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Flaw identification from time and frequency features of ultrasonic waveforms

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL 1996年第4期43卷 592-600页

作者： Case, TJ Waag, RC UNIV ROCHESTER DEPT ELECT ENGNROCHESTERNY 14627 UNIV ROCHESTER DEPT RADIOLROCHESTERNY 14627

Time and frequency features have been used with classification algorithms to distinguish between ultrasonic echoes from flaws in pipes and ultrasonic echoes from various geometric configurations of weld root and counterbore. Waveforms containing reflections from known geometries and from flaws were obtained and sets of features were defined using a k-nearest neighbor approach to separate waveforms into classes, Two independent databases containing various flaws and pipe geometries were used to determine these feature sets, From these databases, optimal feature sets were found to separate counterbore waveforms from crack waveforms, Optimal feature sets were also found to distinguish between waveforms from counterbore, waveforms containing both counterbore and root echoes, and waveforms from flaws, The best feature sets used with the classifier algorithms could separate waveforms from the same database with accuracy in the 92-97% range and with high confidence, Another database was obtained from pipe structures in a nuclear power plant to provide a field test of the method, When applied to this database, the same classifier algorithms and feature sets used with the other databases either resulted in a comparable percentage of correct decisions, but with low confidence, or could not classify anywhere from 79 to 88% of the waveforms, Spatial parameters based on averaging feature vectors in axial and circumferential directions were also defined and used for classification, These classifications had higher accuracy but lower confidence levels than the classifications based on individual waveforms.

关键词： echo feature extraction flaw detection pattern classification ultrasonic materials testing welding classification algorithms counterbore crack waveforms feature vectors flaw identification frequency features geometric configurations k-nearest neighbor ap sorting algorithm Echoes Eigenvector Test Method ultrasonic materials testing Feature extraction flaws SETTING waveforms Taxonomy Welding Geometric forms Flaw detection Pattern recognition

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Development of a sky imager for cloud cover assessment

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION 2008年第1期25卷 29-39页

作者： Cazorla, A. Olmo, F. J. Alados-Arboledasl, L. Univ Granada Ctr Andaluz Medio Ambiente Grp Fis & Atmosfera E-18071 Granada Spain Univ Granada Fac Ciencias Dept Fis Aplicada E-18071 Granada Spain

Based on a CCD camera, we have developed an in-house sky imager system for the purpose of cloud cover estimation and characterization. The system captures a multispectral image every 5 min, and the analysis is done with a method based on an optimized neural network classification procedure and a genetic algorithm. The method discriminates between clear sky and two cloud classes: opaque and thin clouds. It also divides the image into sectors and finds the percentage of clouds in those different regions. We have validated the classification algorithm on two levels: image level, using the cloud observations included in the METAR register performed at the closest meteorological station, and pixel level, determining whether the final classification is correct. (c) 2007 Optical Society of America.

关键词： sorting algorithm cloud cover Charge Coupled Device camera images imaging instrument sky Clouds Imagery (Psychotherapy) Sectoring

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Design and control of battery charger for electric vehicles using modular multilevel converters

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IET POWER ELECTRONICS 2021年第1期14卷 140-157页

作者： Quraan, Mahran Abu-Khaizaran, Muhammad Sa'ed, Jaser Hashlamoun, Wael Tricoli, Pietro Birzeit Univ Dept Elect & Comp Engn Ramallah Palestine Univ Birmingham Sch Elect Elect & Syst Engn Birmingham W Midlands England

Double-star modular multilevel converters with embedded battery cells are a ground breaking technology for the power converter of electric vehicles. In this topology, the battery cells are connected in series via half bridge DC-DC buck converter and can be independently discharged and recharged. This paper proposes a novel control system for this converter topology that can charge the battery cells from the grid at unity power factor and instantaneously balance them in terms of their state of charges without affecting the grid voltages and currents. The grid current controller is designed and implemented in the stationary reference frame using a proportional-resonant controller, while the state of charge balancing algorithm is designed using sorting algorithm and circulating current control. The simulation and experimental results have demonstrated that the proposed control strategy can effectively charge the battery cells with a negligible distortion of the grid current and can ensure the balance of cells during the recharge without affecting the grid current.

