检索结果-内蒙古大学图书馆

Frequent Event Pattern Extraction of Drilling Time Series Using Change Point Detection and Event Sequence Generation

引用

IFAC-PapersOnLine 2023年第2期56卷 6168-6173页

作者： Yupeng Li Wenkai Hu Weihua Cao R. Bhushan Gopaluni Liang Cao Chao Gan Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China Department of Chemical and Biological Engineering University of British Columbia Vancouver BC V6T 1Z3 Canada

In drilling processes, non-stationary phases corresponding to shifts between operating conditions and changes in downhole formations typically lead to false alarms. Extracting these frequent event patterns is critical to build drilling process monitoring and fault diagnosis models. This study aims to extract the frequent event patterns associated with non-stationary phases in drilling time series. In this way, diversified information related to signal changes under normal conditions can be obtained, which is beneficial for suppressing false alarms and improving fault detection performance. The main contributions of this study are twofold: 1) a non-stationary phase detection method is proposed to extract drilling frequent event patterns based on t -distributed stochastic neighbor embedding and relative unconstrained least-squares importance fitting; 2) an event sequence generation method is proposed to express drilling frequent event patterns with a group of symbols. The effectiveness of the proposed method is demonstrated by data from a real drilling project.

关键词： Drilling processes pattern extraction change point detection event sequence generation frequent event pattern

来源：评论

学校读者我要写书评

暂无评论

Continuous Human Learning Optimization with Enhanced Exploitation 7th

Continuous Human Learning Optimization with Enhanced Exploit...

引用

7th International Conference on Life System Modeling and Simulation, LSMS 2021, and the 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021

作者： Wang, Ling Huang, Bowen Wu, Xian Yang, Ruixin Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China Department of Computer Science North Carolina State University RaleighNC United States

ISBN: (纸本)9789811672125

Human Learning Optimization (HLO) is an emerging meta-heuristic with promising potential. Although HLO can be directly applied to real-coded problems as a binary algorithm, the search efficiency may be significantly spoiled due to "the curse of dimensionality". To extend HLO, Continuous HLO (CHLO) is developed to solve real-values problems. However, the research on CHLO is still in its initial stages, and further efforts are needed to exploit the effectiveness of the CHLO. Therefore, this paper proposes a novel continuous human learning optimization with enhanced exploitation (CHLOEE), in which the social learning operator is redesigned to perform global search more efficiently so that the individual learning operator is relieved to focus on performing local search for enhancing the exploitation ability. Finally, the CHLOEE is evaluated on the benchmark problem and compared with CHLO as well as recent state-of-the-art meta-heuristics. The experimental results show that the proposed CHLOEE has better optimization performance. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Actuator Fault Reconstruction for a Class of OSL Nonlinear Systems

Actuator Fault Reconstruction for a Class of OSL Nonlinear S...

引用

International Conference on Sciences and Techniques of Automatic control and computer engineering (STA)

作者： Omar Naifar Hamdi Gassara Mourad Elloumi Assaad Jmal Electrical Engineering Department Control and energy management laboratory (CEM lab) Sfax University Engineering National School Sfax Tunisia Laboratory of Sciences and Technology of Automatic Control and Computer Engineering National School of Engineering of Sfax University of Sfax Sfax Tunisia

ISBN: (纸本)9781665482622

A single study has addressed actuator failure reconstruction for the One-sided Lipschitz (OSL) family of nonlinear systems. The predicted fault vector in that work does not provide any insight into the underlying problematic physical characteristics of the system, which is a significant shortcoming. In this work, we offer a way for estimating the incorrect physical parameters of actuators using an adaptive observer strategy. To demonstrate the utility of the suggested method, a numerical example and simulation research are provided.

关键词： Actuators Adaptation models Additives Computational modeling Observers Numerical models Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Dynamic Parameter Identification based on the Least Squares method for a 6-DOF Manipulator

Dynamic Parameter Identification based on the Least Squares ...

引用

International Conference on System Science and engineering (ICSSE)

作者： Ngoc Thien Nguyen Thi Ngoc Thuy Nguyen Hai Ninh Tong Hoai Vu Anh Truong Duc Thien Tran Automation Control Department Ho Chi Minh City University of Technology and Education Ho Chi Minh City Vietnam Department of Mechanical Engineering Pohang University of Science and Technology (Postech) Gyeongbuk South Korea

Accurate dynamics play crucial roles in designing advanced control algorithms to ensure the feasibility, stability, and efficiency of the system. However, the manipulator is a complex multi-input-multi-output system, and so many system noises seriously affect parameter identification results, thereby the process of determining them is challenging. In order to manage this challenge, a Least Squares (LS) method is proposed to estimate the dynamic parameters. First of all, the kinematics of the system is built according to Denavit-Hartenberg (DH) notation, and the dynamic model is calculated by using Lagrange-Euler equations. After that, the regrouped parameters in the dynamic model are given to the general linear matrix to apply the least squares method for the model. Finally, to demonstrate the effectiveness and reliability of the proposed method, data acquisition is carried out by using a PD controller in simulations via Simscape Multibody/MATLAB Simulink for the dynamic estimate model and the Solidworks robot model. After that, the Root Mean Squared Error (RMSE) formula is used to analyze the accuracy of the LS method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Future of Beyond 5G Sensing: Transforming Activity Recognition with Reconfigurable Intelligent Surfaces

The Future of Beyond 5G Sensing: Transforming Activity Recog...

