检索结果-内蒙古大学图书馆

IEEE International Symposium on Systems Engineering (ISSE)

作者： R. Pirani J. Cale Department of Systems Engineering Colorado State University Fort Collins CO USA

This paper introduces an approach for pre-screening manufactured batteries before system deployment, with the goal of reducing higher lifecycle maintenance costs attributed to failure-prone batteries. The method employs a pattern recognition algorithm for classifying parts for acceptance or rejection. The paper describes the classification algorithm and demonstrates its performance on example pre-acceptance test data. Using an example system maintenance concept, the economic and operational impacts of the classification are also demonstrated.

关键词： battery management systems cost reduction failure analysis maintenance engineering pattern classification power engineering computing reliability secondary cells Battery management systems Power engineering computing Secondary batteries Maintenance engineering Batteries pattern recognition COST REDUCTION FAILURE ANALYSIS Sorting algorithm Life cycle pattern recognition method pictorial pattern recognition algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of the Data on the Lithospheric Magnetic Anomalies in the Problem of Recognizing the Earthquake Prone Areas

引用

IZVESTIYA-PHYSICS OF THE SOLID EARTH 2016年第6期52卷 803-809页

作者： Soloviev, Alexander A. Gorshkov, A. I. Soloviev, Anatoly A. Russian Acad Sci Inst Earthquake Predict Theory & Math Geophys Ul Profsoyuznaya 84-32 Moscow 117997 Russia Russian Acad Sci Geophys Ctr Ul Molodezhnaya 3 Moscow 119296 Russia Russian Acad Sci Schmidt Inst Phys Earth Ul B Gruzinskaya 10 Moscow 123995 Russia

For the first time, an attempt is made to apply the data on the lithospheric magnetic anomalies of the Earth for determining the areas prone to strong earthquakes by means of the pattern recognition algorithms. The Caucasian region with the threshold magnitude of the strong earthquakes M-0 = 6 is considered. It is established that the data on the lithospheric magnetic anomalies are informative from the standpoint of recognizing the strong earthquake prone areas. Application of these data is promising for solving the similar problems for different seismically active regions.

关键词： MAGNETIC ANOMALIES Earth topsoil pictorial pattern recognition algorithm Earthquakes

来源：评论

学校读者我要写书评

暂无评论

A Star pattern recognition algorithm for the Double-FOV Star Sensor

引用

IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE 2015年第8期30卷 24-31页

作者： Li, Baohua Sun, Qi Zhang, Tongshuang Harbin Inst Technol Harbin 150001 Heilongjiang Peoples R China China Satellite Maritime Tracking & Controlling D Jiangyin Peoples R China

A reliable attitude determination system is critical to the success of spacecrafts [1]-[3]. As high accuracy and high reliability devices, star sensors play an important role in attitude determination for satellites [4]-[6]. Based on the star images sampled by star sensors, the locations of the star image in the star sensor coordinate system can be identified with identification algorithms. With the help of the coordinates of the star images in the field of view (FOV), a three-axis attitude of the star sensor in the inertial coordinate can be calculated and then the attitude of the satellites can be calculated through coordinate transforming. However, the star pattern recognition algorithm is the most important for attitude determination of star sensors. The probability of success and the time to identify stars of the star pattern recognition algorithm are the key factors for star sensors [7].

关键词： star sensors A STARS pictorial pattern recognition algorithm pattern recognition

来源：评论

学校读者我要写书评

暂无评论

The Ninapro Database: a Resource for sEMG Naturally Controlled Robotic Hand Prosthetics 37

The Ninapro Database: a Resource for sEMG Naturally Controll...

引用

37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Atzori, Manfredo Mueller, Henning Univ Appl Sci Western Switzerland Inst Informat Syst CH-3960 Sierre Switzerland

ISBN: (纸本)9781424492701

The dexterous natural control of robotic prosthetic hands with non-invasive techniques is still a challenge: surface electromyography gives some control capabilities but these are limited, often not natural and require long training times;the application of pattern recognition techniques recently started to be applied in practice. While results in the scientific literature are promising they have to be improved to reach the real needs. The Ninapro database aims to improve the field of naturally controlled robotic hand prosthetics by permitting to worldwide research groups to develop and test movement recognition and force control algorithms on a benchmark database. Currently, the Ninapro database includes data from 67 intact subjects and 11 amputated subject performing approximately 50 different movements. The data are aimed at permitting the study of the relationships between surface electromyography, kinematics and dynamics. The Ninapro acquisition protocol was created in order to be easy to be reproduced. Currently, the number of datasets included in the database is increasing thanks to the collaboration of several research groups.