关键词： power converter power factor electric vehicles double-star modular multilevel converters Control of electric power systems novel control system proportional-resonant controller unity power factor control strategy sorting algorithm half bridge DC-DC buck converter embedded battery cells grid voltages Current control DC-DC power convertors power grids Transportation electric current control power convertors charge balancing algorithm circulating current control Power convertors and power supplies to apparatus battery chargers battery charger converter topology grid current controller Power electronics, supply and supervisory circuits

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Modeling a Problem-Solving Approach Through Computational Thinking for Teaching Programming

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IEEE TRANSACTIONS ON EDUCATION 2024年第2期67卷 282-291页

作者： Zebel-Al Tareq Yusof, Raja Jamilah Raja Univ Malaya Fac Comp Sci & Informat Technol Dept Software Engn Kuala Lumpur 50306 Malaysia

Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available;however, being able to formulate an algorithmic solution computationally and then transform it into code is essential for students. Research Questions: What are the effective teaching approaches for fostering the development of problem-solving and programming skills? How do CT concepts contribute to the formulation of a PSA model for programming problems and its translation into an effective teaching method? How can an effective teaching method that utilizes the PSA model be identified and distinguished from other approaches? Methodology: A preliminary study pointed out the difficulties experienced when teaching programming, inspiring the formulation of a PSA model that used CT concepts. An experimental study on problem-based and game-based programming workshops that utilized the PSA model through sorting algorithms was performed on experimental groups consisting of 30 students each. A syntax-based programming workshop consisting of 30 students was used as the control group. All the participants were recruited through a pretest that incorporated basic programming questions. The participants had to answer a posttest after the workshop. Findings: The results showed that the participants exhibited no significant difference between the pretest and posttest for the syntax-based learning (SBL). However, there is a significant difference between the pretest and posttest of both the problem-based learning (PBL) and the game-based learning (GBL) workshops. There was no significant difference significant difference for the pretest scores of all three workshops. The analysis of the posttest further confirmed that the experimental groups (PBL and GBL)

关键词： Programming profession Education Problem-solving sorting Computational modeling Conferences Software algorithms Active learning approach model computational thinking (CT) computer science computing skills game-based learning (GBL) problem-based learning (PBL) problem-solving instructional methods sorting algorithm syntax-based learning (SBL)

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Quicksort asymptotics

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JOURNAL OF algorithmS 2002年第1期44卷 4-28页

作者： Fill, JA Janson, S Johns Hopkins Univ Dept Math Sci Baltimore MD 21218 USA Univ Uppsala Dept Math S-75105 Uppsala Sweden

The number of comparisons X, used by Quicksort to sort an array of it distinct numbers has mean mu(n) of order n log n and standard deviation of order it. Using different methods, Regnier and Rosler each showed that the normalized variate Y-n := (X-n - mu(n))/n converges in distribution, say to Y;the distribution of Y can be characterized as the unique fixed point with zero mean of a certain distributional trans formal ion. We provide the first rates of convergence for the distribution of Y-n to that of F, using various metrics. In particular, we establish the bound 2n(-1/2) in the d(2)-metric, and the rate O(n(epsilon-(1/2))) for Kolmogorov-Smirnov distance, for any positive (C) 2002 Elsevier Science (USA). All rights reserved.

