47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

Code of Federal Regulations, 2012 CFR

2012-10-01

... identified through the use of an automatic transmitter identification system as specified below. (a.... (3) The ATIS signal as a minimum shall consist of the following: (i) The FCC assigned earth station... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON...

47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

Code of Federal Regulations, 2011 CFR

2011-10-01

... identified through the use of an automatic transmitter identification system as specified below. (a.... (3) The ATIS signal as a minimum shall consist of the following: (i) The FCC assigned earth station... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON...

Optical Automatic Car Identification (OACI) : Volume 1. Advanced System Specification.

DOT National Transportation Integrated Search

1978-12-01

A performance specification is provided in this report for an Optical Automatic Car Identification (OACI) scanner system which features 6% improved readability over existing industry scanner systems. It also includes the analysis and rationale which ...

The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia

NASA Astrophysics Data System (ADS)

Kao, Meng-Chun; Ting, Chien-Kun; Kuo, Wen-Chuan

2018-02-01

Incorrect placement of the needle causes medical complications in the epidural block, such as dural puncture or spinal cord injury. This study proposes a system which combines an optical coherence tomography (OCT) imaging probe with an automatic identification (AI) system to objectively identify the position of the epidural needle tip. The automatic identification system uses three features as image parameters to distinguish the different tissue by three classifiers. Finally, we found that the support vector machine (SVM) classifier has highest accuracy, specificity, and sensitivity, which reached to 95%, 98%, and 92%, respectively.

47 CFR 80.275 - Technical Requirements for Class A Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Compulsory Ships § 80.275 Technical Requirements for Class A Automatic Identification System (AIS) equipment. (a) Prior to submitting a certification application for a Class A AIS device, the following... Identification System (AIS) equipment. 80.275 Section 80.275 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 80.275 - Technical Requirements for Class A Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Compulsory Ships § 80.275 Technical Requirements for Class A Automatic Identification System (AIS) equipment. (a) Prior to submitting a certification application for a Class A AIS device, the following... Identification System (AIS) equipment. 80.275 Section 80.275 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 80.275 - Technical Requirements for Class A Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Compulsory Ships § 80.275 Technical Requirements for Class A Automatic Identification System (AIS) equipment. (a) Prior to submitting a certification application for a Class A AIS device, the following... Identification System (AIS) equipment. 80.275 Section 80.275 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 80.275 - Technical Requirements for Class A Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Compulsory Ships § 80.275 Technical Requirements for Class A Automatic Identification System (AIS) equipment. (a) Prior to submitting a certification application for a Class A AIS device, the following... Identification System (AIS) equipment. 80.275 Section 80.275 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

Automatic limb identification and sleeping parameters assessment for pressure ulcer prevention.

PubMed

Baran Pouyan, Maziyar; Birjandtalab, Javad; Nourani, Mehrdad; Matthew Pompeo, M D

2016-08-01

Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automatic building identification under bomb damage conditions

NASA Astrophysics Data System (ADS)

Woodley, Robert; Noll, Warren; Barker, Joseph; Wunsch, Donald C., II

2009-05-01

Given the vast amount of image intelligence utilized in support of planning and executing military operations, a passive automated image processing capability for target identification is urgently required. Furthermore, transmitting large image streams from remote locations would quickly use available band width (BW) precipitating the need for processing to occur at the sensor location. This paper addresses the problem of automatic target recognition for battle damage assessment (BDA). We utilize an Adaptive Resonance Theory approach to cluster templates of target buildings. The results show that the network successfully classifies targets from non-targets in a virtual test bed environment.

Roadway system assessment using bluetooth-based automatic vehicle identification travel time data.

DOT National Transportation Integrated Search

2012-12-01

This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection : systems. This includes considerations in the physical setup of the collection system as well as the interpretation of...

Automatic vasculature identification in coronary angiograms by adaptive geometrical tracking.

PubMed

Xiao, Ruoxiu; Yang, Jian; Goyal, Mahima; Liu, Yue; Wang, Yongtian

2013-01-01

As the uneven distribution of contrast agents and the perspective projection principle of X-ray, the vasculatures in angiographic image are with low contrast and are generally superposed with other organic tissues; therefore, it is very difficult to identify the vasculature and quantitatively estimate the blood flow directly from angiographic images. In this paper, we propose a fully automatic algorithm named adaptive geometrical vessel tracking (AGVT) for coronary artery identification in X-ray angiograms. Initially, the ridge enhancement (RE) image is obtained utilizing multiscale Hessian information. Then, automatic initialization procedures including seed points detection, and initial directions determination are performed on the RE image. The extracted ridge points can be adjusted to the geometrical centerline points adaptively through diameter estimation. Bifurcations are identified by discriminating connecting relationship of the tracked ridge points. Finally, all the tracked centerlines are merged and smoothed by classifying the connecting components on the vascular structures. Synthetic angiographic images and clinical angiograms are used to evaluate the performance of the proposed algorithm. The proposed algorithm is compared with other two vascular tracking techniques in terms of the efficiency and accuracy, which demonstrate successful applications of the proposed segmentation and extraction scheme in vasculature identification.

MAC, A System for Automatically IPR Identification, Collection and Distribution

NASA Astrophysics Data System (ADS)

Serrão, Carlos

Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.

Automatic poisson peak harvesting for high throughput protein identification.

PubMed

Breen, E J; Hopwood, F G; Williams, K L; Wilkins, M R

2000-06-01

High throughput identification of proteins by peptide mass fingerprinting requires an efficient means of picking peaks from mass spectra. Here, we report the development of a peak harvester to automatically pick monoisotopic peaks from spectra generated on matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometers. The peak harvester uses advanced mathematical morphology and watershed algorithms to first process spectra to stick representations. Subsequently, Poisson modelling is applied to determine which peak in an isotopically resolved group represents the monoisotopic mass of a peptide. We illustrate the features of the peak harvester with mass spectra of standard peptides, digests of gel-separated bovine serum albumin, and with Escherictia coli proteins prepared by two-dimensional polyacrylamide gel electrophoresis. In all cases, the peak harvester proved effective in its ability to pick similar monoisotopic peaks as an experienced human operator, and also proved effective in the identification of monoisotopic masses in cases where isotopic distributions of peptides were overlapping. The peak harvester can be operated in an interactive mode, or can be completely automated and linked through to peptide mass fingerprinting protein identification tools to achieve high throughput automated protein identification.

Experiments in automatic word class and word sense identification for information retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gauch, S.; Futrelle, R.P.

Automatic identification of related words and automatic detection of word senses are two long-standing goals of researchers in natural language processing. Word class information and word sense identification may enhance the performance of information retrieval system4ms. Large online corpora and increased computational capabilities make new techniques based on corpus linguisitics feasible. Corpus-based analysis is especially needed for corpora from specialized fields for which no electronic dictionaries or thesauri exist. The methods described here use a combination of mutual information and word context to establish word similarities. Then, unsupervised classification is done using clustering in the word space, identifying word classesmore » without pretagging. We also describe an extension of the method to handle the difficult problems of disambiguation and of determining part-of-speech and semantic information for low-frequency words. The method is powerful enough to produce high-quality results on a small corpus of 200,000 words from abstracts in a field of molecular biology.« less

Accuracy of Automatic Cephalometric Software on Landmark Identification

NASA Astrophysics Data System (ADS)

Anuwongnukroh, N.; Dechkunakorn, S.; Damrongsri, S.; Nilwarat, C.; Pudpong, N.; Radomsutthisarn, W.; Kangern, S.

2017-11-01

This study was to assess the accuracy of an automatic cephalometric analysis software in the identification of cephalometric landmarks. Thirty randomly selected digital lateral cephalograms of patients undergoing orthodontic treatment were used in this study. Thirteen landmarks (S, N, Or, A-point, U1T, U1A, B-point, Gn, Pog, Me, Go, L1T, and L1A) were identified on the digital image by an automatic cephalometric software and on cephalometric tracing by manual method. Superimposition of printed image and manual tracing was done by registration at the soft tissue profiles. The accuracy of landmarks located by the automatic method was compared with that of the manually identified landmarks by measuring the mean differences of distances of each landmark on the Cartesian plane where X and Y coordination axes passed through the center of ear rod. One-Sample T test was used to evaluate the mean differences. Statistically significant mean differences (p<0.05) were found in 5 landmarks (Or, A-point, Me, L1T, and L1A) in horizontal direction and 7 landmarks (Or, A-point, U1T, U1A, B-point, Me, and L1A) in vertical direction. Four landmarks (Or, A-point, Me, and L1A) showed significant (p<0.05) mean differences in both horizontal and vertical directions. Small mean differences (<0.5mm) were found for S, N, B-point, Gn, and Pog in horizontal direction and N, Gn, Me, and L1T in vertical direction. Large mean differences were found for A-point (3.0 < 3.5mm) in horizontal direction and L1A (>4mm) in vertical direction. Only 5 of 13 landmarks (38.46%; S, N, Gn, Pog, and Go) showed no significant mean difference between the automatic and manual landmarking methods. It is concluded that if this automatic cephalometric analysis software is used for orthodontic diagnosis, the orthodontist must correct or modify the position of landmarks in order to increase the accuracy of cephalometric analysis.

33 CFR 164.43 - Automatic Identification System Shipborne Equipment-Prince William Sound.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (AISSE) system consisting of a: (1) Twelve-channel all-in-view Differential Global Positioning System (d... to indicate to shipboard personnel that the U.S. Coast Guard dGPS system cannot provide the required... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Automatic Identification System...

Automatic Ammunition Identification Technology Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weil, B.

1993-01-01

The Automatic Ammunition Identification Technology (AAIT) Project is an activity of the Robotics Process Systems Division at the Oak Ridge National Laboratory (ORNL) for the US Army's Project Manager-Ammunition Logistics (PM-AMMOLOG) at the Picatinny Arsenal in Picatinny, New Jersey. The project objective is to evaluate new two-dimensional bar code symbologies for potential use in ammunition logistics systems and automated reloading equipment. These new symbologies are a significant improvement over typical linear bar codes since machine-readable alphanumeric messages up to 2000 characters long are achievable. These compressed data symbologies are expected to significantly improve logistics and inventory management tasks and permitmore » automated feeding and handling of ammunition to weapon systems. The results will be increased throughout capability, better inventory control, reduction of human error, lower operation and support costs, and a more timely re-supply of various weapon systems. This paper will describe the capabilities of existing compressed data symbologies and the symbol testing activities being conducted at ORNL for the AAIT Project.« less

Automatic Molar Extraction from Dental Panoramic Radiographs for Forensic Personal Identification

NASA Astrophysics Data System (ADS)

Samopa, Febriliyan; Asano, Akira; Taguchi, Akira

Measurement of an individual molar provides rich information for forensic personal identification. We propose a computer-based system for extracting an individual molar from dental panoramic radiographs. A molar is obtained by extracting the region-of-interest, separating the maxilla and mandible, and extracting the boundaries between teeth. The proposed system is almost fully automatic; all that the user has to do is clicking three points on the boundary between the maxilla and the mandible.

Identification of mycobacterium tuberculosis in sputum smear slide using automatic scanning microscope

NASA Astrophysics Data System (ADS)

Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

2015-04-01

Sputum smear observation has an important role in tuberculosis (TB) disease diagnosis, because it needs accurate identification to avoid high errors diagnosis. In development countries, sputum smear slide observation is commonly done with conventional light microscope from Ziehl-Neelsen stained tissue and it doesn't need high cost to maintain the microscope. The clinicians do manual screening process for sputum smear slide which is time consuming and needs highly training to detect the presence of TB bacilli (mycobacterium tuberculosis) accurately, especially for negative slide and slide with less number of TB bacilli. For helping the clinicians, we propose automatic scanning microscope with automatic identification of TB bacilli. The designed system modified the field movement of light microscope with stepper motor which was controlled by microcontroller. Every sputum smear field was captured by camera. After that some image processing techniques were done for the sputum smear images. The color threshold was used for background subtraction with hue canal in HSV color space. Sobel edge detection algorithm was used for TB bacilli image segmentation. We used feature extraction based on shape for bacilli analyzing and then neural network classified TB bacilli or not. The results indicated identification of TB bacilli that we have done worked well and detected TB bacilli accurately in sputum smear slide with normal staining, but not worked well in over staining and less staining tissue slide. However, overall the designed system can help the clinicians in sputum smear observation becomes more easily.

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

Automatic identification of inertial sensor placement on human body segments during walking

PubMed Central

2013-01-01

Background Current inertial motion capture systems are rarely used in biomedical applications. The attachment and connection of the sensors with cables is often a complex and time consuming task. Moreover, it is prone to errors, because each sensor has to be attached to a predefined body segment. By using wireless inertial sensors and automatic identification of their positions on the human body, the complexity of the set-up can be reduced and incorrect attachments are avoided. We present a novel method for the automatic identification of inertial sensors on human body segments during walking. This method allows the user to place (wireless) inertial sensors on arbitrary body segments. Next, the user walks for just a few seconds and the segment to which each sensor is attached is identified automatically. Methods Walking data was recorded from ten healthy subjects using an Xsens MVN Biomech system with full-body configuration (17 inertial sensors). Subjects were asked to walk for about 6 seconds at normal walking speed (about 5 km/h). After rotating the sensor data to a global coordinate frame with x-axis in walking direction, y-axis pointing left and z-axis vertical, RMS, mean, and correlation coefficient features were extracted from x-, y- and z-components and magnitudes of the accelerations, angular velocities and angular accelerations. As a classifier, a decision tree based on the C4.5 algorithm was developed using Weka (Waikato Environment for Knowledge Analysis). Results and conclusions After testing the algorithm with 10-fold cross-validation using 31 walking trials (involving 527 sensors), 514 sensors were correctly classified (97.5%). When a decision tree for a lower body plus trunk configuration (8 inertial sensors) was trained and tested using 10-fold cross-validation, 100% of the sensors were correctly identified. This decision tree was also tested on walking trials of 7 patients (17 walking trials) after anterior cruciate ligament reconstruction, which

Automatic identification of inertial sensor placement on human body segments during walking.

PubMed

Weenk, Dirk; van Beijnum, Bert-Jan F; Baten, Chris T M; Hermens, Hermie J; Veltink, Peter H

2013-03-21

Current inertial motion capture systems are rarely used in biomedical applications. The attachment and connection of the sensors with cables is often a complex and time consuming task. Moreover, it is prone to errors, because each sensor has to be attached to a predefined body segment. By using wireless inertial sensors and automatic identification of their positions on the human body, the complexity of the set-up can be reduced and incorrect attachments are avoided.We present a novel method for the automatic identification of inertial sensors on human body segments during walking. This method allows the user to place (wireless) inertial sensors on arbitrary body segments. Next, the user walks for just a few seconds and the segment to which each sensor is attached is identified automatically. Walking data was recorded from ten healthy subjects using an Xsens MVN Biomech system with full-body configuration (17 inertial sensors). Subjects were asked to walk for about 6 seconds at normal walking speed (about 5 km/h). After rotating the sensor data to a global coordinate frame with x-axis in walking direction, y-axis pointing left and z-axis vertical, RMS, mean, and correlation coefficient features were extracted from x-, y- and z-components and magnitudes of the accelerations, angular velocities and angular accelerations. As a classifier, a decision tree based on the C4.5 algorithm was developed using Weka (Waikato Environment for Knowledge Analysis). After testing the algorithm with 10-fold cross-validation using 31 walking trials (involving 527 sensors), 514 sensors were correctly classified (97.5%). When a decision tree for a lower body plus trunk configuration (8 inertial sensors) was trained and tested using 10-fold cross-validation, 100% of the sensors were correctly identified. This decision tree was also tested on walking trials of 7 patients (17 walking trials) after anterior cruciate ligament reconstruction, which also resulted in 100% correct identification

Automatic identification of bullet signatures based on consecutive matching striae (CMS) criteria.

PubMed

Chu, Wei; Thompson, Robert M; Song, John; Vorburger, Theodore V

2013-09-10

The consecutive matching striae (CMS) numeric criteria for firearm and toolmark identifications have been widely accepted by forensic examiners, although there have been questions concerning its observer subjectivity and limited statistical support. In this paper, based on signal processing and extraction, a model for the automatic and objective counting of CMS is proposed. The position and shape information of the striae on the bullet land is represented by a feature profile, which is used for determining the CMS number automatically. Rapid counting of CMS number provides a basis for ballistics correlations with large databases and further statistical and probability analysis. Experimental results in this report using bullets fired from ten consecutively manufactured barrels support this developed model. Published by Elsevier Ireland Ltd.

Automatic Adviser on Mobile Objects Status Identification and Classification

NASA Astrophysics Data System (ADS)

Shabelnikov, A. N.; Liabakh, N. N.; Gibner, Ya M.; Saryan, A. S.

2018-05-01

A mobile object status identification task is defined within the image discrimination theory. It is proposed to classify objects into three classes: object operation status; its maintenance is required and object should be removed from the production process. Two methods were developed to construct the separating boundaries between the designated classes: a) using statistical information on the research objects executed movement, b) basing on regulatory documents and expert commentary. Automatic Adviser operation simulation and the operation results analysis complex were synthesized. Research results are commented using a specific example of cuts rolling from the hump yard. The work was supported by Russian Fundamental Research Fund, project No. 17-20-01040.

47 CFR 80.275 - Technical Requirements for Class A Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Technical Requirements for Class A Automatic Identification System (AIS) equipment. 80.275 Section 80.275 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES STATIONS IN THE MARITIME SERVICES Equipment Authorization for Compulsory Ships § 80.275...

Automatic identification of alpine mass movements based on seismic and infrasound signals

NASA Astrophysics Data System (ADS)

Schimmel, Andreas; Hübl, Johannes

2017-04-01

The automatic detection and identification of alpine mass movements like debris flows, debris floods or landslides gets increasing importance for mitigation measures in the densely populated and intensively used alpine regions. Since this mass movement processes emits characteristically seismic and acoustic waves in the low frequency range this events can be detected and identified based on this signals. So already several approaches for detection and warning systems based on seismic or infrasound signals has been developed. But a combination of both methods, which can increase detection probability and reduce false alarms is currently used very rarely and can serve as a promising method for developing an automatic detection and identification system. So this work presents an approach for a detection and identification system based on a combination of seismic and infrasound sensors, which can detect sediment related mass movements from a remote location unaffected by the process. The system is based on one infrasound sensor and one geophone which are placed co-located and a microcontroller where a specially designed detection algorithm is executed which can detect mass movements in real time directly at the sensor site. Further this work tries to get out more information from the seismic and infrasound spectrum produced by different sediment related mass movements to identify the process type and estimate the magnitude of the event. The system is currently installed and tested on five test sites in Austria, two in Italy and one in Switzerland as well as one in Germany. This high number of test sites is used to get a large database of very different events which will be the basis for a new identification method for alpine mass movements. These tests shows promising results and so this system provides an easy to install and inexpensive approach for a detection and warning system.

Evaluating current automatic de-identification methods with Veteran's health administration clinical documents.

PubMed

Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

2012-07-27

The increased use and adoption of Electronic Health Records (EHR) causes a tremendous growth in digital information useful for clinicians, researchers and many other operational purposes. However, this information is rich in Protected Health Information (PHI), which severely restricts its access and possible uses. A number of investigators have developed methods for automatically de-identifying EHR documents by removing PHI, as specified in the Health Insurance Portability and Accountability Act "Safe Harbor" method.This study focuses on the evaluation of existing automated text de-identification methods and tools, as applied to Veterans Health Administration (VHA) clinical documents, to assess which methods perform better with each category of PHI found in our clinical notes; and when new methods are needed to improve performance. We installed and evaluated five text de-identification systems "out-of-the-box" using a corpus of VHA clinical documents. The systems based on machine learning methods were trained with the 2006 i2b2 de-identification corpora and evaluated with our VHA corpus, and also evaluated with a ten-fold cross-validation experiment using our VHA corpus. We counted exact, partial, and fully contained matches with reference annotations, considering each PHI type separately, or only one unique 'PHI' category. Performance of the systems was assessed using recall (equivalent to sensitivity) and precision (equivalent to positive predictive value) metrics, as well as the F(2)-measure. Overall, systems based on rules and pattern matching achieved better recall, and precision was always better with systems based on machine learning approaches. The highest "out-of-the-box" F(2)-measure was 67% for partial matches; the best precision and recall were 95% and 78%, respectively. Finally, the ten-fold cross validation experiment allowed for an increase of the F(2)-measure to 79% with partial matches. The "out-of-the-box" evaluation of text de-identification

Automatic identification and location technology of glass insulator self-shattering

NASA Astrophysics Data System (ADS)

Huang, Xinbo; Zhang, Huiying; Zhang, Ye

2017-11-01

The insulator of transmission lines is one of the most important infrastructures, which is vital to ensure the safe operation of transmission lines under complex and harsh operating conditions. The glass insulator often self-shatters but the available identification methods are inefficient and unreliable. Then, an automatic identification and localization technology of self-shattered glass insulators is proposed, which consists of the cameras installed on the tower video monitoring devices or the unmanned aerial vehicles, the 4G/OPGW network, and the monitoring center, where the identification and localization algorithm is embedded into the expert software. First, the images of insulators are captured by cameras, which are processed to identify the region of insulator string by the presented identification algorithm of insulator string. Second, according to the characteristics of the insulator string image, a mathematical model of the insulator string is established to estimate the direction and the length of the sliding blocks. Third, local binary pattern histograms of the template and the sliding block are extracted, by which the self-shattered insulator can be recognized and located. Finally, a series of experiments is fulfilled to verify the effectiveness of the algorithm. For single insulator images, Ac, Pr, and Rc of the algorithm are 94.5%, 92.38%, and 96.78%, respectively. For double insulator images, Ac, Pr, and Rc are 90.00%, 86.36%, and 93.23%, respectively.

System Identification and Automatic Mass Balancing of Ground-Based Three-Axis Spacecraft Simulator

DTIC Science & Technology

2006-08-01

commanded torque to move away from these singularity points. The introduction of this error may not degrade the performance for large slew angle ...trajectory has been generated and quaternion feedback control has been implemented for reference trajectory tracking. The testbed was reasonably well...System Identification and Automatic Mass Balancing of Ground-Based Three-Axis Spacecraft Simulator Jae-Jun Kim∗ and Brij N. Agrawal † Department of

A discrete optimization approach for locating automatic vehicle identification readers for the provision of roadway travel times

DOT National Transportation Integrated Search

2002-11-01

This paper develops an algorithm for optimally locating surveillance technologies with an emphasis on Automatic Vehicle Identification tag readers by maximizing the benefit that would accrue from measuring travel times on a transportation network. Th...

Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision.

PubMed

Heinrich, Andreas; Güttler, Felix; Wendt, Sebastian; Schenkl, Sebastian; Hubig, Michael; Wagner, Rebecca; Mall, Gita; Teichgräber, Ulf

2018-06-18

 In forensic odontology the comparison between antemortem and postmortem panoramic radiographs (PRs) is a reliable method for person identification. The purpose of this study was to improve and automate identification of unknown people by comparison between antemortem and postmortem PR using computer vision.  The study includes 43 467 PRs from 24 545 patients (46 % females/54 % males). All PRs were filtered and evaluated with Matlab R2014b including the toolboxes image processing and computer vision system. The matching process used the SURF feature to find the corresponding points between two PRs (unknown person and database entry) out of the whole database.  From 40 randomly selected persons, 34 persons (85 %) could be reliably identified by corresponding PR matching points between an already existing scan in the database and the most recent PR. The systematic matching yielded a maximum of 259 points for a successful identification between two different PRs of the same person and a maximum of 12 corresponding matching points for other non-identical persons in the database. Hence 12 matching points are the threshold for reliable assignment.  Operating with an automatic PR system and computer vision could be a successful and reliable tool for identification purposes. The applied method distinguishes itself by virtue of its fast and reliable identification of persons by PR. This Identification method is suitable even if dental characteristics were removed or added in the past. The system seems to be robust for large amounts of data.   · Computer vision allows an automated antemortem and postmortem comparison of panoramic radiographs (PRs) for person identification.. · The present method is able to find identical matching partners among huge datasets (big data) in a short computing time.. · The identification method is suitable even if dental characteristics were removed or added.. · Heinrich A, Güttler F, Wendt S et al. Forensic Odontology

Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck region

NASA Astrophysics Data System (ADS)

Leavens, Claudia; Vik, Torbjørn; Schulz, Heinrich; Allaire, Stéphane; Kim, John; Dawson, Laura; O'Sullivan, Brian; Breen, Stephen; Jaffray, David; Pekar, Vladimir

2008-03-01

Manual contouring of target volumes and organs at risk in radiation therapy is extremely time-consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves towards adaptive treatment, the need for more efficient segmentation techniques will increase. We are developing a method for automatic model-based segmentation of the head and neck. This process can be broken down into three main steps: i) automatic landmark identification in the image dataset of interest, ii) automatic landmark-based initialization of deformable surface models to the patient image dataset, and iii) adaptation of the deformable models to the patient-specific anatomical boundaries of interest. In this paper, we focus on the validation of the first step of this method, quantifying the results of our automatic landmark identification method. We use an image atlas formed by applying thin-plate spline (TPS) interpolation to ten atlas datasets, using 27 manually identified landmarks in each atlas/training dataset. The principal variation modes returned by principal component analysis (PCA) of the landmark positions were used by an automatic registration algorithm, which sought the corresponding landmarks in the clinical dataset of interest using a controlled random search algorithm. Applying a run time of 60 seconds to the random search, a root mean square (rms) distance to the ground-truth landmark position of 9.5 +/- 0.6 mm was calculated for the identified landmarks. Automatic segmentation of the brain, mandible and brain stem, using the detected landmarks, is demonstrated.

Automatic Identification System modular receiver for academic purposes

NASA Astrophysics Data System (ADS)

Cabrera, F.; Molina, N.; Tichavska, M.; Araña, V.

2016-07-01

The Automatic Identification System (AIS) standard is encompassed within the Global Maritime Distress and Safety System (GMDSS), in force since 1999. The GMDSS is a set of procedures, equipment, and communication protocols designed with the aim of increasing the safety of sea crossings, facilitating navigation, and the rescue of vessels in danger. The use of this system not only is increasingly attractive to security issues but also potentially creates intelligence products throughout the added-value information that this network can transmit from ships on real time (identification, position, course, speed, dimensions, flag, among others). Within the marine electronics market, commercial receivers implement this standard and allow users to access vessel-broadcasted information if in the range of coverage. In addition to satellite services, users may request actionable information from private or public AIS terrestrial networks where real-time feed or historical data can be accessed from its nodes. This paper describes the configuration of an AIS receiver based on a modular design. This modular design facilitates the evaluation of specific modules and also a better understanding of the standard and the possibility of changing hardware modules to improve the performance of the prototype. Thus, the aim of this paper is to describe the system's specifications, its main hardware components, and to present educational didactics on the setup and use of a modular and terrestrial AIS receiver. The latter is for academic purposes and in undergraduate studies such as electrical engineering, telecommunications, and maritime studies.

Automatic digital image analysis for identification of mitotic cells in synchronous mammalian cell cultures.

PubMed

Eccles, B A; Klevecz, R R

1986-06-01

Mitotic frequency in a synchronous culture of mammalian cells was determined fully automatically and in real time using low-intensity phase-contrast microscopy and a newvicon video camera connected to an EyeCom III image processor. Image samples, at a frequency of one per minute for 50 hours, were analyzed by first extracting the high-frequency picture components, then thresholding and probing for annular objects indicative of putative mitotic cells. Both the extraction of high-frequency components and the recognition of rings of varying radii and discontinuities employed novel algorithms. Spatial and temporal relationships between annuli were examined to discern the occurrences of mitoses, and such events were recorded in a computer data file. At present, the automatic analysis is suited for random cell proliferation rate measurements or cell cycle studies. The automatic identification of mitotic cells as described here provides a measure of the average proliferative activity of the cell population as a whole and eliminates more than eight hours of manual review per time-lapse video recording.

Automatic Identification of Subtechniques in Skating-Style Roller Skiing Using Inertial Sensors

PubMed Central

Sakurai, Yoshihisa; Fujita, Zenya; Ishige, Yusuke

2016-01-01

This study aims to develop and validate an automated system for identifying skating-style cross-country subtechniques using inertial sensors. In the first experiment, the performance of a male cross-country skier was used to develop an automated identification system. In the second, eight male and seven female college cross-country skiers participated to validate the developed identification system. Each subject wore inertial sensors on both wrists and both roller skis, and a small video camera on a backpack. All subjects skied through a 3450 m roller ski course using a skating style at their maximum speed. The adopted subtechniques were identified by the automated method based on the data obtained from the sensors, as well as by visual observations from a video recording of the same ski run. The system correctly identified 6418 subtechniques from a total of 6768 cycles, which indicates an accuracy of 94.8%. The precisions of the automatic system for identifying the V1R, V1L, V2R, V2L, V2AR, and V2AL subtechniques were 87.6%, 87.0%, 97.5%, 97.8%, 92.1%, and 92.0%, respectively. Most incorrect identification cases occurred during a subtechnique identification that included a transition and turn event. Identification accuracy can be improved by separately identifying transition and turn events. This system could be used to evaluate each skier’s subtechniques in course conditions. PMID:27049388

[Wearable Automatic External Defibrillators].

PubMed

Luo, Huajie; Luo, Zhangyuan; Jin, Xun; Zhang, Leilei; Wang, Changjin; Zhang, Wenzan; Tu, Quan

2015-11-01

Defibrillation is the most effective method of treating ventricular fibrillation(VF), this paper introduces wearable automatic external defibrillators based on embedded system which includes EGG measurements, bioelectrical impedance measurement, discharge defibrillation module, which can automatic identify VF signal, biphasic exponential waveform defibrillation discharge. After verified by animal tests, the device can realize EGG acquisition and automatic identification. After identifying the ventricular fibrillation signal, it can automatic defibrillate to abort ventricular fibrillation and to realize the cardiac electrical cardioversion.

Automatic Ammunition Identification Technology Project. Ammunition Logistics Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weil, B.

1993-03-01

The Automatic Ammunition Identification Technology (AAIT) Project is an activity of the Robotics & Process Systems Division at the Oak Ridge National Laboratory (ORNL) for the US Army`s Project Manager-Ammunition Logistics (PM-AMMOLOG) at the Picatinny Arsenal in Picatinny, New Jersey. The project objective is to evaluate new two-dimensional bar code symbologies for potential use in ammunition logistics systems and automated reloading equipment. These new symbologies are a significant improvement over typical linear bar codes since machine-readable alphanumeric messages up to 2000 characters long are achievable. These compressed data symbologies are expected to significantly improve logistics and inventory management tasks andmore » permit automated feeding and handling of ammunition to weapon systems. The results will be increased throughout capability, better inventory control, reduction of human error, lower operation and support costs, and a more timely re-supply of various weapon systems. This paper will describe the capabilities of existing compressed data symbologies and the symbol testing activities being conducted at ORNL for the AAIT Project.« less

Automatic topic identification of health-related messages in online health community using text classification.

PubMed

Lu, Yingjie

2013-01-01

To facilitate patient involvement in online health community and obtain informative support and emotional support they need, a topic identification approach was proposed in this paper for identifying automatically topics of the health-related messages in online health community, thus assisting patients in reaching the most relevant messages for their queries efficiently. Feature-based classification framework was presented for automatic topic identification in our study. We first collected the messages related to some predefined topics in a online health community. Then we combined three different types of features, n-gram-based features, domain-specific features and sentiment features to build four feature sets for health-related text representation. Finally, three different text classification techniques, C4.5, Naïve Bayes and SVM were adopted to evaluate our topic classification model. By comparing different feature sets and different classification techniques, we found that n-gram-based features, domain-specific features and sentiment features were all considered to be effective in distinguishing different types of health-related topics. In addition, feature reduction technique based on information gain was also effective to improve the topic classification performance. In terms of classification techniques, SVM outperformed C4.5 and Naïve Bayes significantly. The experimental results demonstrated that the proposed approach could identify the topics of online health-related messages efficiently.

Automatic firearm class identification from cartridge cases

NASA Astrophysics Data System (ADS)

Kamalakannan, Sridharan; Mann, Christopher J.; Bingham, Philip R.; Karnowski, Thomas P.; Gleason, Shaun S.

2011-03-01

We present a machine vision system for automatic identification of the class of firearms by extracting and analyzing two significant properties from spent cartridge cases, namely the Firing Pin Impression (FPI) and the Firing Pin Aperture Outline (FPAO). Within the framework of the proposed machine vision system, a white light interferometer is employed to image the head of the spent cartridge cases. As a first step of the algorithmic procedure, the Primer Surface Area (PSA) is detected using a circular Hough transform. Once the PSA is detected, a customized statistical region-based parametric active contour model is initialized around the center of the PSA and evolved to segment the FPI. Subsequently, the scaled version of the segmented FPI is used to initialize a customized Mumford-Shah based level set model in order to segment the FPAO. Once the shapes of FPI and FPAO are extracted, a shape-based level set method is used in order to compare these extracted shapes to an annotated dataset of FPIs and FPAOs from varied firearm types. A total of 74 cartridge case images non-uniformly distributed over five different firearms are processed using the aforementioned scheme and the promising nature of the results (95% classification accuracy) demonstrate the efficacy of the proposed approach.

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

PubMed

Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

2018-04-30

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

PubMed

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2016-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP)-related independent components. However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g., identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by nonbiological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature-based clustering algorithm used to identify artifacts which have physiological origins; and 2) the electrode-scalp impedance information employed for identifying nonbiological artifacts. The results on EEG data collected from ten subjects show that our algorithm can effectively detect, separate, and remove both physiological and nonbiological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods.

Automatic Identification of Artifact-related Independent Components for Artifact Removal in EEG Recordings

PubMed Central

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2017-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from Independent Component Analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event related potential (ERP)-related independent components (ICs). However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g. identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by non-biological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature based clustering algorithm used to identify artifacts which have physiological origins and 2) the electrode-scalp impedance information employed for identifying non-biological artifacts. The results on EEG data collected from 10 subjects show that our algorithm can effectively detect, separate, and remove both physiological and non-biological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods. PMID:25415992

Automatic quality assessment and peak identification of auditory brainstem responses with fitted parametric peaks.

