarios while maintaining superior performance compared to traditional caching schemes in terms of cache hit ratio, quality of service(QoS),a

关键词： deep reinforcement learning (DRL) explainable artificial intelligence (XAI) multi-level cache content delivery network (CDN) D3QN algorithm Deep-SHAP

来源：评论

学校读者我要写书评

暂无评论

Multi-attribute wearable pressure sensor based on multilayered modulation with high constant sensitivity over a wide range

引用

Nano Research 2023年第5期16卷 7583-7592页

作者： Ning Li Song Gao Yang Li Jianwen Liu Wenhao Song Guozhen Shen School of Information Science and Engineering University of JinanJinan 250022China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of JinanJinan 250022China School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China School of Aeronautical and Astronautical Engineering Purdue University West LafayetteIN 47907USA

Flexible pressure sensors capable of monitoring diverse physiological signals and body movements have garnered tremendous attention in wearable electronic ***,high constant sensitivity over a wide pressure range combined with breathability,biocompatibility,biodegradability is pivotal for manufacturing of reliable pressure sensors in practical sensing *** this work,inspired by the multilayered structure of skin epidermis,we propose and demonstrate a multi-attribute wearable piezoresistive pressure sensor consisting of multilayered gradient conductive poly(ε-caprolactone)nanofiber membranes *** response to externally applied pressure,a layer-by-layer current path is activated inside the multilayered membranes composites,leading to the most salient sensing performance of high constant sensitivity of 33.955 kPa^(−1) within the pressure range of 0–80 *** proposed pressure sensor also exhibits a fast response–relaxation time,a low detection limit,excellent stability,which can be successfully used to measure human physiological ***,an integrated sensor array system that can locate objects’positions is constructed and applied to simulate sitting posture *** results indicate that the proposed pressure sensor holds great potential in health monitoring and wearable electronic devices.

关键词： wearable pressure sensors multilayer structure high constant sensitivity multi-attribute physiological signals monitoring

来源：评论

学校读者我要写书评

暂无评论

SynPrompt: Syntax-aware Enhanced Prompt Engineering for Aspect-based Sentiment Analysis 30

SynPrompt: Syntax-aware Enhanced Prompt Engineering for Aspe...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Yin, Wen Liu, Cencen Xu, Yi Wahla, Ahmad Yiting, Huang Zheng, Dezhang School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China Laboratory of Intelligent Collaborative Computing Chengdu611731 China Bashu Middle School Chongqing400013 China

ISBN: (纸本)9782493814104

Although there have been some studies uses prompt learning for the Aspect-based Sentiment Analysis(ABSA) tasks, their methods of prompt-tuning are simple and crude. Compared with vanilla fine-tuning methods, prompt learning intuitively bridges the objective form gap between pre-training and fine-tuning. Concretely, simply constructing prompt related to aspect words fails to fully exploit the potential of Pre-trained Language Models, and conducting more robust and professional prompt engineering for downstream tasks is a challenging problem that needs to be solved urgently. Therefore, in this paper, we propose a novel syntax-aware enhanced prompt method (SynPrompt), which sufficiently mines the key syntactic information related to aspect words from the syntactic dependency tree. Additionally, to effectively harness the domain-specific knowledge embedded within PLMs for the ABSA tasks, we constructed two adaptive prompt frameworks to enhance the perception ability of the above method. After conducting extensive experiments on three benchmark datasets, we have found that our method consistently achieves favorable results. These findings not only demonstrate the effectiveness and rationality of our proposed methods but also provide a powerful alternative to traditional prompt-tuning. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Enhancing Earthquake Prediction through Hybrid Deep Learning Approach 2

Enhancing Earthquake Prediction through Hybrid Deep Learning...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Kandan, M. Sarkar, Swagata Sharma, Meenakshi Rajeswari, V. Poonkuzhali, P. Srimathi, S. SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur India Sri Sairam Engineering College Artificial Intelligence and Data Science Chennai India Global Group of Institute Department of CSE Amritsar India Panimalar Engineering College Information Technology India R.M.D Engineering College Kavaraipettai India Saveetha School of Engineering SIMATS Department of Bio Technology Tamilnadu Chennai India

ISBN: (纸本)9798350317558

Earthquakes, one of the greatest natural catastrophes, kill people and harm the economy. Heavy earthquakes and tsunamis may kill thousands and cost millions. Globally, predicting major earthquakes is important. Because earthquake prediction is difficult, researchers employ machine learning to improve forecasts. Many countries have early earthquake warning systems to save lives. Temporal rather than geographical characteristics dominated previous research. A similarity between earthquake and non-seismic signals makes real-time earthquake detection with cellphones or IoT devices problematic. This system may change entity interactions using ML and an IoT network. EEWS metrics are tracked using IoT. However, ML can assess these actions and determine smart city risk reduction and catastrophe management strategies. A deep learning approach for continuous earthquake forecasting utilising past seismic events is proposed. This research predicts earthquakes by position and depth using machine learning and deep learning. ConvLSTM, a Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN), extracts important waveform elements to make the classifier reliable in earthquake parameters. © 2024 IEEE.

