检索结果-内蒙古大学图书馆

Probabilistic global maps of crop-specific areas from 1961 to 2014

ENVIRONMENTAL RESEARCH LETTERS 2019年第9期14卷 094023-094023页

作者： Jackson, Nicole D. Konar, Megan Debaere, Peter Estes, Lyndon Univ Illinois Dept Civil & Environm Engn Urbana IL 61801 USA Univ Virginia Darden Sch Business Charlottesville VA 22903 USA Clark Univ Grad Sch Geog Worcester MA 01610 USA

Agriculture has substantial socioeconomic and environmental impacts that vary between crops. However, information on how the spatial distribution of specific crops has changed over time across the globe is relatively sparse. We introduce the Probabilistic Cropland Allocation Model (PCAM), a novel algorithm to estimate where specific crops have likely been grown over time. Specifically, PCAM downscales annual and national-scale data on the crop-specific area harvested of 17 major crops to a global 0.5-degree grid from 1961 to 2014. To do this, pixels are assigned into probability clusters based upon crop-specific pixel suitability (based on mean climate and soil characteristics) and gridded historical agricultural areas. PCAM maps compare relatively well with an existing gridded dataset of crop-specific areas circa 2000 (simple matching coefficient value >0.8 for all crops). PCAM estimates compare less well with time series county-level agricultural census data for the United States. Importantly, deviations between census data and PCAM benchmark estimates (driven by soil and climate suitability) can be used to infer the importance of other factors of agricultural production (e.g. labor, agricultural policy, extreme climate) in future work. Our results provide new insights into the likely changes in the spatial distribution of major crops over the past half-century.

关键词： algorithm development global gridded probabilistic allocation crop suitability agricultural geography time series

来源：评论

学校读者我要写书评

暂无评论

Process and alarm data integration under a two-stage Bayesian framework for fault diagnostics

引用

IFAC-PapersOnLine 2018年第24期51卷 1220-1226页

作者： Stief, Anna Ottewill, James R. Tan, Ruomu Cao, Yi ABB Corporate Research Center ul. Starowislna 13a Krakow31-038 Poland School of Water Energy and Environment Cranfield University CranfieldUK MK43 0AL United Kingdom College of Chemical and Biological Engineering Zhejiang University Hangzhou310027 China

Process and alarm data are usually available from industrial processes. It is common practice to use process data for process monitoring and diagnostics. In contrast, alarm data is typically used to determine the instantaneous health state of the process, often as part of a protection system. Alarm data is also used in alarm management systems and for alarm flood detection. Despite the fact that both data types perform similar, although not identical, functions in process monitoring, they are rarely used in combination. One of the main reasons for this is that the fusion between alarm and process data is not trivial: process data is sampled continually and is numerical, while alarm data is binary and appears at discrete times. The two data sources can contain complimentary information regarding the health state of the process, therefore their fusion is a promising direction for fault diagnostics algorithm development. A two-stage Bayesian framework is proposed to fuse alarm and process data on the decision level for fault diagnostics targeting industrial processes. Instead of the raw process data, the principal components of the process variables are used as the inputs of a naïve Bayes classifier. This step reduces the correlation between the process variables and reduces the dimension of the data. The alarm history is transformed into binary alarm features and input to a second, separate naïve Bayes classifier. The second stage of the method fuses the local classification results of the alarm and process data and provides the final classification result. The results show that the overall performance of the method fusing alarm and process data is superior when compared to the results of a similar single stage method using either alarm or process data. © 2018

关键词： Alarm systems Data fusion Data integration Fault detection Information management Plasma diagnostics Process control Process monitoring Alarms algorithm development Bayes method Classification results In process monitoring Industrial processs Principal Components Process monitoring and diagnostic

来源：评论

学校读者我要写书评

暂无评论

Simulation As A Tool In Designing And Evaluating A Robotic Apple Harvesting System

引用

IFAC-PapersOnLine 2018年第17期51卷 135-140页

作者： Wang, Heng Hohimer, Cameron J. Bhusal, Santosh Karkee, Manoj Mo, Changki Miller, John H. Washington State University Tri-Cities 2710 Crimson Way RichlandWA99354 United States Washington State University 24106 N. Bunn Rd ProsserWA99350 United States