PubMed

Valderrama, Joaquin T; de la Torre, Angel; Alvarez, Isaac; Segura, Jose Carlos; Thornton, A Roger D; Sainz, Manuel; Vargas, Jose Luis

2014-05-01

The recording of the auditory brainstem response (ABR) is used worldwide for hearing screening purposes. In this process, a precise estimation of the most relevant components is essential for an accurate interpretation of these signals. This evaluation is usually carried out subjectively by an audiologist. However, the use of automatic methods for this purpose is being encouraged nowadays in order to reduce human evaluation biases and ensure uniformity among test conditions, patients, and screening personnel. This article describes a new method that performs automatic quality assessment and identification of the peaks, the fitted parametric peaks (FPP). This method is based on the use of synthesized peaks that are adjusted to the ABR response. The FPP is validated, on one hand, by an analysis of amplitudes and latencies measured manually by an audiologist and automatically by the FPP method in ABR signals recorded at different stimulation rates; and on the other hand, contrasting the performance of the FPP method with the automatic evaluation techniques based on the correlation coefficient, FSP, and cross correlation with a predefined template waveform by comparing the automatic evaluations of the quality of these methods with subjective evaluations provided by five experienced evaluators on a set of ABR signals of different quality. The results of this study suggest (a) that the FPP method can be used to provide an accurate parameterization of the peaks in terms of amplitude, latency, and width, and (b) that the FPP remains as the method that best approaches the averaged subjective quality evaluation, as well as provides the best results in terms of sensitivity and specificity in ABR signals validation. The significance of these findings and the clinical value of the FPP method are highlighted on this paper. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Automatic identification and normalization of dosage forms in drug monographs

PubMed Central

2012-01-01

Background Each day, millions of health consumers seek drug-related information on the Web. Despite some efforts in linking related resources, drug information is largely scattered in a wide variety of websites of different quality and credibility. Methods As a step toward providing users with integrated access to multiple trustworthy drug resources, we aim to develop a method capable of identifying drug's dosage form information in addition to drug name recognition. We developed rules and patterns for identifying dosage forms from different sections of full-text drug monographs, and subsequently normalized them to standardized RxNorm dosage forms. Results Our method represents a significant improvement compared with a baseline lookup approach, achieving overall macro-averaged Precision of 80%, Recall of 98%, and F-Measure of 85%. Conclusions We successfully developed an automatic approach for drug dosage form identification, which is critical for building links between different drug-related resources. PMID:22336431

Identification of forensic samples by using an infrared-based automatic DNA sequencer.

PubMed

Ricci, Ugo; Sani, Ilaria; Klintschar, Michael; Cerri, Nicoletta; De Ferrari, Francesco; Giovannucci Uzielli, Maria Luisa

2003-06-01

We have recently introduced a new protocol for analyzing all core loci of the Federal Bureau of Investigation's (FBI) Combined DNA Index System (CODIS) with an infrared (IR) automatic DNA sequencer (LI-COR 4200). The amplicons were labeled with forward oligonucleotide primers, covalently linked to a new infrared fluorescent molecule (IRDye 800). The alleles were displayed as familiar autoradiogram-like images with real-time detection. This protocol was employed for paternity testing, population studies, and identification of degraded forensic samples. We extensively analyzed some simulated forensic samples and mixed stains (blood, semen, saliva, bones, and fixed archival embedded tissues), comparing the results with donor samples. Sensitivity studies were also performed for the four multiplex systems. Our results show the efficiency, reliability, and accuracy of the IR system for the analysis of forensic samples. We also compared the efficiency of the multiplex protocol with ultraviolet (UV) technology. Paternity tests, undegraded DNA samples, and real forensic samples were analyzed with this approach based on IR technology and with UV-based automatic sequencers in combination with commercially-available kits. The comparability of the results with the widespread UV methods suggests that it is possible to exchange data between laboratories using the same core group of markers but different primer sets and detection methods.

21 CFR 892.1900 - Automatic radiographic film processor.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Automatic radiographic film processor. 892.1900... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1900 Automatic radiographic film processor. (a) Identification. An automatic radiographic film processor is a device intended to be used to...

21 CFR 892.1900 - Automatic radiographic film processor.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Automatic radiographic film processor. 892.1900... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1900 Automatic radiographic film processor. (a) Identification. An automatic radiographic film processor is a device intended to be used to...

21 CFR 892.1900 - Automatic radiographic film processor.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Automatic radiographic film processor. 892.1900... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1900 Automatic radiographic film processor. (a) Identification. An automatic radiographic film processor is a device intended to be used to...

21 CFR 892.1900 - Automatic radiographic film processor.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Automatic radiographic film processor. 892.1900... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1900 Automatic radiographic film processor. (a) Identification. An automatic radiographic film processor is a device intended to be used to...

21 CFR 892.1900 - Automatic radiographic film processor.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automatic radiographic film processor. 892.1900... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1900 Automatic radiographic film processor. (a) Identification. An automatic radiographic film processor is a device intended to be used to...

An automatic identification procedure to promote the use of FES-cycling training for hemiparetic patients.

PubMed

Ambrosini, Emilia; Ferrante, Simona; Schauer, Thomas; Ferrigno, Giancarlo; Molteni, Franco; Pedrocchi, Alessandra

2014-01-01

Cycling induced by Functional Electrical Stimulation (FES) training currently requires a manual setting of different parameters, which is a time-consuming and scarcely repeatable procedure. We proposed an automatic procedure for setting session-specific parameters optimized for hemiparetic patients. This procedure consisted of the identification of the stimulation strategy as the angular ranges during which FES drove the motion, the comparison between the identified strategy and the physiological muscular activation strategy, and the setting of the pulse amplitude and duration of each stimulated muscle. Preliminary trials on 10 healthy volunteers helped define the procedure. Feasibility tests on 8 hemiparetic patients (5 stroke, 3 traumatic brain injury) were performed. The procedure maximized the motor output within the tolerance constraint, identified a biomimetic strategy in 6 patients, and always lasted less than 5 minutes. Its reasonable duration and automatic nature make the procedure usable at the beginning of every training session, potentially enhancing the performance of FES-cycling training.

Automatic Identification of Critical Data Items in a Database to Mitigate the Effects of Malicious Insiders

NASA Astrophysics Data System (ADS)

White, Jonathan; Panda, Brajendra

A major concern for computer system security is the threat from malicious insiders who target and abuse critical data items in the system. In this paper, we propose a solution to enable automatic identification of critical data items in a database by way of data dependency relationships. This identification of critical data items is necessary because insider threats often target mission critical data in order to accomplish malicious tasks. Unfortunately, currently available systems fail to address this problem in a comprehensive manner. It is more difficult for non-experts to identify these critical data items because of their lack of familiarity and due to the fact that data systems are constantly changing. By identifying the critical data items automatically, security engineers will be better prepared to protect what is critical to the mission of the organization and also have the ability to focus their security efforts on these critical data items. We have developed an algorithm that scans the database logs and forms a directed graph showing which items influence a large number of other items and at what frequency this influence occurs. This graph is traversed to reveal the data items which have a large influence throughout the database system by using a novel metric based formula. These items are critical to the system because if they are maliciously altered or stolen, the malicious alterations will spread throughout the system, delaying recovery and causing a much more malignant effect. As these items have significant influence, they are deemed to be critical and worthy of extra security measures. Our proposal is not intended to replace existing intrusion detection systems, but rather is intended to complement current and future technologies. Our proposal has never been performed before, and our experimental results have shown that it is very effective in revealing critical data items automatically.

Automatically identifying health outcome information in MEDLINE records.

PubMed

Demner-Fushman, Dina; Few, Barbara; Hauser, Susan E; Thoma, George

2006-01-01

Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes. An annotation scheme based on an evidence-based medicine model for critical appraisal of evidence was developed and used to annotate 633 MEDLINE citations. Textual, structural, and meta-information features essential to outcome identification were learned from the created collection and used to develop an automatic system. Accuracy of automatic outcome identification was assessed in an intrinsic evaluation and in an extrinsic evaluation, in which ranking of MEDLINE search results obtained using PubMed Clinical Queries relied on identified outcome statements. The accuracy and positive predictive value of outcome identification were calculated. Effectiveness of the outcome-based ranking was measured using mean average precision and precision at rank 10. Automatic outcome identification achieved 88% to 93% accuracy. The positive predictive value of individual sentences identified as outcomes ranged from 30% to 37%. Outcome-based ranking improved retrieval accuracy, tripling mean average precision and achieving 389% improvement in precision at rank 10. Preliminary results in outcome-based document ranking show potential validity of the evidence-based medicine-model approach in timely delivery of information critical to clinical decision support at the point of service.

Analysis and automatic identification of sleep stages using higher order spectra.

PubMed

Acharya, U Rajendra; Chua, Eric Chern-Pin; Chua, Kuang Chua; Min, Lim Choo; Tamura, Toshiyo

2010-12-01

Electroencephalogram (EEG) signals are widely used to study the activity of the brain, such as to determine sleep stages. These EEG signals are nonlinear and non-stationary in nature. It is difficult to perform sleep staging by visual interpretation and linear techniques. Thus, we use a nonlinear technique, higher order spectra (HOS), to extract hidden information in the sleep EEG signal. In this study, unique bispectrum and bicoherence plots for various sleep stages were proposed. These can be used as visual aid for various diagnostics application. A number of HOS based features were extracted from these plots during the various sleep stages (Wakefulness, Rapid Eye Movement (REM), Stage 1-4 Non-REM) and they were found to be statistically significant with p-value lower than 0.001 using ANOVA test. These features were fed to a Gaussian mixture model (GMM) classifier for automatic identification. Our results indicate that the proposed system is able to identify sleep stages with an accuracy of 88.7%.

Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions

PubMed Central

Risteska Stojkoska, Biljana; Standl, Marie; Schulz, Holger

2017-01-01

Background Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. Methods The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. Results The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance

Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

PubMed

Zdravevski, Eftim; Risteska Stojkoska, Biljana; Standl, Marie; Schulz, Holger

2017-01-01

Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be achieved from

Automatic identification of artifacts in electrodermal activity data.

PubMed

Taylor, Sara; Jaques, Natasha; Chen, Weixuan; Fedor, Szymon; Sano, Akane; Picard, Rosalind

2015-01-01

Recently, wearable devices have allowed for long term, ambulatory measurement of electrodermal activity (EDA). Despite the fact that ambulatory recording can be noisy, and recording artifacts can easily be mistaken for a physiological response during analysis, to date there is no automatic method for detecting artifacts. This paper describes the development of a machine learning algorithm for automatically detecting EDA artifacts, and provides an empirical evaluation of classification performance. We have encoded our results into a freely available web-based tool for artifact and peak detection.

A new technology for automatic identification and sorting of plastics for recycling.

PubMed

Ahmad, S R

2004-10-01

A new technology for automatic sorting of plastics, based upon optical identification of fluorescence signatures of dyes, incorporated in such materials in trace concentrations prior to product manufacturing, is described. Three commercial tracers were selected primarily on the basis of their good absorbency in the 310-370 nm spectral band and their identifiable narrow-band fluorescence signatures in the visible band of the spectrum when present in binary combinations. This absorption band was selected because of the availability of strong emission lines in this band from a commercial Hg-arc lamp and high fluorescence quantum yields of the tracers at this excitation wavelength band. The plastics chosen for tracing and identification are HDPE, LDPE, PP, EVA, PVC and PET and the tracers were compatible and chemically non-reactive with the host matrices and did not affect the transparency of the plastics. The design of a monochromatic and collimated excitation source, the sensor system are described and their performances in identifying and sorting plastics doped with tracers at a few parts per million concentration levels are evaluated. In an industrial sorting system, the sensor was able to sort 300 mm long plastic bottles at a conveyor belt speed of 3.5 m.sec(-1) with a sorting purity of -95%. The limitation was imposed due to mechanical singulation irregularities at high speed and the limited processing speed of the computer used.

Ontology-based automatic identification of public health-related Turkish tweets.

PubMed

Küçük, Emine Ela; Yapar, Kürşad; Küçük, Dilek; Küçük, Doğan

2017-04-01

Social media analysis, such as the analysis of tweets, is a promising research topic for tracking public health concerns including epidemics. In this paper, we present an ontology-based approach to automatically identify public health-related Turkish tweets. The system is based on a public health ontology that we have constructed through a semi-automated procedure. The ontology concepts are expanded through a linguistically motivated relaxation scheme as the last stage of ontology development, before being integrated into our system to increase its coverage. The ultimate lexical resource which includes the terms corresponding to the ontology concepts is used to filter the Twitter stream so that a plausible tweet subset, including mostly public-health related tweets, can be obtained. Experiments are carried out on two million genuine tweets and promising precision rates are obtained. Also implemented within the course of the current study is a Web-based interface, to track the results of this identification system, to be used by the related public health staff. Hence, the current social media analysis study has both technical and practical contributions to the significant domain of public health. Copyright © 2017 Elsevier Ltd. All rights reserved.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

An automatic and efficient pipeline for disease gene identification through utilizing family-based sequencing data.

PubMed

Song, Dandan; Li, Ning; Liao, Lejian

2015-01-01

Due to the generation of enormous amounts of data at both lower costs as well as in shorter times, whole-exome sequencing technologies provide dramatic opportunities for identifying disease genes implicated in Mendelian disorders. Since upwards of thousands genomic variants can be sequenced in each exome, it is challenging to filter pathogenic variants in protein coding regions and reduce the number of missing true variants. Therefore, an automatic and efficient pipeline for finding disease variants in Mendelian disorders is designed by exploiting a combination of variants filtering steps to analyze the family-based exome sequencing approach. Recent studies on the Freeman-Sheldon disease are revisited and show that the proposed method outperforms other existing candidate gene identification methods.

Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

PubMed

González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

2015-03-01

A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

Automatic identification of watercourses in flat and engineered landscapes by computing the skeleton of a LiDAR point cloud

NASA Astrophysics Data System (ADS)

Broersen, Tom; Peters, Ravi; Ledoux, Hugo

2017-09-01

Drainage networks play a crucial role in protecting land against floods. It is therefore important to have an accurate map of the watercourses that form the drainage network. Previous work on the automatic identification of watercourses was typically based on grids, focused on natural landscapes, and used mostly the slope and curvature of the terrain. We focus in this paper on areas that are characterised by low-lying, flat, and engineered landscapes; these are characteristic to the Netherlands for instance. We propose a new methodology to identify watercourses automatically from elevation data, it uses solely a raw classified LiDAR point cloud as input. We show that by computing twice a skeleton of the point cloud-once in 2D and once in 3D-and that by using the properties of the skeletons we can identify most of the watercourses. We have implemented our methodology and tested it for three different soil types around Utrecht, the Netherlands. We were able to detect 98% of the watercourses for one soil type, and around 75% for the worst case, when we compared to a reference dataset that was obtained semi-automatically.

Automatic identification of bird targets with radar via patterns produced by wing flapping.

PubMed

Zaugg, Serge; Saporta, Gilbert; van Loon, Emiel; Schmaljohann, Heiko; Liechti, Felix

2008-09-06

Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical pattern due to wing flapping. The data were labelled by experts into the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a classification algorithm aimed at automatic recognition of bird targets. Variables related to signal intensity and wing flapping pattern were extracted (via continuous wavelet transform). We used support vector classifiers to build predictive models. We estimated classification performance via cross validation on four datasets. When data from the same dataset were used for training and testing the classifier, the classification performance was extremely to moderately high. When data from one dataset were used for training and the three remaining datasets were used as test sets, the performance was lower but still extremely to moderately high. This shows that the method generalizes well across different locations or times. Our method provides a substantial gain of time when birds must be identified in large collections of radar signals and it represents the first substantial step in developing a real time bird identification radar system. We provide some guidelines and ideas for future research.

Maritime over the Horizon Sensor Integration: High Frequency Surface-Wave-Radar and Automatic Identification System Data Integration Algorithm.

PubMed

Nikolic, Dejan; Stojkovic, Nikola; Lekic, Nikola

2018-04-09

To obtain the complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) which lies over the horizon (OTH) requires the integration of data obtained from various sensors. These sensors include: high frequency surface-wave-radar (HFSWR), satellite automatic identification system (SAIS) and land automatic identification system (LAIS). The algorithm proposed in this paper utilizes radar tracks obtained from the network of HFSWRs, which are already processed by a multi-target tracking algorithm and associates SAIS and LAIS data to the corresponding radar tracks, thus forming an integrated data pair. During the integration process, all HFSWR targets in the vicinity of AIS data are evaluated and the one which has the highest matching factor is used for data association. On the other hand, if there is multiple AIS data in the vicinity of a single HFSWR track, the algorithm still makes only one data pair which consists of AIS and HFSWR data with the highest mutual matching factor. During the design and testing, special attention is given to the latency of AIS data, which could be very high in the EEZs of developing countries. The algorithm is designed, implemented and tested in a real working environment. The testing environment is located in the Gulf of Guinea and includes a network of HFSWRs consisting of two HFSWRs, several coastal sites with LAIS receivers and SAIS data provided by provider of SAIS data.

RFID: A Revolution in Automatic Data Recognition

ERIC Educational Resources Information Center

Deal, Walter F., III

2004-01-01

Radio frequency identification, or RFID, is a generic term for technologies that use radio waves to automatically identify people or objects. There are several methods of identification, but the most common is to store a serial number that identifies a person or object, and perhaps other information, on a microchip that is attached to an antenna…

Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors

PubMed Central

Hübl, Johannes; McArdell, Brian W.; Walter, Fabian

2018-01-01

The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz), several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio. PMID:29789449

An Analysis of Serial Number Tracking Automatic Identification Technology as Used in Naval Aviation Programs

NASA Astrophysics Data System (ADS)

Csorba, Robert

2002-09-01

The Government Accounting Office found that the Navy, between 1996 and 1998, lost 3 billion in materiel in-transit. This thesis explores the benefits and cost of automatic identification and serial number tracking technologies under consideration by the Naval Supply Systems Command and the Naval Air Systems Command. Detailed cost-savings estimates are made for each aircraft type in the Navy inventory. Project and item managers of repairable components using Serial Number Tracking were surveyed as to the value of this system. It concludes that two thirds of the in-transit losses can be avoided with implementation of effective information technology-based logistics and maintenance tracking systems. Recommendations are made for specific steps and components of such an implementation. Suggestions are made for further research.

Visible and NIR spectral band combination to produce high security ID tags for automatic identification

NASA Astrophysics Data System (ADS)

Pérez-Cabré, Elisabet; Millán, María S.; Javidi, Bahram

2006-09-01

Verification of a piece of information and/or authentication of a given object or person are common operations carried out by automatic security systems that can be applied, for instance, to control the entrance to restricted areas, access to public buildings, identification of cardholders, etc. Vulnerability of such security systems may depend on the ease of counterfeiting the information used as a piece of identification for verification and authentication. To protect data against tampering, the signature that identifies an object is usually encrypted to avoid an easy recognition at human sight and an easy reproduction using conventional devices for imaging or scanning. To make counterfeiting even more difficult, we propose to combine data from visible and near infrared (NIR) spectral bands. By doing this, neither the visible content nor the NIR data by theirselves are sufficient to allow the signature recognition and thus, the identification of a given object. Only the appropriate combination of both signals permits a satisfactory authentication. In addition, the resulting signature is encrypted following a fully-phase encryption technique and the obtained complex-amplitude distribution is encoded on an ID tag. Spatial multiplexing of the encrypted signature allows us to build a distortion-invariant ID tag, so that remote authentication can be achieved even if the tag is captured under rotation or at different distances. We also explore the possibility of using partial information of the encrypted signature to simplify the ID tag design.

Automatic identification of individual killer whales.

PubMed

Brown, Judith C; Smaragdis, Paris; Nousek-McGregor, Anna

2010-09-01

Following the successful use of HMM and GMM models for classification of a set of 75 calls of northern resident killer whales into call types [Brown, J. C., and Smaragdis, P., J. Acoust. Soc. Am. 125, 221-224 (2009)], the use of these same methods has been explored for the identification of vocalizations from the same call type N2 of four individual killer whales. With an average of 20 vocalizations from each of the individuals the pairwise comparisons have an extremely high success rate of 80 to 100% and the identifications within the entire group yield around 78%.

Genetic fingerprinting proves cross-correlated automatic photo-identification of individuals as highly efficient in large capture–mark–recapture studies

PubMed Central

Drechsler, Axel; Helling, Tobias; Steinfartz, Sebastian

2015-01-01

Capture–mark–recapture (CMR) approaches are the backbone of many studies in population ecology to gain insight on the life cycle, migration, habitat use, and demography of target species. The reliable and repeatable recognition of an individual throughout its lifetime is the basic requirement of a CMR study. Although invasive techniques are available to mark individuals permanently, noninvasive methods for individual recognition mainly rest on photographic identification of external body markings, which are unique at the individual level. The re-identification of an individual based on comparing shape patterns of photographs by eye is commonly used. Automated processes for photographic re-identification have been recently established, but their performance in large datasets (i.e., > 1000 individuals) has rarely been tested thoroughly. Here, we evaluated the performance of the program AMPHIDENT, an automatic algorithm to identify individuals on the basis of ventral spot patterns in the great crested newt (Triturus cristatus) versus the genotypic fingerprint of individuals based on highly polymorphic microsatellite loci using GENECAP. Between 2008 and 2010, we captured, sampled and photographed adult newts and calculated for 1648 samples/photographs recapture rates for both approaches. Recapture rates differed slightly with 8.34% for GENECAP and 9.83% for AMPHIDENT. With an estimated rate of 2% false rejections (FRR) and 0.00% false acceptances (FAR), AMPHIDENT proved to be a highly reliable algorithm for CMR studies of large datasets. We conclude that the application of automatic recognition software of individual photographs can be a rather powerful and reliable tool in noninvasive CMR studies for a large number of individuals. Because the cross-correlation of standardized shape patterns is generally applicable to any pattern that provides enough information, this algorithm is capable of becoming a single application with broad use in CMR studies for many

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish.

PubMed

Vieira, Manuel; Fonseca, Paulo J; Amorim, M Clara P; Teixeira, Carlos J C

2015-12-01

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.

Automatic modal identification of cable-supported bridges instrumented with a long-term monitoring system

NASA Astrophysics Data System (ADS)

Ni, Y. Q.; Fan, K. Q.; Zheng, G.; Chan, T. H. T.; Ko, J. M.

2003-08-01

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm to identify modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers deployed on the cable-stayed Ting Kau Bridge. With the continuously identified results, normal variability of modal vectors caused by varying environmental and operational conditions is observed. Such observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring applications.

Space-Based Identification of Archaeological Illegal Excavations and a New Automatic Method for Looting Feature Extraction in Desert Areas

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Masini, Nicola

2018-06-01

The identification and quantification of disturbance of archaeological sites has been generally approached by visual inspection of optical aerial or satellite pictures. In this paper, we briefly summarize the state of the art of the traditionally satellite-based approaches for looting identification and propose a new automatic method for archaeological looting feature extraction approach (ALFEA). It is based on three steps: the enhancement using spatial autocorrelation, unsupervised classification, and segmentation. ALFEA has been applied to Google Earth images of two test areas, selected in desert environs in Syria (Dura Europos), and in Peru (Cahuachi-Nasca). The reliability of ALFEA was assessed through field surveys in Peru and visual inspection for the Syrian case study. Results from the evaluation procedure showed satisfactory performance from both of the two analysed test cases with a rate of success higher than 90%.

Automatic identification of the reference system based on the fourth ventricular landmarks in T1-weighted MR images.

PubMed

Fu, Yili; Gao, Wenpeng; Chen, Xiaoguang; Zhu, Minwei; Shen, Weigao; Wang, Shuguo

2010-01-01

The reference system based on the fourth ventricular landmarks (including the fastigial point and ventricular floor plane) is used in medical image analysis of the brain stem. The objective of this study was to develop a rapid, robust, and accurate method for the automatic identification of this reference system on T1-weighted magnetic resonance images. The fully automated method developed in this study consisted of four stages: preprocessing of the data set, expectation-maximization algorithm-based extraction of the fourth ventricle in the region of interest, a coarse-to-fine strategy for identifying the fastigial point, and localization of the base point. The method was evaluated on 27 Brain Web data sets qualitatively and 18 Internet Brain Segmentation Repository data sets and 30 clinical scans quantitatively. The results of qualitative evaluation indicated that the method was robust to rotation, landmark variation, noise, and inhomogeneity. The results of quantitative evaluation indicated that the method was able to identify the reference system with an accuracy of 0.7 +/- 0.2 mm for the fastigial point and 1.1 +/- 0.3 mm for the base point. It took <6 seconds for the method to identify the related landmarks on a personal computer with an Intel Core 2 6300 processor and 2 GB of random-access memory. The proposed method for the automatic identification of the reference system based on the fourth ventricular landmarks was shown to be rapid, robust, and accurate. The method has potentially utility in image registration and computer-aided surgery.

An automatic microseismic or acoustic emission arrival identification scheme with deep recurrent neural networks

NASA Astrophysics Data System (ADS)

Zheng, Jing; Lu, Jiren; Peng, Suping; Jiang, Tianqi

2018-02-01

The conventional arrival pick-up algorithms cannot avoid the manual modification of the parameters for the simultaneous identification of multiple events under different signal-to-noise ratios (SNRs). Therefore, in order to automatically obtain the arrivals of multiple events with high precision under different SNRs, in this study an algorithm was proposed which had the ability to pick up the arrival of microseismic or acoustic emission events based on deep recurrent neural networks. The arrival identification was performed using two important steps, which included a training phase and a testing phase. The training process was mathematically modelled by deep recurrent neural networks using Long Short-Term Memory architecture. During the testing phase, the learned weights were utilized to identify the arrivals through the microseismic/acoustic emission data sets. The data sets were obtained by rock physics experiments of the acoustic emission. In order to obtain the data sets under different SNRs, this study added random noise to the raw experiments' data sets. The results showed that the outcome of the proposed method was able to attain an above 80 per cent hit-rate at SNR 0 dB, and an approximately 70 per cent hit-rate at SNR -5 dB, with an absolute error in 10 sampling points. These results indicated that the proposed method had high selection precision and robustness.

Automatic Publication of a MIS Product to GeoNetwork: Case of the AIS Indexer

DTIC Science & Technology

2012-11-01

installation and configuration The following instructions are for installing and configuring the software packages Java 1.6 and MySQL 5.5 which are...An Automatic Identification System (AIS) reception indexer Java application was developed in the summer of 2011, based on the work of Lapinski and...release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT An Automatic Identification System (AIS) reception indexer Java application was

Research on the Additional Secondary Phase Factor for Automatic Identification System Signals Transmitted over a Rough Sea Surface

PubMed Central

Zhang, Shufang; Sun, Xiaowen

2018-01-01

This paper investigates the Additional Secondary Phase Factor (ASF) characteristics of Automatic Identification System (AIS) signals spreading over a rough sea surface. According to the change of the ASFs for AIS signals in different signal form, the influences of the different propagation conditions on the ASFs are analyzed. The expression, numerical calculation, and simulation analysis of the ASFs of AIS signal are performed in the rough sea surface. The results contribute to the high-accuracy propagation delay measurement of AIS signals spreading over the rough sea surface as, well as providing a reference for reliable communication link design in marine engineering for Very High Frequency (VHF) signals. PMID:29462995

Benefit Analyses of Technologies for Automatic Identification to Be Implemented in the Healthcare Sector

NASA Astrophysics Data System (ADS)

Krey, Mike; Schlatter, Ueli

The tasks and objectives of automatic identification (Auto-ID) are to provide information on goods and products. It has already been established for years in the areas of logistics and trading and can no longer be ignored by the German healthcare sector. Some German hospitals have already discovered the capabilities of Auto-ID. Improvements in quality, safety and reductions in risk, cost and time are aspects and areas where improvements are achievable. Privacy protection, legal restraints, and the personal rights of patients and staff members are just a few aspects which make the heath care sector a sensible field for the implementation of Auto-ID. Auto-ID in this context contains the different technologies, methods and products for the registration, provision and storage of relevant data. With the help of a quantifiable and science-based evaluation, an answer is sought as to which Auto-ID has the highest capability to be implemented in healthcare business.

Automatic and Direct Identification of Blink Components from Scalp EEG

PubMed Central

Kong, Wanzeng; Zhou, Zhanpeng; Hu, Sanqing; Zhang, Jianhai; Babiloni, Fabio; Dai, Guojun

2013-01-01

Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn't need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects. PMID:23959240

Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

PubMed

Giménez, Estela; Gay, Marina; Vilaseca, Marta

2017-01-30

Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans. Copyright © 2016 Elsevier B.V. All rights reserved.

Need of a consistent and convenient nucleus identification in ENDF files for the automatic construction of the depletion chains

NASA Astrophysics Data System (ADS)

Mosca, Pietro; Mounier, Claude

2016-03-01

The automatic construction of evolution chains recently implemented in GALILEE system is based on the analysis of several ENDF files : the multigroup production cross sections present in the GENDF files processed by NJOY from the ENDF evaluation, the decay file and the fission product yields (FPY) file. In this context, this paper highlights the importance of the nucleus identification to properly interconnect the data mentioned above. The first part of the paper describes the present status of the nucleus identification among the several ENDF files focusing, in particular, on the use of the excited state number and of the isomeric state number. The second part reviews the problems encountered during the automatic construction of the depletion chains using recent ENDF data. The processing of the JEFF-3.1.1, ENDF/B-VII.0 (decay and FPY) and the JEFF-3.2 (production cross section) points out problems about the compliance or not of the nucleus identifiers with the ENDF-6 format and sometimes the inconsistencies among the various ENDF files. In addition, the analysis of EAF-2003 and EAF-2010 shows some incoherence between the ZA product identifier and the reaction identifier MT for the reactions (n, pα) and (n, 2np). As a main result of this work, our suggestion is to change the ENDF format using systematically the isomeric state number to identify the nuclei. This proposal is already compliant to a huge amount ENDF data that are not in agreement with the present ENDF format. This choice is the most convenient because, ultimately, it allows one to give human readable names to the nuclei of the depletion chains.

FragIdent--automatic identification and characterisation of cDNA-fragments.

PubMed

Seelow, Dominik; Goehler, Heike; Hoffmann, Katrin

2009-03-02

Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments. Even in characterised libraries, a considerable number of clones are wrongly annotated. Furthermore, mix-ups can happen in the laboratory. It is therefore essential to the relevance of experimental results to confirm or determine the identity of the employed cDNA fragments. However, the manual approach for the characterisation of these fragments using BLAST web interfaces is not suited for larger number of sequences and so far, no user-friendly software is publicly available. Here we present the development of FragIdent, an application for the automatic identification of open reading frames (ORFs) within cDNA-fragments. The software performs BLAST analyses to identify the genes represented by the sequences and suggests primers to complete the sequencing of the whole insert. Gene-specific information as well as the protein domains encoded by the cDNA fragment are retrieved from Internet-based databases and included in the output. The application features an intuitive graphical interface and is designed for researchers without any bioinformatics skills. It is suited for projects comprising up to several hundred different clones. We used FragIdent to identify 84 cDNA clones from a yeast two-hybrid experiment. Furthermore, we identified 131 protein domains within our analysed clones. The source code is freely available from our homepage at http://compbio.charite.de/genetik/FragIdent/.

Research into automatic recognition of joints in human symmetrical movements

NASA Astrophysics Data System (ADS)

Fan, Yifang; Li, Zhiyu

2008-03-01

High speed photography is a major means of collecting data from human body movement. It enables the automatic identification of joints, which brings great significance to the research, treatment and recovery of injuries, the analysis to the diagnosis of sport techniques and the ergonomics. According to the features that when the adjacent joints of human body are in planetary motion, their distance remains the same, and according to the human body joint movement laws (such as the territory of the articular anatomy and the kinematic features), a new approach is introduced to process the image thresholding of joints filmed by the high speed camera, to automatically identify the joints and to automatically trace the joint points (by labeling markers at the joints). Based upon the closure of marking points, automatic identification can be achieved through thresholding treatment. Due to the screening frequency and the laws of human segment movement, when the marking points have been initialized, their automatic tracking can be achieved with the progressive sequential images.Then the testing results, the data from three-dimensional force platform and the characteristics that human body segment will only rotate around the closer ending segment when the segment has no boding force and only valid to the conservative force all tell that after being analyzed kinematically, the approach is approved to be valid.

Automatic topics segmentation for TV news video

NASA Astrophysics Data System (ADS)

Hmayda, Mounira; Ejbali, Ridha; Zaied, Mourad

2017-03-01

Automatic identification of television programs in the TV stream is an important task for operating archives. This article proposes a new spatio-temporal approach to identify the programs in TV stream into two main steps: First, a reference catalogue for video features visual jingles built. We operate the features that characterize the instances of the same program type to identify the different types of programs in the flow of television. The role of video features is to represent the visual invariants for each visual jingle using appropriate automatic descriptors for each television program. On the other hand, programs in television streams are identified by examining the similarity of the video signal for visual grammars in the catalogue. The main idea of the identification process is to compare the visual similarity of the video signal features in the flow of television to the catalogue. After presenting the proposed approach, the paper overviews encouraging experimental results on several streams extracted from different channels and compounds of several programs.

Management of natural resources through automatic cartographic inventory

NASA Technical Reports Server (NTRS)

Rey, P.; Gourinard, Y.; Cambou, F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Significant results of the ARNICA program from August 1972 - January 1973 have been: (1) establishment of image to object correspondence codes for all types of soil use and forestry in northern Spain; (2) establishment of a transfer procedure between qualitative (remote identification and remote interpretation) and quantitative (numerization, storage, automatic statistical cartography) use of images; (3) organization of microdensitometric data processing and automatic cartography software; and (4) development of a system for measuring reflectance simultaneous with imagery.

A support vector machine approach to the automatic identification of fluorescence spectra emitted by biological agents

NASA Astrophysics Data System (ADS)

Gelfusa, M.; Murari, A.; Lungaroni, M.; Malizia, A.; Parracino, S.; Peluso, E.; Cenciarelli, O.; Carestia, M.; Pizzoferrato, R.; Vega, J.; Gaudio, P.