关键词： Convolutional Neural Network Deep Learning Earthquake LSTM Machine Learning

来源：评论

学校读者我要写书评

暂无评论

MindTerior: A Mental Healthcare Game with Metaphoric Gamespace and Effective Activities for Mitigating Mild Emotional Difficulties

MindTerior: A Mental Healthcare Game with Metaphoric Gamespa...

引用

Extended Abstracts of the 2023 CHI Conference on Human Factors in computing Systems, CHI EA 2023

作者： Lee, Ain Lee, Juhyun Ahn, Sooyeon Lee, Youngik Graduate School of Culture Technology Games and Life Lab Korea Advanced Institute of Science and Technology Korea Republic of Graduate School of Culture Technology Information-Based Design Lab Korea Advanced Institute of Science and Technology Korea Republic of Department of Industrial Design DxD Lab Korea Advanced Institute of Science and Technology Korea Republic of Graduate School of Culture Technology Social Computing Lab Korea Advanced Institute of Science and Technology Korea Republic of

ISBN: (纸本)9781450394222

Contemporaries suffer from more stress and emotional difficulties, but developing practices that allow them to manage and become aware of emotional states has been a challenge. MindTerior is a mental health care game developed for people who occasionally experience mild emotional difficulties. The game contains four mechanisms: measuring players' emotional state, providing game activities that help mitigate certain negative emotions, visualizing players' emotional state and letting players cultivate the game space with customizable items, and completing game events that educate players on how to cope with certain negative emotions. This set of gameplays can allow players to experience effective positive emotional relaxation and to perform gamified mental health care activities. Playtest showed that projecting players' emotional state to a virtual game space is helpful for players to be conscious of their emotional state, and playing gamified activities is helpful for mental health care. Additionally, the game motivated players to practice the equivalent activities in real life. © 2023 Owner/Author.

关键词： Health care

来源：评论

学校读者我要写书评

暂无评论

Software Bug Prediction using Machine Learning 15

Software Bug Prediction using Machine Learning

引用

15th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sathiyaraj, A. Angel, T.G. Ruby Turukmane, Anil V. Ramkumar, D. Guravaiah, Y. Department of Information Technology School of Computing Sathyabama Institute of Science and Technology Tamil Nadu Chennai600 119 India School of Computer Science and Engineering VIT-AP University Inavolu Andhra Pradesh Amaravati522237 India Department of Computer Science and Engineering MJR College of Engineering and Technology Diguvapokulavaripalli Pulicherla Andra Pradesh Chittoor District517214 India

ISBN: (纸本)9798331300579

The entire success of software is impacted by software bug prediction (SBP), a crucial part of the software development and maintenance life cycles. It is necessary to anticipate issues in order to increase the software's dependability, efficiency, and cost. In spite of the fact that a number of methods have been put out in the literature, it is difficult to create a reliable bug prediction model. In this paper, a machine learning (ML) based prediction method for software issues is introduced. Algorithms for guided machine learning that are based on historical data have been used to predict software errors. Two of the classifiers are Support Vector Machine and Naive Bayes (NB). How accurate and useful ML methods can be employed was demonstrated through the evaluation process. Included is the utilization of a comparative measure. © Grenze Scientific Society, 2024.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Publicly verifiable secure communication with user and data privacy

引用

Personal and Ubiquitous computing 2022年第3期26卷 863-879页

作者： Yao, Zhongyuan Mu, Yi Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia School of Mathematics and Computer Science Fujian Normal University Fuzhou China

Security surveillance system plays an important role in the society. However, how to securely send the sensitive information from the surveillance node to the server is a critical issue which should be well addressed. In this paper, to develop a secure communication scheme applied between the surveillance camera and the server, we propose the important and desirable security and privacy features that should be achieved by such systems, and present a secure scheme that can achieve the security goals. Our scheme ensures that encrypted datagrams not sent from the surveillance cameras can be filtrated by a public message filter while data and sender privacy is still well preserved for encrypted data sent from legitimated cameras. Furthermore, the server in our scheme is the only entity which can reveal the real sender given a ciphertext produced by it and give a proof to convince others the origination of that ciphertext without leaking its content. Such property enables the server to build a searchable database using the camera’s identifier as index and also the message auditor to check the ciphertext and its origination stored in the database without any dispute. We provide the formal security models to define these security requirements and give formal security proofs in the random oracle model. © 2019, Springer-Verlag London Ltd., part of Springer Nature.

关键词： Data privacy

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：