引用

Activity and Behavior Computing (ABC), International Conference on

作者： Sherief Hashima Hamada Rizk Hirozumi Yamaguchi Computational Learning Theory Team RIKEN-AIP Fukuoka Japan Engineering Dept Egyptian Atomic Energy Authority Cairo Egypt Graduate School of Information Science and Technology Osaka University Suita Japan Computer and Control Engineering Department Tanta University Tanta Egypt

ISBN: (数字)9798350375503

ISBN: (纸本)9798350375510

The advent of Beyond 5G (B5G) and the anticipated arrival of 6G have spurred a remarkable impact on various aspects of human life. Next-generation Human Activity Recognition (HAR) systems are poised to advance healthcare, create smart environments, and enhance overall well-being. The imperative for next-gen HAR systems lies in their capability to be intelligent, privacy-preserving, and deeply accurate. These systems, leveraging the cutting-edge capabilities of B5G and 6G, such as Re-configurable Intelligent Surface (RIS), aim to revolutionize the monitoring process and intelligently discern various human activities. Hence, this paper introduces BSgActiv, a smart RIS-enhanced HAR system. BSgActiv utilizes fractional wavelet transform to effectively highlight time and frequency features of activities from the measured channel state information (CSI) reflected from RIS. Afterward, these features are utilized to train a recurrent neural network that records the temporal characteristics of the input, hence promoting activity recognition. Moreover, BSgActiv integrates diverse modules that enhance the deep model's overall observation and ability to withstand and perform well in the presence of noise. BSgActiv evaluations contain two different realistic scenarios, including both non-line-of-sight and multi-floor setups, proofing its efficacy. Particularly, BSgActiv overcomes benchmark techniques and delivers an activity recognition accuracy of 89.7%.

关键词： 6G mobile communication Wavelet transforms Time-frequency analysis Accuracy 5G mobile communication Reconfigurable intelligent surfaces Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Mdc-Net: Multimodal Defect Captioning Network for Surface Steel Defects

SSRN

引用

SSRN 2024年

作者： Chazhoor, Anthony Ashwin Peter Hu, Shanfeng Gao, Bin Woo, Wai Lok Department of Computer and Information Sciences Northumbria University Newcastle upon TyneNE1 8ST United Kingdom School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

During steel production, ensuring the integrity of the product’s surface is crucialfor maintaining a competitive edge. Detecting surface flaws is a key component inpreserving high standards of production quality, affecting both the end product’sreliability and the efficiency of the manufacturing process. Traditional methodsfor identifying these defects have relied heavily on manual inspection or basiccomputer vision techniques, both of which present a significant challenge in termsof accuracy and the health and safety of the inspectors. This paper explores aninnovative approach by integrating a sequence generation model incorporatingthe transformer architecture, enhancing the detection of defects in the produc-tion of quality hot-rolled steel sheets. This method, which solves object detectionthrough the lens of sequence generation, offers a more intricate analysis of images,enabling a comprehensive examination of surface anomalies along with detailedannotations regarding their nature and precise location. The approach not onlyproposes to increase the accuracy of defect detection but also highlights itsadaptability for broader industrial uses. © 2024, The Authors. All rights reserved.

关键词： Hot rolling

来源：评论

学校读者我要写书评

暂无评论

A Fault-Tolerant Soft/Hard Hybrid control for Fault Diagnosis of Aero-engine Sensors

A Fault-Tolerant Soft/Hard Hybrid Control for Fault Diagnosi...

引用

Chinese control and Decision Conference, CCDC

作者： Hang Yang Tao Sun Xian Du Xi-Ming Sun Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China Department of Automation Tsinghua University Beijing China

In this brief paper, a fault-tolerant soft/hard hybrid control scheme based on the Kalman filter is proposed for fault diagnosis of aero-engine sensors. The designed soft fault diagnosis system, in particular, can detect whether a fault exists by residual processing sensor measurement values and a set of Kalman filter estimation values and summing their weighted squares to compare the known thresholds. In addition, to determine whether there is a fault, the developed hard fault diagnosis system compares the residual absolute value of the sensor measurement value and the estimated value of a Kalman filter with the known threshold value. Finally, some numerical simulations of the fault of the low-pressure rotor speed sensor of an aero-engine are performed to validate the proposed method's feasibility and fault tolerance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Formation control for Multi-Agent Systems for Event-Trigger-Based Variable Gain controllers

A Formation Control for Multi-Agent Systems for Event-Trigge...