2016-10-01

Two of the major new concerns of modern societies are biosecurity and biosafety. Several biological agents (BAs) such as toxins, bacteria, viruses, fungi and parasites are able to cause damage to living systems either humans, animals or plants. Optical techniques, in particular LIght Detection And Ranging (LIDAR), based on the transmission of laser pulses and analysis of the return signals, can be successfully applied to monitoring the release of biological agents into the atmosphere. It is well known that most of biological agents tend to emit specific fluorescence spectra, which in principle allow their detection and identification, if excited by light of the appropriate wavelength. For these reasons, the detection of the UVLight Induced Fluorescence (UV-LIF) emitted by BAs is particularly promising. On the other hand, the stand-off detection of BAs poses a series of challenging issues; one of the most severe is the automatic discrimination between various agents which emit very similar fluorescence spectra. In this paper, a new data analysis method, based on a combination of advanced filtering techniques and Support Vector Machines, is described. The proposed approach covers all the aspects of the data analysis process, from filtering and denoising to automatic recognition of the agents. A systematic series of numerical tests has been performed to assess the potential and limits of the proposed methodology. The first investigations of experimental data have already given very encouraging results.

Automatic contact in DYNA3D for vehicle crashworthiness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whirley, R.G.; Engelmann, B.E.

1993-07-15

This paper presents a new formulation for the automatic definition and treatment of mechanical contact in explicit nonlinear finite element analysis. Automatic contact offers the benefits of significantly reduced model construction time and fewer opportunities for user error, but faces significant challenges in reliability and computational costs. This paper discusses in detail a new four-step automatic contact algorithm. Key aspects of the proposed method include automatic identification of adjacent and opposite surfaces in the global search phase, and the use of a smoothly varying surface normal which allows a consistent treatment of shell intersection and corner contact conditions without ad-hocmore » rules. The paper concludes with three examples which illustrate the performance of the newly proposed algorithm in the public DYNA3D code.« less

Automatic integration of data from dissimilar sensors

NASA Astrophysics Data System (ADS)

Citrin, W. I.; Proue, R. W.; Thomas, J. W.

The present investigation is concerned with the automatic integration of radar and electronic support measures (ESM) sensor data, and with the development of a method for the automatical integration of identification friend or foe (IFF) and radar sensor data. On the basis of the two considered proojects, significant advances have been made in the areas of sensor data integration. It is pointed out that the log likelihood approach in sensor data correlation is appropriate for both similar and dissimilar sensor data. Attention is given to the real time integration of radar and ESM sensor data, and a radar ESM correlation simulation program.

Automatic identification of physical activity types and sedentary behaviors from triaxial accelerometer: laboratory-based calibrations are not enough.

PubMed

Bastian, Thomas; Maire, Aurélia; Dugas, Julien; Ataya, Abbas; Villars, Clément; Gris, Florence; Perrin, Emilie; Caritu, Yanis; Doron, Maeva; Blanc, Stéphane; Jallon, Pierre; Simon, Chantal

2015-03-15

"Objective" methods to monitor physical activity and sedentary patterns in free-living conditions are necessary to further our understanding of their impacts on health. In recent years, many software solutions capable of automatically identifying activity types from portable accelerometry data have been developed, with promising results in controlled conditions, but virtually no reports on field tests. An automatic classification algorithm initially developed using laboratory-acquired data (59 subjects engaging in a set of 24 standardized activities) to discriminate between 8 activity classes (lying, slouching, sitting, standing, walking, running, and cycling) was applied to data collected in the field. Twenty volunteers equipped with a hip-worn triaxial accelerometer performed at their own pace an activity set that included, among others, activities such as walking the streets, running, cycling, and taking the bus. Performances of the laboratory-calibrated classification algorithm were compared with those of an alternative version of the same model including field-collected data in the learning set. Despite good results in laboratory conditions, the performances of the laboratory-calibrated algorithm (assessed by confusion matrices) decreased for several activities when applied to free-living data. Recalibrating the algorithm with data closer to real-life conditions and from an independent group of subjects proved useful, especially for the detection of sedentary behaviors while in transports, thereby improving the detection of overall sitting (sensitivity: laboratory model = 24.9%; recalibrated model = 95.7%). Automatic identification methods should be developed using data acquired in free-living conditions rather than data from standardized laboratory activity sets only, and their limits carefully tested before they are used in field studies. Copyright © 2015 the American Physiological Society.

Automatic script identification from images using cluster-based templates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hochberg, J.; Kerns, L.; Kelly, P.

We have developed a technique for automatically identifying the script used to generate a document that is stored electronically in bit image form. Our approach differs from previous work in that the distinctions among scripts are discovered by an automatic learning procedure, without any handson analysis. We first develop a set of representative symbols (templates) for each script in our database (Cyrillic, Roman, etc.). We do this by identifying all textual symbols in a set of training documents, scaling each symbol to a fixed size, clustering similar symbols, pruning minor clusters, and finding each cluster`s centroid. To identify a newmore » document`s script, we identify and scale a subset of symbols from the document and compare them to the templates for each script. We choose the script whose templates provide the best match. Our current system distinguishes among the Armenian, Burmese, Chinese, Cyrillic, Ethiopic, Greek, Hebrew, Japanese, Korean, Roman, and Thai scripts with over 90% accuracy.« less

Estimating Ocean Currents from Automatic Identification System Based Ship Drift Measurements

NASA Astrophysics Data System (ADS)

Jakub, Thomas D.

Ship drift is a technique that has been used over the last century and a half to estimate ocean currents. Several of the shortcomings of the ship drift technique include obtaining the data from multiple ships, the time delay in getting those ship positions to a data center for processing and the limited resolution based on the amount of time between position measurements. These shortcomings can be overcome through the use of the Automatic Identification System (AIS). AIS enables more precise ocean current estimates, the option of finer resolution and more timely estimates. In this work, a demonstration of the use of AIS to compute ocean currents is performed. A corresponding error and sensitivity analysis is performed to help identify under which conditions errors will be smaller. A case study in San Francisco Bay with constant AIS message updates was compared against high frequency radar and demonstrated ocean current magnitude residuals of 19 cm/s for ship tracks in a high signal to noise environment. These ship tracks were only minutes long compared to the normally 12 to 24 hour ship tracks. The Gulf of Mexico case study demonstrated the ability to estimate ocean currents over longer baselines and identified the dependency of the estimates on the accuracy of time measurements. Ultimately, AIS measurements when combined with ship drift can provide another method of estimating ocean currents, particularly when other measurements techniques are not available.

Suspect/foil identification in actual crimes and in the laboratory: a reality monitoring analysis.

PubMed

Behrman, Bruce W; Richards, Regina E

2005-06-01

Four reality monitoring variables were used to discriminate suspect from foil identifications in 183 actual criminal cases. Four hundred sixty-one identification attempts based on five and six-person lineups were analyzed. These identification attempts resulted in 238 suspect identifications and 68 foil identifications. Confidence, automatic processing, eliminative processing and feature use comprised the set of reality monitoring variables. Thirty-five verbal confidence phrases taken from police reports were assigned numerical values on a 10-point confidence scale. Automatic processing identifications were those that occurred "immediately" or "without hesitation." Eliminative processing identifications occurred when witnesses compared or eliminated persons in the lineups. Confidence, automatic processing and eliminative processing were significant predictors, but feature use was not. Confidence was the most effective discriminator. In cases that involved substantial evidence extrinsic to the identification 43% of the suspect identifications were made with high confidence, whereas only 10% of the foil identifications were made with high confidence. The results of a laboratory study using the same predictors generally paralleled the archival results. Forensic implications are discussed.

Automatic photointerpretation for plant species and stress identification (ERTS-A1)

NASA Technical Reports Server (NTRS)

Swanlund, G. D. (Principal Investigator); Kirvida, L.; Johnson, G. R.

1973-01-01

The author has identified the following significant results. Automatic stratification of forested land from ERTS-1 data provides a valuable tool for resource management. The results are useful for wood product yield estimates, recreation and wildlife management, forest inventory, and forest condition monitoring. Automatic procedures based on both multispectral and spatial features are evaluated. With five classes, training and testing on the same samples, classification accuracy of 74 percent was achieved using the MSS multispectral features. When adding texture computed from 8 x 8 arrays, classification accuracy of 90 percent was obtained.

Automatic tracking of wake vortices using ground-wind sensor data

DOT National Transportation Integrated Search

1977-01-03

Algorithms for automatic tracking of wake vortices using ground-wind anemometer : data are developed. Methods of bad-data suppression, track initiation, and : track termination are included. An effective sensor-failure detection-and identification : ...

Automatic identification of abstract online groups

DOEpatents

Engel, David W; Gregory, Michelle L; Bell, Eric B; Cowell, Andrew J; Piatt, Andrew W

2014-04-15

Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.

Auto identification technology and its impact on patient safety in the Operating Room of the Future.

PubMed

Egan, Marie T; Sandberg, Warren S

2007-03-01

Automatic identification technologies, such as bar coding and radio frequency identification, are ubiquitous in everyday life but virtually nonexistent in the operating room. User expectations, based on everyday experience with automatic identification technologies, have generated much anticipation that these systems will improve readiness, workflow, and safety in the operating room, with minimal training requirements. We report, in narrative form, a multi-year experience with various automatic identification technologies in the Operating Room of the Future Project at Massachusetts General Hospital. In each case, the additional human labor required to make these ;labor-saving' technologies function in the medical environment has proved to be their undoing. We conclude that while automatic identification technologies show promise, significant barriers to realizing their potential still exist. Nevertheless, overcoming these obstacles is necessary if the vision of an operating room of the future in which all processes are monitored, controlled, and optimized is to be achieved.

Automatic retinal interest evaluation system (ARIES).

PubMed

Yin, Fengshou; Wong, Damon Wing Kee; Yow, Ai Ping; Lee, Beng Hai; Quan, Ying; Zhang, Zhuo; Gopalakrishnan, Kavitha; Li, Ruoying; Liu, Jiang

2014-01-01

In recent years, there has been increasing interest in the use of automatic computer-based systems for the detection of eye diseases such as glaucoma, age-related macular degeneration and diabetic retinopathy. However, in practice, retinal image quality is a big concern as automatic systems without consideration of degraded image quality will likely generate unreliable results. In this paper, an automatic retinal image quality assessment system (ARIES) is introduced to assess both image quality of the whole image and focal regions of interest. ARIES achieves 99.54% accuracy in distinguishing fundus images from other types of images through a retinal image identification step in a dataset of 35342 images. The system employs high level image quality measures (HIQM) to perform image quality assessment, and achieves areas under curve (AUCs) of 0.958 and 0.987 for whole image and optic disk region respectively in a testing dataset of 370 images. ARIES acts as a form of automatic quality control which ensures good quality images are used for processing, and can also be used to alert operators of poor quality images at the time of acquisition.

Investigation of an automatic trim algorithm for restructurable aircraft control

NASA Technical Reports Server (NTRS)

Weiss, J.; Eterno, J.; Grunberg, D.; Looze, D.; Ostroff, A.

1986-01-01

This paper develops and solves an automatic trim problem for restructurable aircraft control. The trim solution is applied as a feed-forward control to reject measurable disturbances following control element failures. Disturbance rejection and command following performances are recovered through the automatic feedback control redesign procedure described by Looze et al. (1985). For this project the existence of a failure detection mechanism is assumed, and methods to cope with potential detection and identification inaccuracies are addressed.

Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle.

PubMed

Diaz-Varela, R A; Zarco-Tejada, P J; Angileri, V; Loudjani, P

2014-02-15

Agricultural terraces are features that provide a number of ecosystem services. As a result, their maintenance is supported by measures established by the European Common Agricultural Policy (CAP). In the framework of CAP implementation and monitoring, there is a current and future need for the development of robust, repeatable and cost-effective methodologies for the automatic identification and monitoring of these features at farm scale. This is a complex task, particularly when terraces are associated to complex vegetation cover patterns, as happens with permanent crops (e.g. olive trees). In this study we present a novel methodology for automatic and cost-efficient identification of terraces using only imagery from commercial off-the-shelf (COTS) cameras on board unmanned aerial vehicles (UAVs). Using state-of-the-art computer vision techniques, we generated orthoimagery and digital surface models (DSMs) at 11 cm spatial resolution with low user intervention. In a second stage, these data were used to identify terraces using a multi-scale object-oriented classification method. Results show the potential of this method even in highly complex agricultural areas, both regarding DSM reconstruction and image classification. The UAV-derived DSM had a root mean square error (RMSE) lower than 0.5 m when the height of the terraces was assessed against field GPS data. The subsequent automated terrace classification yielded an overall accuracy of 90% based exclusively on spectral and elevation data derived from the UAV imagery. Copyright © 2014 Elsevier Ltd. All rights reserved.

[The maintenance of automatic analysers and associated documentation].

PubMed

Adjidé, V; Fournier, P; Vassault, A

2010-12-01

The maintenance of automatic analysers and associated documentation taking part in the requirements of the ISO 15189 Standard and the French regulation as well have to be defined in the laboratory policy. The management of the periodic maintenance and documentation shall be implemented and fulfilled. The organisation of corrective maintenance has to be managed to avoid interruption of the task of the laboratory. The different recommendations concern the identification of materials including automatic analysers, the environmental conditions to take into account, the documentation provided by the manufacturer and documents prepared by the laboratory including procedures for maintenance.

Integration of low level and ontology derived features for automatic weapon recognition and identification

NASA Astrophysics Data System (ADS)

Sirakov, Nikolay M.; Suh, Sang; Attardo, Salvatore

2011-06-01

This paper presents a further step of a research toward the development of a quick and accurate weapons identification methodology and system. A basic stage of this methodology is the automatic acquisition and updating of weapons ontology as a source of deriving high level weapons information. The present paper outlines the main ideas used to approach the goal. In the next stage, a clustering approach is suggested on the base of hierarchy of concepts. An inherent slot of every node of the proposed ontology is a low level features vector (LLFV), which facilitates the search through the ontology. Part of the LLFV is the information about the object's parts. To partition an object a new approach is presented capable of defining the objects concavities used to mark the end points of weapon parts, considered as convexities. Further an existing matching approach is optimized to determine whether an ontological object matches the objects from an input image. Objects from derived ontological clusters will be considered for the matching process. Image resizing is studied and applied to decrease the runtime of the matching approach and investigate its rotational and scaling invariance. Set of experiments are preformed to validate the theoretical concepts.

Automatic detection of patient identification and positioning errors in radiation therapy treatment using 3-dimensional setup images.

PubMed

Jani, Shyam S; Low, Daniel A; Lamb, James M

2015-01-01

To develop an automated system that detects patient identification and positioning errors between 3-dimensional computed tomography (CT) and kilovoltage CT planning images. Planning kilovoltage CT images were collected for head and neck (H&N), pelvis, and spine treatments with corresponding 3-dimensional cone beam CT and megavoltage CT setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. For positioning errors, setup and planning images were misaligned by 1 to 5 cm in the 6 anatomical directions for H&N and pelvis patients. Spinal misalignments were simulated by misaligning to adjacent vertebral bodies. Image pairs were assessed using commonly used image similarity metrics as well as custom-designed metrics. Linear discriminant analysis classification models were trained and tested on the imaging datasets, and misclassification error (MCE), sensitivity, and specificity parameters were estimated using 10-fold cross-validation. For patient identification, our workflow produced MCE estimates of 0.66%, 1.67%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivity and specificity ranged from 97.5% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 95.4% and 97.7%. MCEs for 1-cm H&N/pelvis misalignments were 1.3%/5.1% and 9.1%/8.6% for TomoTherapy and TrueBeam images, respectively. Two-centimeter MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. MCEs for vertebral body misalignments were 4.8% and 3.6% for TomoTherapy and TrueBeam images, respectively. Patient identification and gross misalignment errors can be robustly and automatically detected using 3-dimensional setup images of different energies across 3 commonly treated anatomical sites. Copyright © 2015 American Society for Radiation Oncology. Published by

Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae).

PubMed

Wang, Jiang-Ning; Chen, Xiao-Lin; Hou, Xin-Wen; Zhou, Li-Bing; Zhu, Chao-Dong; Ji, Li-Qiang

2017-07-01

Many species of Tephritidae are damaging to fruit, which might negatively impact international fruit trade. Automatic or semi-automatic identification of fruit flies are greatly needed for diagnosing causes of damage and quarantine protocols for economically relevant insects. A fruit fly image identification system named AFIS1.0 has been developed using 74 species belonging to six genera, which include the majority of pests in the Tephritidae. The system combines automated image identification and manual verification, balancing operability and accuracy. AFIS1.0 integrates image analysis and expert system into a content-based image retrieval framework. In the the automatic identification module, AFIS1.0 gives candidate identification results. Afterwards users can do manual selection based on comparing unidentified images with a subset of images corresponding to the automatic identification result. The system uses Gabor surface features in automated identification and yielded an overall classification success rate of 87% to the species level by Independent Multi-part Image Automatic Identification Test. The system is useful for users with or without specific expertise on Tephritidae in the task of rapid and effective identification of fruit flies. It makes the application of computer vision technology to fruit fly recognition much closer to production level. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

A new methodology for automatic detection of reference points in 3D cephalometry: A pilot study.

PubMed

Ed-Dhahraouy, Mohammed; Riri, Hicham; Ezzahmouly, Manal; Bourzgui, Farid; El Moutaoukkil, Abdelmajid

2018-04-05

The aim of this study was to develop a new method for an automatic detection of reference points in 3D cephalometry to overcome the limits of 2D cephalometric analyses. A specific application was designed using the C++ language for automatic and manual identification of 21 (reference) points on the craniofacial structures. Our algorithm is based on the implementation of an anatomical and geometrical network adapted to the craniofacial structure. This network was constructed based on the anatomical knowledge of the 3D cephalometric (reference) points. The proposed algorithm was tested on five CBCT images. The proposed approach for the automatic 3D cephalometric identification was able to detect 21 points with a mean error of 2.32mm. In this pilot study, we propose an automated methodology for the identification of the 3D cephalometric (reference) points. A larger sample will be implemented in the future to assess the method validity and reliability. Copyright © 2018 CEO. Published by Elsevier Masson SAS. All rights reserved.

Automatic measurement of images on astrometric plates

NASA Astrophysics Data System (ADS)

Ortiz Gil, A.; Lopez Garcia, A.; Martinez Gonzalez, J. M.; Yershov, V.

1994-04-01

We present some results on the process of automatic detection and measurement of objects in overlapped fields of astrometric plates. The main steps of our algorithm are the following: determination of the Scale and Tilt between charge coupled devices (CCD) and microscope coordinate systems and estimation of signal-to-noise ratio in each field;--image identification and improvement of its position and size;--image final centering;--image selection and storage. Several parameters allow the use of variable criteria for image identification, characterization and selection. Problems related with faint images and crowded fields will be approached by special techniques (morphological filters, histogram properties and fitting models).

Automatic Identification and Organization of Index Terms for Interactive Browsing.

ERIC Educational Resources Information Center

Wacholder, Nina; Evans, David K.; Klavans, Judith L.

The potential of automatically generated indexes for information access has been recognized for several decades, but the quantity of text and the ambiguity of natural language processing have made progress at this task more difficult than was originally foreseen. Recently, a body of work on development of interactive systems to support phrase…

Assessing sound exposure from shipping in coastal waters using a single hydrophone and Automatic Identification System (AIS) data.

PubMed

Merchant, Nathan D; Witt, Matthew J; Blondel, Philippe; Godley, Brendan J; Smith, George H

2012-07-01

Underwater noise from shipping is a growing presence throughout the world's oceans, and may be subjecting marine fauna to chronic noise exposure with potentially severe long-term consequences. The coincidence of dense shipping activity and sensitive marine ecosystems in coastal environments is of particular concern, and noise assessment methodologies which describe the high temporal variability of sound exposure in these areas are needed. We present a method of characterising sound exposure from shipping using continuous passive acoustic monitoring combined with Automatic Identification System (AIS) shipping data. The method is applied to data recorded in Falmouth Bay, UK. Absolute and relative levels of intermittent ship noise contributions to the 24-h sound exposure level are determined using an adaptive threshold, and the spatial distribution of potential ship sources is then analysed using AIS data. This technique can be used to prioritize shipping noise mitigation strategies in coastal marine environments. Copyright © 2012 Elsevier Ltd. All rights reserved.

33 CFR 164.46 - Automatic Identification System (AIS).

Code of Federal Regulations, 2014 CFR

2014-07-01

... (AIS). 164.46 Section 164.46 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND... Identification System (AIS). (a) The following vessels must have a properly installed, operational, type approved AIS as of the date specified: (1) Self-propelled vessels of 65 feet or more in length, other than...

33 CFR 164.46 - Automatic Identification System (AIS).

Code of Federal Regulations, 2013 CFR

2013-07-01

... (AIS). 164.46 Section 164.46 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND... Identification System (AIS). (a) The following vessels must have a properly installed, operational, type approved AIS as of the date specified: (1) Self-propelled vessels of 65 feet or more in length, other than...

33 CFR 164.46 - Automatic Identification System (AIS).

Code of Federal Regulations, 2010 CFR

2010-07-01

... (AIS). 164.46 Section 164.46 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND... Identification System (AIS). (a) The following vessels must have a properly installed, operational, type approved AIS as of the date specified: (1) Self-propelled vessels of 65 feet or more in length, other than...

33 CFR 164.46 - Automatic Identification System (AIS).

Code of Federal Regulations, 2011 CFR

2011-07-01

... (AIS). 164.46 Section 164.46 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND... Identification System (AIS). (a) The following vessels must have a properly installed, operational, type approved AIS as of the date specified: (1) Self-propelled vessels of 65 feet or more in length, other than...

33 CFR 164.46 - Automatic Identification System (AIS).

Code of Federal Regulations, 2012 CFR

2012-07-01

... (AIS). 164.46 Section 164.46 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND... Identification System (AIS). (a) The following vessels must have a properly installed, operational, type approved AIS as of the date specified: (1) Self-propelled vessels of 65 feet or more in length, other than...

Multiple layer identification label using stacked identification symbols

NASA Technical Reports Server (NTRS)

Schramm, Harry F. (Inventor)

2005-01-01

An automatic identification system and method are provided which employ a machine readable multiple layer label. The label has a plurality of machine readable marking layers stacked one upon another. Each of the marking layers encodes an identification symbol detectable using one or more sensing technologies. The various marking layers may comprise the same marking material or each marking layer may comprise a different medium having characteristics detectable by a different sensing technology. These sensing technologies include x-ray, radar, capacitance, thermal, magnetic and ultrasonic. A complete symbol may be encoded within each marking layer or a symbol may be segmented into fragments which are then divided within a single marking layer or encoded across multiple marking layers.

Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

PubMed Central

Mannan, Malik M. Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M. Ahmad

2016-01-01

Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI). In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data. PMID:26907276

Hybrid EEG--Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal.

PubMed

Mannan, Malik M Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M Ahmad

2016-02-19

Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI). In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

The Iqmulus Urban Showcase: Automatic Tree Classification and Identification in Huge Mobile Mapping Point Clouds

NASA Astrophysics Data System (ADS)

Böhm, J.; Bredif, M.; Gierlinger, T.; Krämer, M.; Lindenberg, R.; Liu, K.; Michel, F.; Sirmacek, B.

2016-06-01

Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.

Rapid and automatic chemical identification of the medicinal flower buds of Lonicera plants by the benchtop and hand-held Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Jianbo; Guo, Baolin; Yan, Rui; Sun, Suqin; Zhou, Qun

2017-07-01

With the utilization of the hand-held equipment, Fourier transform infrared (FT-IR) spectroscopy is a promising analytical technique to minimize the time cost for the chemical identification of herbal materials. This research examines the feasibility of the hand-held FT-IR spectrometer for the on-site testing of herbal materials, using Lonicerae Japonicae Flos (LJF) and Lonicerae Flos (LF) as examples. Correlation-based linear discriminant models for LJF and LF are established based on the benchtop and hand-held FT-IR instruments. The benchtop FT-IR models can exactly recognize all articles of LJF and LF. Although a few LF articles are misjudged at the sub-class level, the hand-held FT-IR models are able to exactly discriminate LJF and LF. As a direct and label-free analytical technique, FT-IR spectroscopy has great potential in the rapid and automatic chemical identification of herbal materials either in laboratories or in fields. This is helpful to prevent the spread and use of adulterated herbal materials in time.

Semi-automatic 10/20 Identification Method for MRI-Free Probe Placement in Transcranial Brain Mapping Techniques.

PubMed

Xiao, Xiang; Zhu, Hao; Liu, Wei-Jie; Yu, Xiao-Ting; Duan, Lian; Li, Zheng; Zhu, Chao-Zhe

2017-01-01

The International 10/20 system is an important head-surface-based positioning system for transcranial brain mapping techniques, e.g., fNIRS and TMS. As guidance for probe placement, the 10/20 system permits both proper ROI coverage and spatial consistency among multiple subjects and experiments in a MRI-free context. However, the traditional manual approach to the identification of 10/20 landmarks faces problems in reliability and time cost. In this study, we propose a semi-automatic method to address these problems. First, a novel head surface reconstruction algorithm reconstructs head geometry from a set of points uniformly and sparsely sampled on the subject's head. Second, virtual 10/20 landmarks are determined on the reconstructed head surface in computational space. Finally, a visually-guided real-time navigation system guides the experimenter to each of the identified 10/20 landmarks on the physical head of the subject. Compared with the traditional manual approach, our proposed method provides a significant improvement both in reliability and time cost and thus could contribute to improving both the effectiveness and efficiency of 10/20-guided MRI-free probe placement.

Identification of fracture zones and its application in automatic bone fracture reduction.

PubMed

Paulano-Godino, Félix; Jiménez-Delgado, Juan J

2017-04-01

The preoperative planning of bone fractures using information from CT scans increases the probability of obtaining satisfactory results, since specialists are provided with additional information before surgery. The reduction of complex bone fractures requires solving a 3D puzzle in order to place each fragment into its correct position. Computer-assisted solutions may aid in this process by identifying the number of fragments and their location, by calculating the fracture zones or even by computing the correct position of each fragment. The main goal of this paper is the development of an automatic method to calculate contact zones between fragments and thus to ease the computation of bone fracture reduction. In this paper, an automatic method to calculate the contact zone between two bone fragments is presented. In a previous step, bone fragments are segmented and labelled from CT images and a point cloud is generated for each bone fragment. The calculated contact zones enable the automatic reduction of complex fractures. To that end, an automatic method to match bone fragments in complex fractures is also presented. The proposed method has been successfully applied in the calculation of the contact zone of 4 different bones from the ankle area. The calculated fracture zones enabled the reduction of all the tested cases using the presented matching algorithm. The performed tests show that the reduction of these fractures using the proposed methods leaded to a small overlapping between fragments. The presented method makes the application of puzzle-solving strategies easier, since it does not obtain the entire fracture zone but the contact area between each pair of fragments. Therefore, it is not necessary to find correspondences between fracture zones and fragments may be aligned two by two. The developed algorithms have been successfully applied in different fracture cases in the ankle area. The small overlapping error obtained in the performed tests

Neural networks: Alternatives to conventional techniques for automatic docking

NASA Technical Reports Server (NTRS)

Vinz, Bradley L.

1994-01-01

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Automatic Method of Pause Measurement for Normal and Dysarthric Speech

ERIC Educational Resources Information Center

Rosen, Kristin; Murdoch, Bruce; Folker, Joanne; Vogel, Adam; Cahill, Louise; Delatycki, Martin; Corben, Louise

2010-01-01

This study proposes an automatic method for the detection of pauses and identification of pause types in conversational speech for the purpose of measuring the effects of Friedreich's Ataxia (FRDA) on speech. Speech samples of [approximately] 3 minutes were recorded from 13 speakers with FRDA and 18 healthy controls. Pauses were measured from the…

Automatic identification of bacterial types using statistical imaging methods

NASA Astrophysics Data System (ADS)

Trattner, Sigal; Greenspan, Hayit; Tepper, Gapi; Abboud, Shimon

2003-05-01

The objective of the current study is to develop an automatic tool to identify bacterial types using computer-vision and statistical modeling techniques. Bacteriophage (phage)-typing methods are used to identify and extract representative profiles of bacterial types, such as the Staphylococcus Aureus. Current systems rely on the subjective reading of plaque profiles by human expert. This process is time-consuming and prone to errors, especially as technology is enabling the increase in the number of phages used for typing. The statistical methodology presented in this work, provides for an automated, objective and robust analysis of visual data, along with the ability to cope with increasing data volumes.

Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

PubMed

Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

2014-01-01

EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM

Automatic Processing and the Unitization of Two Features.

DTIC Science & Technology

1980-02-01

experiment, LaBerge (1973) showed that with practice two features could be automatically unitized to form a novel character. We wish to address a...different from a search for a target which requires identification of one of the features alone. Page 2 Indeed, LaBerge (1973) used a similar implicit...perception? Journal of Experimental Child Psychology, 1978, 26, 498-507. LaBerge , D. Attention and the measurement of perceptual learning. Memory and

SU-F-R-25: Automatic Identification of Suspicious Recurrent/residual Disease Regions After Prostatectomy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parra, N A; Abramowitz, M; Pollack, A

2016-06-15

Purpose: To automatically identify and outline suspicious regions of recurrent or residual disease in the prostate bed using Dynamic Contrast Enhanced-MRI (DCE-MRI) in patients after prostatectomy. Methods: Twenty-two patients presenting for salvage radiotherapy and with identified Gross Tumor Volume (GTV) in the prostate bed were retrospectively analyzed. The MRI data consisted of Axial T2weighted-MRI (T2w) of the pelvis: resolution 1.25×1.25×2.5 mm; Field of View (FOV): 320×320 mm; slice thickness=2.5mm; 72 slices; and Dynamic Contrast Enhanced MRI (DCE-MRI)–12 series of T1w with identical spatial resolution to T2w and at 30–34s temporal resolution. Unsupervised pattern recognition was used to decompose the 4Dmore » DCE data as the product W.H of weights W of k patterns H. A well-perfused pattern Hwp was identified and the weight map Wwp associated to Hwp was used to delineate suspicious volumes. Threshold of Wwp set at mean(Wwp)+S*std(Wwp), S=1,1.5,2 and 2.5 defined four volumes labeled as DCE1.0 to DCE2.5. These volumes were displayed on T2w and, along with GTV, were correlated with the highest pre-treatment PSA values, and with pharmacokinetic analysis constants. Results: GTV was significantly correlated with DCE2.0(ρ= 0.60, p<0.003), and DCE 2.5 (ρ=0.58, p=0.004)). Significant correlation was found between highest pre-treatment PSA and GTV(ρ=0.42, p<0.049), DCE2.0(ρ= 0.52, p<0.012), and DCE 2.5 (ρ=0.67, p<<0.01)). Kruskal-Wallis analysis showed that Ktrans median value was statistically different between non-specific prostate bed tissue NSPBT and both GTV (p<<0.001) and DCE2.5 (p<<0.001), but while median Ve was statistically different between DCE2.5 and NSPBT (p=0.002), it was not statistically different between GTV and NSPBT (p=0.054), suggesting that automatic volumes capture more accurately the area of malignancy. Conclusion: Software developed for identification and visualization of suspicions regions in DCE-MRI from post

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Automatic Adviser on stationary devices status identification and anticipated change

NASA Astrophysics Data System (ADS)

Shabelnikov, A. N.; Liabakh, N. N.; Gibner, Ya M.; Pushkarev, E. A.

2018-05-01

A task is defined to synthesize an Automatic Adviser to identify the automation systems stationary devices status using an autoregressive model of changing their key parameters. An applied model type was rationalized and the research objects monitoring process algorithm was developed. A complex of mobile objects status operation simulation and prediction results analysis was proposed. Research results are commented using a specific example of a hump yard compressor station. The work was supported by the Russian Fundamental Research Fund, project No. 17-20-01040.

Automatic source camera identification using the intrinsic lens radial distortion

NASA Astrophysics Data System (ADS)

Choi, Kai San; Lam, Edmund Y.; Wong, Kenneth K. Y.

2006-11-01

Source camera identification refers to the task of matching digital images with the cameras that are responsible for producing these images. This is an important task in image forensics, which in turn is a critical procedure in law enforcement. Unfortunately, few digital cameras are equipped with the capability of producing watermarks for this purpose. In this paper, we demonstrate that it is possible to achieve a high rate of accuracy in the identification by noting the intrinsic lens radial distortion of each camera. To reduce manufacturing cost, the majority of digital cameras are equipped with lenses having rather spherical surfaces, whose inherent radial distortions serve as unique fingerprints in the images. We extract, for each image, parameters from aberration measurements, which are then used to train and test a support vector machine classifier. We conduct extensive experiments to evaluate the success rate of a source camera identification with five cameras. The results show that this is a viable approach with high accuracy. Additionally, we also present results on how the error rates may change with images captured using various optical zoom levels, as zooming is commonly available in digital cameras.

An investigation into the factors that influence toolmark identifications on ammunition discharged from semi-automatic pistols recovered from car fires.

PubMed

Collender, Mark A; Doherty, Kevin A J; Stanton, Kenneth T

2017-01-01

Following a shooting incident where a vehicle is used to convey the culprits to and from the scene, both the getaway car and the firearm are often deliberately burned in an attempt to destroy any forensic evidence which may be subsequently recovered. Here we investigate the factors that influence the ability to make toolmark identifications on ammunition discharged from pistols recovered from such car fires. This work was carried out by conducting a number of controlled furnace tests in conjunction with real car fire tests in which three 9mm semi-automatic pistols were burned. Comparisons between pre-burn and post burn test fired ammunition discharged from these pistols were then performed to establish if identifications were still possible. The surfaces of the furnace heated samples and car fire samples were examined following heating/burning to establish what factors had influenced their surface morphology. The primary influence on the surfaces of the furnace heated and car fire samples was the formation of oxide layers. The car fire samples were altered to a greater extent than the furnace heated samples. Identifications were still possible between pre- and post-burn discharged cartridge cases, but this was not the case for the discharged bullets. It is suggested that the reason for this is a difference between the types of firearms discharge-generated toolmarks impressed onto the base of cartridge cases compared to those striated along the surfaces of bullets. It was also found that the temperatures recorded in the front foot wells were considerably less than those recorded on top of the rear seats during the car fires. These factors should be assessed by forensic firearms examiners when performing casework involving pistols recovered from car fires. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Phase coherence adaptive processor for automatic signal detection and identification

NASA Astrophysics Data System (ADS)

Wagstaff, Ronald A.