关键词： electromyography medical robotics medical signal processing pattern recognition prosthetics Ninapro acquisition protocol Ninapro database benchmark database dexterous natural control force control algorithms noninvasive techniques pattern recognition techniques robotic prosthetic hands sEMG sEMG naturally controlled robotic hand prosthetics Databases Electrodes Electromyography Kinematics Prosthetics Protocols Robots Prosthesis Electromyogram SEMA5B gene Database medical robotics medical signal processing pictorial pattern recognition algorithm pattern recognition kinematics Robot protocols Electrodes robotic hand

来源：评论

学校读者我要写书评

暂无评论

Classification and pattern recognition algorithms applied to E-Nose

Classification and pattern recognition algorithms applied to...

引用

International Conference on Electrical Information and Communication Technology (EICT)

作者： Md. Mizanur Rahman Chalie Charoenlarpnopparut Prapun Suksompong Electronics and Communication Engineering Khulna University Khulna Bangladesh Electronics and Communication Engineering SIIT Thammasat University Pathum Thani Thailand

Electronic noses (E-Nose) are seen to be good substitute to human or animal nose for food, and fruit quality identification. It is also used for explosive and chemical identification. We have generated typical E-Nose data to compare the existing algorithms in terms of training, and testing/validation. We have observed that k-nearest neighbor (k-NN) algorithm, support vector machine (SVM) machine learning algorithms; and radial basis function (RBF), and generalized regression neural networks (GRNNs) shows good odor detection performance. In terms of speed GRNN tops compared to other methods.

关键词： LDA PCA RBF VOC electronic nose Electronic Nose Volatile Organic Compounds laser Doppler anemometry Anterior interventricular branch of left coronary artery Left-sided displacement of abomasum principal components analysis Passive Cutaneous Anaphylaxis General regression neural networks pictorial pattern recognition algorithm EXPLOSIVES

来源：评论

学校读者我要写书评

暂无评论

Processing of Surface EMG Through pattern recognition Techniques Aimed at Classifying Shoulder Joint Movements

Processing of Surface EMG Through Pattern Recognition Techni...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Diletta Rivela Alessia Scannella Esteban E. Pavan Carlo A. Frigo Paolo Belluco Giuseppina Gini Dipartimento di Elettronica Informazione e Bioingegneria Politécnico di Milano 1-20133 Milan Italy Movement Biomechanics and Motor Control Laboratory Politecnico di Milano 1-20133 Milan Italy B10nix 1-20131 Milan Italy Artificial Intelligence and Robotics Laboratory Politecnico di Milano 1-20133 Milan Italy

ISBN: (纸本)9781424492695

Artificial arms for shoulder disarticulation need a high number of degrees of freedom to be controlled. In order to control a prosthetic shoulder joint, an intention detection system based on surface electromyography (sEMG) pattern recognition methods was proposed and experimentally investigated. Signals from eight trunk muscles that are generally preserved after shoulder disarticulation were recorded from a group of eight normal subjects in nine shoulder positions. After data segmentation, four different features were extracted (sample entropy, cepstral coefficients of the 4th order, root mean square and waveform length) and classified by means of linear discriminant analysis. The classification accuracy was 92.1% and this performance reached 97.9% after reducing the positions considered to five classes. To reduce the computational cost, the two channels with the least discriminating information were neglected yielding to a classification accuracy diminished by just 4.08%.

关键词： sEMG reduce computational SEMA5B gene Surface Electromyography Muscle of trunk Root mean square Shoulder Joint Disarticulation Shoulder pictorial pattern recognition algorithm Normal subjects

来源：评论

学校读者我要写书评

暂无评论

Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms

引用

INTERNATIONAL JOURNAL OF REMOTE SENSING 2014年第10期35卷 3427-3439页

作者： Liaghat, Shohreh Ehsani, Reza Mansor, Shattri Shafri, Helmi Z. M. Meon, Sariah Sankaran, Sindhuja Azam, Siti H. M. N. Univ Putra Malaysia UPM Dept Civil Engn Fac Engn Serdang 43400 Selangor Malaysia Univ Florida IFAS Citrus Res & Educ Ctr Lake Alfred FL 33850 USA Univ Putra Malaysia UPM Fac Agr Dept Plant Protect Serdang 43400 Selangor Malaysia Washington State Univ Dept Biol Syst Engn Pullman WA 99164 USA Sime Darby Res Sdn Plant Protect R&D Plantat Banting 42700 Selangor Malaysia

Basal stem rot (BSR) is a fatal fungal (Ganoderma) disease of oil palm plantations and has a significant impact on the production of palm oil in Malaysia. Because there is no effective treatment to control this disease, early detection of BSR is vital for sustainable disease management. The limitations of visual detection have led to an interest in the development of spectroscopically based detection techniques for rapid diagnosis of this disease. The aim of this work was to develop a procedure for early and accurate detection and differentiation of Ganoderma disease with different severities, based on spectral analysis and statistical models. Reflectance spectroscopy analysis ranging from the visible to near infrared region (325-1075nm) was applied to analyse oil palm leaf samples of 47 healthy (G0), 55 slightly damaged (G1), 48 moderately damaged (G2), and 40 heavily damaged (G3) trees in order to detect and quantify Ganoderma disease at different levels of severity. Reflectance spectra were pre-processed, and principal component analysis (PCA) was performed on different pre-processed datasets including the raw dataset, first derivative, and second derivative datasets. The classification models: linear and quadratic discrimination analysis, k-nearest neighbour (kNN), and Naive-Bayes were applied to PC scores for classifying four levels of stress in BSR-infected oil palm trees. The analysis showed that the kNN-based model predicted the disease with a high average overall classification accuracy of 97% with the second derivative dataset. Results confirmed the usefulness and efficiency of the spectrally based classification approach in rapid screening of BSR in oil palm.