During the past several years, significant effort has been made to develop a robotic system to harvest fresh market apples in a modern apple orchard at Washington State University (WSU). This system has gone through several modifications to achieve enhanced system accuracy, speed, robustness, and reduction of fruit damage and cost. However, due to the short window of apple picking each year and the challenging environment of the orchard, those modifications had limited success in improving the robotic systems performance even with extensive laboratory testing before each field trial. To further assess potential problems, better prepare for the field trial, and make best use of the limited time in the field, in silico testing is necessary in addition to laboratory testing. In this work, computer modeling and simulation were used to help identify potential problem in the robotic system, evaluate the effectiveness of the newly made modifications, and aid in both algorithm development and configuration design of the system. By doing simulations with field study data and workspace analysis of the system, we developed a novel algorithm to improve the reachability of the picking arm. We also concluded that the overlap of the arm's workspace and the fruit space is the key in deciding the reachability of the manipulator instead of the volume of arm's workspace. © 2018

关键词： Fruits algorithms Computer simulation Orchards Robotics Agricultural robot algorithm development Computer modeling and simulation Configuration designs Laboratory testing Potential problems Washington State University Workspace analysis

来源：评论

学校读者我要写书评

暂无评论

Estimating CDOM Concentration in Highly Turbid Estuarine Coastal Waters

引用

JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS 2018年第8期123卷 5856-5873页

作者： Zhao, Jun Cao, Wenxi Xu, Zhantang Ai, Bin Yang, Yuezhong Jin, Guangzhen Wang, Guifen Zhou, Wen Chen, Yong Chen, Haiyun Sun, Zhaohua Sun Yat Sen Univ Sch Marine Sci Guangzhou Guangdong Peoples R China Chinese Acad Sci South China Sea Inst Oceanol State Key Lab Trop Oceanog Guangzhou Guangdong Peoples R China Hohai Univ Coll Oceanog Nanjing Jiangsu Peoples R China Chinese Acad Sci South China Sea Inst Oceanol Key Lab Ocean & Marginal Sea Geol Guangzhou Guangdong Peoples R China

We proposed a support vector machine (SVM) algorithm to retrieve colored dissolved organic matter (CDOM) concentration (using a(g)(443) as a proxy) in the highly turbid Pearl River estuary. Two band ratios, namely, R-rs(443)/R-rs(547) and R-rs(488)/R-rs(547), were used as inputs. Comparisons between the estimated and measured a(g)(443) illustrated high accuracy of the SVM algorithm, yielding R(2)s of 0.98 and 0.89, mean absolute percentage errors of 5.18% and 13.1%, and root-mean-square deviations of 0.012 and 0.034m(-1) for the training and validation data sets, respectively. The SVM algorithm was also evaluated against existing ones for the study area and gave the best accuracy with a R-2 of 0.9, a mean absolute percentage error of 10.23%, and a root-mean-square deviation of 0.025m(-1). The diurnal dynamics of CDOM in the Pearl River estuary was revealed showing complicated variations and influenced by the combined effects of wind, tide, circulation, and river discharge. As for remote sensing applications, the SVM-based CDOM product exhibited great potential to trace the Pearl River plume and the satellite-derived plume area agreed well with the FVCOM model simulation result. SVM is an accurate and fast tool for retrieving CDOM concentration, especially in highly turbid estuarine coastal waters, and thus, river plume dynamics can be traced. Plain Language Summary Colored dissolved organic matter is an important optically active component in the water column. Together with others, it determines the water color. In this study, we developed an algorithm to retrieve colored dissolved organic matter from remote sensing measurements in the turbid Pearl River estuary. The algorithm performs with high accuracy and outcompetes existing ones. Based on the algorithm, the diurnal dynamics of colored dissolved organic matter and the forcing factors were analyzed. The algorithm was also applied to a satellite scene. The characteristics of the Pearl River plume were elucidated.

关键词： CDOM remote sensing turbid coastal waters algorithm development SVM FVCOM

来源：评论

学校读者我要写书评

暂无评论

Analytics of Heterogeneous Process Data: Multiphase Flow Facility Case Study

引用

IFAC-PapersOnLine 2018年第18期51卷 363-368页

作者： Stief, Anna Tan, Ruomu Cao, Yi Ottewill, James R. ABB Corporate Research Center ul. Starowislna 13a Krakow31-038 Poland School of Water Energy and Environment Cranfield University CranfieldMK43 0AL United Kingdom College of Chemical and Biological Engineering Zhejiang University Hangzhou310027 China

Improvements in sensing, connectivity and computing technologies mean that industrial processes now generate a vast amount of data from a variety of disparate sources. Data may take a number of different forms, from different time-domain signals, sampled at different rates using various types of sensors, through to more disparate sources such as alarm and event logs. New process and condition monitoring techniques are needed to be developed to tackle the new challenges of big and heterogeneous data. Although there are a few publicly available benchmark studies, e.g. the Tennessee Eastman process plant (Ricker, 1995), a multiphase flow benchmark case for statistical process monitoring (Ruiz-Cárcel et al., 2015), they provide only standard process data. This work presents a benchmark case on an industrial scale multiphase flow facility. Various operational conditions were tested under normal operating modes as well as with seeded faults. Heterogeneous data was collected from various sources, including process data, alarm data and high frequency ultrasonic and pressure data. Two different fault detection algorithms are applied to the data, a multivariate PCA-enhanced Canonical Variate Analysis (CVA) and a probabilistic Bayesian method. This benchmark case study with data from disparate sources can be used for algorithm development and validation for fault detection, fault identification, fault classification, fault severity detection, monitoring of fault evolution and prognostics. © 2018