2006-05-01

A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

An automatic method to detect and track the glottal gap from high speed videoendoscopic images.

PubMed

Andrade-Miranda, Gustavo; Godino-Llorente, Juan I; Moro-Velázquez, Laureano; Gómez-García, Jorge Andrés

2015-10-29

The image-based analysis of the vocal folds vibration plays an important role in the diagnosis of voice disorders. The analysis is based not only on the direct observation of the video sequences, but also in an objective characterization of the phonation process by means of features extracted from the recorded images. However, such analysis is based on a previous accurate identification of the glottal gap, which is the most challenging step for a further automatic assessment of the vocal folds vibration. In this work, a complete framework to automatically segment and track the glottal area (or glottal gap) is proposed. The algorithm identifies a region of interest that is adapted along time, and combine active contours and watershed transform for the final delineation of the glottis and also an automatic procedure for synthesize different videokymograms is proposed. Thanks to the ROI implementation, our technique is robust to the camera shifting and also the objective test proved the effectiveness and performance of the approach in the most challenging scenarios that it is when exist an inappropriate closure of the vocal folds. The novelties of the proposed algorithm relies on the used of temporal information for identify an adaptive ROI and the use of watershed merging combined with active contours for the glottis delimitation. Additionally, an automatic procedure for synthesize multiline VKG by the identification of the glottal main axis is developed.

Completing fishing monitoring with spaceborne Vessel Detection System (VDS) and Automatic Identification System (AIS) to assess illegal fishing in Indonesia.

PubMed

Longépé, Nicolas; Hajduch, Guillaume; Ardianto, Romy; Joux, Romain de; Nhunfat, Béatrice; Marzuki, Marza I; Fablet, Ronan; Hermawan, Indra; Germain, Olivier; Subki, Berny A; Farhan, Riza; Muttaqin, Ahmad Deni; Gaspar, Philippe

2017-10-26

The Indonesian fisheries management system is now equipped with the state-of-the-art technologies to deter and combat Illegal, Unreported and Unregulated (IUU) fishing. Since October 2014, non-cooperative fishing vessels can be detected from spaceborne Vessel Detection System (VDS) based on high resolution radar imagery, which directly benefits to coordinated patrol vessels in operation context. This study attempts to monitor the amount of illegal fishing in the Arafura Sea based on this new source of information. It is analyzed together with Vessel Monitoring System (VMS) and satellite-based Automatic Identification System (Sat-AIS) data, taking into account their own particularities. From October 2014 to March 2015, i.e. just after the establishment of a new moratorium by the Indonesian authorities, the estimated share of fishing vessels not carrying VMS, thus being illegal, ranges from 42 to 47%. One year later in January 2016, this proportion decreases and ranges from 32 to 42%. Copyright © 2017 Elsevier Ltd. All rights reserved.

GPU-accelerated automatic identification of robust beam setups for proton and carbon-ion radiotherapy

NASA Astrophysics Data System (ADS)

Ammazzalorso, F.; Bednarz, T.; Jelen, U.

2014-03-01

We demonstrate acceleration on graphic processing units (GPU) of automatic identification of robust particle therapy beam setups, minimizing negative dosimetric effects of Bragg peak displacement caused by treatment-time patient positioning errors. Our particle therapy research toolkit, RobuR, was extended with OpenCL support and used to implement calculation on GPU of the Port Homogeneity Index, a metric scoring irradiation port robustness through analysis of tissue density patterns prior to dose optimization and computation. Results were benchmarked against an independent native CPU implementation. Numerical results were in agreement between the GPU implementation and native CPU implementation. For 10 skull base cases, the GPU-accelerated implementation was employed to select beam setups for proton and carbon ion treatment plans, which proved to be dosimetrically robust, when recomputed in presence of various simulated positioning errors. From the point of view of performance, average running time on the GPU decreased by at least one order of magnitude compared to the CPU, rendering the GPU-accelerated analysis a feasible step in a clinical treatment planning interactive session. In conclusion, selection of robust particle therapy beam setups can be effectively accelerated on a GPU and become an unintrusive part of the particle therapy treatment planning workflow. Additionally, the speed gain opens new usage scenarios, like interactive analysis manipulation (e.g. constraining of some setup) and re-execution. Finally, through OpenCL portable parallelism, the new implementation is suitable also for CPU-only use, taking advantage of multiple cores, and can potentially exploit types of accelerators other than GPUs.

Automatic cytometric device using multiple wavelength excitations

NASA Astrophysics Data System (ADS)

Rongeat, Nelly; Ledroit, Sylvain; Chauvet, Laurence; Cremien, Didier; Urankar, Alexandra; Couderc, Vincent; Nérin, Philippe

2011-05-01

Precise identification of eosinophils, basophils, and specific subpopulations of blood cells (B lymphocytes) in an unconventional automatic hematology analyzer is demonstrated. Our specific apparatus mixes two excitation radiations by means of an acousto-optics tunable filter to properly control fluorescence emission of phycoerythrin cyanin 5 (PC5) conjugated to antibodies (anti-CD20 or anti-CRTH2) and Thiazole Orange. This way our analyzer combining techniques of hematology analysis and flow cytometry based on multiple fluorescence detection, drastically improves the signal to noise ratio and decreases the spectral overlaps impact coming from multiple fluorescence emissions.

Automatic interpretation of oblique ionograms

NASA Astrophysics Data System (ADS)

Ippolito, Alessandro; Scotto, Carlo; Francis, Matthew; Settimi, Alessandro; Cesaroni, Claudio

2015-03-01

We present an algorithm for the identification of trace characteristics of oblique ionograms allowing determination of the Maximum Usable Frequency (MUF) for communication between the transmitter and receiver. The algorithm automatically detects and rejects poor quality ionograms. We performed an exploratory test of the algorithm using data from a campaign of oblique soundings between Rome, Italy (41.90 N, 12.48 E) and Chania, Greece (35.51 N, 24.01 E) and also between Kalkarindji, Australia (17.43 S, 130.81 E) and Culgoora, Australia (30.30 S, 149.55 E). The success of these tests demonstrates the applicability of the method to ionograms recorded by different ionosondes in various helio and geophysical conditions.

Automated Drug Identification for Urban Hospitals

NASA Technical Reports Server (NTRS)

Shirley, Donna L.

1971-01-01

Many urban hospitals are becoming overloaded with drug abuse cases requiring chemical analysis for identification of drugs. In this paper, the requirements for chemical analysis of body fluids for drugs are determined and a system model for automated drug analysis is selected. The system as modeled, would perform chemical preparation of samples, gas-liquid chromatographic separation of drugs in the chemically prepared samples, infrared spectrophotometric analysis of the drugs, and would utilize automatic data processing and control for drug identification. Requirements of cost, maintainability, reliability, flexibility, and operability are considered.

Monitoring caustic injuries from emergency department databases using automatic keyword recognition software.

PubMed

Vignally, P; Fondi, G; Taggi, F; Pitidis, A

2011-03-31

In Italy the European Union Injury Database reports the involvement of chemical products in 0.9% of home and leisure accidents. The Emergency Department registry on domestic accidents in Italy and the Poison Control Centres record that 90% of cases of exposure to toxic substances occur in the home. It is not rare for the effects of chemical agents to be observed in hospitals, with a high potential risk of damage - the rate of this cause of hospital admission is double the domestic injury average. The aim of this study was to monitor the effects of injuries caused by caustic agents in Italy using automatic free-text recognition in Emergency Department medical databases. We created a Stata software program to automatically identify caustic or corrosive injury cases using an agent-specific list of keywords. We focused attention on the procedure's sensitivity and specificity. Ten hospitals in six regions of Italy participated in the study. The program identified 112 cases of injury by caustic or corrosive agents. Checking the cases by quality controls (based on manual reading of ED reports), we assessed 99 cases as true positive, i.e. 88.4% of the patients were automatically recognized by the software as being affected by caustic substances (99% CI: 80.6%- 96.2%), that is to say 0.59% (99% CI: 0.45%-0.76%) of the whole sample of home injuries, a value almost three times as high as that expected (p < 0.0001) from European codified information. False positives were 11.6% of the recognized cases (99% CI: 5.1%- 21.5%). Our automatic procedure for caustic agent identification proved to have excellent product recognition capacity with an acceptable level of excess sensitivity. Contrary to our a priori hypothesis, the automatic recognition system provided a level of identification of agents possessing caustic effects that was significantly much greater than was predictable on the basis of the values from current codifications reported in the European Database.

Evaluation of the automatic optical authentication technologies for control systems of objects

NASA Astrophysics Data System (ADS)

Averkin, Vladimir V.; Volegov, Peter L.; Podgornov, Vladimir A.

2000-03-01

The report considers the evaluation of the automatic optical authentication technologies for the automated integrated system of physical protection, control and accounting of nuclear materials at RFNC-VNIITF, and for providing of the nuclear materials nonproliferation regime. The report presents the nuclear object authentication objectives and strategies, the methodology of the automatic optical authentication and results of the development of pattern recognition techniques carried out under the ISTC project #772 with the purpose of identification of unique features of surface structure of a controlled object and effects of its random treatment. The current decision of following functional control tasks is described in the report: confirmation of the item authenticity (proof of the absence of its substitution by an item of similar shape), control over unforeseen change of item state, control over unauthorized access to the item. The most important distinctive feature of all techniques is not comprehensive description of some properties of controlled item, but unique identification of item using minimum necessary set of parameters, properly comprising identification attribute of the item. The main emphasis in the technical approach is made on the development of rather simple technological methods for the first time intended for use in the systems of physical protection, control and accounting of nuclear materials. The developed authentication devices and system are described.

Semi-automated identification of leopard frogs

USGS Publications Warehouse

Petrovska-Delacrétaz, Dijana; Edwards, Aaron; Chiasson, John; Chollet, Gérard; Pilliod, David S.

2014-01-01

Principal component analysis is used to implement a semi-automatic recognition system to identify recaptured northern leopard frogs (Lithobates pipiens). Results of both open set and closed set experiments are given. The presented algorithm is shown to provide accurate identification of 209 individual leopard frogs from a total set of 1386 images.

Automatic Imitation

ERIC Educational Resources Information Center

Heyes, Cecilia

2011-01-01

"Automatic imitation" is a type of stimulus-response compatibility effect in which the topographical features of task-irrelevant action stimuli facilitate similar, and interfere with dissimilar, responses. This article reviews behavioral, neurophysiological, and neuroimaging research on automatic imitation, asking in what sense it is "automatic"…

Retrieval, automaticity, vocabulary elaboration, orthography (RAVE-O): a comprehensive, fluency-based reading intervention program.

PubMed

Wolf, M; Miller, L; Donnelly, K

2000-01-01

The most important implication of the double-deficit hypothesis (Wolf & Bowers, in this issue) concerns a new emphasis on fluency and automaticity in intervention for children with developmental reading disabilities. The RAVE-O (Retrieval, Automaticity, Vocabulary Elaboration, Orthography) program is an experimental, fluency-based approach to reading intervention that is designed to accompany a phonological analysis program. In an effort to address multiple possible sources of dysfluency in readers with disabilities, the program involves comprehensive emphases both on fluency in word attack, word identification, and comprehension and on automaticity in underlying componential processes (e.g., phonological, orthographic, semantic, and lexical retrieval skills). The goals, theoretical principles, and applied activities of the RAVE-O curriculum are described with particular stress on facilitating the development of rapid orthographic pattern recognition and on changing children's attitudes toward language.

Automatic high-throughput screening of colloidal crystals using machine learning

NASA Astrophysics Data System (ADS)

Spellings, Matthew; Glotzer, Sharon C.

Recent improvements in hardware and software have united to pose an interesting problem for computational scientists studying self-assembly of particles into crystal structures: while studies covering large swathes of parameter space can be dispatched at once using modern supercomputers and parallel architectures, identifying the different regions of a phase diagram is often a serial task completed by hand. While analytic methods exist to distinguish some simple structures, they can be difficult to apply, and automatic identification of more complex structures is still lacking. In this talk we describe one method to create numerical ``fingerprints'' of local order and use them to analyze a study of complex ordered structures. We can use these methods as first steps toward automatic exploration of parameter space and, more broadly, the strategic design of new materials.

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Automatic Identification of Web-Based Risk Markers for Health Events

PubMed Central

Borsa, Diana; Hayward, Andrew C; McKendry, Rachel A; Cox, Ingemar J

2015-01-01

Background The escalating cost of global health care is driving the development of new technologies to identify early indicators of an individual’s risk of disease. Traditionally, epidemiologists have identified such risk factors using medical databases and lengthy clinical studies but these are often limited in size and cost and can fail to take full account of diseases where there are social stigmas or to identify transient acute risk factors. Objective Here we report that Web search engine queries coupled with information on Wikipedia access patterns can be used to infer health events associated with an individual user and automatically generate Web-based risk markers for some of the common medical conditions worldwide, from cardiovascular disease to sexually transmitted infections and mental health conditions, as well as pregnancy. Methods Using anonymized datasets, we present methods to first distinguish individuals likely to have experienced specific health events, and classify them into distinct categories. We then use the self-controlled case series method to find the incidence of health events in risk periods directly following a user’s search for a query category, and compare to the incidence during other periods for the same individuals. Results Searches for pet stores were risk markers for allergy. We also identified some possible new risk markers; for example: searching for fast food and theme restaurants was associated with a transient increase in risk of myocardial infarction, suggesting this exposure goes beyond a long-term risk factor but may also act as an acute trigger of myocardial infarction. Dating and adult content websites were risk markers for sexually transmitted infections, such as human immunodeficiency virus (HIV). Conclusions Web-based methods provide a powerful, low-cost approach to automatically identify risk factors, and support more timely and personalized public health efforts to bring human and economic benefits. PMID

Automatic extraction of road features in urban environments using dense ALS data

NASA Astrophysics Data System (ADS)

Soilán, Mario; Truong-Hong, Linh; Riveiro, Belén; Laefer, Debra

2018-02-01

This paper describes a methodology that automatically extracts semantic information from urban ALS data for urban parameterization and road network definition. First, building façades are segmented from the ground surface by combining knowledge-based information with both voxel and raster data. Next, heuristic rules and unsupervised learning are applied to the ground surface data to distinguish sidewalk and pavement points as a means for curb detection. Then radiometric information was employed for road marking extraction. Using high-density ALS data from Dublin, Ireland, this fully automatic workflow was able to generate a F-score close to 95% for pavement and sidewalk identification with a resolution of 20 cm and better than 80% for road marking detection.

Face recognition for criminal identification: An implementation of principal component analysis for face recognition

NASA Astrophysics Data System (ADS)

Abdullah, Nurul Azma; Saidi, Md. Jamri; Rahman, Nurul Hidayah Ab; Wen, Chuah Chai; Hamid, Isredza Rahmi A.

2017-10-01

In practice, identification of criminal in Malaysia is done through thumbprint identification. However, this type of identification is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene. With the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. However, because of limited software developed to automatically detect the similarity between photo in the footage and recorded photo of criminals, the law enforce thumbprint identification. In this paper, an automated facial recognition system for criminal database was proposed using known Principal Component Analysis approach. This system will be able to detect face and recognize face automatically. This will help the law enforcements to detect or recognize suspect of the case if no thumbprint present on the scene. The results show that about 80% of input photo can be matched with the template data.

Accuracy of computerized automatic identification of cephalometric landmarks by a designed software.

PubMed

Shahidi, Sh; Shahidi, S; Oshagh, M; Gozin, F; Salehi, P; Danaei, S M

2013-01-01

The purpose of this study was to design software for localization of cephalometric landmarks and to evaluate its accuracy in finding landmarks. 40 digital cephalometric radiographs were randomly selected. 16 landmarks which were important in most cephalometric analyses were chosen to be identified. Three expert orthodontists manually identified landmarks twice. The mean of two measurements of each landmark was defined as the baseline landmark. The computer was then able to compare the automatic system's estimate of a landmark with the baseline landmark. The software was designed using Delphi and Matlab programming languages. The techniques were template matching, edge enhancement and some accessory techniques. The total mean error between manually identified and automatically identified landmarks was 2.59 mm. 12.5% of landmarks had mean errors less than 1 mm. 43.75% of landmarks had mean errors less than 2 mm. The mean errors of all landmarks except the anterior nasal spine were less than 4 mm. This software had significant accuracy for localization of cephalometric landmarks and could be used in future applications. It seems that the accuracy obtained with the software which was developed in this study is better than previous automated systems that have used model-based and knowledge-based approaches.

MASGOMAS PROJECT, New automatic-tool for cluster search on IR photometric surveys

NASA Astrophysics Data System (ADS)

Rübke, K.; Herrero, A.; Borissova, J.; Ramirez-Alegria, S.; García, M.; Marin-Franch, A.

2015-05-01

The Milky Way is expected to contain a large number of young massive (few x 1000 solar masses) stellar clusters, borne in dense cores of gas and dust. Yet, their known number remains small. We have started a programme to search for such clusters, MASGOMAS (MAssive Stars in Galactic Obscured MAssive clusterS). Initially, we selected promising candidates by means of visual inspection of infrared images. In a second phase of the project we have presented a semi-automatic method to search for obscured massive clusters that resulted in the identification of new massive clusters, like MASGOMAS-1 (with more than 10,000 solar masses) and MASGOMAS-4 (a double-cored association of about 3,000 solar masses). We have now developped a new automatic tool for MASGOMAS that allows the identification of a large number of massive cluster candidates from the 2MASS and VVV catalogues. Cluster candidates fulfilling criteria appropriated for massive OB stars are thus selected in an efficient and objective way. We present the results from this tool and the observations of the first selected cluster, and discuss the implications for the Milky Way structure.

Assigning unique identification numbers to new user accounts and groups in a computing environment with multiple registries

DOEpatents

DeRobertis, Christopher V.; Lu, Yantian T.

2010-02-23

A method, system, and program storage device for creating a new user account or user group with a unique identification number in a computing environment having multiple user registries is provided. In response to receiving a command to create a new user account or user group, an operating system of a clustered computing environment automatically checks multiple registries configured for the operating system to determine whether a candidate identification number for the new user account or user group has been assigned already to one or more existing user accounts or groups, respectively. The operating system automatically assigns the candidate identification number to the new user account or user group created in a target user registry if the checking indicates that the candidate identification number has not been assigned already to any of the existing user accounts or user groups, respectively.

Automatic Identification of Systolic Time Intervals in Seismocardiogram

PubMed Central

Shafiq, Ghufran; Tatinati, Sivanagaraja; Ang, Wei Tech; Veluvolu, Kalyana C.

2016-01-01

Continuous and non-invasive monitoring of hemodynamic parameters through unobtrusive wearable sensors can potentially aid in early detection of cardiac abnormalities, and provides a viable solution for long-term follow-up of patients with chronic cardiovascular diseases without disrupting the daily life activities. Electrocardiogram (ECG) and siesmocardiogram (SCG) signals can be readily acquired from light-weight electrodes and accelerometers respectively, which can be employed to derive systolic time intervals (STI). For this purpose, automated and accurate annotation of the relevant peaks in these signals is required, which is challenging due to the inter-subject morphological variability and noise prone nature of SCG signal. In this paper, an approach is proposed to automatically annotate the desired peaks in SCG signal that are related to STI by utilizing the information of peak detected in the sliding template to narrow-down the search for the desired peak in actual SCG signal. Experimental validation of this approach performed in conventional/controlled supine and realistic/challenging seated conditions, containing over 5600 heart beat cycles shows good performance and robustness of the proposed approach in noisy conditions. Automated measurement of STI in wearable configuration can provide a quantified cardiac health index for long-term monitoring of patients, elderly people at risk and health-enthusiasts. PMID:27874050

Automatic Identification of Systolic Time Intervals in Seismocardiogram

NASA Astrophysics Data System (ADS)

Shafiq, Ghufran; Tatinati, Sivanagaraja; Ang, Wei Tech; Veluvolu, Kalyana C.

2016-11-01

Continuous and non-invasive monitoring of hemodynamic parameters through unobtrusive wearable sensors can potentially aid in early detection of cardiac abnormalities, and provides a viable solution for long-term follow-up of patients with chronic cardiovascular diseases without disrupting the daily life activities. Electrocardiogram (ECG) and siesmocardiogram (SCG) signals can be readily acquired from light-weight electrodes and accelerometers respectively, which can be employed to derive systolic time intervals (STI). For this purpose, automated and accurate annotation of the relevant peaks in these signals is required, which is challenging due to the inter-subject morphological variability and noise prone nature of SCG signal. In this paper, an approach is proposed to automatically annotate the desired peaks in SCG signal that are related to STI by utilizing the information of peak detected in the sliding template to narrow-down the search for the desired peak in actual SCG signal. Experimental validation of this approach performed in conventional/controlled supine and realistic/challenging seated conditions, containing over 5600 heart beat cycles shows good performance and robustness of the proposed approach in noisy conditions. Automated measurement of STI in wearable configuration can provide a quantified cardiac health index for long-term monitoring of patients, elderly people at risk and health-enthusiasts.

Report: Unsupervised identification of malaria parasites using computer vision.

PubMed

Khan, Najeed Ahmed; Pervaz, Hassan; Latif, Arsalan; Musharaff, Ayesha

2017-01-01

Malaria in human is a serious and fatal tropical disease. This disease results from Anopheles mosquitoes that are infected by Plasmodium species. The clinical diagnosis of malaria based on the history, symptoms and clinical findings must always be confirmed by laboratory diagnosis. Laboratory diagnosis of malaria involves identification of malaria parasite or its antigen / products in the blood of the patient. Manual diagnosis of malaria parasite by the pathologists has proven to become cumbersome. Therefore, there is a need of automatic, efficient and accurate identification of malaria parasite. In this paper, we proposed a computer vision based approach to identify the malaria parasite from light microscopy images. This research deals with the challenges involved in the automatic detection of malaria parasite tissues. Our proposed method is based on the pixel-based approach. We used K-means clustering (unsupervised approach) for the segmentation to identify malaria parasite tissues.

Hybrid neuro-fuzzy approach for automatic vehicle license plate recognition

NASA Astrophysics Data System (ADS)

Lee, Hsi-Chieh; Jong, Chung-Shi

1998-03-01

Most currently available vehicle identification systems use techniques such as R.F., microwave, or infrared to help identifying the vehicle. Transponders are usually installed in the vehicle in order to transmit the corresponding information to the sensory system. It is considered expensive to install a transponder in each vehicle and the malfunction of the transponder will result in the failure of the vehicle identification system. In this study, novel hybrid approach is proposed for automatic vehicle license plate recognition. A system prototype is built which can be used independently or cooperating with current vehicle identification system in identifying a vehicle. The prototype consists of four major modules including the module for license plate region identification, the module for character extraction from the license plate, the module for character recognition, and the module for the SimNet neuro-fuzzy system. To test the performance of the proposed system, three hundred and eighty vehicle image samples are taken by a digital camera. The license plate recognition success rate of the prototype is approximately 91% while the character recognition success rate of the prototype is approximately 97%.

Automatic Target Recognition Based on Cross-Plot

PubMed Central

Wong, Kelvin Kian Loong; Abbott, Derek

2011-01-01

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository. PMID:21980508

48 CFR 252.211-7003 - Item identification and valuation.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., used to retrieve data encoded on machine-readable media. Concatenated unique item identifier means— (1... (or controlling) authority for the enterprise identifier. Item means a single hardware article or a...-readable means an automatic identification technology media, such as bar codes, contact memory buttons...

48 CFR 252.211-7003 - Item identification and valuation.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., used to retrieve data encoded on machine-readable media. Concatenated unique item identifier means— (1... (or controlling) authority for the enterprise identifier. Item means a single hardware article or a...-readable means an automatic identification technology media, such as bar codes, contact memory buttons...

48 CFR 252.211-7003 - Item identification and valuation.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., used to retrieve data encoded on machine-readable media. Concatenated unique item identifier means— (1... (or controlling) authority for the enterprise identifier. Item means a single hardware article or a...-readable means an automatic identification technology media, such as bar codes, contact memory buttons...

Automated colour identification in melanocytic lesions.

PubMed

Sabbaghi, S; Aldeen, M; Garnavi, R; Varigos, G; Doliantis, C; Nicolopoulos, J

2015-08-01

Colour information plays an important role in classifying skin lesion. However, colour identification by dermatologists can be very subjective, leading to cases of misdiagnosis. Therefore, a computer-assisted system for quantitative colour identification is highly desirable for dermatologists to use. Although numerous colour detection systems have been developed, few studies have focused on imitating the human visual perception of colours in melanoma application. In this paper we propose a new methodology based on QuadTree decomposition technique for automatic colour identification in dermoscopy images. Our approach mimics the human perception of lesion colours. The proposed method is trained on a set of 47 images from NIH dataset and applied to a test set of 190 skin lesions obtained from PH2 dataset. The results of our proposed method are compared with a recently reported colour identification method using the same dataset. The effectiveness of our method in detecting colours in dermoscopy images is vindicated by obtaining approximately 93% accuracy when the CIELab1 colour space is used.

Semi-automatic forensic approach using mandibular midline lingual structures as fingerprint: a pilot study.

PubMed

Shaheen, E; Mowafy, B; Politis, C; Jacobs, R

2017-12-01

Previous research proposed the use of the mandibular midline neurovascular canal structures as a forensic finger print. In their observer study, an average correct identification of 95% was reached which triggered this study. To present a semi-automatic computer recognition approach to replace the observers and to validate the accuracy of this newly proposed method. Imaging data from Computer Tomography (CT) and Cone Beam Computer Tomography (CBCT) of mandibles scanned at two different moments were collected to simulate an AM and PM situation where the first scan presented AM and the second scan was used to simulate PM. Ten cases with 20 scans were used to build a classifier which relies on voxel based matching and results with classification into one of two groups: "Unmatched" and "Matched". This protocol was then tested using five other scans out of the database. Unpaired t-testing was applied and accuracy of the computerized approach was determined. A significant difference was found between the "Unmatched" and "Matched" classes with means of 0.41 and 0.86 respectively. Furthermore, the testing phase showed an accuracy of 100%. The validation of this method pushes this protocol further to a fully automatic identification procedure for victim identification based on the mandibular midline canals structures only in cases with available AM and PM CBCT/CT data.

Two-dimensional PCA-based human gait identification

NASA Astrophysics Data System (ADS)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

NASA Astrophysics Data System (ADS)

de Siqueira, Alexandre Fioravante; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Tello Saenz, Carlos Alberto; Job, Aldo Eloizo

2014-08-01

Manual identification of fission tracks has practical problems, such as variation due to observe-observation efficiency. An automatic processing method that could identify fission tracks in a photomicrograph could solve this problem and improve the speed of track counting. However, separation of nontrivial images is one of the most difficult tasks in image processing. Several commercial and free softwares are available, but these softwares are meant to be used in specific images. In this paper, an automatic method based on starlet wavelets is presented in order to separate fission tracks in mineral photomicrographs. Automatization is obtained by the Matthews correlation coefficient, and results are evaluated by precision, recall and accuracy. This technique is an improvement of a method aimed at segmentation of scanning electron microscopy images. This method is applied in photomicrographs of epidote phenocrystals, in which accuracy higher than 89% was obtained in fission track segmentation, even for difficult images. Algorithms corresponding to the proposed method are available for download. Using the method presented here, a user could easily determine fission tracks in photomicrographs of mineral samples.

A manual and an automatic TERS based virus discrimination

NASA Astrophysics Data System (ADS)

Olschewski, Konstanze; Kämmer, Evelyn; Stöckel, Stephan; Bocklitz, Thomas; Deckert-Gaudig, Tanja; Zell, Roland; Cialla-May, Dana; Weber, Karina; Deckert, Volker; Popp, Jürgen

2015-02-01

Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%.Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

Parametric diagnosis of the adaptive gas path in the automatic control system of the aircraft engine

NASA Astrophysics Data System (ADS)

Kuznetsova, T. A.

2017-01-01

The paper dwells on the adaptive multimode mathematical model of the gas-turbine aircraft engine (GTE) embedded in the automatic control system (ACS). The mathematical model is based on the throttle performances, and is characterized by high accuracy of engine parameters identification in stationary and dynamic modes. The proposed on-board engine model is the state space linearized low-level simulation. The engine health is identified by the influence of the coefficient matrix. The influence coefficient is determined by the GTE high-level mathematical model based on measurements of gas-dynamic parameters. In the automatic control algorithm, the sum of squares of the deviation between the parameters of the mathematical model and real GTE is minimized. The proposed mathematical model is effectively used for gas path defects detecting in on-line GTE health monitoring. The accuracy of the on-board mathematical model embedded in ACS determines the quality of adaptive control and reliability of the engine. To improve the accuracy of identification solutions and sustainability provision, the numerical method of Monte Carlo was used. The parametric diagnostic algorithm based on the LPτ - sequence was developed and tested. Analysis of the results suggests that the application of the developed algorithms allows achieving higher identification accuracy and reliability than similar models used in practice.

AUTOMOTIVE DIESEL MAINTENANCE 2. UNIT VII, AUTOMATIC TRANSMISSIONS--ALLISON, TORQUMATIC SERIES 5960 AND 6060 (PART I).

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 25-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF SPECIFIC MODELS OF AUTOMATIC TRANSMISSIONS USED ON DIESEL POWERED VEHICLES. TOPICS ARE (1) GENERAL SPECIFICATION DATA, (2) OPTIONS FOR VARIOUS APPLICATIONS, (3) ROAD TEST INSTRUCTIONS, (4) IDENTIFICATION AND SPECIFICATION DATA, (5) ALLISON…

Automatic detection and notification of "wrong patient-wrong location'' errors in the operating room.

PubMed

Sandberg, Warren S; Häkkinen, Matti; Egan, Marie; Curran, Paige K; Fairbrother, Pamela; Choquette, Ken; Daily, Bethany; Sarkka, Jukka-Pekka; Rattner, David

2005-09-01

When procedures and processes to assure patient location based on human performance do not work as expected, patients are brought incrementally closer to a possible "wrong patient-wrong procedure'' error. We developed a system for automated patient location monitoring and management. Real-time data from an active infrared/radio frequency identification tracking system provides patient location data that are robust and can be compared with an "expected process'' model to automatically flag wrong-location events as soon as they occur. The system also generates messages that are automatically sent to process managers via the hospital paging system, thus creating an active alerting function to annunciate errors. We deployed the system to detect and annunciate "patient-in-wrong-OR'' events. The system detected all "wrong-operating room (OR)'' events, and all "wrong-OR'' locations were correctly assigned within 0.50+/-0.28 minutes (mean+/-SD). This corresponded to the measured latency of the tracking system. All wrong-OR events were correctly annunciated via the paging function. This experiment demonstrates that current technology can automatically collect sufficient data to remotely monitor patient flow through a hospital, provide decision support based on predefined rules, and automatically notify stakeholders of errors.

A tool for developing an automatic insect identification system based on wing outlines

PubMed Central

Yang, He-Ping; Ma, Chun-Sen; Wen, Hui; Zhan, Qing-Bin; Wang, Xin-Li

2015-01-01

For some insect groups, wing outline is an important character for species identification. We have constructed a program as the integral part of an automated system to identify insects based on wing outlines (DAIIS). This program includes two main functions: (1) outline digitization and Elliptic Fourier transformation and (2) classifier model training by pattern recognition of support vector machines and model validation. To demonstrate the utility of this program, a sample of 120 owlflies (Neuroptera: Ascalaphidae) was split into training and validation sets. After training, the sample was sorted into seven species using this tool. In five repeated experiments, the mean accuracy for identification of each species ranged from 90% to 98%. The accuracy increased to 99% when the samples were first divided into two groups based on features of their compound eyes. DAIIS can therefore be a useful tool for developing a system of automated insect identification. PMID:26251292

48 CFR 252.211-7003 - Item unique identification and valuation.

Code of Federal Regulations, 2014 CFR

2014-10-01

... reader or interrogator, used to retrieve data encoded on machine-readable media. Concatenated unique item... identifier. Item means a single hardware article or a single unit formed by a grouping of subassemblies... manufactured under identical conditions. Machine-readable means an automatic identification technology media...

Toward Automatic Georeferencing of Archival Aerial Photogrammetric Surveys

NASA Astrophysics Data System (ADS)

Giordano, S.; Le Bris, A.; Mallet, C.

2018-05-01

Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes over the past 100 years. They provide a relatively dense temporal sampling of the territories with very high spatial resolution. Such time series image analysis is a mandatory baseline for a large variety of long-term environmental monitoring studies. The current bottleneck for accurate comparison between epochs is their fine georeferencing step. No fully automatic method has been proposed yet and existing studies are rather limited in terms of area and number of dates. State-of-the art shows that the major challenge is the identification of ground references: cartographic coordinates and their position in the archival images. This task is manually performed, and extremely time-consuming. This paper proposes to use a photogrammetric approach, and states that the 3D information that can be computed is the key to full automation. Its original idea lies in a 2-step approach: (i) the computation of a coarse absolute image orientation; (ii) the use of the coarse Digital Surface Model (DSM) information for automatic absolute image orientation. It only relies on a recent orthoimage+DSM, used as master reference for all epochs. The coarse orthoimage, compared with such a reference, allows the identification of dense ground references and the coarse DSM provides their position in the archival images. Results on two areas and 5 dates show that this method is compatible with long and dense archival aerial image series. Satisfactory planimetric and altimetric accuracies are reported, with variations depending on the ground sampling distance of the images and the location of the Ground Control Points.

A Review on Automatic Mammographic Density and Parenchymal Segmentation

PubMed Central

He, Wenda; Juette, Arne; Denton, Erika R. E.; Oliver, Arnau

2015-01-01

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models. PMID:26171249

Crop Identification Technolgy Assessment for Remote Sensing (CITARS). Volume 1: Task design plan

NASA Technical Reports Server (NTRS)

Hall, F. G.; Bizzell, R. M.