关键词： Early Diagnosis rapid diagnosis Second derivative Oil palm trees Dataset palm oil maladjustment Visual inspection Elaeis guineensis Ganoderma Stem rot oil palm plantations inspection technique pictorial pattern recognition algorithm

来源：评论

学校读者我要写书评

暂无评论

The Ninapro Database: a Resource for sEMG Naturally Controlled Robotic Hand Prosthetics

The Ninapro Database: a Resource for sEMG Naturally Controll...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Manfredo Atzori Henning Müller the Institute of Information Systems University of Applied Sciences Western Switzerland Sierre 3960 Switzerland

ISBN: (纸本)9781424492695

关键词： sEMG Ninapro acquisition protocol dexterous natural control SEMA5B gene pictorial pattern recognition algorithm Database robotic hand Prosthesis Prosthetic hand Surface Electromyography

来源：评论

学校读者我要写书评

暂无评论

Effects of Prosthesis Use on the Capability to Control Myoelectric Robotic Prosthetic Hands

Effects of Prosthesis Use on the Capability to Control Myoel...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Manfredo Atzori Anne-Gabrielle Mittaz Hager Simone Elsig Giorgio Giatsidis Franco Bassetto Henning Müller the Institute of Information Systems University of Applied Sciences Western Switzerland Sierre 3960 Switzerland the School of Health Sciences Physiotherapy University of Applied Sciences Western Switzerland Leukerbad 3954 Switzerland the Clinic of Plastic Surgery Padova University Hospital 35128 Padova Italy

ISBN: (纸本)9781424492695

The natural control of robotic prosthetic hands with non-invasive techniques is still a challenge: myoelectric prostheses currently give some control capabilities;the application of pattern recognition techniques is promising and recently started to be applied in practice but still many questions are open in the field. In particular, the effects of clinical factors on movement classification accuracy and the capability to control myoelectric prosthetic hands are analyzed in very few studies. The effect of regularly using prostheses on movement classification accuracy has been previously studied, showing differences between users of myoelectric and cosmetic prostheses. In this paper we compare users of myoelectric and body-powered prostheses and intact subjects. 36 machine-learning methods are applied on 6 amputees and 40 intact subjects performing 40 movements. Then, statistical analyses are performed in order to highlight significant differences between the groups of subjects. The statistical analyses do not show significant differences between the two groups of amputees, while significant differences are obtained between amputees and intact subjects. These results constitute new information in the field and suggest new interpretations to previous hypotheses, thus adding precious information towards natural control of robotic prosthetic hands.

关键词： Effects Prosthesis Use Capability to Control Myoelectric Robotic Prosthetic Hands Prosthetic hand biological control Amputees Prosthesis pictorial pattern recognition algorithm Information Field Consumers intact

来源：评论

学校读者我要写书评

暂无评论

Impact of Feature Extraction Techniques on Classification Accuracy for EMG based Ankle Joint Movements

Impact of Feature Extraction Techniques on Classification Ac...

引用

Asian Control Conference

作者： Maged S. Al-Quraishi Asnor J. Ishak Siti A. Ahmad Mohd K. Hasan Electrical and Electronic Engineering Universiti Putra Malaysia

ISBN: (纸本)9781479978632

EMG based control becomes the core of the pros-theses, orthoses and rehabilitation devices in the recent research. Though the difficulties of using EMG as a control signal due to the complexity nature of this signal, the researchers employed the pattern recognition technique to overcome this problem. The EMG pattern recognition mainly consists of four stages;signal detection and preprocessing feature extraction, dimensionality reduction and classification. However, the success of any pattern recognition technique depends on the feature extraction and dimensionality reduction stages. In this paper time domain (TD) with 6th order auto regressive (AR) coefficients features and three techniques of dimensionality reduction;principal component analysis (PCA), uncorrelated linear discriminant analysis (ULDA) and fuzzy neighborhood preserving analysis with QR decomposition (FNPA-QR) were demonstrated. The EMG data were recorded from the below knee muscles of ten intact-subjects. Four ankle joint movements are classified using three classifiers;LDA, k-NN and MLP. The results show the superiority of TD&6th AR with FNPA-QR and k-NN combination with (96.20% ±4.1) accuracy.

关键词： Electromyogram Feature extraction dimensionality reduction pictorial pattern recognition algorithm Ankle Joint pattern recognition signal acquisition Movements

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：