关键词： Quicksort sorting algorithm asymptotics limit distribution rate of convergence Kolmogorov-Smirnov distance density moment generating function numerical analysis d(p)-metric coupling

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DEVELOPMENT OF A FIELD-PORTABLE IMAGING-SYSTEM FOR SCENE CLASSIFICATION USING MULTISPECTRAL DATA FUSION algorithmS

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IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE 1994年第9期9卷 13-19页

作者： PRESTON, E BERGMAN, T GORENFLO, R HERMANN, D KOPALA, E KUZMA, T LAZOFSON, L ORKIS, R Battelle Columbus OH USA Battelle Memorial Institute Columbus OH US Battelle Memorial Inst. Columbus OH USA

Battelle scientists have assembled a reconfigurable multispectral imaging and classification system which can be taken into the field to support automated real-time target/background discrimination. The system may be used for a variety of applications including environmental remote sensing, industrial inspection and medical imaging. This paper discusses hard tactical target and runway detection applications performed with the multispectral system. The Battelle-developed system consists of a passive, multispectral imaging electro-optical (EO) sensor suite and a real-time digital data collection and data fusion image processor. The EO sensor suite, able to collect imagery in 12 distinct wavebands from the ultraviolet (UV) through the long wave infrared (LWIR), consists of five charge-coupled device (CCD) cameras and two thermal IR imagers integrated on a common portable platform. The data collection and processing system consists of video switchers, recorders and a real-time sensor fusion/classification hardware system which combines any three input wavebands to perform real-time data fusion by applying ''look-up tables,'' derived from tailored neural network algorithms, to classify the imaged scene pixel by pixel. The result is then visualized in a video format on a full color, 9-inch, active matrix Liquid Crystal Display (LCD). A variety of classification algorithms including artificial neural networks and data clustering techniques were successfully optimized to perform pixel-level classification of imagery in complex scenes comprised of tactical targets, buildings, roads, aircraft runways, and vegetaton. algorithms implemented included unsupervised maximum likelihood, Linde Buzo Gray, and ''fuzzy'' clustering algorithms along with Multilayer Perceptron and Learning Vector Quantization (LVQ) neural networks. Supervised clustering of the data was also evaluated. To assess classification robustness, algorithms were tested on imagery recorded over broad periods of tim

关键词： CCD image sensors aircraft instrumentation data acquisition feedforward neural nets image processing equipment image recognition infrared detectors infrared imaging learning (artificial intelligence) liquid crystal displays maximum likelihood estimation INFRARED DETECTORS sorting algorithm Infrared imaging data integration Data fusion algorithms image processing equipment LIQUID CRYSTAL DISPLAY maximum likelihood estimation CCD image sensors feedforward neural nets Image recognition

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Adaptive Order-of-Addition Experiments via the Quick-Sort algorithm

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TECHNOMETRICS 2023年第3期65卷 396-405页

作者： Lin, Dennis K. J. Chen, Jianbin Purdue Univ Dept Stat W Lafayette IN USA Beijing Inst Technol Sch Math & Stat Beijing 100081 Peoples R China

The order-of-addition (OofA) experiment has received a great deal of attention in the recent literature. The primary goal of the OofA experiment is to identify the optimal order in a sequence of m components. All the existing methods are model-dependent and are limited to small number of components. The appropriateness of the resulting optimal order heavily depends on (a) the correctness of the underlying assumed model, and (b) the goodness of model fitting. Moreover, these methods are not applicable to deal with large m (e.g., m >= 7 ). With this in mind, this article proposes an efficient adaptive methodology, building upon the quick-sort algorithm, to explore the optimal order without any model specification. Compared to the existing work, the run sizes of the proposed method needed to achieve the optimal order are much smaller. Theoretical supports are given to illustrate the effectiveness of the proposed method. The proposed method is able to obtain the optimal order for large m (e.g., m >= 20 ). Numerical experiments are used to demonstrate the effectiveness of the proposed method.