1975-01-01

A plan for quantifying the crop identification performances resulting from the remote identification of corn, soybeans, and wheat is described. Steps for the conversion of multispectral data tapes to classification results are specified. The crop identification performances resulting from the use of several basic types of automatic data processing techniques are compared and examined for significant differences. The techniques are evaluated also for changes in geographic location, time of the year, management practices, and other physical factors. The results of the Crop Identification Technology Assessment for Remote Sensing task will be applied extensively in the Large Area Crop Inventory Experiment.

An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework.

PubMed

Wolterink, Jelmer M; Leiner, Tim; de Vos, Bob D; Coatrieux, Jean-Louis; Kelm, B Michael; Kondo, Satoshi; Salgado, Rodrigo A; Shahzad, Rahil; Shu, Huazhong; Snoeren, Miranda; Takx, Richard A P; van Vliet, Lucas J; van Walsum, Theo; Willems, Tineke P; Yang, Guanyu; Zheng, Yefeng; Viergever, Max A; Išgum, Ivana

2016-05-01

The amount of coronary artery calcification (CAC) is a strong and independent predictor of cardiovascular disease (CVD) events. In clinical practice, CAC is manually identified and automatically quantified in cardiac CT using commercially available software. This is a tedious and time-consuming process in large-scale studies. Therefore, a number of automatic methods that require no interaction and semiautomatic methods that require very limited interaction for the identification of CAC in cardiac CT have been proposed. Thus far, a comparison of their performance has been lacking. The objective of this study was to perform an independent evaluation of (semi)automatic methods for CAC scoring in cardiac CT using a publicly available standardized framework. Cardiac CT exams of 72 patients distributed over four CVD risk categories were provided for (semi)automatic CAC scoring. Each exam consisted of a noncontrast-enhanced calcium scoring CT (CSCT) and a corresponding coronary CT angiography (CCTA) scan. The exams were acquired in four different hospitals using state-of-the-art equipment from four major CT scanner vendors. The data were divided into 32 training exams and 40 test exams. A reference standard for CAC in CSCT was defined by consensus of two experts following a clinical protocol. The framework organizers evaluated the performance of (semi)automatic methods on test CSCT scans, per lesion, artery, and patient. Five (semi)automatic methods were evaluated. Four methods used both CSCT and CCTA to identify CAC, and one method used only CSCT. The evaluated methods correctly detected between 52% and 94% of CAC lesions with positive predictive values between 65% and 96%. Lesions in distal coronary arteries were most commonly missed and aortic calcifications close to the coronary ostia were the most common false positive errors. The majority (between 88% and 98%) of correctly identified CAC lesions were assigned to the correct artery. Linearly weighted Cohen's kappa

Flow Pattern Identification of Horizontal Two-Phase Refrigerant Flow Using Neural Networks

DTIC Science & Technology

2015-12-31

AFRL-RQ-WP-TP-2016-0079 FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING NEURAL NETWORKS (POSTPRINT) Abdeel J...Journal Article Postprint 01 October 2013 – 22 June 2015 4. TITLE AND SUBTITLE FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING...networks were used to automatically identify two-phase flow patterns for refrigerant R-134a flowing in a horizontal tube. In laboratory experiments

Critical Assessment of Small Molecule Identification 2016: automated methods.

PubMed

Schymanski, Emma L; Ruttkies, Christoph; Krauss, Martin; Brouard, Céline; Kind, Tobias; Dührkop, Kai; Allen, Felicity; Vaniya, Arpana; Verdegem, Dries; Böcker, Sebastian; Rousu, Juho; Shen, Huibin; Tsugawa, Hiroshi; Sajed, Tanvir; Fiehn, Oliver; Ghesquière, Bart; Neumann, Steffen

2017-03-27

The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest ( www.casmi-contest.org ) was held in 2016, with two new categories for automated methods. This article covers the 208 challenges in Categories 2 and 3, without and with metadata, from organization, participation, results and post-contest evaluation of CASMI 2016 through to perspectives for future contests and small molecule annotation/identification. The Input Output Kernel Regression (CSI:IOKR) machine learning approach performed best in "Category 2: Best Automatic Structural Identification-In Silico Fragmentation Only", won by Team Brouard with 41% challenge wins. The winner of "Category 3: Best Automatic Structural Identification-Full Information" was Team Kind (MS-FINDER), with 76% challenge wins. The best methods were able to achieve over 30% Top 1 ranks in Category 2, with all methods ranking the correct candidate in the Top 10 in around 50% of challenges. This success rate rose to 70% Top 1 ranks in Category 3, with candidates in the Top 10 in over 80% of the challenges. The machine learning and chemistry-based approaches are shown to perform in complementary ways. The improvement in (semi-)automated fragmentation methods for small molecule identification has been substantial. The achieved high rates of correct candidates in the Top 1 and Top 10, despite large candidate numbers, open up great possibilities for high-throughput annotation of untargeted analysis for "known unknowns". As more high quality training data becomes available, the improvements in machine learning methods will likely continue, but the alternative approaches still provide valuable complementary information. Improved integration of experimental context will also improve identification success further for "real life" annotations. The true "unknown unknowns" remain to be evaluated in future CASMI contests. Graphical abstract .

Automatic NMR-Based Identification of Chemical Reaction Types in Mixtures of Co-Occurring Reactions

PubMed Central

Latino, Diogo A. R. S.; Aires-de-Sousa, João

2014-01-01

The combination of chemoinformatics approaches with NMR techniques and the increasing availability of data allow the resolution of problems far beyond the original application of NMR in structure elucidation/verification. The diversity of applications can range from process monitoring, metabolic profiling, authentication of products, to quality control. An application related to the automatic analysis of complex mixtures concerns mixtures of chemical reactions. We encoded mixtures of chemical reactions with the difference between the 1H NMR spectra of the products and the reactants. All the signals arising from all the reactants of the co-occurring reactions were taken together (a simulated spectrum of the mixture of reactants) and the same was done for products. The difference spectrum is taken as the representation of the mixture of chemical reactions. A data set of 181 chemical reactions was used, each reaction manually assigned to one of 6 types. From this dataset, we simulated mixtures where two reactions of different types would occur simultaneously. Automatic learning methods were trained to classify the reactions occurring in a mixture from the 1H NMR-based descriptor of the mixture. Unsupervised learning methods (self-organizing maps) produced a reasonable clustering of the mixtures by reaction type, and allowed the correct classification of 80% and 63% of the mixtures in two independent test sets of different similarity to the training set. With random forests (RF), the percentage of correct classifications was increased to 99% and 80% for the same test sets. The RF probability associated to the predictions yielded a robust indication of their reliability. This study demonstrates the possibility of applying machine learning methods to automatically identify types of co-occurring chemical reactions from NMR data. Using no explicit structural information about the reactions participants, reaction elucidation is performed without structure elucidation of the

Automatic NMR-based identification of chemical reaction types in mixtures of co-occurring reactions.

PubMed

Latino, Diogo A R S; Aires-de-Sousa, João

2014-01-01

The combination of chemoinformatics approaches with NMR techniques and the increasing availability of data allow the resolution of problems far beyond the original application of NMR in structure elucidation/verification. The diversity of applications can range from process monitoring, metabolic profiling, authentication of products, to quality control. An application related to the automatic analysis of complex mixtures concerns mixtures of chemical reactions. We encoded mixtures of chemical reactions with the difference between the (1)H NMR spectra of the products and the reactants. All the signals arising from all the reactants of the co-occurring reactions were taken together (a simulated spectrum of the mixture of reactants) and the same was done for products. The difference spectrum is taken as the representation of the mixture of chemical reactions. A data set of 181 chemical reactions was used, each reaction manually assigned to one of 6 types. From this dataset, we simulated mixtures where two reactions of different types would occur simultaneously. Automatic learning methods were trained to classify the reactions occurring in a mixture from the (1)H NMR-based descriptor of the mixture. Unsupervised learning methods (self-organizing maps) produced a reasonable clustering of the mixtures by reaction type, and allowed the correct classification of 80% and 63% of the mixtures in two independent test sets of different similarity to the training set. With random forests (RF), the percentage of correct classifications was increased to 99% and 80% for the same test sets. The RF probability associated to the predictions yielded a robust indication of their reliability. This study demonstrates the possibility of applying machine learning methods to automatically identify types of co-occurring chemical reactions from NMR data. Using no explicit structural information about the reactions participants, reaction elucidation is performed without structure elucidation of

Five-way smoking status classification using text hot-spot identification and error-correcting output codes.

PubMed

Cohen, Aaron M

2008-01-01

We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2b2 task organizers, using micro- and macro-averaged F1 as the primary performance metric. Our best performing system achieved a micro-F1 of 0.9000 on the test collection, equivalent to the best performing system submitted to the i2b2 challenge. Hot-spot identification, zero-vector filtering, classifier weighting, and error correcting output coding contributed additively to increased performance, with hot-spot identification having by far the largest positive effect. High performance on automatic identification of patient smoking status from discharge summaries is achievable with the efficient and straightforward machine learning techniques studied here.

Automatic identification of IASLC-defined mediastinal lymph node stations on CT scans using multi-atlas organ segmentation

NASA Astrophysics Data System (ADS)

Hoffman, Joanne; Liu, Jiamin; Turkbey, Evrim; Kim, Lauren; Summers, Ronald M.

2015-03-01

Station-labeling of mediastinal lymph nodes is typically performed to identify the location of enlarged nodes for cancer staging. Stations are usually assigned in clinical radiology practice manually by qualitative visual assessment on CT scans, which is time consuming and highly variable. In this paper, we developed a method that automatically recognizes the lymph node stations in thoracic CT scans based on the anatomical organs in the mediastinum. First, the trachea, lungs, and spines are automatically segmented to locate the mediastinum region. Then, eight more anatomical organs are simultaneously identified by multi-atlas segmentation. Finally, with the segmentation of those anatomical organs, we convert the text definitions of the International Association for the Study of Lung Cancer (IASLC) lymph node map into patient-specific color-coded CT image maps. Thus, a lymph node station is automatically assigned to each lymph node. We applied this system to CT scans of 86 patients with 336 mediastinal lymph nodes measuring equal or greater than 10 mm. 84.8% of mediastinal lymph nodes were correctly mapped to their stations.

Automatic Identification of Character Types from Film Dialogs

PubMed Central

Skowron, Marcin; Trapp, Martin; Payr, Sabine; Trappl, Robert

2016-01-01

ABSTRACT We study the detection of character types from fictional dialog texts such as screenplays. As approaches based on the analysis of utterances’ linguistic properties are not sufficient to identify all fictional character types, we develop an integrative approach that complements linguistic analysis with interactive and communication characteristics, and show that it can improve the identification performance. The interactive characteristics of fictional characters are captured by the descriptive analysis of semantic graphs weighted by linguistic markers of expressivity and social role. For this approach, we introduce a new data set of action movie character types with their corresponding sequences of dialogs. The evaluation results demonstrate that the integrated approach outperforms baseline approaches on the presented data set. Comparative in-depth analysis of a single screenplay leads on to the discussion of possible limitations of this approach and to directions for future research. PMID:29118463

Metaphor Identification in Large Texts Corpora

PubMed Central

Neuman, Yair; Assaf, Dan; Cohen, Yohai; Last, Mark; Argamon, Shlomo; Howard, Newton; Frieder, Ophir

2013-01-01

Identifying metaphorical language-use (e.g., sweet child) is one of the challenges facing natural language processing. This paper describes three novel algorithms for automatic metaphor identification. The algorithms are variations of the same core algorithm. We evaluate the algorithms on two corpora of Reuters and the New York Times articles. The paper presents the most comprehensive study of metaphor identification in terms of scope of metaphorical phrases and annotated corpora size. Algorithms’ performance in identifying linguistic phrases as metaphorical or literal has been compared to human judgment. Overall, the algorithms outperform the state-of-the-art algorithm with 71% precision and 27% averaged improvement in prediction over the base-rate of metaphors in the corpus. PMID:23658625

Research on gait-based human identification

NASA Astrophysics Data System (ADS)

Li, Youguo

Gait recognition refers to automatic identification of individual based on his/her style of walking. This paper proposes a gait recognition method based on Continuous Hidden Markov Model with Mixture of Gaussians(G-CHMM). First, we initialize a Gaussian mix model for training image sequence with K-means algorithm, then train the HMM parameters using a Baum-Welch algorithm. These gait feature sequences can be trained and obtain a Continuous HMM for every person, therefore, the 7 key frames and the obtained HMM can represent each person's gait sequence. Finally, the recognition is achieved by Front algorithm. The experiments made on CASIA gait databases obtain comparatively high correction identification ratio and comparatively strong robustness for variety of bodily angle.

Automatic fluid dispenser

NASA Technical Reports Server (NTRS)

Sakellaris, P. C. (Inventor)

1977-01-01

Fluid automatically flows to individual dispensing units at predetermined times from a fluid supply and is available only for a predetermined interval of time after which an automatic control causes the fluid to drain from the individual dispensing units. Fluid deprivation continues until the beginning of a new cycle when the fluid is once again automatically made available at the individual dispensing units.

Automatic blood vessel based-liver segmentation using the portal phase abdominal CT

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen

2018-02-01

Liver segmentation is the basis for computer-based planning of hepatic surgical interventions. In diagnosis and analysis of hepatic diseases and surgery planning, automatic segmentation of liver has high importance. Blood vessel (BV) has showed high performance at liver segmentation. In our previous work, we developed a semi-automatic method that segments the liver through the portal phase abdominal CT images in two stages. First stage was interactive segmentation of abdominal blood vessels (ABVs) and subsequent classification into hepatic (HBVs) and non-hepatic (non-HBVs). This stage had 5 interactions that include selective threshold for bone segmentation, selecting two seed points for kidneys segmentation, selection of inferior vena cava (IVC) entrance for starting ABVs segmentation, identification of the portal vein (PV) entrance to the liver and the IVC-exit for classifying HBVs from other ABVs (non-HBVs). Second stage is automatic segmentation of the liver based on segmented ABVs as described in [4]. For full automation of our method we developed a method [5] that segments ABVs automatically tackling the first three interactions. In this paper, we propose full automation of classifying ABVs into HBVs and non- HBVs and consequently full automation of liver segmentation that we proposed in [4]. Results illustrate that the method is effective at segmentation of the liver through the portal abdominal CT images.

Open Dataset for the Automatic Recognition of Sedentary Behaviors.

PubMed

Possos, William; Cruz, Robinson; Cerón, Jesús D; López, Diego M; Sierra-Torres, Carlos H

2017-01-01

Sedentarism is associated with the development of noncommunicable diseases (NCD) such as cardiovascular diseases (CVD), type 2 diabetes, and cancer. Therefore, the identification of specific sedentary behaviors (TV viewing, sitting at work, driving, relaxing, etc.) is especially relevant for planning personalized prevention programs. To build and evaluate a public a dataset for the automatic recognition (classification) of sedentary behaviors. The dataset included data from 30 subjects, who performed 23 sedentary behaviors while wearing a commercial wearable on the wrist, a smartphone on the hip and another in the thigh. Bluetooth Low Energy (BLE) beacons were used in order to improve the automatic classification of different sedentary behaviors. The study also compared six well know data mining classification techniques in order to identify the more precise method of solving the classification problem of the 23 defined behaviors. A better classification accuracy was obtained using the Random Forest algorithm and when data were collected from the phone on the hip. Furthermore, the use of beacons as a reference for obtaining the symbolic location of the individual improved the precision of the classification.

Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Writer identification on historical Glagolitic documents

NASA Astrophysics Data System (ADS)

Fiel, Stefan; Hollaus, Fabian; Gau, Melanie; Sablatnig, Robert

2013-12-01

This work aims at automatically identifying scribes of historical Slavonic manuscripts. The quality of the ancient documents is partially degraded by faded-out ink or varying background. The writer identification method used is based on image features, which are described with Scale Invariant Feature Transform (SIFT) features. A visual vocabulary is used for the description of handwriting characteristics, whereby the features are clustered using a Gaussian Mixture Model and employing the Fisher kernel. The writer identification approach is originally designed for grayscale images of modern handwritings. But contrary to modern documents, the historical manuscripts are partially corrupted by background clutter and water stains. As a result, SIFT features are also found on the background. Since the method shows also good results on binarized images of modern handwritings, the approach was additionally applied on binarized images of the ancient writings. Experiments show that this preprocessing step leads to a significant performance increase: The identification rate on binarized images is 98.9%, compared to an identification rate of 87.6% gained on grayscale images.

Automatic dirt trail analysis in dermoscopy images.

PubMed

Cheng, Beibei; Joe Stanley, R; Stoecker, William V; Osterwise, Christopher T P; Stricklin, Sherea M; Hinton, Kristen A; Moss, Randy H; Oliviero, Margaret; Rabinovitz, Harold S

2013-02-01

Basal cell carcinoma (BCC) is the most common cancer in the US. Dermatoscopes are devices used by physicians to facilitate the early detection of these cancers based on the identification of skin lesion structures often specific to BCCs. One new lesion structure, referred to as dirt trails, has the appearance of dark gray, brown or black dots and clods of varying sizes distributed in elongated clusters with indistinct borders, often appearing as curvilinear trails. In this research, we explore a dirt trail detection and analysis algorithm for extracting, measuring, and characterizing dirt trails based on size, distribution, and color in dermoscopic skin lesion images. These dirt trails are then used to automatically discriminate BCC from benign skin lesions. For an experimental data set of 35 BCC images with dirt trails and 79 benign lesion images, a neural network-based classifier achieved a 0.902 are under a receiver operating characteristic curve using a leave-one-out approach. Results obtained from this study show that automatic detection of dirt trails in dermoscopic images of BCC is feasible. This is important because of the large number of these skin cancers seen every year and the challenge of discovering these earlier with instrumentation. © 2011 John Wiley & Sons A/S.

Automatic extraction and identification of users' responses in Facebook medical quizzes.

PubMed

Rodríguez-González, Alejandro; Menasalvas Ruiz, Ernestina; Mayer Pujadas, Miguel A

2016-04-01

In the last few years the use of social media in medicine has grown exponentially, providing a new area of research based on the analysis and use of Web 2.0 capabilities. In addition, the use of social media in medical education is a subject of particular interest which has been addressed in several studies. One example of this application is the medical quizzes of The New England Journal of Medicine (NEJM) that regularly publishes a set of questions through their Facebook timeline. We present an approach for the automatic extraction of medical quizzes and their associated answers on a Facebook platform by means of a set of computer-based methods and algorithms. We have developed a tool for the extraction and analysis of medical quizzes stored on Facebook timeline at the NEJM Facebook page, based on a set of computer-based methods and algorithms using Java. The system is divided into two main modules: Crawler and Data retrieval. The system was launched on December 31, 2014 and crawled through a total of 3004 valid posts and 200,081 valid comments. The first post was dated on July 23, 2009 and the last one on December 30, 2014. 285 quizzes were analyzed with 32,780 different users providing answers to the aforementioned quizzes. Of the 285 quizzes, patterns were found in 261 (91.58%). From these 261 quizzes where trends were found, we saw that users follow trends of incorrect answers in 13 quizzes and trends of correct answers in 248. This tool is capable of automatically identifying the correct and wrong answers to a quiz provided on Facebook posts in a text format to a quiz, with a small rate of false negative cases and this approach could be applicable to the extraction and analysis of other sources after including some adaptations of the information on the Internet. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Increasing Accuracy: A New Design and Algorithm for Automatically Measuring Weights, Travel Direction and Radio Frequency Identification (RFID) of Penguins.

PubMed

Afanasyev, Vsevolod; Buldyrev, Sergey V; Dunn, Michael J; Robst, Jeremy; Preston, Mark; Bremner, Steve F; Briggs, Dirk R; Brown, Ruth; Adlard, Stacey; Peat, Helen J

2015-01-01

A fully automated weighbridge using a new algorithm and mechanics integrated with a Radio Frequency Identification System is described. It is currently in use collecting data on Macaroni penguins (Eudyptes chrysolophus) at Bird Island, South Georgia. The technology allows researchers to collect very large, highly accurate datasets of both penguin weight and direction of their travel into or out of a breeding colony, providing important contributory information to help understand penguin breeding success, reproductive output and availability of prey. Reliable discrimination between single and multiple penguin crossings is demonstrated. Passive radio frequency tags implanted into penguins allow researchers to match weight and trip direction to individual birds. Low unit and operation costs, low maintenance needs, simple operator requirements and accurate time stamping of every record are all important features of this type of weighbridge, as is its proven ability to operate 24 hours a day throughout a breeding season, regardless of temperature or weather conditions. Users are able to define required levels of accuracy by adjusting filters and raw data are automatically recorded and stored allowing for a range of processing options. This paper presents the underlying principles, design specification and system description, provides evidence of the weighbridge's accurate performance and demonstrates how its design is a significant improvement on existing systems.

Real-time Monitoring of Subsea Gas Pipelines, Offshore Platforms, and Ship Inspection Scores Using an Automatic Identification System

NASA Astrophysics Data System (ADS)

Artana, K. B.; Pitana, T.; Dinariyana, D. P.; Ariana, M.; Kristianto, D.; Pratiwi, E.

2018-06-01

The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system (AIS). The research also focuses on the integration of shipping database, AIS data, and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines. A simple concept is used in the development of this prototype, which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship's coordinates (longitude/latitude) as detected by AIS. Using such information, we can then build an early warning system (EWS) relayed through short message service (SMS), email, or other means when the ship enters the restricted and exclusion zone of platforms and pipelines. The ship inspection system is developed by combining several attributes. Then, decision analysis software is employed to prioritize the vessel's four attributes, including ship age, ship type, classification, and flag state. Results show that the EWS can increase the safety level of offshore platforms and pipelines, as well as the efficient use of patrol boats in monitoring the safety of the facilities. Meanwhile, ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.

Attention to Automatic Movements in Parkinson's Disease: Modified Automatic Mode in the Striatum

PubMed Central

Wu, Tao; Liu, Jun; Zhang, Hejia; Hallett, Mark; Zheng, Zheng; Chan, Piu

2015-01-01

We investigated neural correlates when attending to a movement that could be made automatically in healthy subjects and Parkinson's disease (PD) patients. Subjects practiced a visuomotor association task until they could perform it automatically, and then directed their attention back to the automated task. Functional MRI was obtained during the early-learning, automatic stage, and when re-attending. In controls, attention to automatic movement induced more activation in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex, and rostral supplementary motor area. The motor cortex received more influence from the cortical motor association regions. In contrast, the pattern of the activity and connectivity of the striatum remained at the level of the automatic stage. In PD patients, attention enhanced activity in the DLPFC, premotor cortex, and cerebellum, but the connectivity from the putamen to the motor cortex decreased. Our findings demonstrate that, in controls, when a movement achieves the automatic stage, attention can influence the attentional networks and cortical motor association areas, but has no apparent effect on the striatum. In PD patients, attention induces a shift from the automatic mode back to the controlled pattern within the striatum. The shifting between controlled and automatic behaviors relies in part on striatal function. PMID:24925772

The busy social brain: evidence for automaticity and control in the neural systems supporting social cognition and action understanding.

PubMed

Spunt, Robert P; Lieberman, Matthew D

2013-01-01

Much social-cognitive processing is believed to occur automatically; however, the relative automaticity of the brain systems underlying social cognition remains largely undetermined. We used functional MRI to test for automaticity in the functioning of two brain systems that research has indicated are important for understanding other people's behavior: the mirror neuron system and the mentalizing system. Participants remembered either easy phone numbers (low cognitive load) or difficult phone numbers (high cognitive load) while observing actions after adopting one of four comprehension goals. For all four goals, mirror neuron system activation showed relatively little evidence of modulation by load; in contrast, the association of mentalizing system activation with the goal of inferring the actor's mental state was extinguished by increased cognitive load. These results support a dual-process model of the brain systems underlying action understanding and social cognition; the mirror neuron system supports automatic behavior identification, and the mentalizing system supports controlled social causal attribution.

Automatic differential analysis of NMR experiments in complex samples.

PubMed

Margueritte, Laure; Markov, Petar; Chiron, Lionel; Starck, Jean-Philippe; Vonthron-Sénécheau, Catherine; Bourjot, Mélanie; Delsuc, Marc-André

2018-06-01

Liquid state nuclear magnetic resonance (NMR) is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, and characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. Although acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly, and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D, and diffusion-ordered spectroscopy experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of a bioactive species in a natural extract, we use it for the automatic detection of small amounts of artemisinin added to a series of plant extracts and for the generation of the spectral fingerprint of this molecule. This program called Plasmodesma is a novel tool that should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts but can also in drug discovery or metabolomics studies. Copyright © 2017 John Wiley & Sons, Ltd.

Automatic extraction of blocks from 3D point clouds of fractured rock

NASA Astrophysics Data System (ADS)

Chen, Na; Kemeny, John; Jiang, Qinghui; Pan, Zhiwen

2017-12-01

This paper presents a new method for extracting blocks and calculating block size automatically from rock surface 3D point clouds. Block size is an important rock mass characteristic and forms the basis for several rock mass classification schemes. The proposed method consists of four steps: 1) the automatic extraction of discontinuities using an improved Ransac Shape Detection method, 2) the calculation of discontinuity intersections based on plane geometry, 3) the extraction of block candidates based on three discontinuities intersecting one another to form corners, and 4) the identification of "true" blocks using an improved Floodfill algorithm. The calculated block sizes were compared with manual measurements in two case studies, one with fabricated cardboard blocks and the other from an actual rock mass outcrop. The results demonstrate that the proposed method is accurate and overcomes the inaccuracies, safety hazards, and biases of traditional techniques.

Automatic detection and visualisation of MEG ripple oscillations in epilepsy.

PubMed

van Klink, Nicole; van Rosmalen, Frank; Nenonen, Jukka; Burnos, Sergey; Helle, Liisa; Taulu, Samu; Furlong, Paul Lawrence; Zijlmans, Maeike; Hillebrand, Arjan

2017-01-01

High frequency oscillations (HFOs, 80-500 Hz) in invasive EEG are a biomarker for the epileptic focus. Ripples (80-250 Hz) have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~ 2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

Automatic extraction of disease-specific features from Doppler images

NASA Astrophysics Data System (ADS)

Negahdar, Mohammadreza; Moradi, Mehdi; Parajuli, Nripesh; Syeda-Mahmood, Tanveer

2017-03-01

Flow Doppler imaging is widely used by clinicians to detect diseases of the valves. In particular, continuous wave (CW) Doppler mode scan is routinely done during echocardiography and shows Doppler signal traces over multiple heart cycles. Traditionally, echocardiographers have manually traced such velocity envelopes to extract measurements such as decay time and pressure gradient which are then matched to normal and abnormal values based on clinical guidelines. In this paper, we present a fully automatic approach to deriving these measurements for aortic stenosis retrospectively from echocardiography videos. Comparison of our method with measurements made by echocardiographers shows large agreement as well as identification of new cases missed by echocardiographers.

Applying face identification to detecting hijacking of airplane

NASA Astrophysics Data System (ADS)

Luo, Xuanwen; Cheng, Qiang

2004-09-01

That terrorists hijacked the airplanes and crashed the World Trade Center is disaster to civilization. To avoid the happening of hijack is critical to homeland security. To report the hijacking in time, limit the terrorist to operate the plane if happened and land the plane to the nearest airport could be an efficient way to avoid the misery. Image processing technique in human face recognition or identification could be used for this task. Before the plane take off, the face images of pilots are input into a face identification system installed in the airplane. The camera in front of pilot seat keeps taking the pilot face image during the flight and comparing it with pre-input pilot face images. If a different face is detected, a warning signal is sent to ground automatically. At the same time, the automatic cruise system is started or the plane is controlled by the ground. The terrorists will have no control over the plane. The plane will be landed to a nearest or appropriate airport under the control of the ground or cruise system. This technique could also be used in automobile industry as an image key to avoid car stealth.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

PubMed

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Laser-aided material identification for the waste sorting process

NASA Astrophysics Data System (ADS)

Haferkamp, Heinz; Burmester, Ingo; Engel, Kai

1994-03-01

The LZH has carried out investigations in the field of rapid laser-supported material- identification systems for automatic material-sorting systems. The aim of this research is the fast identification of different sorts of plastics coming from recycled rubbish or electronic waste. Within a few milliseconds a spot on the sample which has to be identified is heated with a CO2 laser. The different and specific chemical and physical material properties of the examined sample cause a different temperature distribution on the surface which is measured with an IR thermographic system. This `thermal impulse response' has to be analyzed by means of a computer system. The results of previous investigations have shown that material identification of different sorts of plastics can possibly be done at a frequency of 30 Hz. Due to economic efficiency, a high velocity identification process is necessary to sort huge waste currents.

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

PubMed Central

Ye-Lin, Yiyao; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique. PMID:24523828

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

PubMed

Ye-Lin, Yiyao; Garcia-Casado, Javier; Prats-Boluda, Gema; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Automatic identification of comparative effectiveness research from Medline citations to support clinicians’ treatment information needs

PubMed Central

Zhang, Mingyuan; Fiol, Guilherme Del; Grout, Randall W.; Jonnalagadda, Siddhartha; Medlin, Richard; Mishra, Rashmi; Weir, Charlene; Liu, Hongfang; Mostafa, Javed; Fiszman, Marcelo

2014-01-01

Online knowledge resources such as Medline can address most clinicians’ patient care information needs. Yet, significant barriers, notably lack of time, limit the use of these sources at the point of care. The most common information needs raised by clinicians are treatment-related. Comparative effectiveness studies allow clinicians to consider multiple treatment alternatives for a particular problem. Still, solutions are needed to enable efficient and effective consumption of comparative effectiveness research at the point of care. Objective Design and assess an algorithm for automatically identifying comparative effectiveness studies and extracting the interventions investigated in these studies. Methods The algorithm combines semantic natural language processing, Medline citation metadata, and machine learning techniques. We assessed the algorithm in a case study of treatment alternatives for depression. Results Both precision and recall for identifying comparative studies was 0.83. A total of 86% of the interventions extracted perfectly or partially matched the gold standard. Conclusion Overall, the algorithm achieved reasonable performance. The method provides building blocks for the automatic summarization of comparative effectiveness research to inform point of care decision-making. PMID:23920677

Automatic Temporal Tracking of Supra-Glacial Lakes

NASA Astrophysics Data System (ADS)

Liang, Y.; Lv, Q.; Gallaher, D. W.; Fanning, D.

2010-12-01

During the recent years, supra-glacial lakes in Greenland have attracted extensive global attention as they potentially play an important role in glacier movement, sea level rise, and climate change. Previous works focused on classification methods and individual cloud-free satellite images, which have limited capabilities in terms of tracking changes of lakes over time. The challenges of tracking supra-glacial lakes automatically include (1) massive amount of satellite images with diverse qualities and frequent cloud coverage, and (2) diversity and dynamics of large number of supra-glacial lakes on the Greenland ice sheet. In this study, we develop an innovative method to automatically track supra-glacial lakes temporally using the Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data. The method works for both cloudy and cloud-free data and is unsupervised, i.e., no manual identification is required. After selecting the highest-quality image within each time interval, our method automatically detects supra-glacial lakes in individual images, using adaptive thresholding to handle diverse image qualities. We then track lakes across time series of images as lakes appear, change in size, and disappear. Using multi-year MODIS data during melting season, we demonstrate that this new method can detect and track supra-glacial lakes in both space and time with 95% accuracy. Attached figure shows an example of the current result. Detailed analysis of the temporal variation of detected lakes will be presented. (a) One of our experimental data. The Investigated region is centered at Jakobshavn Isbrae glacier in west Greenland. (b) Enlarged view of part of ice sheet. It is partially cloudy and with supra-glacial lakes on it. Lakes are shown as dark spots. (c) Current result. Red spots are detected lakes.

Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

PubMed Central

Joo, Deokjin; Kwan, Ye-seul; Song, Jongwoo; Pinho, Catarina; Hey, Jody; Won, Yong-Jin

2013-01-01

Background The explosively radiating evolution of cichlid fishes of Lake Malawi has yielded an amazing number of haplochromine species estimated as many as 500 to 800 with a surprising degree of diversity not only in color and stripe pattern but also in the shape of jaw and body among them. As these morphological diversities have been a central subject of adaptive speciation and taxonomic classification, such high diversity could serve as a foundation for automation of species identification of cichlids. Methodology/Principal Finding Here we demonstrate a method for automatic classification of the Lake Malawi cichlids based on computer vision and geometric morphometrics. For this end we developed a pipeline that integrates multiple image processing tools to automatically extract informative features of color and stripe patterns from a large set of photographic images of wild cichlids. The extracted information was evaluated by statistical classifiers Support Vector Machine and Random Forests. Both classifiers performed better when body shape information was added to the feature of color and stripe. Besides the coloration and stripe pattern, body shape variables boosted the accuracy of classification by about 10%. The programs were able to classify 594 live cichlid individuals belonging to 12 different classes (species and sexes) with an average accuracy of 78%, contrasting to a mere 42% success rate by human eyes. The variables that contributed most to the accuracy were body height and the hue of the most frequent color. Conclusions Computer vision showed a notable performance in extracting information from the color and stripe patterns of Lake Malawi cichlids although the information was not enough for errorless species identification. Our results indicate that there appears an unavoidable difficulty in automatic species identification of cichlid fishes, which may arise from short divergence times and gene flow between closely related species. PMID:24204918

The automatic component of habit in health behavior: habit as cue-contingent automaticity.

PubMed

Orbell, Sheina; Verplanken, Bas

2010-07-01

Habit might be usefully characterized as a form of automaticity that involves the association of a cue and a response. Three studies examined habitual automaticity in regard to different aspects of the cue-response relationship characteristic of unhealthy and healthy habits. In each study, habitual automaticity was assessed by the Self-Report Habit Index (SRHI). In Study 1 SRHI scores correlated with attentional bias to smoking cues in a Stroop task. Study 2 examined the ability of a habit cue to elicit an unwanted habit response. In a prospective field study, habitual automaticity in relation to smoking when drinking alcohol in a licensed public house (pub) predicted the likelihood of cigarette-related action slips 2 months later after smoking in pubs had become illegal. In Study 3 experimental group participants formed an implementation intention to floss in response to a specified situational cue. Habitual automaticity of dental flossing was rapidly enhanced compared to controls. The studies provided three different demonstrations of the importance of cues in the automatic operation of habits. Habitual automaticity assessed by the SRHI captured aspects of a habit that go beyond mere frequency or consistency of the behavior. PsycINFO Database Record (c) 2010 APA, all rights reserved.