引用

Annual Conference of Industrial Electronics Society

作者： Daiki Asada Takuya Nakagawa Yoshikatsu Hoshi Hidetoshi Oya Shunya Nagai Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan The Department of Computer Science Tokyo City University Tokyo Japan Department of Electronics and Control Engineering National Institute of Technology (KOSEN) Niihama College Ehime Japan

This paper deals with a design problem for a new event-trigger-based variable gain controller which achieves consensus for multi-agent systems (MASs) with the leader-follower structure. The proposed variable gain controller consists of stabilizing state feedback laws, state feedback inputs for consensus, and compensation inputs with adjustable parameters, and is designed by taking relative positions into account explicitly. In this paper, we show that sufficient conditions for the existence of the proposed formation control system are given in terms of Linear Matrix Inequalities (LMIs).

关键词：

来源：评论

学校读者我要写书评

暂无评论

SG-Transunet: A segmentation-guided Transformer U-Net model for KRAS gene mutation status identification in colorectal cancer

引用

computers in Biology and Medicine 2024年 173卷 108293-108293页

作者： Ma, Yulan Guo, Yuzhu Cui, Weigang Liu, Jingyu Li, Yang Wang, Yingsen Qiang, Yan Department of Automation Science and Electrical Engineering Beihang University Beijing100191 China School of Engineering Medicine Beihang University Beijing100191 China School of Medical Technology Beijing Institute of Technology Beijing100081 China School of Software North University of China Taiyuan China College of Computer Science and Technology Taiyuan University of Technology Taiyuan China

Accurately identifying the Kirsten rat sarcoma virus (KRAS) gene mutation status in colorectal cancer (CRC) patients can assist doctors in deciding whether to use specific targeted drugs for treatment. Although deep learning methods are popular, they are often affected by redundant features from non-lesion areas. Moreover, existing methods commonly extract spatial features from imaging data, which neglect important frequency domain features and may degrade the performance of KRAS gene mutation status identification. To address this deficiency, we propose a segmentation-guided Transformer U-Net (SG-Transunet) model for KRAS gene mutation status identification in CRC. Integrating the strength of convolutional neural networks (CNNs) and Transformers, SG-Transunet offers a unique approach for both lesion segmentation and KRAS mutation status identification. Specifically, for precise lesion localization, we employ an encoder–decoder to obtain segmentation results and guide the KRAS gene mutation status identification task. Subsequently, a frequency domain supplement block is designed to capture frequency domain features, integrating it with high-level spatial features extracted in the encoding path to derive advanced spatial-frequency domain features. Furthermore, we introduce a pre-trained Xception block to mitigate the risk of overfitting associated with small-scale datasets. Following this, an aggregate attention module is devised to consolidate spatial-frequency domain features with global information extracted by the Transformer at shallow and deep levels, thereby enhancing feature discriminability. Finally, we propose a mutual-constrained loss function that simultaneously constrains the segmentation mask acquisition and gene status identification process. Experimental results demonstrate the superior performance of SG-Transunet over state-of-the-art methods in discriminating KRAS gene mutation status. © 2024

关键词： Aggregates

来源：评论

学校读者我要写书评

暂无评论

Comparison of Deep Learning Models for Body Cavity Fluid Cytology Images Classification

Comparison of Deep Learning Models for Body Cavity Fluid Cyt...

引用

Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), International Conference on

作者： Murat UÇAn Buket Kaya Mehmet Kaya Department of Computer Technologies Dicle University Diyarbakır Turkey Department of Electronics and Automation Firat University Elazığ Turkey Department of Computer Engineering Firat University Elazığ Turkey

ISBN: (纸本)9781665490597

Disease detection is successfully performed in many medical fields using medical images and deep learning architectures. Deep learning architectures used in many fields such as brain images, gastroenterological images and chest x-rays support doctors in the detection of diseases. By using deep learning architectures, diseases can be detected more accurately and faster. With faster detection of diseases, treatment can be started more quickly. Early and accurate diagnosis of cytology images is also very important. After the cytology samples are taken from the patients in general health screenings, they should be interpreted by specialist doctors. The aim of this study is to detect benign and malignant cells from cytology images quickly and accurately. In this study, the Body Cavity Fluid Cytology Images dataset, which includes the data of a total of 21 patients with 14 malignant and 7 benign samples, was used. The dataset contains 693 images of 256x192 size. The images in the dataset are trained using the still popular ResNet50, GoogleNet and AlexNet classification architectures. The classification results obtained were compared with other studies using the same data set. As a result of the test processes, AlexNet architecture achieved 97.26%, GoogleNet architecture 98.12% and ResNet50 architecture 99.13% classification accuracy. The ResNet50 architecture with the best classification result achieved 99.25% specificity, 98.75% sensitivity and 99.13% accuracy. Training and testing in this study showed that the ResNet50 architecture classifies cytology images most successfully.

关键词： Training Sensitivity Fluids Medical services Data models Classification algorithms Medical diagnostic imaging

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：