关键词： Fault detection Bayesian networks Condition monitoring Data Analytics Experiments Multiphase flow Process monitoring Statistical process control Time domain analysis Ultrasonic applications algorithm development Benchmark case studies Canonical variate analysis Fault detection algorithm Operational conditions Process and condition monitoring Statistical process monitoring Tennessee Eastman process

来源：评论

学校读者我要写书评

暂无评论

Machine-learning for biopharmaceutical batch process monitoring with limited data

引用

IFAC-PapersOnLine 2018年第18期51卷 126-131页

作者： Tulsyan, Aditya Garvin, Christopher Undey, Cenk Digital Integration & Predictive Technologies Amgen Inc. 360 Binney Street CambridgeMA02141 United States Digital Integration & Predictive Technologies Amgen Inc. 40 Technology Way West GreenwichRI02817 United States Digital Integration & Predictive Technologies Amgen Inc. One Amgen Center Drive Thousand OaksCA91320 United States

Commercial biopharmaceutical manufacturing comprises of multiple distinct processing steps that require effective and efficient monitoring of many variables simultaneously in real-time. This article addresses the problem of real-time statistical batch process monitoring (BPM) for biopharmaceutical processes with limited production history; herein, referred to as the ‘Low-N’ problem. In this article, we propose an approach to transition from a Low-N scenario to a Large-N scenario by generating an arbitrarily large number of in silico batch data sets. The proposed method is a combination of hardware exploitation and algorithm development. To this effect, we propose a Bayesian non-parametric approach to model a batch process, and then use probabilistic programming to generate an arbitrarily large number of dynamic in silico campaign data sets. The efficacy of the proposed solution is elucidated on an industrial process. © 2018

关键词： Batch data processing Learning systems Process control Process monitoring algorithm development Batch process monitoring Efficient monitoring Industrial processs Low N problem Nonparametric approaches Probabilistic programming Statistical batch process monitoring

来源：评论

学校读者我要写书评

暂无评论

Evaluation of ECG algorithms designed to improve detect of transient myocardial ischemia to minimize false alarms in patients with suspected acute coronary syndrome

引用

JOURNAL OF ELECTROCARDIOLOGY 2018年第2期51卷 288-295页

作者： Pelter, Michele M. Xu, Yuan Fidler, Richard Xiao, Ran Mortara, David W. Hu, Xiao Univ Calif San Francisco Dept Physiol Nursing 2 Koret Way San Francisco CA 94143 USA

Background: Patients hospitalized for suspected acute coronary syndrome (ACS) are at risk for transient myocardial ischemia. During the "rule-out" phase, continuous ECG ST-segment monitoring can identify transient myocardial ischemia, even when asymptomatic. However, current ST-segment monitoring software is vastly underutilized due to false positive alarms, with resultant alarm fatigue. Current ST algorithms may contribute to alarm fatigue because;(I) they are not designed with a delay (minutes), rather alarm to brief spikes (i.e., turning, heart rate changes), and (2) alarm to changes in a single ECG lead, rather than contiguous leads. Purpose: This study was designed to determine sensitivity, and specificity, of ST algorithms when accounting for;ST magnitude (100 mu V vs 200 mu V), duration, and changes in contiguous ECG leads (i.e., aVL, I, aVR, II, aVF, III;V1, V2, V3, V4, V5, V6, V6, I). Methods: This was a secondary analysis from the COMPARE Study, which assessed occurrence rates for transient myocardial ischemia in hospitalized patients with suspected ACS using 12-lead Holter. Transient myocardial ischemia was identified from Holter using >100 mu V ST-segment up arrow or down arrow, in >1 ECG lead, > I min. algorithms tested against Holter transient myocardial ischemia were done using the University of California San Francisco (UCSF) ECG algorithm and included: (1)100 mu V vs 200 mu V any lead during a 5-min ST average;(2)100 mu V vs 200 mu V any lead >5 min, (3) 100 mu V vs 200 mu V any lead during a 5-min ST average in contiguous leads, and (4) 100 mu V vs 200 mu V > 5 min in contiguous leads (Table below). Results: In 361 patients;mean age 63 + 12 years, 63% male, 56% prior CAD, 43 (11%) had transient myocardial ischemia. Of the 43 patients with transient myocardial ischemia, 17 (40%) had ST-segment elevation events, and 26 (60%) ST-segment depression events. A higher proportion of patients with ST segment depression has missed ischemic events. [GRAPHICS]