An automatic editing algorithm for GPS data

NASA Technical Reports Server (NTRS)

Blewitt, Geoffrey

1990-01-01

An algorithm has been developed to edit automatically Global Positioning System data such that outlier deletion, cycle slip identification, and correction are independent of clock instability, selective availability, receiver-satellite kinematics, and tropospheric conditions. This algorithm, called TurboEdit, operates on undifferenced, dual frequency carrier phase data, and requires the use of P code pseudorange data and a smoothly varying ionospheric electron content. TurboEdit was tested on the large data set from the CASA Uno experiment, which contained over 2500 cycle slips.Analyst intervention was required on 1 percent of the station-satellite passes, almost all of these problems being due to difficulties in extrapolating variations in the ionospheric delay. The algorithm is presently being adapted for real time data editing in the Rogue receiver for continuous monitoring applications.

Automatic identification of cochlear implant electrode arrays for post-operative assessment

NASA Astrophysics Data System (ADS)

Noble, Jack H.; Schuman, Theodore A.; Wright, Charles G.; Labadie, Robert F.; Dawant, Benoit M.

2011-03-01

Cochlear implantation is a procedure performed to treat profound hearing loss. Accurately determining the postoperative position of the implant in vivo would permit studying the correlations between implant position and hearing restoration. To solve this problem, we present an approach based on parametric Gradient Vector Flow snakes to segment the electrode array in post-operative CT. By combining this with existing methods for localizing intra-cochlear anatomy, we have developed a system that permits accurate assessment of the implant position in vivo. The system is validated using a set of seven temporal bone specimens. The algorithms were run on pre- and post-operative CTs of the specimens, and the results were compared to histological images. It was found that the position of the arrays observed in the histological images is in excellent agreement with the position of their automatically generated 3D reconstructions in the CT scans.

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining.

PubMed

Hettne, Kristina M; Williams, Antony J; van Mulligen, Erik M; Kleinjans, Jos; Tkachenko, Valery; Kors, Jan A

2010-03-23

Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus. To achieve an acceptable recall and precision we used a number of automatic and semi-automatic processing steps together with disambiguation rules. However, it remained to be investigated which impact an extensive manual curation of a multi-source chemical dictionary would have on chemical term identification in text. ChemSpider is a chemical database that has undergone extensive manual curation aimed at establishing valid chemical name-to-structure relationships. We acquired the component of ChemSpider containing only manually curated names and synonyms. Rule-based term filtering, semi-automatic manual curation, and disambiguation rules were applied. We tested the dictionary from ChemSpider on an annotated corpus and compared the results with those for the Chemlist dictionary. The ChemSpider dictionary of ca. 80 k names was only a 1/3 to a 1/4 the size of Chemlist at around 300 k. The ChemSpider dictionary had a precision of 0.43 and a recall of 0.19 before the application of filtering and disambiguation and a precision of 0.87 and a recall of 0.19 after filtering and disambiguation. The Chemlist dictionary had a precision of 0.20 and a recall of 0.47 before the application of filtering and disambiguation and a precision of 0.67 and a recall of 0.40 after filtering and disambiguation. We conclude the following: (1) The ChemSpider dictionary achieved the best precision but the Chemlist dictionary had a higher recall and the best F-score; (2) Rule-based filtering and disambiguation is necessary to achieve a high precision for both the automatically generated and the manually curated dictionary. ChemSpider is available as a web service at http://www.chemspider.com/ and the Chemlist dictionary is freely available as an XML file in Simple Knowledge Organization

Automatic identification approach for high-performance liquid chromatography-multiple reaction monitoring fatty acid global profiling.

PubMed

Tie, Cai; Hu, Ting; Jia, Zhi-Xin; Zhang, Jin-Lan

2015-08-18

Fatty acids (FAs) are a group of lipid molecules that are essential to organisms. As potential biomarkers for different diseases, FAs have attracted increasing attention from both biological researchers and the pharmaceutical industry. A sensitive and accurate method for globally profiling and identifying FAs is required for biomarker discovery. The high selectivity and sensitivity of high-performance liquid chromatography-multiple reaction monitoring (HPLC-MRM) gives it great potential to fulfill the need to identify FAs from complicated matrices. This paper developed a new approach for global FA profiling and identification for HPLC-MRM FA data mining. Mathematical models for identifying FAs were simulated using the isotope-induced retention time (RT) shift (IRS) and peak area ratios between parallel isotope peaks for a series of FA standards. The FA structures were predicated using another model based on the RT and molecular weight. Fully automated FA identification software was coded using the Qt platform based on these mathematical models. Different samples were used to verify the software. A high identification efficiency (greater than 75%) was observed when 96 FA species were identified in plasma. This FAs identification strategy promises to accelerate FA research and applications.

Detection and identification of concealed weapons using matrix pencil

NASA Astrophysics Data System (ADS)

Adve, Raviraj S.; Thayaparan, Thayananthan

2011-06-01

The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

Automatic Identification of Critical Follow-Up Recommendation Sentences in Radiology Reports

PubMed Central

Yetisgen-Yildiz, Meliha; Gunn, Martin L.; Xia, Fei; Payne, Thomas H.

2011-01-01

Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. When recommendations are not systematically identified and promptly communicated to referrers, poor patient outcomes can result. Using information technology can improve communication and improve patient safety. In this paper, we describe a text processing approach that uses natural language processing (NLP) and supervised text classification methods to automatically identify critical recommendation sentences in radiology reports. To increase the classification performance we enhanced the simple unigram token representation approach with lexical, semantic, knowledge-base, and structural features. We tested different combinations of those features with the Maximum Entropy (MaxEnt) classification algorithm. Classifiers were trained and tested with a gold standard corpus annotated by a domain expert. We applied 5-fold cross validation and our best performing classifier achieved 95.60% precision, 79.82% recall, 87.0% F-score, and 99.59% classification accuracy in identifying the critical recommendation sentences in radiology reports. PMID:22195225

Automatic identification of critical follow-up recommendation sentences in radiology reports.

PubMed

Yetisgen-Yildiz, Meliha; Gunn, Martin L; Xia, Fei; Payne, Thomas H

2011-01-01

Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. When recommendations are not systematically identified and promptly communicated to referrers, poor patient outcomes can result. Using information technology can improve communication and improve patient safety. In this paper, we describe a text processing approach that uses natural language processing (NLP) and supervised text classification methods to automatically identify critical recommendation sentences in radiology reports. To increase the classification performance we enhanced the simple unigram token representation approach with lexical, semantic, knowledge-base, and structural features. We tested different combinations of those features with the Maximum Entropy (MaxEnt) classification algorithm. Classifiers were trained and tested with a gold standard corpus annotated by a domain expert. We applied 5-fold cross validation and our best performing classifier achieved 95.60% precision, 79.82% recall, 87.0% F-score, and 99.59% classification accuracy in identifying the critical recommendation sentences in radiology reports.

Motor automaticity in Parkinson’s disease

PubMed Central

Wu, Tao; Hallett, Mark; Chan, Piu

2017-01-01

Bradykinesia is the most important feature contributing to motor difficulties in Parkinson’s disease (PD). However, the pathophysiology underlying bradykinesia is not fully understood. One important aspect is that PD patients have difficulty in performing learned motor skills automatically, but this problem has been generally overlooked. Here we review motor automaticity associated motor deficits in PD, such as reduced arm swing, decreased stride length, freezing of gait, micrographia and reduced facial expression. Recent neuroimaging studies have revealed some neural mechanisms underlying impaired motor automaticity in PD, including less efficient neural coding of movement, failure to shift automated motor skills to the sensorimotor striatum, instability of the automatic mode within the striatum, and use of attentional control and/or compensatory efforts to execute movements usually performed automatically in healthy people. PD patients lose previously acquired automatic skills due to their impaired sensorimotor striatum, and have difficulty in acquiring new automatic skills or restoring lost motor skills. More investigations on the pathophysiology of motor automaticity, the effect of L-dopa or surgical treatments on automaticity, and the potential role of using measures of automaticity in early diagnosis of PD would be valuable. PMID:26102020

Improving automatic peptide mass fingerprint protein identification by combining many peak sets.

PubMed

Rögnvaldsson, Thorsteinn; Häkkinen, Jari; Lindberg, Claes; Marko-Varga, György; Potthast, Frank; Samuelsson, Jim

2004-08-05

An automated peak picking strategy is presented where several peak sets with different signal-to-noise levels are combined to form a more reliable statement on the protein identity. The strategy is compared against both manual peak picking and industry standard automated peak picking on a set of mass spectra obtained after tryptic in gel digestion of 2D-gel samples from human fetal fibroblasts. The set of spectra contain samples ranging from strong to weak spectra, and the proposed multiple-scale method is shown to be much better on weak spectra than the industry standard method and a human operator, and equal in performance to these on strong and medium strong spectra. It is also demonstrated that peak sets selected by a human operator display a considerable variability and that it is impossible to speak of a single "true" peak set for a given spectrum. The described multiple-scale strategy both avoids time-consuming parameter tuning and exceeds the human operator in protein identification efficiency. The strategy therefore promises reliable automated user-independent protein identification using peptide mass fingerprints.

Screening for Protein-DNA Interactions by Automatable DNA-Protein Interaction ELISA

PubMed Central

Schüssler, Axel; Kolukisaoglu, H. Üner; Koch, Grit; Wallmeroth, Niklas; Hecker, Andreas; Thurow, Kerstin; Zell, Andreas; Harter, Klaus; Wanke, Dierk

2013-01-01

DNA-binding proteins (DBPs), such as transcription factors, constitute about 10% of the protein-coding genes in eukaryotic genomes and play pivotal roles in the regulation of chromatin structure and gene expression by binding to short stretches of DNA. Despite their number and importance, only for a minor portion of DBPs the binding sequence had been disclosed. Methods that allow the de novo identification of DNA-binding motifs of known DBPs, such as protein binding microarray technology or SELEX, are not yet suited for high-throughput and automation. To close this gap, we report an automatable DNA-protein-interaction (DPI)-ELISA screen of an optimized double-stranded DNA (dsDNA) probe library that allows the high-throughput identification of hexanucleotide DNA-binding motifs. In contrast to other methods, this DPI-ELISA screen can be performed manually or with standard laboratory automation. Furthermore, output evaluation does not require extensive computational analysis to derive a binding consensus. We could show that the DPI-ELISA screen disclosed the full spectrum of binding preferences for a given DBP. As an example, AtWRKY11 was used to demonstrate that the automated DPI-ELISA screen revealed the entire range of in vitro binding preferences. In addition, protein extracts of AtbZIP63 and the DNA-binding domain of AtWRKY33 were analyzed, which led to a refinement of their known DNA-binding consensi. Finally, we performed a DPI-ELISA screen to disclose the DNA-binding consensus of a yet uncharacterized putative DBP, AtTIFY1. A palindromic TGATCA-consensus was uncovered and we could show that the GATC-core is compulsory for AtTIFY1 binding. This specific interaction between AtTIFY1 and its DNA-binding motif was confirmed by in vivo plant one-hybrid assays in protoplasts. Thus, the value and applicability of the DPI-ELISA screen for de novo binding site identification of DBPs, also under automatized conditions, is a promising approach for a deeper understanding

Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

PubMed

Zare, Marzieh; Rezvani, Zahra; Benasich, April A

2016-07-01

This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier detection of developmental disorders that disrupt language acquisition. Network connectivity measures derived from 62-channel electroencephalogram (EEG) recording were used to identify selected features within two infant groups who differed on LLD risk: infants with a family history of LLD (FH+) and typically-developing infants without such a history (FH-). A support vector machine was deployed; global efficiency and global and local clustering coefficients were computed. A novel minimum spanning tree (MST) approach was also applied. Cross-validation was employed to assess the resultant classification. Infants were classified with about 80% accuracy into FH+ and FH- groups with 89% specificity and precision of 92%. Clustering patterns differed by risk group and MST network analysis suggests that FH+ infants' EEG complexity patterns were significantly different from FH- infants. The automatic classification techniques used here were shown to be both robust and reliable and should provide valuable information when applied to early identification of risk or clinical groups. The ability to identify infants at highest risk for LLD using "automatic classification" strategies is a novel convergent approach that may facilitate earlier diagnosis and remediation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Automatic imitation: A meta-analysis.

PubMed

Cracco, Emiel; Bardi, Lara; Desmet, Charlotte; Genschow, Oliver; Rigoni, Davide; De Coster, Lize; Radkova, Ina; Deschrijver, Eliane; Brass, Marcel

2018-05-01

Automatic imitation is the finding that movement execution is facilitated by compatible and impeded by incompatible observed movements. In the past 15 years, automatic imitation has been studied to understand the relation between perception and action in social interaction. Although research on this topic started in cognitive science, interest quickly spread to related disciplines such as social psychology, clinical psychology, and neuroscience. However, important theoretical questions have remained unanswered. Therefore, in the present meta-analysis, we evaluated seven key questions on automatic imitation. The results, based on 161 studies containing 226 experiments, revealed an overall effect size of g z = 0.95, 95% CI [0.88, 1.02]. Moderator analyses identified automatic imitation as a flexible, largely automatic process that is driven by movement and effector compatibility, but is also influenced by spatial compatibility. Automatic imitation was found to be stronger for forced choice tasks than for simple response tasks, for human agents than for nonhuman agents, and for goalless actions than for goal-directed actions. However, it was not modulated by more subtle factors such as animacy beliefs, motion profiles, or visual perspective. Finally, there was no evidence for a relation between automatic imitation and either empathy or autism. Among other things, these findings point toward actor-imitator similarity as a crucial modulator of automatic imitation and challenge the view that imitative tendencies are an indicator of social functioning. The current meta-analysis has important theoretical implications and sheds light on longstanding controversies in the literature on automatic imitation and related domains. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Automatic Text Structuring and Summarization.

ERIC Educational Resources Information Center

Salton, Gerard; And Others

1997-01-01

Discussion of the use of information retrieval techniques for automatic generation of semantic hypertext links focuses on automatic text summarization. Topics include World Wide Web links, text segmentation, and evaluation of text summarization by comparing automatically generated abstracts with manually prepared abstracts. (Author/LRW)

First tests of a multi-wavelength mini-DIAL system for the automatic detection of greenhouse gases

NASA Astrophysics Data System (ADS)

Parracino, S.; Gelfusa, M.; Lungaroni, M.; Murari, A.; Peluso, E.; Ciparisse, J. F.; Malizia, A.; Rossi, R.; Ventura, P.; Gaudio, P.

2017-10-01

Considering the increase of atmospheric pollution levels in our cities, due to emissions from vehicles and domestic heating, and the growing threat of terrorism, it is necessary to develop instrumentation and gather know-how for the automatic detection and measurement of dangerous substances as quickly and far away as possible. The Multi- Wavelength DIAL, an extension of the conventional DIAL technique, is one of the most powerful remote sensing methods for the identification of multiple substances and seems to be a promising solution compared to existing alternatives. In this paper, first in-field tests of a smart and fully automated Multi-Wavelength mini-DIAL will be presented and discussed in details. The recently developed system, based on a long-wavelength infrared (IR-C) CO2 laser source, has the potential of giving an early warning, whenever something strange is found in the atmosphere, followed by identification and simultaneous concentration measurements of many chemical species, ranging from the most important Greenhouse Gases (GHG) to other harmful Volatile Organic Compounds (VOCs). Preliminary studies, regarding the fingerprint of the investigated substances, have been carried out by cross-referencing database of infrared (IR) spectra, obtained using in-cell measurements, and typical Mixing Ratios in the examined region, extrapolated from the literature. First experiments in atmosphere have been performed into a suburban and moderately-busy area of Rome. Moreover, to optimize the automatic identification of the harmful species to be recognized on the basis of in cell measurements of the absorption coefficient spectra, an advanced multivariate statistical method for classification has been developed and tested.

Comparison of automatic control systems

NASA Technical Reports Server (NTRS)

Oppelt, W

1941-01-01

This report deals with a reciprocal comparison of an automatic pressure control, an automatic rpm control, an automatic temperature control, and an automatic directional control. It shows the difference between the "faultproof" regulator and the actual regulator which is subject to faults, and develops this difference as far as possible in a parallel manner with regard to the control systems under consideration. Such as analysis affords, particularly in its extension to the faults of the actual regulator, a deep insight into the mechanism of the regulator process.

A De-Identification Pipeline for Ultrasound Medical Images in DICOM Format.

PubMed

Monteiro, Eriksson; Costa, Carlos; Oliveira, José Luís

2017-05-01

Clinical data sharing between healthcare institutions, and between practitioners is often hindered by privacy protection requirements. This problem is critical in collaborative scenarios where data sharing is fundamental for establishing a workflow among parties. The anonymization of patient information burned in DICOM images requires elaborate processes somewhat more complex than simple de-identification of textual information. Usually, before sharing, there is a need for manual removal of specific areas containing sensitive information in the images. In this paper, we present a pipeline for ultrasound medical image de-identification, provided as a free anonymization REST service for medical image applications, and a Software-as-a-Service to streamline automatic de-identification of medical images, which is freely available for end-users. The proposed approach applies image processing functions and machine-learning models to bring about an automatic system to anonymize medical images. To perform character recognition, we evaluated several machine-learning models, being Convolutional Neural Networks (CNN) selected as the best approach. For accessing the system quality, 500 processed images were manually inspected showing an anonymization rate of 89.2%. The tool can be accessed at https://bioinformatics.ua.pt/dicom/anonymizer and it is available with the most recent version of Google Chrome, Mozilla Firefox and Safari. A Docker image containing the proposed service is also publicly available for the community.

A unified framework for evaluating the risk of re-identification of text de-identification tools.

PubMed

Scaiano, Martin; Middleton, Grant; Arbuckle, Luk; Kolhatkar, Varada; Peyton, Liam; Dowling, Moira; Gipson, Debbie S; El Emam, Khaled

2016-10-01

It has become regular practice to de-identify unstructured medical text for use in research using automatic methods, the goal of which is to remove patient identifying information to minimize re-identification risk. The metrics commonly used to determine if these systems are performing well do not accurately reflect the risk of a patient being re-identified. We therefore developed a framework for measuring the risk of re-identification associated with textual data releases. We apply the proposed evaluation framework to a data set from the University of Michigan Medical School. Our risk assessment results are then compared with those that would be obtained using a typical contemporary micro-average evaluation of recall in order to illustrate the difference between the proposed evaluation framework and the current baseline method. We demonstrate how this framework compares against common measures of the re-identification risk associated with an automated text de-identification process. For the probability of re-identification using our evaluation framework we obtained a mean value for direct identifiers of 0.0074 and a mean value for quasi-identifiers of 0.0022. The 95% confidence interval for these estimates were below the relevant thresholds. The threshold for direct identifier risk was based on previously used approaches in the literature. The threshold for quasi-identifiers was determined based on the context of the data release following commonly used de-identification criteria for structured data. Our framework attempts to correct for poorly distributed evaluation corpora, accounts for the data release context, and avoids the often optimistic assumptions that are made using the more traditional evaluation approach. It therefore provides a more realistic estimate of the true probability of re-identification. This framework should be used as a basis for computing re-identification risk in order to more realistically evaluate future text de-identification tools

Preclinical Biokinetic Modelling of Tc-99m Radiophamaceuticals Obtained from Semi-Automatic Image Processing.

PubMed

Cornejo-Aragón, Luz G; Santos-Cuevas, Clara L; Ocampo-García, Blanca E; Chairez-Oria, Isaac; Diaz-Nieto, Lorenza; García-Quiroz, Janice

2017-01-01

The aim of this study was to develop a semi automatic image processing algorithm (AIPA) based on the simultaneous information provided by X-ray and radioisotopic images to determine the biokinetic models of Tc-99m radiopharmaceuticals from quantification of image radiation activity in murine models. These radioisotopic images were obtained by a CCD (charge couple device) camera coupled to an ultrathin phosphorous screen in a preclinical multimodal imaging system (Xtreme, Bruker). The AIPA consisted of different image processing methods for background, scattering and attenuation correction on the activity quantification. A set of parametric identification algorithms was used to obtain the biokinetic models that characterize the interaction between different tissues and the radiopharmaceuticals considered in the study. The set of biokinetic models corresponded to the Tc-99m biodistribution observed in different ex vivo studies. This fact confirmed the contribution of the semi-automatic image processing technique developed in this study.

Automatic Implementation of Prony Analysis for Electromechanical Mode Identification from Phasor Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ning; Huang, Zhenyu; Tuffner, Francis K.

2010-07-31

Small signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper developed a recursive algorithm for implementing Prony analysis and proposed an oscillation detection method to detect ringdown data in real time. By automatically detect ringdown data, the proposed method helps guarantee that Prony analysis is applied properly and timely on the ringdown data. Thus, the mode estimation results can be performed reliablymore » and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis.« less

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture

DOEpatents

Lassahn, Gordon D.; Lancaster, Gregory D.; Apel, William A.; Thompson, Vicki S.

2013-01-08

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture are described. According to one embodiment, an image portion identification method includes accessing data regarding an image depicting a plurality of biological substrates corresponding to at least one biological sample and indicating presence of at least one biological indicator within the biological sample and, using processing circuitry, automatically identifying a portion of the image depicting one of the biological substrates but not others of the biological substrates.

Automatic picker of P & S first arrivals and robust event locator

NASA Astrophysics Data System (ADS)

Pinsky, V.; Polozov, A.; Hofstetter, A.

2003-12-01

We report on further development of automatic all distances location procedure designed for a regional network. The procedure generalizes the previous "loca l" (R < 500 km) and "regional" (500 < R < 2000 km) routines and comprises: a) preliminary data processing (filtering and de-spiking), b) phase identificatio n, c) P, S first arrival picking, d) preliminary location and e) robust grid-search optimization procedure. Innovations concern phase identification, automa tic picking and teleseismic location. A platform free flexible Java interface was recently created, allowing easy parameter tuning and on/off switching to t he full-scale manual picking mode. Identification of the regional P and S phase is provided by choosing between the two largest peaks in the envelope curve. For automatic on-time estimation we utilize now ratio of two STAs, calculated in two consecutive and equal time windows (instead of previously used Akike Information Criterion). "Teleseismic " location is split in two stages: preliminary and final one. The preliminary part estimates azimuth and apparent velocity by fitting a plane wave to the P automatic pickings. The apparent velocity criterion is used to decide about strategy of the following computations: teleseismic or regional. The preliminary estimates of azimuth and apparent velocity provide starting value for the final teleseismic and regional location. Apparent velocity is used to get first a pproximation distance to the source on the basis of the P, Pn, Pg travel-timetables. The distance estimate together with the preliminary azimuth estimate provides first approximations of the source latitude and longitude via sine and cosine theorems formulated for the spherical triangle. Final location is based on robust grid-search optimization procedure, weighting the number of pickings that simultaneously fit the model travel times. The grid covers initial location and becomes finer while approaching true hypocenter. The target function is a sum

Automatic de-identification of textual documents in the electronic health record: a review of recent research

PubMed Central

2010-01-01

Background In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. Methods This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. Results The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

PubMed

Meystre, Stephane M; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2010-08-02

In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and

In-flight wobble identification for Galileo

NASA Technical Reports Server (NTRS)

Lai, J. Y.; Wong, E. C.

1984-01-01

To achieve in-flight wobble compensation for Galileo, wobble identification is implemented using star scanner data or automatic gain control (AGC) signal as measurement in all-spin mode. The star scanner provides spacecraft attitude in inertial space while the AGC signal provides the spacecraft pointing relative to earth. A linear observation model is defined for each sensor which is being applied to a Kalman Estimator. It can be shown from simulation that better result can be achieved using a combined set of data than any one sensor alone due to correlation reduction among error sources.

Input-output identification of controlled discrete manufacturing systems

NASA Astrophysics Data System (ADS)

Estrada-Vargas, Ana Paula; López-Mellado, Ernesto; Lesage, Jean-Jacques

2014-03-01

The automated construction of discrete event models from observations of external system's behaviour is addressed. This problem, often referred to as system identification, allows obtaining models of ill-known (or even unknown) systems. In this article, an identification method for discrete event systems (DESs) controlled by a programmable logic controller is presented. The method allows processing a large quantity of observed long sequences of input/output signals generated by the controller and yields an interpreted Petri net model describing the closed-loop behaviour of the automated DESs. The proposed technique allows the identification of actual complex systems because it is sufficiently efficient and well adapted to cope with both the technological characteristics of industrial controllers and data collection requirements. Based on polynomial-time algorithms, the method is implemented as an efficient software tool which constructs and draws the model automatically; an overview of this tool is given through a case study dealing with an automated manufacturing system.

Automatic Collision Avoidance Technology (ACAT)

NASA Technical Reports Server (NTRS)

Swihart, Donald E.; Skoog, Mark A.

2007-01-01

This document represents two views of the Automatic Collision Avoidance Technology (ACAT). One viewgraph presentation reviews the development and system design of Automatic Collision Avoidance Technology (ACAT). Two types of ACAT exist: Automatic Ground Collision Avoidance (AGCAS) and Automatic Air Collision Avoidance (AACAS). The AGCAS Uses Digital Terrain Elevation Data (DTED) for mapping functions, and uses Navigation data to place aircraft on map. It then scans DTED in front of and around aircraft and uses future aircraft trajectory (5g) to provide automatic flyup maneuver when required. The AACAS uses data link to determine position and closing rate. It contains several canned maneuvers to avoid collision. Automatic maneuvers can occur at last instant and both aircraft maneuver when using data link. The system can use sensor in place of data link. The second viewgraph presentation reviews the development of a flight test and an evaluation of the test. A review of the operation and comparison of the AGCAS and a pilot's performance are given. The same review is given for the AACAS is given.

Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models

NASA Astrophysics Data System (ADS)

Matsumoto, Monica M. S.; Beig, Niha G.; Udupa, Jayaram K.; Archer, Steven; Torigian, Drew A.

2014-03-01

Lung cancer is associated with the highest cancer mortality rates among men and women in the United States. The accurate and precise identification of the lymph node stations on computed tomography (CT) images is important for staging disease and potentially for prognosticating outcome in patients with lung cancer, as well as for pretreatment planning and response assessment purposes. To facilitate a standard means of referring to lymph nodes, the International Association for the Study of Lung Cancer (IASLC) has recently proposed a definition of the different lymph node stations and zones in the thorax. However, nodal station identification is typically performed manually by visual assessment in clinical radiology. This approach leaves room for error due to the subjective and potentially ambiguous nature of visual interpretation, and is labor intensive. We present a method of automatically recognizing the mediastinal IASLC-defined lymph node stations by modifying a hierarchical fuzzy modeling approach previously developed for body-wide automatic anatomy recognition (AAR) in medical imagery. Our AAR-lymph node (AAR-LN) system follows the AAR methodology and consists of two steps. In the first step, the various lymph node stations are manually delineated on a set of CT images following the IASLC definitions. These delineations are then used to build a fuzzy hierarchical model of the nodal stations which are considered as 3D objects. In the second step, the stations are automatically located on any given CT image of the thorax by using the hierarchical fuzzy model and object recognition algorithms. Based on 23 data sets used for model building, 22 independent data sets for testing, and 10 lymph node stations, a mean localization accuracy of within 1-6 voxels has been achieved by the AAR-LN system.

Attendance fingerprint identification system using arduino and single board computer

NASA Astrophysics Data System (ADS)

Muchtar, M. A.; Seniman; Arisandi, D.; Hasanah, S.

2018-03-01

Fingerprint is one of the most unique parts of the human body that distinguishes one person from others and is easily accessed. This uniqueness is supported by technology that can automatically identify or recognize a person called fingerprint sensor. Yet, the existing Fingerprint Sensor can only do fingerprint identification on one machine. For the mentioned reason, we need a method to be able to recognize each user in a different fingerprint sensor. The purpose of this research is to build fingerprint sensor system for fingerprint data management to be centralized so identification can be done in each Fingerprint Sensor. The result of this research shows that by using Arduino and Raspberry Pi, data processing can be centralized so that fingerprint identification can be done in each fingerprint sensor with 98.5 % success rate of centralized server recording.

Automatic Coal-Mining System

NASA Technical Reports Server (NTRS)

Collins, E. R., Jr.

1985-01-01

Coal cutting and removal done with minimal hazard to people. Automatic coal mine cutting, transport and roof-support movement all done by automatic machinery. Exposure of people to hazardous conditions reduced to inspection tours, maintenance, repair, and possibly entry mining.

Learning Efficient Spatial-Temporal Gait Features with Deep Learning for Human Identification.

PubMed

Liu, Wu; Zhang, Cheng; Ma, Huadong; Li, Shuangqun

2018-02-06

The integration of the latest breakthroughs in bioinformatics technology from one side and artificial intelligence from another side, enables remarkable advances in the fields of intelligent security guard computational biology, healthcare, and so on. Among them, biometrics based automatic human identification is one of the most fundamental and significant research topic. Human gait, which is a biometric features with the unique capability, has gained significant attentions as the remarkable characteristics of remote accessed, robust and security in the biometrics based human identification. However, the existed methods cannot well handle the indistinctive inter-class differences and large intra-class variations of human gait in real-world situation. In this paper, we have developed an efficient spatial-temporal gait features with deep learning for human identification. First of all, we proposed a gait energy image (GEI) based Siamese neural network to automatically extract robust and discriminative spatial gait features for human identification. Furthermore, we exploit the deep 3-dimensional convolutional networks to learn the human gait convolutional 3D (C3D) as the temporal gait features. Finally, the GEI and C3D gait features are embedded into the null space by the Null Foley-Sammon Transform (NFST). In the new space, the spatial-temporal features are sufficiently combined with distance metric learning to drive the similarity metric to be small for pairs of gait from the same person, and large for pairs from different persons. Consequently, the experiments on the world's largest gait database show our framework impressively outperforms state-of-the-art methods.

Patient identification error among prostate needle core biopsy specimens--are we ready for a DNA time-out?

PubMed

Suba, Eric J; Pfeifer, John D; Raab, Stephen S

2007-10-01

Patient identification errors in surgical pathology often involve switches of prostate or breast needle core biopsy specimens among patients. We assessed strategies for decreasing the occurrence of these uncommon and yet potentially catastrophic events. Root cause analyses were performed following 3 cases of patient identification error involving prostate needle core biopsy specimens. Patient identification errors in surgical pathology result from slips and lapses of automatic human action that may occur at numerous steps during pre-laboratory, laboratory and post-laboratory work flow processes. Patient identification errors among prostate needle biopsies may be difficult to entirely prevent through the optimization of work flow processes. A DNA time-out, whereby DNA polymorphic microsatellite analysis is used to confirm patient identification before radiation therapy or radical surgery, may eliminate patient identification errors among needle biopsies.

6 CFR 37.19 - Machine readable technology on the driver's license or identification card.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., States must use the ISO/IEC 15438:2006(E) Information Technology—Automatic identification and data... 6 Domestic Security 1 2011-01-01 2011-01-01 false Machine readable technology on the driver's..., Verification, and Card Issuance Requirements § 37.19 Machine readable technology on the driver's license or...

6 CFR 37.19 - Machine readable technology on the driver's license or identification card.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., States must use the ISO/IEC 15438:2006(E) Information Technology—Automatic identification and data... 6 Domestic Security 1 2010-01-01 2010-01-01 false Machine readable technology on the driver's..., Verification, and Card Issuance Requirements § 37.19 Machine readable technology on the driver's license or...

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

PubMed Central

2010-01-01

Background Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus. To achieve an acceptable recall and precision we used a number of automatic and semi-automatic processing steps together with disambiguation rules. However, it remained to be investigated which impact an extensive manual curation of a multi-source chemical dictionary would have on chemical term identification in text. ChemSpider is a chemical database that has undergone extensive manual curation aimed at establishing valid chemical name-to-structure relationships. Results We acquired the component of ChemSpider containing only manually curated names and synonyms. Rule-based term filtering, semi-automatic manual curation, and disambiguation rules were applied. We tested the dictionary from ChemSpider on an annotated corpus and compared the results with those for the Chemlist dictionary. The ChemSpider dictionary of ca. 80 k names was only a 1/3 to a 1/4 the size of Chemlist at around 300 k. The ChemSpider dictionary had a precision of 0.43 and a recall of 0.19 before the application of filtering and disambiguation and a precision of 0.87 and a recall of 0.19 after filtering and disambiguation. The Chemlist dictionary had a precision of 0.20 and a recall of 0.47 before the application of filtering and disambiguation and a precision of 0.67 and a recall of 0.40 after filtering and disambiguation. Conclusions We conclude the following: (1) The ChemSpider dictionary achieved the best precision but the Chemlist dictionary had a higher recall and the best F-score; (2) Rule-based filtering and disambiguation is necessary to achieve a high precision for both the automatically generated and the manually curated dictionary. ChemSpider is available as a web service at http://www.chemspider.com/ and the Chemlist dictionary is freely available as an XML file in

Automatic switching matrix

DOEpatents

Schlecht, Martin F.; Kassakian, John G.; Caloggero, Anthony J.; Rhodes, Bruce; Otten, David; Rasmussen, Neil

1982-01-01

An automatic switching matrix that includes an apertured matrix board containing a matrix of wires that can be interconnected at each aperture. Each aperture has associated therewith a conductive pin which, when fully inserted into the associated aperture, effects electrical connection between the wires within that particular aperture. Means is provided for automatically inserting the pins in a determined pattern and for removing all the pins to permit other interconnecting patterns.

A hybrid model for automatic identification of risk factors for heart disease.

PubMed

Yang, Hui; Garibaldi, Jonathan M

2015-12-01

Coronary artery disease (CAD) is the leading cause of death in both the UK and worldwide. The detection of related risk factors and tracking their progress over time is of great importance for early prevention and treatment of CAD. This paper describes an information extraction system that was developed to automatically identify risk factors for heart disease in medical records while the authors participated in the 2014 i2b2/UTHealth NLP Challenge. Our approaches rely on several nature language processing (NLP) techniques such as machine learning, rule-based methods, and dictionary-based keyword spotting to cope with complicated clinical contexts inherent in a wide variety of risk factors. Our system achieved encouraging performance on the challenge test data with an overall micro-averaged F-measure of 0.915, which was competitive to the best system (F-measure of 0.927) of this challenge task. Copyright © 2015 Elsevier Inc. All rights reserved.