关键词： Design of experiment Optimal order Sequential design sorting algorithm

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The use of multi-temporal Landsat Normalized Difference Vegetation Index (NDVI) data for mapping fuel models in Yosemite National Park, USA

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2003年第8期24卷 1639-1651页

作者： Van Wagtendonk, JW Root, RR US Geol Survey Western Ecol Res Ctr Yosemite Field Stn El Portal CA 95318 USA US Geol Survey Rocky Mt Mapping Ctr Denver Fed Ctr Denver CO 80225 USA

The objective of this study was to test the applicability of using Normalized Difference Vegetation Index (NDVI) values derived from a temporal sequence of six Landsat Thematic Mapper (TM) scenes to map fuel models for Yosemite National Park, USA. An unsupervised classification algorithm was used to define 30 unique spectral-temporal classes of NDVI values. A combination of graphical, statistical and visual techniques was used to characterize the 30 classes and identify those that responded similarly and could be combined into fuel models. The final classification of fuel models included six different types: short annual and perennial grasses, tall perennial grasses, medium brush and evergreen hardwoods, short-needled conifers with no heavy fuels, long-needled conifers and deciduous hardwoods, and short-needled conifers with a component of heavy fuels. The NDVI, when analysed over a season of phenologically distinct periods along with ancillary data, can elicit information necessary to distinguish fuel model types. Fuels information derived from remote sensors has proven to be useful for initial classification of fuels and has been applied to fire management situations on the ground.

关键词： EVERGREEN Yosemite National Park heavy oil Fuel models Conifers Remote sensing equipment ancillary data normalized difference vegetation index sorting algorithm

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A method for classification accuracy evaluation for a precipitation-oriented classifier

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2005年第21期26卷 4785-4800页

作者： Anthis, AI Cracknell, AP Reg Meteorol Ctr Hellen Tact Air Force Hellen Natl Meteorol Serv Larisa Greece Univ Dundee Div Elect Engn & Phys Dundee Scotland

A method of classification accuracy evaluation for a cloud and precipitation classifier applied to geostationary meteorological satellite data is presented. The method has been developed to evaluate the accuracy of a rather precise classification algorithm. The algorithm produces nine classes, four of which involve precipitation. The classes are: (1) clear or insignificant cloud, (2) low thin cloud with no rain, (3) low or middle thin cloud with no rain, (4) low or middle thick cloud with no rain, (5) middle or high cloud with no rain, (6) middle or high cloud with the possibility of rain, (7) middle or high cloud with light-moderate precipitation, (8) middle-high cloud with moderate-heavy precipitation, (9) heavy thunderstorm. The evaluation classifier has been tested for its accuracy (ground truth) using comparison between actual meteorological weather reports and classification results derived from the algorithm applied. For the estimation of classification accuracy, the omission/commission method is applied between the observed and the classification-produced values. The classifier used has proved to be very reliable for classifying major cloud types and precipitation, tested during the synoptic situation of depression systems approaching the south Balkan Peninsula from the west. In that synoptic situation, different intensities of rainfall as well as heavy thunderstorm were present, and the results are very satisfactory. The method can be used to evaluate classification results produced by algorithms applied to meteorological satellite data, classifying precipitation areas as well as the heaviness of precipitation.

关键词： Classifiers Cloud Types algorithms mean point rain Satellite Imagery sorting algorithm

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Video Behavior Analysis Using Topic Models and Rough Sets

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IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 2013年第1期8卷 56-67页

作者： Zhao, Liang Shang, Lin Gao, Yang Yang, Yubin Jia, Xiuyi Nanjing Univ Nanjing Jiangsu Peoples R China Nanjing Univ Sci & Technol Nanjing Jiangsu Peoples R China

Video behavior analysis is both meaningful and challenging in computer vision. As the monitoring equipment become readily cheaper and available, massive video data have been generated. As abnormal behaviors are rare, manual surveillance may drastically increase the chances of false positives or false negatives. It is hence useful to achieve automatic surveillance. Abnormal behaviors are usually complex and short. It is however difficult to completely list the abnormal behaviors. We can view abnormalities as outliers. Sometimes abnormalities co-occur with normalities, which cannot be distinguished in some feature space.

关键词： Analytical models Classification algorithms Computational modeling Computer vision Data models Feature extraction Rough sets Rough sets Feature extraction ANALYSIS MODELS monitoring equipment data models Eigenvector behavioral research abnormal behavior computer vision sorting algorithm Computational modeling

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