关键词： Myocardial Ischemia ST Monitoring Acute Coronary Syndrome algorithm development Hospital ECG Monitoring

来源：评论

学校读者我要写书评

暂无评论

Special Section Guest Editorial: Quantitative Imaging and the Pioneering Efforts of Laurence P. Clarke

引用

Journal of Medical Imaging 2018年第1期5卷 011001页

作者： Nordstrom, Robert J. National Cancer Institute Image Guided Interventions Cancer Imaging Program Division of Cancer Treatment and Diagnosis United States

This guest editorial introduces the Special Section honoring Dr. Laurence P. Clarke.

关键词： Cancer Medical imaging Databases Clinical trials Diagnostics Information science Oncology Software development algorithm development Image analysis

来源：评论

学校读者我要写书评

暂无评论

Adaptive smoothing algorithms for MBIR in CT applications 15

Adaptive smoothing algorithms for MBIR in CT applications

引用

15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine

作者： Xu, Jingyan Noo, Frederic Johns Hopkins Univ Baltimore MD 21218 USA Univ Utah Salt Lake City UT USA

ISBN: (数字)9781510628380

ISBN: (纸本)9781510628380

Many model based image reconstruction (MBIR) methods for x-ray CT are formulated as convex minimization problems. If the objective function is nonsmooth. primal-dual algorithms are applicable with the drawback that there is an increased memory cost due to the dual variables. Some algorithms recently developed for large-scale nonsmooth convex programs use adaptive smoothing techniques and are of the primal type. That is, they achieve convergence without introducing the dual variables, hence without the increased memory. We discuss one such algorithm with an O(1/k) convergence rate, where k is the iteration number. We then present an extension of it to handle strong convex objective functions. This new algorithm has the optimal convergence rate of O(1/k(2)) for its problem class. Our preliminary numerical studies demonstrate competitive performance with respect to an alternative method.

关键词： Reconstruction algorithms algorithm development Image restoration Computer programming Control systems CT reconstruction Performance modeling computer programming Reconstruction algorithm image restoration technique control systems computer programs PERFORMANCE MODELING smoothing Objective function X-Ray Computed Tomography Converge Convexity algorithms

来源：评论

学校读者我要写书评

暂无评论

A semiautomatic algorithm for three-dimensional segmentation of the prostate on CT images using shape and local texture characteristics

A semiautomatic algorithm for three-dimensional segmentation...

引用

Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Shahedi, Maysam Ma, Ling Halicek, Martin Guo, Rongrong Zhang, Guoyi Schuster, David M. Nieh, Peter Master, Viraj Fei, Baowei Emory Univ Dept Radiol & Imaging Sci Atlanta GA 30322 USA Georgia Inst Technol Wallace H Coulter Dept Biomed Engn Atlanta GA 30332 USA Emory Univ Atlanta GA 30322 USA Emory Univ Dept Urol Atlanta GA 30322 USA Emory Univ Winship Canc Inst Atlanta GA 30322 USA

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

Prostate segmentation in computed tomography (CT) images is useful for planning and guidance of the diagnostic and therapeutic procedures. However, the low soft-tissue contrast of CT images makes the manual prostate segmentation a time-consuming task with high inter-observer variation. We developed a semi-automatic, three-dimensional (3D) prostate segmentation algorithm using shape and texture analysis and have evaluated the method against manual reference segmentations. In a training data set we defined an inter-subject correspondence between surface points in the spherical coordinate system. We applied this correspondence to model the globular and smoothly curved shape of the prostate with 86, well-distributed surface points using a point distribution model that captures prostate shape variation. We also studied the local texture difference between prostate and non-prostate tissues close to the prostate surface. For segmentation, we used the learned shape and texture characteristics of the prostate in CT images and we used a set of user inputs for prostate localization. We trained our algorithm using 23 CT images and tested it on 10 images. We evaluated the results compared with those of two experts' manual reference segmentations using different error metrics. The average measured Dice similarity coefficient (DSC) and mean absolute distance (MAD) were 88 +/- 2% and 1.9 +/- 0.5 mm, respectively. The averaged inter-expert difference measured on the same dataset was 91 +/- 4% (DSC) and 1.3 +/- 0.6 mm (MAD). With no prior intra-patient information, the proposed algorithm showed a fast, robust and accurate performance for 3D CT segmentation.

关键词： Image segmentation Prostate Computed tomography Image processing algorithms and systems 3D image processing 3D modeling algorithm development Cancer Shape analysis

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：