Perfusion CT in acute stroke: effectiveness of automatically-generated colour maps.

PubMed

Ukmar, Maja; Degrassi, Ferruccio; Pozzi Mucelli, Roberta Antea; Neri, Francesca; Mucelli, Fabio Pozzi; Cova, Maria Assunta

2017-04-01

To evaluate the accuracy of perfusion CT (pCT) in the definition of the infarcted core and the penumbra, comparing the data obtained from the evaluation of parametric maps [cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT)] with software-generated colour maps. A retrospective analysis was performed to identify patients with suspected acute ischaemic strokes and who had undergone unenhanced CT and pCT carried out within 4.5 h from the onset of the symptoms. A qualitative evaluation of the CBV, CBF and MTT maps was performed, followed by an analysis of the colour maps automatically generated by the software. 26 patients were identified, but a direct CT follow-up was performed only on 19 patients after 24-48 h. In the qualitative analysis, 14 patients showed perfusion abnormalities. Specifically, 29 perfusion deficit areas were detected, of which 15 areas suggested the penumbra and the remaining 14 areas suggested the infarct. As for automatically software-generated maps, 12 patients showed perfusion abnormalities. 25 perfusion deficit areas were identified, 15 areas of which suggested the penumbra and the other 10 areas the infarct. The McNemar's test showed no statistically significant difference between the two methods of evaluation in highlighting infarcted areas proved later at CT follow-up. We demonstrated how pCT provides good diagnostic accuracy in the identification of acute ischaemic lesions. The limits of identification of the lesions mainly lie at the pons level and in the basal ganglia area. Qualitative analysis has proven to be more efficient in identification of perfusion lesions in comparison with software-generated maps. However, software-generated maps have proven to be very useful in the emergency setting. Advances in knowledge: The use of CT perfusion is requested in increasingly more patients in order to optimize the treatment, thanks also to the technological evolution of CT, which now allows a whole

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection.

PubMed

Ghose, Soumya; Mitra, Jhimli; Rivest-Hénault, David; Fazlollahi, Amir; Stanwell, Peter; Pichler, Peter; Sun, Jidi; Fripp, Jurgen; Greer, Peter B; Dowling, Jason A

2016-05-01

The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering "similar" gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a

Automatic assembly of micro-optical components

NASA Astrophysics Data System (ADS)

Gengenbach, Ulrich K.

1996-12-01

Automatic assembly becomes an important issue as hybrid micro systems enter industrial fabrication. Moving from a laboratory scale production with manual assembly and bonding processes to automatic assembly requires a thorough re- evaluation of the design, the characteristics of the individual components and of the processes involved. Parts supply for automatic operation, sensitive and intelligent grippers adapted to size, surface and material properties of the microcomponents gain importance when the superior sensory and handling skills of a human are to be replaced by a machine. This holds in particular for the automatic assembly of micro-optical components. The paper outlines these issues exemplified at the automatic assembly of a micro-optical duplexer consisting of a micro-optical bench fabricated by the LIGA technique, two spherical lenses, a wavelength filter and an optical fiber. Spherical lenses, wavelength filter and optical fiber are supplied by third party vendors, which raises the question of parts supply for automatic assembly. The bonding processes for these components include press fit and adhesive bonding. The prototype assembly system with all relevant components e.g. handling system, parts supply, grippers and control is described. Results of first automatic assembly tests are presented.

Automated detection of retinal landmarks for the identification of clinically relevant regions in fundus photography

NASA Astrophysics Data System (ADS)

Ometto, Giovanni; Calivá, Francesco; Al-Diri, Bashir; Bek, Toke; Hunter, Andrew

2016-03-01

Automatic, quick and reliable identification of retinal landmarks from fundus photography is key for measurements used in research, diagnosis, screening and treating of common diseases affecting the eyes. This study presents a fast method for the detection of the centre of mass of the vascular arcades, optic nerve head (ONH) and fovea, used in the definition of five clinically relevant areas in use for screening programmes for diabetic retinopathy (DR). Thirty-eight fundus photographs showing 7203 DR lesions were analysed to find the landmarks manually by two retina-experts and automatically by the proposed method. The automatic identification of the ONH and fovea were performed using template matching based on normalised cross correlation. The centre of mass of the arcades was obtained by fitting an ellipse on sample coordinates of the main vessels. The coordinates were obtained by processing the image with hessian filtering followed by shape analyses and finally sampling the results. The regions obtained manually and automatically were used to count the retinal lesions falling within, and to evaluate the method. 92.7% of the lesions were falling within the same regions based on the landmarks selected by the two experts. 91.7% and 89.0% were counted in the same areas identified by the method and the first and second expert respectively. The inter-repeatability of the proposed method and the experts is comparable, while the 100% intra-repeatability makes the algorithm a valuable tool in tasks like analyses in real-time, of large datasets and of intra-patient variability.

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

Neural Bases of Automaticity

ERIC Educational Resources Information Center

Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.

2018-01-01

Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…

A novel GLM-based method for the Automatic IDentification of functional Events (AIDE) in fNIRS data recorded in naturalistic environments.

PubMed

Pinti, Paola; Merla, Arcangelo; Aichelburg, Clarisse; Lind, Frida; Power, Sarah; Swingler, Elizabeth; Hamilton, Antonia; Gilbert, Sam; Burgess, Paul W; Tachtsidis, Ilias

2017-07-15

Recent technological advances have allowed the development of portable functional Near-Infrared Spectroscopy (fNIRS) devices that can be used to perform neuroimaging in the real-world. However, as real-world experiments are designed to mimic everyday life situations, the identification of event onsets can be extremely challenging and time-consuming. Here, we present a novel analysis method based on the general linear model (GLM) least square fit analysis for the Automatic IDentification of functional Events (or AIDE) directly from real-world fNIRS neuroimaging data. In order to investigate the accuracy and feasibility of this method, as a proof-of-principle we applied the algorithm to (i) synthetic fNIRS data simulating both block-, event-related and mixed-design experiments and (ii) experimental fNIRS data recorded during a conventional lab-based task (involving maths). AIDE was able to recover functional events from simulated fNIRS data with an accuracy of 89%, 97% and 91% for the simulated block-, event-related and mixed-design experiments respectively. For the lab-based experiment, AIDE recovered more than the 66.7% of the functional events from the fNIRS experimental measured data. To illustrate the strength of this method, we then applied AIDE to fNIRS data recorded by a wearable system on one participant during a complex real-world prospective memory experiment conducted outside the lab. As part of the experiment, there were four and six events (actions where participants had to interact with a target) for the two different conditions respectively (condition 1: social-interact with a person; condition 2: non-social-interact with an object). AIDE managed to recover 3/4 events and 3/6 events for conditions 1 and 2 respectively. The identified functional events were then corresponded to behavioural data from the video recordings of the movements and actions of the participant. Our results suggest that "brain-first" rather than "behaviour-first" analysis is

SAVLOC, computer program for automatic control and analysis of X-ray fluorescence experiments

NASA Technical Reports Server (NTRS)

Leonard, R. F.

1977-01-01

A program for a PDP-15 computer is presented which provides for control and analysis of trace element determinations by using X-ray fluorescence. The program simultaneously handles data accumulation for one sample and analysis of data from previous samples. Data accumulation consists of sample changing, timing, and data storage. Analysis requires the locating of peaks in X-ray spectra, determination of intensities of peaks, identification of origins of peaks, and determination of a real density of the element responsible for each peak. The program may be run in either a manual (supervised) mode or an automatic (unsupervised) mode.

46 CFR 52.01-10 - Automatic controls.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 2 2013-10-01 2013-10-01 false Automatic controls. 52.01-10 Section 52.01-10 Shipping... Requirements § 52.01-10 Automatic controls. (a) Each main boiler must meet the special requirements for automatic safety controls in § 62.35-20(a)(1) of this chapter. (b) Each automatically controlled auxiliary...

46 CFR 52.01-10 - Automatic controls.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Automatic controls. 52.01-10 Section 52.01-10 Shipping... Requirements § 52.01-10 Automatic controls. (a) Each main boiler must meet the special requirements for automatic safety controls in § 62.35-20(a)(1) of this chapter. (b) Each automatically controlled auxiliary...

46 CFR 52.01-10 - Automatic controls.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 2 2014-10-01 2014-10-01 false Automatic controls. 52.01-10 Section 52.01-10 Shipping... Requirements § 52.01-10 Automatic controls. (a) Each main boiler must meet the special requirements for automatic safety controls in § 62.35-20(a)(1) of this chapter. (b) Each automatically controlled auxiliary...

46 CFR 52.01-10 - Automatic controls.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 2 2012-10-01 2012-10-01 false Automatic controls. 52.01-10 Section 52.01-10 Shipping... Requirements § 52.01-10 Automatic controls. (a) Each main boiler must meet the special requirements for automatic safety controls in § 62.35-20(a)(1) of this chapter. (b) Each automatically controlled auxiliary...

46 CFR 52.01-10 - Automatic controls.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 2 2011-10-01 2011-10-01 false Automatic controls. 52.01-10 Section 52.01-10 Shipping... Requirements § 52.01-10 Automatic controls. (a) Each main boiler must meet the special requirements for automatic safety controls in § 62.35-20(a)(1) of this chapter. (b) Each automatically controlled auxiliary...

Google Earth Visualizations of the Marine Automatic Identification System (AIS): Monitoring Ship Traffic in National Marine Sanctuaries

NASA Astrophysics Data System (ADS)

Schwehr, K.; Hatch, L.; Thompson, M.; Wiley, D.

2007-12-01

The Automatic Identification System (AIS) is a new technology that provides ship position reports with location, time, and identity information without human intervention from ships carrying the transponders to any receiver listening to the broadcasts. In collaboration with the USCG's Research and Development Center, NOAA's Stellwagen Bank National Marine Sanctuary (SBNMS) has installed 3 AIS receivers around Massachusetts Bay to monitor ship traffic transiting the sanctuary and surrounding waters. The SBNMS and the USCG also worked together propose the shifting the shipping lanes (termed the traffic separation scheme; TSS) that transit the sanctuary slightly to the north to reduce the probability of ship strikes of whales that frequent the sanctuary. Following approval by the United Nation's International Maritime Organization, AIS provided a means for NOAA to assess changes in the distribution of shipping traffic caused by formal change in the TSS effective July 1, 2007. However, there was no easy way to visualize this type of time series data. We have created a software package called noaadata-py to process the AIS ship reports and produce KML files for viewing in Google Earth. Ship tracks can be shown changing over time to allow the viewer to feel the motion of traffic through the sanctuary. The ship tracks can also be gridded to create ship traffic density reports for specified periods of time. The density is displayed as map draped on the sea surface or as vertical histogram columns. Additional visualizations such as bathymetry images, S57 nautical charts, and USCG Marine Information for Safety and Law Enforcement (MISLE) can be combined with the ship traffic visualizations to give a more complete picture of the maritime environment. AIS traffic analyses have the potential to give managers throughout NOAA's National Marine Sanctuaries an improved ability to assess the impacts of ship traffic on the marine resources they seek to protect. Viewing ship traffic

Fully automatic oil spill detection from COSMO-SkyMed imagery using a neural network approach

NASA Astrophysics Data System (ADS)

Avezzano, Ruggero G.; Del Frate, Fabio; Latini, Daniele

2012-09-01

The increased amount of available Synthetic Aperture Radar (SAR) images acquired over the ocean represents an extraordinary potential for improving oil spill detection activities. On the other side this involves a growing workload on the operators at analysis centers. In addition, even if the operators go through extensive training to learn manual oil spill detection, they can provide different and subjective responses. Hence, the upgrade and improvements of algorithms for automatic detection that can help in screening the images and prioritizing the alarms are of great benefit. In the framework of an ASI Announcement of Opportunity for the exploitation of COSMO-SkyMed data, a research activity (ASI contract L/020/09/0) aiming at studying the possibility to use neural networks architectures to set up fully automatic processing chains using COSMO-SkyMed imagery has been carried out and results are presented in this paper. The automatic identification of an oil spill is seen as a three step process based on segmentation, feature extraction and classification. We observed that a PCNN (Pulse Coupled Neural Network) was capable of providing a satisfactory performance in the different dark spots extraction, close to what it would be produced by manual editing. For the classification task a Multi-Layer Perceptron (MLP) Neural Network was employed.

ADMAP (automatic data manipulation program)

NASA Technical Reports Server (NTRS)

Mann, F. I.

1971-01-01

Instructions are presented on the use of ADMAP, (automatic data manipulation program) an aerospace data manipulation computer program. The program was developed to aid in processing, reducing, plotting, and publishing electric propulsion trajectory data generated by the low thrust optimization program, HILTOP. The program has the option of generating SC4020 electric plots, and therefore requires the SC4020 routines to be available at excution time (even if not used). Several general routines are present, including a cubic spline interpolation routine, electric plotter dash line drawing routine, and single parameter and double parameter sorting routines. Many routines are tailored for the manipulation and plotting of electric propulsion data, including an automatic scale selection routine, an automatic curve labelling routine, and an automatic graph titling routine. Data are accepted from either punched cards or magnetic tape.

Results from the Crop Identification Technology Assessment for Remote Sensing (CITARS) project

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Davis, B. J.; Bizzell, R. M.; Hall, F. G.; Feiveson, A. H.; Malila, W. A.; Rice, D. P.

1976-01-01

The author has identified the following significant results. It was found that several factors had a significant effect on crop identification performance: (1) crop maturity and site characteristics, (2) which of several different single date automatic data processing procedures was used for local recognition, (3) nonlocal recognition, both with and without preprocessing for the extension of recognition signatures, and (4) use of multidate data. It also was found that classification accuracy for field center pixels was not a reliable indicator of proportion estimation performance for whole areas, that bias was present in proportion estimates, and that training data and procedures strongly influenced crop identification performance.

Automatic Classification of the Sub-Techniques (Gears) Used in Cross-Country Ski Skating Employing a Mobile Phone

PubMed Central

Stöggl, Thomas; Holst, Anders; Jonasson, Arndt; Andersson, Erik; Wunsch, Tobias; Norström, Christer; Holmberg, Hans-Christer

2014-01-01

The purpose of the current study was to develop and validate an automatic algorithm for classification of cross-country (XC) ski-skating gears (G) using Smartphone accelerometer data. Eleven XC skiers (seven men, four women) with regional-to-international levels of performance carried out roller skiing trials on a treadmill using fixed gears (G2left, G2right, G3, G4left, G4right) and a 950-m trial using different speeds and inclines, applying gears and sides as they normally would. Gear classification by the Smartphone (on the chest) and based on video recordings were compared. Formachine-learning, a collective database was compared to individual data. The Smartphone application identified the trials with fixed gears correctly in all cases. In the 950-m trial, participants executed 140 ± 22 cycles as assessed by video analysis, with the automatic Smartphone application giving a similar value. Based on collective data, gears were identified correctly 86.0% ± 8.9% of the time, a value that rose to 90.3% ± 4.1% (P < 0.01) with machine learning from individual data. Classification was most often incorrect during transition between gears, especially to or from G3. Identification was most often correct for skiers who made relatively few transitions between gears. The accuracy of the automatic procedure for identifying G2left, G2right, G3, G4left and G4right was 96%, 90%, 81%, 88% and 94%, respectively. The algorithm identified gears correctly 100% of the time when a single gear was used and 90% of the time when different gears were employed during a variable protocol. This algorithm could be improved with respect to identification of transitions between gears or the side employed within a given gear. PMID:25365459

Automatic classification of the sub-techniques (gears) used in cross-country ski skating employing a mobile phone.

PubMed

Stöggl, Thomas; Holst, Anders; Jonasson, Arndt; Andersson, Erik; Wunsch, Tobias; Norström, Christer; Holmberg, Hans-Christer

2014-10-31

The purpose of the current study was to develop and validate an automatic algorithm for classification of cross-country (XC) ski-skating gears (G) using Smartphone accelerometer data. Eleven XC skiers (seven men, four women) with regional-to-international levels of performance carried out roller skiing trials on a treadmill using fixed gears (G2left, G2right, G3, G4left, G4right) and a 950-m trial using different speeds and inclines, applying gears and sides as they normally would. Gear classification by the Smartphone (on the chest) and based on video recordings were compared. Formachine-learning, a collective database was compared to individual data. The Smartphone application identified the trials with fixed gears correctly in all cases. In the 950-m trial, participants executed 140 ± 22 cycles as assessed by video analysis, with the automatic Smartphone application giving a similar value. Based on collective data, gears were identified correctly 86.0% ± 8.9% of the time, a value that rose to 90.3% ± 4.1% (P < 0.01) with machine learning from individual data. Classification was most often incorrect during transition between gears, especially to or from G3. Identification was most often correct for skiers who made relatively few transitions between gears. The accuracy of the automatic procedure for identifying G2left, G2right, G3, G4left and G4right was 96%, 90%, 81%, 88% and 94%, respectively. The algorithm identified gears correctly 100% of the time when a single gear was used and 90% of the time when different gears were employed during a variable protocol. This algorithm could be improved with respect to identification of transitions between gears or the side employed within a given gear.

Automatic detection of spermatozoa for laser capture microdissection.

PubMed

Vandewoestyne, Mado; Van Hoofstat, David; Van Nieuwerburgh, Filip; Deforce, Dieter

2009-03-01

In sexual assault crimes, differential extraction of spermatozoa from vaginal swab smears is often ineffective, especially when only a few spermatozoa are present in an overwhelming amount of epithelial cells. Laser capture microdissection (LCM) enables the precise separation of spermatozoa and epithelial cells. However, standard sperm-staining techniques are non-specific and rely on sperm morphology for identification. Moreover, manual screening of the microscope slides is time-consuming and labor-intensive. Here, we describe an automated screening method to detect spermatozoa stained with Sperm HY-LITER. Different ratios of spermatozoa and epithelial cells were used to assess the automatic detection method. In addition, real postcoital samples were also screened. Detected spermatozoa were isolated using LCM and DNA analysis was performed. Robust DNA profiles without allelic dropout could be obtained from as little as 30 spermatozoa recovered from postcoital samples, showing that the staining had no significant influence on DNA recovery.

Efficient road geometry identification from digital vector data

NASA Astrophysics Data System (ADS)

Andrášik, Richard; Bíl, Michal

2016-07-01

A new method for the automatic identification of road geometry from digital vector data is presented. The method is capable of efficiently identifying circular curves with their radii and tangents (straight sections). The average error of identification ranged from 0.01 to 1.30 % for precisely drawn data and 4.81 % in the case of actual road data with noise in the location of vertices. The results demonstrate that the proposed method is faster and more precise than commonly used techniques. This approach can be used by road administrators to complete their databases with information concerning the geometry of roads. It can also be utilized by transport engineers or traffic safety analysts to investigate the possible dependence of traffic accidents on road geometries. The method presented is applicable as well to railroads and rivers or other line features.

High-speed holographic correlation system for video identification on the internet

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ikeda, Kanami; Kodate, Kashiko

2013-12-01

Automatic video identification is important for indexing, search purposes, and removing illegal material on the Internet. By combining a high-speed correlation engine and web-scanning technology, we developed the Fast Recognition Correlation system (FReCs), a video identification system for the Internet. FReCs is an application thatsearches through a number of websites with user-generated content (UGC) and detects video content that violates copyright law. In this paper, we describe the FReCs configuration and an approach to investigating UGC websites using FReCs. The paper also illustrates the combination of FReCs with an optical correlation system, which is capable of easily replacing a digital authorization sever in FReCs with optical correlation.

Comparative analysis of image classification methods for automatic diagnosis of ophthalmic images

NASA Astrophysics Data System (ADS)

Wang, Liming; Zhang, Kai; Liu, Xiyang; Long, Erping; Jiang, Jiewei; An, Yingying; Zhang, Jia; Liu, Zhenzhen; Lin, Zhuoling; Li, Xiaoyan; Chen, Jingjing; Cao, Qianzhong; Li, Jing; Wu, Xiaohang; Wang, Dongni; Li, Wangting; Lin, Haotian

2017-01-01

There are many image classification methods, but it remains unclear which methods are most helpful for analyzing and intelligently identifying ophthalmic images. We select representative slit-lamp images which show the complexity of ocular images as research material to compare image classification algorithms for diagnosing ophthalmic diseases. To facilitate this study, some feature extraction algorithms and classifiers are combined to automatic diagnose pediatric cataract with same dataset and then their performance are compared using multiple criteria. This comparative study reveals the general characteristics of the existing methods for automatic identification of ophthalmic images and provides new insights into the strengths and shortcomings of these methods. The relevant methods (local binary pattern +SVMs, wavelet transformation +SVMs) which achieve an average accuracy of 87% and can be adopted in specific situations to aid doctors in preliminarily disease screening. Furthermore, some methods requiring fewer computational resources and less time could be applied in remote places or mobile devices to assist individuals in understanding the condition of their body. In addition, it would be helpful to accelerate the development of innovative approaches and to apply these methods to assist doctors in diagnosing ophthalmic disease.

Automatic address validation and health record review to identify homeless Social Security disability applicants.

PubMed

Erickson, Jennifer; Abbott, Kenneth; Susienka, Lucinda

2018-06-01

Homeless patients face a variety of obstacles in pursuit of basic social services. Acknowledging this, the Social Security Administration directs employees to prioritize homeless patients and handle their disability claims with special care. However, under existing manual processes for identification of homelessness, many homeless patients never receive the special service to which they are entitled. In this paper, we explore address validation and automatic annotation of electronic health records to improve identification of homeless patients. We developed a sample of claims containing medical records at the moment of arrival in a single office. Using address validation software, we reconciled patient addresses with public directories of homeless shelters, veterans' hospitals and clinics, and correctional facilities. Other tools annotated electronic health records. We trained random forests to identify homeless patients and validated each model with 10-fold cross validation. For our finished model, the area under the receiver operating characteristic curve was 0.942. The random forest improved sensitivity from 0.067 to 0.879 but decreased positive predictive value to 0.382. Presumed false positive classifications bore many characteristics of homelessness. Organizations could use these methods to prompt early collection of information necessary to avoid labor-intensive attempts to reestablish contact with homeless individuals. Annually, such methods could benefit tens of thousands of patients who are homeless, destitute, and in urgent need of assistance. We were able to identify many more homeless patients through a combination of automatic address validation and natural language processing of unstructured electronic health records. Copyright © 2018. Published by Elsevier Inc.

Automatic enforcement and highway safety.

DOT National Transportation Integrated Search

2011-05-01

The objectives of this research are to: 1. Identify aspects of the automatic detection of red light running that the public finds offensive or problematical, and quantify the level of opposition on each aspect. 2. Identify aspects of the automatic de...

Assessment of automatic ligand building in ARP/wARP.

PubMed

Evrard, Guillaume X; Langer, Gerrit G; Perrakis, Anastassis; Lamzin, Victor S

2007-01-01

The efficiency of the ligand-building module of ARP/wARP version 6.1 has been assessed through extensive tests on a large variety of protein-ligand complexes from the PDB, as available from the Uppsala Electron Density Server. Ligand building in ARP/wARP involves two main steps: automatic identification of the location of the ligand and the actual construction of its atomic model. The first step is most successful for large ligands. The second step, ligand construction, is more powerful with X-ray data at high resolution and ligands of small to medium size. Both steps are successful for ligands with low to moderate atomic displacement parameters. The results highlight the strengths and weaknesses of both the method of ligand building and the large-scale validation procedure and help to identify means of further improvement.

Automatic classification of blank substrate defects

NASA Astrophysics Data System (ADS)

Boettiger, Tom; Buck, Peter; Paninjath, Sankaranarayanan; Pereira, Mark; Ronald, Rob; Rost, Dan; Samir, Bhamidipati

2014-10-01

Mask preparation stages are crucial in mask manufacturing, since this mask is to later act as a template for considerable number of dies on wafer. Defects on the initial blank substrate, and subsequent cleaned and coated substrates, can have a profound impact on the usability of the finished mask. This emphasizes the need for early and accurate identification of blank substrate defects and the risk they pose to the patterned reticle. While Automatic Defect Classification (ADC) is a well-developed technology for inspection and analysis of defects on patterned wafers and masks in the semiconductors industry, ADC for mask blanks is still in the early stages of adoption and development. Calibre ADC is a powerful analysis tool for fast, accurate, consistent and automatic classification of defects on mask blanks. Accurate, automated classification of mask blanks leads to better usability of blanks by enabling defect avoidance technologies during mask writing. Detailed information on blank defects can help to select appropriate job-decks to be written on the mask by defect avoidance tools [1][4][5]. Smart algorithms separate critical defects from the potentially large number of non-critical defects or false defects detected at various stages during mask blank preparation. Mechanisms used by Calibre ADC to identify and characterize defects include defect location and size, signal polarity (dark, bright) in both transmitted and reflected review images, distinguishing defect signals from background noise in defect images. The Calibre ADC engine then uses a decision tree to translate this information into a defect classification code. Using this automated process improves classification accuracy, repeatability and speed, while avoiding the subjectivity of human judgment compared to the alternative of manual defect classification by trained personnel [2]. This paper focuses on the results from the evaluation of Automatic Defect Classification (ADC) product at MP Mask

30 CFR 77.314 - Automatic temperature control instruments.

Code of Federal Regulations, 2011 CFR

2011-07-01

... UNDERGROUND COAL MINES Thermal Dryers § 77.314 Automatic temperature control instruments. (a) Automatic temperature control instruments for thermal dryer system shall be of the recording type. (b) Automatic... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Automatic temperature control instruments. 77...

30 CFR 77.314 - Automatic temperature control instruments.

Code of Federal Regulations, 2010 CFR

2010-07-01

... UNDERGROUND COAL MINES Thermal Dryers § 77.314 Automatic temperature control instruments. (a) Automatic temperature control instruments for thermal dryer system shall be of the recording type. (b) Automatic... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic temperature control instruments. 77...

30 CFR 77.314 - Automatic temperature control instruments.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Automatic temperature control instruments. 77... UNDERGROUND COAL MINES Thermal Dryers § 77.314 Automatic temperature control instruments. (a) Automatic temperature control instruments for thermal dryer system shall be of the recording type. (b) Automatic...

30 CFR 77.314 - Automatic temperature control instruments.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Automatic temperature control instruments. 77... UNDERGROUND COAL MINES Thermal Dryers § 77.314 Automatic temperature control instruments. (a) Automatic temperature control instruments for thermal dryer system shall be of the recording type. (b) Automatic...

30 CFR 77.314 - Automatic temperature control instruments.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Automatic temperature control instruments. 77... UNDERGROUND COAL MINES Thermal Dryers § 77.314 Automatic temperature control instruments. (a) Automatic temperature control instruments for thermal dryer system shall be of the recording type. (b) Automatic...

Identification of granite varieties from colour spectrum data.

PubMed

Araújo, María; Martínez, Javier; Ordóñez, Celestino; Vilán, José Antonio

2010-01-01

The granite processing sector of the northwest of Spain handles many varieties of granite with specific technical and aesthetic properties that command different prices in the natural stone market. Hence, correct granite identification and classification from the outset of processing to the end-product stage optimizes the management and control of stocks of granite slabs and tiles and facilitates the operation of traceability systems. We describe a methodology for automatically identifying granite varieties by processing spectral information captured by a spectrophotometer at various stages of processing using functional machine learning techniques.

Identification of Granite Varieties from Colour Spectrum Data

PubMed Central

Araújo, María; Martínez, Javier; Ordóñez, Celestino; Vilán, José Antonio

2010-01-01

The granite processing sector of the northwest of Spain handles many varieties of granite with specific technical and aesthetic properties that command different prices in the natural stone market. Hence, correct granite identification and classification from the outset of processing to the end-product stage optimizes the management and control of stocks of granite slabs and tiles and facilitates the operation of traceability systems. We describe a methodology for automatically identifying granite varieties by processing spectral information captured by a spectrophotometer at various stages of processing using functional machine learning techniques. PMID:22163673

Thai Automatic Speech Recognition

DTIC Science & Technology

2005-01-01

used in an external DARPA evaluation involving medical scenarios between an American Doctor and a naïve monolingual Thai patient. 2. Thai Language... dictionary generation more challenging, and (3) the lack of word segmentation, which calls for automatic segmentation approaches to make n-gram language...requires a dictionary and provides various segmentation algorithms to automatically select suitable segmentations. Here we used a maximal matching

Automatic pattern identification of rock moisture based on the Staff-RF model

NASA Astrophysics Data System (ADS)

Zheng, Wei; Tao, Kai; Jiang, Wei

2018-04-01

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

Automatic programming of simulation models

NASA Technical Reports Server (NTRS)

Schroer, Bernard J.; Tseng, Fan T.; Zhang, Shou X.; Dwan, Wen S.

1988-01-01

The objective of automatic programming is to improve the overall environment for describing the program. This improved environment is realized by a reduction in the amount of detail that the programmer needs to know and is exposed to. Furthermore, this improved environment is achieved by a specification language that is more natural to the user's problem domain and to the user's way of thinking and looking at the problem. The goal of this research is to apply the concepts of automatic programming (AP) to modeling discrete event simulation system. Specific emphasis is on the design and development of simulation tools to assist the modeler define or construct a model of the system and to then automatically write the corresponding simulation code in the target simulation language, GPSS/PC. A related goal is to evaluate the feasibility of various languages for constructing automatic programming simulation tools.

Clothes Dryer Automatic Termination Evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

TeGrotenhuis, Ward E.

Volume 2: Improved Sensor and Control Designs Many residential clothes dryers on the market today provide automatic cycles that are intended to stop when the clothes are dry, as determined by the final remaining moisture content (RMC). However, testing of automatic termination cycles has shown that many dryers are susceptible to over-drying of loads, leading to excess energy consumption. In particular, tests performed using the DOE Test Procedure in Appendix D2 of 10 CFR 430 subpart B have shown that as much as 62% of the energy used in a cycle may be from over-drying. Volume 1 of this reportmore » shows an average of 20% excess energy from over-drying when running automatic cycles with various load compositions and dryer settings. Consequently, improving automatic termination sensors and algorithms has the potential for substantial energy savings in the U.S.« less

Design and development of an automatic data acquisition system for a balance study using a smartcard system.

PubMed

Ambrozy, C; Kolar, N A; Rattay, F

2010-01-01

For measurement value logging of board angle values during balance training, it is necessary to develop a measurement system. This study will provide data for a balance study using the smartcard. The data acquisition comes automatically. An individually training plan for each proband is necessary. To store the proband identification a smartcard with an I2C data bus protocol and an E2PROM memory system is used. For reading the smartcard data a smartcard reader is connected via universal serial bus (USB) to a notebook. The data acquisition and smartcard read programme is designed with Microsoft® Visual C#. A training plan file contains the individual training plan for each proband. The data of the test persons are saved in a proband directory. Each event is automatically saved as a log-file for the exact documentation. This system makes study development easy and time-saving.

Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

PubMed

Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

2018-01-01

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Cough-Based Algorithm for Automatic Diagnosis of Pertussis.

PubMed

Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

2016-01-01

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control.

A Cough-Based Algorithm for Automatic Diagnosis of Pertussis

PubMed Central

Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

2016-01-01

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control. PMID:27583523

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, Donald C.

1996-01-01

A reactor protection system having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically "identical" values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, D.C.

1996-12-17

A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically ``identical`` values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic. 16 figs.

10 CFR 429.45 - Automatic commercial ice makers.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 3 2012-01-01 2012-01-01 false Automatic commercial ice makers. 429.45 Section 429.45... PRODUCTS AND COMMERCIAL AND INDUSTRIAL EQUIPMENT Certification § 429.45 Automatic commercial ice makers. (a... automatic commercial ice makers; and (2) For each basic model of automatic commercial ice maker selected for...

10 CFR 429.45 - Automatic commercial ice makers.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 3 2014-01-01 2014-01-01 false Automatic commercial ice makers. 429.45 Section 429.45... PRODUCTS AND COMMERCIAL AND INDUSTRIAL EQUIPMENT Certification § 429.45 Automatic commercial ice makers. (a... automatic commercial ice makers; and (2) For each basic model of automatic commercial ice maker selected for...

10 CFR 429.45 - Automatic commercial ice makers.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 3 2013-01-01 2013-01-01 false Automatic commercial ice makers. 429.45 Section 429.45... PRODUCTS AND COMMERCIAL AND INDUSTRIAL EQUIPMENT Certification § 429.45 Automatic commercial ice makers. (a... automatic commercial ice makers; and (2) For each basic model of automatic commercial ice maker selected for...

Automated Coronal Loop Identification Using Digital Image Processing Techniques

NASA Technical Reports Server (NTRS)

Lee, Jong K.; Gary, G. Allen; Newman, Timothy S.

2003-01-01

The results of a master thesis project on a study of computer algorithms for automatic identification of optical-thin, 3-dimensional solar coronal loop centers from extreme ultraviolet and X-ray 2-dimensional images will be presented. These center splines are proxies of associated magnetic field lines. The project is pattern recognition problems in which there are no unique shapes or edges and in which photon and detector noise heavily influence the images. The study explores extraction techniques using: (1) linear feature recognition of local patterns (related to the inertia-tensor concept), (2) parametric space via the Hough transform, and (3) topological adaptive contours (snakes) that constrains curvature and continuity as possible candidates for digital loop detection schemes. We have developed synthesized images for the coronal loops to test the various loop identification algorithms. Since the topology of these solar features is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information in the identification process. Results from both synthesized and solar images will be presented.

Computer systems for automatic earthquake detection

USGS Publications Warehouse

Stewart, S.W.

1974-01-01

U.S Geological Survey seismologists in Menlo park, California, are utilizing the speed, reliability, and efficiency of minicomputers to monitor seismograph stations and to automatically detect earthquakes. An earthquake detection computer system, believed to be the only one of its kind in operation, automatically reports about 90 percent of all local earthquakes recorded by a network of over 100 central California seismograph stations. The system also monitors the stations for signs of malfunction or abnormal operation. Before the automatic system was put in operation, all of the earthquakes recorded had to be detected by manually searching the records, a time-consuming process. With the automatic detection system, the stations are efficiently monitored continuously. 

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

AUTOMATIC COUNTING APPARATUS

DOEpatents

Howell, W.D.

1957-08-20

An apparatus for automatically recording the results of counting operations on trains of electrical pulses is described. The disadvantages of prior devices utilizing the two common methods of obtaining the count rate are overcome by this apparatus; in the case of time controlled operation, the disclosed system automatically records amy information stored by the scaler but not transferred to the printer at the end of the predetermined time controlled operations and, in the case of count controlled operation, provision is made to prevent a weak sample from occupying the apparatus for an excessively long period of time.

Tests with VHR images for the identification of olive trees and other fruit trees in the European Union

NASA Astrophysics Data System (ADS)

Masson, Josiane; Soille, Pierre; Mueller, Rick

2004-10-01

In the context of the Common Agricultural Policy (CAP) there is a strong interest of the European Commission for counting and individually locating fruit trees. An automatic counting algorithm developed by the JRC (OLICOUNT) was used in the past for olive trees only, on 1m black and white orthophotos but with limits in case of young trees or irregular groves. This study investigates the improvement of fruit tree identification using VHR images on a large set of data in three test sites, one in Creta (Greece; one in the south-east of France with a majority of olive trees and associated fruit trees, and the last one in Florida on citrus trees. OLICOUNT was compared with two other automatic tree counting, applications, one using the CRISP software on citrus trees and the other completely automatic based on regional minima (morphological image analysis). Additional investigation was undertaken to refine the methods. This paper describes the automatic methods and presents the results derived from the tests.

Semi-automatic knee cartilage segmentation

NASA Astrophysics Data System (ADS)

Dam, Erik B.; Folkesson, Jenny; Pettersen, Paola C.; Christiansen, Claus

2006-03-01

Osteo-Arthritis (OA) is a very common age-related cause of pain and reduced range of motion. A central effect of OA is wear-down of the articular cartilage that otherwise ensures smooth joint motion. Quantification of the cartilage breakdown is central in monitoring disease progression and therefore cartilage segmentation is required. Recent advances allow automatic cartilage segmentation with high accuracy in most cases. However, the automatic methods still fail in some problematic cases. For clinical studies, even if a few failing cases will be averaged out in the overall results, this reduces the mean accuracy and precision and thereby necessitates larger/longer studies. Since the severe OA cases are often most problematic for the automatic methods, there is even a risk that the quantification will introduce a bias in the results. Therefore, interactive inspection and correction of these problematic cases is desirable. For diagnosis on individuals, this is even more crucial since the diagnosis will otherwise simply fail. We introduce and evaluate a semi-automatic cartilage segmentation method combining an automatic pre-segmentation with an interactive step that allows inspection and correction. The automatic step consists of voxel classification based on supervised learning. The interactive step combines a watershed transformation of the original scan with the posterior probability map from the classification step at sub-voxel precision. We evaluate the method for the task of segmenting the tibial cartilage sheet from low-field magnetic resonance imaging (MRI) of knees. The evaluation shows that the combined method allows accurate and highly reproducible correction of the segmentation of even the worst cases in approximately ten minutes of interaction.

The power grid AGC frequency bias coefficient online identification method based on wide area information

NASA Astrophysics Data System (ADS)

Wang, Zian; Li, Shiguang; Yu, Ting

2015-12-01

This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

Early identification and interventions for students with mathematics difficulties.

PubMed

Gersten, Russell; Jordan, Nancy C; Flojo, Jonathan R

2005-01-01

This article highlights key findings from the small body of research on mathematics difficulties (MD) relevant to early identification and early intervention. The research demonstrates that (a) for many children, mathematics difficulties are not stable over time; (b) the presence of reading difficulties seems related to slower progress in many aspects of mathematics; (c) almost all students with MD demonstrate problems with accurate and automatic retrieval of basic arithmetic combinations, such as 6 + 3. The following measures appear to be valid and reliable indicators of potential MD in kindergartners: (a) magnitude comparison (i.e., knowing which digit in a pair is larger), (b) sophistication of counting strategies, (c) fluent identification of numbers, and (d) working memory (as evidenced by reverse digit span). These are discussed in terms of the components of number sense. Implications for early intervention strategies are explored.

Automatic detection and quantitative analysis of cells in the mouse primary motor cortex

NASA Astrophysics Data System (ADS)

Meng, Yunlong; He, Yong; Wu, Jingpeng; Chen, Shangbin; Li, Anan; Gong, Hui

2014-09-01

Neuronal cells play very important role on metabolism regulation and mechanism control, so cell number is a fundamental determinant of brain function. Combined suitable cell-labeling approaches with recently proposed three-dimensional optical imaging techniques, whole mouse brain coronal sections can be acquired with 1-μm voxel resolution. We have developed a completely automatic pipeline to perform cell centroids detection, and provided three-dimensional quantitative information of cells in the primary motor cortex of C57BL/6 mouse. It involves four principal steps: i) preprocessing; ii) image binarization; iii) cell centroids extraction and contour segmentation; iv) laminar density estimation. Investigations on the presented method reveal promising detection accuracy in terms of recall and precision, with average recall rate 92.1% and average precision rate 86.2%. We also analyze laminar density distribution of cells from pial surface to corpus callosum from the output vectorizations of detected cell centroids in mouse primary motor cortex, and find significant cellular density distribution variations in different layers. This automatic cell centroids detection approach will be beneficial for fast cell-counting and accurate density estimation, as time-consuming and error-prone manual identification is avoided.

A network identity authentication system based on Fingerprint identification technology

NASA Astrophysics Data System (ADS)

Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

2005-10-01

Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghose, Soumya, E-mail: soumya.ghose@case.edu; Mitra, Jhimli; Rivest-Hénault, David

Purpose: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Methods: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contoursmore » were selected in a spectral clustering manifold learning framework. This aids in clustering “similar” gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. Results: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). Conclusions: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all

AUTOMATIC DIRT TRAIL ANALYSIS IN DERMOSCOPY IMAGES

PubMed Central

Cheng, Beibei; Stanley, R. Joe; Stoecker, William V.; Osterwise, Christopher T.P.; Stricklin, Sherea M.; Hinton, Kristen A.; Moss, Randy H.; Oliviero, Margaret; Rabinovitz, Harold S.

2011-01-01

Basal cell carcinoma (BCC) is the most common cancer in the U.S. Dermatoscopes are devices used by physicians to facilitate the early detection of these cancers based on the identification of skin lesion structures often specific to BCCs. One new lesion structure, referred to as dirt trails, has the appearance of dark gray, brown or black dots and clods of varying sizes distributed in elongated clusters with indistinct borders, often appearing as curvilinear trails. In this research, we explore a dirt trail detection and analysis algorithm for extracting, measuring, and characterizing dirt trails based on size, distribution, and color in dermoscopic skin lesion images. These dirt trails are then used to automatically discriminate BCC from benign skin lesions. For an experimental data set of 35 BCC images with dirt trails and 79 benign lesion images, a neural network-based classifier achieved a 0.902 area under a receiver operating characteristic curve using a leave-one-out approach, demonstrating the potential of dirt trails for BCC lesion discrimination. PMID:22233099

An intelligent identification algorithm for the monoclonal picking instrument

NASA Astrophysics Data System (ADS)

Yan, Hua; Zhang, Rongfu; Yuan, Xujun; Wang, Qun

2017-11-01

The traditional colony selection is mainly operated by manual mode, which takes on low efficiency and strong subjectivity. Therefore, it is important to develop an automatic monoclonal-picking instrument. The critical stage of the automatic monoclonal-picking and intelligent optimal selection is intelligent identification algorithm. An auto-screening algorithm based on Support Vector Machine (SVM) is proposed in this paper, which uses the supervised learning method, which combined with the colony morphological characteristics to classify the colony accurately. Furthermore, through the basic morphological features of the colony, system can figure out a series of morphological parameters step by step. Through the establishment of maximal margin classifier, and based on the analysis of the growth trend of the colony, the selection of the monoclonal colony was carried out. The experimental results showed that the auto-screening algorithm could screen out the regular colony from the other, which meets the requirement of various parameters.

INTERPOL survey of the use of speaker identification by law enforcement agencies.

PubMed

Morrison, Geoffrey Stewart; Sahito, Farhan Hyder; Jardine, Gaëlle; Djokic, Djordje; Clavet, Sophie; Berghs, Sabine; Goemans Dorny, Caroline

2016-06-01

A survey was conducted of the use of speaker identification by law enforcement agencies around the world. A questionnaire was circulated to law enforcement agencies in the 190 member countries of INTERPOL. 91 responses were received from 69 countries. 44 respondents reported that they had speaker identification capabilities in house or via external laboratories. Half of these came from Europe. 28 respondents reported that they had databases of audio recordings of speakers. The clearest pattern in the responses was that of diversity. A variety of different approaches to speaker identification were used: The human-supervised-automatic approach was the most popular in North America, the auditory-acoustic-phonetic approach was the most popular in Europe, and the spectrographic/auditory-spectrographic approach was the most popular in Africa, Asia, the Middle East, and South and Central America. Globally, and in Europe, the most popular framework for reporting conclusions was identification/exclusion/inconclusive. In Europe, the second most popular framework was the use of verbal likelihood ratio scales. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Automatic query formulations in information retrieval.

PubMed

Salton, G; Buckley, C; Fox, E A

1983-07-01

Modern information retrieval systems are designed to supply relevant information in response to requests received from the user population. In most retrieval environments the search requests consist of keywords, or index terms, interrelated by appropriate Boolean operators. Since it is difficult for untrained users to generate effective Boolean search requests, trained search intermediaries are normally used to translate original statements of user need into useful Boolean search formulations. Methods are introduced in this study which reduce the role of the search intermediaries by making it possible to generate Boolean search formulations completely automatically from natural language statements provided by the system patrons. Frequency considerations are used automatically to generate appropriate term combinations as well as Boolean connectives relating the terms. Methods are covered to produce automatic query formulations both in a standard Boolean logic system, as well as in an extended Boolean system in which the strict interpretation of the connectives is relaxed. Experimental results are supplied to evaluate the effectiveness of the automatic query formulation process, and methods are described for applying the automatic query formulation process in practice.

Adding Automatic Evaluation to Interactive Virtual Labs

ERIC Educational Resources Information Center

Farias, Gonzalo; Muñoz de la Peña, David; Gómez-Estern, Fabio; De la Torre, Luis; Sánchez, Carlos; Dormido, Sebastián

2016-01-01

Automatic evaluation is a challenging field that has been addressed by the academic community in order to reduce the assessment workload. In this work we present a new element for the authoring tool Easy Java Simulations (EJS). This element, which is named automatic evaluation element (AEE), provides automatic evaluation to virtual and remote…

MICRA: an automatic pipeline for fast characterization of microbial genomes from high-throughput sequencing data.

PubMed

Caboche, Ségolène; Even, Gaël; Loywick, Alexandre; Audebert, Christophe; Hot, David

2017-12-19

The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data.

What Automaticity Deficit? Activation of Lexical Information by Readers with Dyslexia in a Rapid Automatized Naming Stroop-Switch Task

ERIC Educational Resources Information Center

Jones, Manon W.; Snowling, Margaret J.; Moll, Kristina

2016-01-01

Reading fluency is often predicted by rapid automatized naming (RAN) speed, which as the name implies, measures the automaticity with which familiar stimuli (e.g., letters) can be retrieved and named. Readers with dyslexia are considered to have less "automatized" access to lexical information, reflected in longer RAN times compared with…

Automatic Layout Design for Power Module

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ning, Puqi; Wang, Fei; Ngo, Khai

The layout of power modules is one of the most important elements in power module design, especially for high power densities, where couplings are increased. In this paper, an automatic design process using a genetic algorithm is presented. Some practical considerations are introduced in the optimization of the layout design of the module. This paper presents a process for automatic layout design for high power density modules. Detailed GA implementations are introduced both for outer loop and inner loop. As verified by a design example, the results of the automatic design process presented here are better than those from manualmore » design and also better than the results from a popular design software. This automatic design procedure could be a major step toward improving the overall performance of future layout design.« less

Framework for automatic information extraction from research papers on nanocrystal devices

PubMed Central

Yoshioka, Masaharu; Hara, Shinjiro; Newton, Marcus C

2015-01-01

Summary To support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called “ NaDev” (Nanocrystal Device Development) for this purpose. We also proposed an automatic information extraction system called “NaDevEx” (Nanocrystal Device Automatic Information Extraction Framework). NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization) on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities) on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms), the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material). However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39–73%); however, precision is better (75–97%). The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for

Framework for automatic information extraction from research papers on nanocrystal devices.

PubMed

Dieb, Thaer M; Yoshioka, Masaharu; Hara, Shinjiro; Newton, Marcus C

2015-01-01

To support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called " NaDev" (Nanocrystal Device Development) for this purpose. We also proposed an automatic information extraction system called "NaDevEx" (Nanocrystal Device Automatic Information Extraction Framework). NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization) on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities) on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms), the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material). However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39-73%); however, precision is better (75-97%). The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for characterization papers

An online ID identification system for liquefied-gas cylinder plant

NASA Astrophysics Data System (ADS)

He, Jin; Ding, Zhenwen; Han, Lei; Zhang, Hao

2017-11-01

An automatic ID identification system for gas cylinders' online production was developed based on the production conditions and requirements of the Technical Committee for Standardization of Gas Cylinders. A cylinder ID image acquisition system was designed to improve the image contrast of ID regions on gas cylinders against the background. Then the ID digits region was located by the CNN template matching algorithm. Following that, an adaptive threshold method based on the analysis of local average grey value and standard deviation was proposed to overcome defects of non-uniform background in the segmentation results. To improve the single digit identification accuracy, two BP neural networks were trained respectively for the identification of all digits and the easily confusable digits. If the single digit was classified as one of confusable digits by the former BP neural network, it was further tested by the later one, and the later result was taken as the final identification result of this single digit. At last, the majority voting was adopted to decide the final identification result for the 6-digit cylinder ID. The developed system was installed on a production line of a liquefied-petroleum-gas cylinder plant and worked in parallel with the existing weighing step on the line. Through the field test, the correct identification rate for single ID digit was 94.73%, and none of the tested 2000 cylinder ID was misclassified through the majority voting.

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, J; Yang, D

2015-06-15

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets,more » and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant

An Automatic Quality Control Pipeline for High-Throughput Screening Hit Identification.

PubMed

Zhai, Yufeng; Chen, Kaisheng; Zhong, Yang; Zhou, Bin; Ainscow, Edward; Wu, Ying-Ta; Zhou, Yingyao

2016-09-01

The correction or removal of signal errors in high-throughput screening (HTS) data is critical to the identification of high-quality lead candidates. Although a number of strategies have been previously developed to correct systematic errors and to remove screening artifacts, they are not universally effective and still require fair amount of human intervention. We introduce a fully automated quality control (QC) pipeline that can correct generic interplate systematic errors and remove intraplate random artifacts. The new pipeline was first applied to ~100 large-scale historical HTS assays; in silico analysis showed auto-QC led to a noticeably stronger structure-activity relationship. The method was further tested in several independent HTS runs, where QC results were sampled for experimental validation. Significantly increased hit confirmation rates were obtained after the QC steps, confirming that the proposed method was effective in enriching true-positive hits. An implementation of the algorithm is available to the screening community. © 2016 Society for Laboratory Automation and Screening.

Infrared Cephalic-Vein to Assist Blood Extraction Tasks: Automatic Projection and Recognition

NASA Astrophysics Data System (ADS)

Lagüela, S.; Gesto, M.; Riveiro, B.; González-Aguilera, D.

2017-05-01

Thermal infrared band is not commonly used in photogrammetric and computer vision algorithms, mainly due to the low spatial resolution of this type of imagery. However, this band captures sub-superficial information, increasing the capabilities of visible bands regarding applications. This fact is especially important in biomedicine and biometrics, allowing the geometric characterization of interior organs and pathologies with photogrammetric principles, as well as the automatic identification and labelling using computer vision algorithms. This paper presents advances of close-range photogrammetry and computer vision applied to thermal infrared imagery, with the final application of Augmented Reality in order to widen its application in the biomedical field. In this case, the thermal infrared image of the arm is acquired and simultaneously projected on the arm, together with the identification label of the cephalic-vein. This way, blood analysts are assisted in finding the vein for blood extraction, especially in those cases where the identification by the human eye is a complex task. Vein recognition is performed based on the Gaussian temperature distribution in the area of the vein, while the calibration between projector and thermographic camera is developed through feature extraction and pattern recognition. The method is validated through its application to a set of volunteers, with different ages and genres, in such way that different conditions of body temperature and vein depth are covered for the applicability and reproducibility of the method.

Design and implementation of an identification system in construction site safety for proactive accident prevention.

PubMed

Yang, Huanjia; Chew, David A S; Wu, Weiwei; Zhou, Zhipeng; Li, Qiming

2012-09-01

Identifying accident precursors using real-time identity information has great potential to improve safety performance in construction industry, which is still suffering from day to day records of accident fatality and injury. Based on the requirements analysis for identifying precursor and the discussion of enabling technology solutions for acquiring and sharing real-time automatic identification information on construction site, this paper proposes an identification system design for proactive accident prevention to improve construction site safety. Firstly, a case study is conducted to analyze the automatic identification requirements for identifying accident precursors in construction site. Results show that it mainly consists of three aspects, namely access control, training and inspection information and operation authority. The system is then designed to fulfill these requirements based on ZigBee enabled wireless sensor network (WSN), radio frequency identification (RFID) technology and an integrated ZigBee RFID sensor network structure. At the same time, an information database is also designed and implemented, which includes 15 tables, 54 queries and several reports and forms. In the end, a demonstration system based on the proposed system design is developed as a proof of concept prototype. The contributions of this study include the requirement analysis and technical design of a real-time identity information tracking solution for proactive accident prevention on construction sites. The technical solution proposed in this paper has a significant importance in improving safety performance on construction sites. Moreover, this study can serve as a reference design for future system integrations where more functions, such as environment monitoring and location tracking, can be added. Copyright © 2011 Elsevier Ltd. All rights reserved.

Methods for automatic detection of artifacts in microelectrode recordings.

PubMed

Bakštein, Eduard; Sieger, Tomáš; Wild, Jiří; Novák, Daniel; Schneider, Jakub; Vostatek, Pavel; Urgošík, Dušan; Jech, Robert

2017-10-01

Extracellular microelectrode recording (MER) is a prominent technique for studies of extracellular single-unit neuronal activity. In order to achieve robust results in more complex analysis pipelines, it is necessary to have high quality input data with a low amount of artifacts. We show that noise (mainly electromagnetic interference and motion artifacts) may affect more than 25% of the recording length in a clinical MER database. We present several methods for automatic detection of noise in MER signals, based on (i) unsupervised detection of stationary segments, (ii) large peaks in the power spectral density, and (iii) a classifier based on multiple time- and frequency-domain features. We evaluate the proposed methods on a manually annotated database of 5735 ten-second MER signals from 58 Parkinson's disease patients. The existing methods for artifact detection in single-channel MER that have been rigorously tested, are based on unsupervised change-point detection. We show on an extensive real MER database that the presented techniques are better suited for the task of artifact identification and achieve much better results. The best-performing classifiers (bagging and decision tree) achieved artifact classification accuracy of up to 89% on an unseen test set and outperformed the unsupervised techniques by 5-10%. This was close to the level of agreement among raters using manual annotation (93.5%). We conclude that the proposed methods are suitable for automatic MER denoising and may help in the efficient elimination of undesirable signal artifacts. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic programming of simulation models

NASA Technical Reports Server (NTRS)

Schroer, Bernard J.; Tseng, Fan T.; Zhang, Shou X.; Dwan, Wen S.

1990-01-01

The concepts of software engineering were used to improve the simulation modeling environment. Emphasis was placed on the application of an element of rapid prototyping, or automatic programming, to assist the modeler define the problem specification. Then, once the problem specification has been defined, an automatic code generator is used to write the simulation code. The following two domains were selected for evaluating the concepts of software engineering for discrete event simulation: manufacturing domain and a spacecraft countdown network sequence. The specific tasks were to: (1) define the software requirements for a graphical user interface to the Automatic Manufacturing Programming System (AMPS) system; (2) develop a graphical user interface for AMPS; and (3) compare the AMPS graphical interface with the AMPS interactive user interface.

Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs

NASA Astrophysics Data System (ADS)

Išgum, Ivana; de Vos, Bob D.; Wolterink, Jelmer M.; Dey, Damini; Berman, Daniel S.; Rubeaux, Mathieu; Leiner, Tim; Slomka, Piotr J.

2016-03-01

CT attenuation correction (CTAC) images acquired with PET/CT visualize coronary artery calcium (CAC) and enable CAC quantification. CAC scores acquired with CTAC have been suggested as a marker of cardiovascular disease (CVD). In this work, an algorithm previously developed for automatic CAC scoring in dedicated cardiac CT was applied to automatic CAC detection in CTAC. The study included 134 consecutive patients undergoing 82-Rb PET/CT. Low-dose rest CTAC scans were acquired (100 kV, 11 mAs, 1.4mm×1.4mm×3mm voxel size). An experienced observer defined the reference standard with the clinically used intensity level threshold for calcium identification (130 HU). Five scans were removed from analysis due to artifacts. The algorithm extracted potential CAC by intensity-based thresholding and 3D connected component labeling. Each candidate was described by location, size, shape and intensity features. An ensemble of extremely randomized decision trees was used to identify CAC. The data set was randomly divided into training and test sets. Automatically identified CAC was quantified using volume and Agatston scores. In 33 test scans, the system detected on average 469mm3/730mm3 (64%) of CAC with 36mm3 false positive volume per scan. The intraclass correlation coefficient for volume scores was 0.84. Each patient was assigned to one of four CVD risk categories based on the Agatston score (0-10, 11-100, 101-400, <400). The correct CVD category was assigned to 85% of patients (Cohen's linearly weighted κ0.82). Automatic detection of CVD risk based on CAC scoring in rest CTAC images is feasible. This may enable large scale studies evaluating clinical value of CAC scoring in CTAC data.

Automatic mathematical modeling for space application

NASA Technical Reports Server (NTRS)

Wang, Caroline K.

1987-01-01

A methodology for automatic mathematical modeling is described. The major objective is to create a very friendly environment for engineers to design, maintain and verify their model and also automatically convert the mathematical model into FORTRAN code for conventional computation. A demonstration program was designed for modeling the Space Shuttle Main Engine simulation mathematical model called Propulsion System Automatic Modeling (PSAM). PSAM provides a very friendly and well organized environment for engineers to build a knowledge base for base equations and general information. PSAM contains an initial set of component process elements for the Space Shuttle Main Engine simulation and a questionnaire that allows the engineer to answer a set of questions to specify a particular model. PSAM is then able to automatically generate the model and the FORTRAN code. A future goal is to download the FORTRAN code to the VAX/VMS system for conventional computation.

49 CFR 236.824 - System, automatic block signal.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false System, automatic block signal. 236.824 Section... § 236.824 System, automatic block signal. A block signal system wherein the use of each block is governed by an automatic block signal, cab signal, or both. ...

Real-time automatic registration in optical surgical navigation

NASA Astrophysics Data System (ADS)

Lin, Qinyong; Yang, Rongqian; Cai, Ken; Si, Xuan; Chen, Xiuwen; Wu, Xiaoming

2016-05-01

An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.

46 CFR 63.25-1 - Small automatic auxiliary boilers.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Small automatic auxiliary boilers. 63.25-1 Section 63.25... AUXILIARY BOILERS Requirements for Specific Types of Automatic Auxiliary Boilers § 63.25-1 Small automatic auxiliary boilers. Small automatic auxiliary boilers defined as having heat-input ratings of 400,000 Btu/hr...

Automatic Fastening Large Structures: a New Approach

NASA Technical Reports Server (NTRS)

Lumley, D. F.

1985-01-01

The external tank (ET) intertank structure for the space shuttle, a 27.5 ft diameter 22.5 ft long externally stiffened mechanically fastened skin-stringer-frame structure, was a labor intensitive manual structure built on a modified Saturn tooling position. A new approach was developed based on half-section subassemblies. The heart of this manufacturing approach will be 33 ft high vertical automatic riveting system with a 28 ft rotary positioner coming on-line in mid 1985. The Automatic Riveting System incorporates many of the latest automatic riveting technologies. Key features include: vertical columns with two sets of independently operating CNC drill-riveting heads; capability of drill, insert and upset any one piece fastener up to 3/8 inch diameter including slugs without displacing the workpiece offset bucking ram with programmable rotation and deep retraction; vision system for automatic parts program re-synchronization and part edge margin control; and an automatic rivet selection/handling system.

AUTOMATIC COUNTER

DOEpatents

Robinson, H.P.

1960-06-01

An automatic counter of alpha particle tracks recorded by a sensitive emulsion of a photographic plate is described. The counter includes a source of mcdulated dark-field illumination for developing light flashes from the recorded particle tracks as the photographic plate is automatically scanned in narrow strips. Photoelectric means convert the light flashes to proportional current pulses for application to an electronic counting circuit. Photoelectric means are further provided for developing a phase reference signal from the photographic plate in such a manner that signals arising from particle tracks not parallel to the edge of the plate are out of phase with the reference signal. The counting circuit includes provision for rejecting the out-of-phase signals resulting from unoriented tracks as well as signals resulting from spurious marks on the plate such as scratches, dust or grain clumpings, etc. The output of the circuit is hence indicative only of the tracks that would be counted by a human operator.

Use of seatbelts in cars with automatic belts.

PubMed Central

Williams, A F; Wells, J K; Lund, A K; Teed, N J

1992-01-01

Use of seatbelts in late model cars with automatic or manual belt systems was observed in suburban Washington, DC, Chicago, Los Angeles, and Philadelphia. In cars with automatic two-point belt systems, the use of shoulder belts by drivers was substantially higher than in the same model cars with manual three-point belts. This finding was true in varying degrees whatever the type of automatic belt, including cars with detachable nonmotorized belts, cars with detachable motorized belts, and especially cars with nondetachable motorized belts. Most of these automatic shoulder belts systems include manual lap belts. Use of lap belts was lower in cars with automatic two-point belt systems than in the same model cars with manual three-point belts; precisely how much lower could not be reliably estimated in this survey. Use of shoulder and lap belts was slightly higher in General Motors cars with detachable automatic three-point belts compared with the same model cars with manual three-point belts; in Hondas there was no difference in the rates of use of manual three-point belts and the rates of use of automatic three-point belts. PMID:1561301

WOLF; automatic typing program

USGS Publications Warehouse

Evenden, G.I.

1982-01-01

A FORTRAN IV program for the Hewlett-Packard 1000 series computer provides for automatic typing operations and can, when employed with manufacturer's text editor, provide a system to greatly facilitate preparation of reports, letters and other text. The input text and imbedded control data can perform nearly all of the functions of a typist. A few of the features available are centering, titles, footnotes, indentation, page numbering (including Roman numerals), automatic paragraphing, and two forms of tab operations. This documentation contains both user and technical description of the program.

A New Semi-Automatic Approach to Find Suitable Virtual Electrodes in Arrays Using an Interpolation Strategy.

PubMed

Salchow, Christina; Valtin, Markus; Seel, Thomas; Schauer, Thomas

2016-06-13

Functional Electrical Stimulation via electrode arrays enables the user to form virtual electrodes (VEs) of dynamic shape, size, and position. We developed a feedback-control-assisted manual search strategy which allows the therapist to conveniently and continuously modify VEs to find a good stimulation area. This works for applications in which the desired movement consists of at least two degrees of freedom. The virtual electrode can be moved to arbitrary locations within the array, and each involved element is stimulated with an individual intensity. Meanwhile, the applied global stimulation intensity is controlled automatically to meet a predefined angle for one degree of freedom. This enables the therapist to concentrate on the remaining degree(s) of freedom while changing the VE position. This feedback-control-assisted approach aims to integrate the user's opinion and the patient's sensation. Therefore, our method bridges the gap between manual search and fully automatic identification procedures for array electrodes. Measurements in four healthy volunteers were performed to demonstrate the usefulness of our concept, using a 24-element array to generate wrist and hand extension.

49 CFR 236.825 - System, automatic train control.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false System, automatic train control. 236.825 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.825 System, automatic train control. A system so arranged that its operation will automatically...

49 CFR 236.825 - System, automatic train control.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false System, automatic train control. 236.825 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.825 System, automatic train control. A system so arranged that its operation will automatically...

7 CFR 58.418 - Automatic cheese making equipment.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 3 2011-01-01 2011-01-01 false Automatic cheese making equipment. 58.418 Section 58.418 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING... Service 1 Equipment and Utensils § 58.418 Automatic cheese making equipment. (a) Automatic Curd Maker. The...

7 CFR 58.418 - Automatic cheese making equipment.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false Automatic cheese making equipment. 58.418 Section 58.418 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING... Service 1 Equipment and Utensils § 58.418 Automatic cheese making equipment. (a) Automatic Curd Maker. The...

Automatic Query Formulations in Information Retrieval.

ERIC Educational Resources Information Center

Salton, G.; And Others

1983-01-01

Introduces methods designed to reduce role of search intermediaries by generating Boolean search formulations automatically using term frequency considerations from natural language statements provided by system patrons. Experimental results are supplied and methods are described for applying automatic query formulation process in practice.…

A fast automatic recognition and location algorithm for fetal genital organs in ultrasound images.

PubMed

Tang, Sheng; Chen, Si-ping

2009-09-01

Severe sex ratio imbalance at birth is now becoming an important issue in several Asian countries. Its leading immediate cause is prenatal sex-selective abortion following illegal sex identification by ultrasound scanning. In this paper, a fast automatic recognition and location algorithm for fetal genital organs is proposed as an effective method to help prevent ultrasound technicians from unethically and illegally identifying the sex of the fetus. This automatic recognition algorithm can be divided into two stages. In the 'rough' stage, a few pixels in the image, which are likely to represent the genital organs, are automatically chosen as points of interest (POIs) according to certain salient characteristics of fetal genital organs. In the 'fine' stage, a specifically supervised learning framework, which fuses an effective feature data preprocessing mechanism into the multiple classifier architecture, is applied to every POI. The basic classifiers in the framework are selected from three widely used classifiers: radial basis function network, backpropagation network, and support vector machine. The classification results of all the POIs are then synthesized to determine whether the fetal genital organ is present in the image, and to locate the genital organ within the positive image. Experiments were designed and carried out based on an image dataset comprising 658 positive images (images with fetal genital organs) and 500 negative images (images without fetal genital organs). The experimental results showed true positive (TP) and true negative (TN) results from 80.5% (265 from 329) and 83.0% (415 from 500) of samples, respectively. The average computation time was 453 ms per image.

49 CFR 236.826 - System, automatic train stop.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false System, automatic train stop. 236.826 Section 236..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.826 System, automatic train stop. A system so arranged that its operation will automatically...

The Use of Automatic Indexing for Authority Control.

ERIC Educational Resources Information Center

Dillon, Martin; And Others

1981-01-01

Uses an experimental system for authority control on a collection of bibliographic records to demonstrate the resemblance between thesaurus-based automatic indexing and automatic authority control. Details of the automatic indexing system are given, results discussed, and the benefits of the resemblance examined. Included are a rules appendix and…

49 CFR 236.826 - System, automatic train stop.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false System, automatic train stop. 236.826 Section 236..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.826 System, automatic train stop. A system so arranged that its operation will automatically...

30 CFR 77.1401 - Automatic controls and brakes.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic controls and brakes. 77.1401 Section... MINES Personnel Hoisting § 77.1401 Automatic controls and brakes. Hoists and elevators shall be equipped with overspeed, overwind, and automatic stop controls and with brakes capable of stopping the elevator...

30 CFR 56.19006 - Automatic hoist braking devices.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic hoist braking devices. 56.19006 Section 56.19006 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND... Hoisting Hoists § 56.19006 Automatic hoist braking devices. Automatic hoists shall be provided with devices...

30 CFR 57.19006 - Automatic hoist braking devices.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic hoist braking devices. 57.19006 Section 57.19006 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND... Hoisting Hoists § 57.19006 Automatic hoist braking devices. Automatic hoists shall be provided with devices...

Robust uncertainty evaluation for system identification on distributed wireless platforms

NASA Astrophysics Data System (ADS)

Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

2016-04-01

Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on

Improved Automatically Locking/Unlocking Orthotic Knee Joint

NASA Technical Reports Server (NTRS)

Weddendorf, Bruce

1995-01-01

Proposed orthotic knee joint improved version of one described in "Automatically Locking/Unlocking Orthotic Knee Joint" (MFS-28633). Locks automatically upon initial application of radial force (wearer's weight) and unlocks automatically, but only when all loads (radial force and bending) relieved. Joints lock whenever wearer applies weight to knee at any joint angle between full extension and 45 degree bend. Both devices offer increased safety and convenience relative to conventional orthotic knee joints.

Towards automatic patient positioning and scan planning using continuously moving table MR imaging.

PubMed

Koken, Peter; Dries, Sebastian P M; Keupp, Jochen; Bystrov, Daniel; Pekar, Vladimir; Börnert, Peter

2009-10-01

A concept is proposed to simplify patient positioning and scan planning to improve ease of use and workflow in MR. After patient preparation in front of the scanner the operator selects the anatomy of interest by a single push-button action. Subsequently, the patient table is moved automatically into the scanner, while real-time 3D isotropic low-resolution continuously moving table scout scanning is performed using patient-independent MR system settings. With a real-time organ identification process running in parallel and steering the scanner, the target anatomy can be positioned fully automatically in the scanner's sensitive volume. The desired diagnostic examination of the anatomy of interest can be planned and continued immediately using the geometric information derived from the acquired 3D data. The concept was implemented and successfully tested in vivo in 12 healthy volunteers, focusing on the liver as the target anatomy. The positioning accuracy achieved was on the order of several millimeters, which turned out to be sufficient for initial planning purposes. Furthermore, the impact of nonoptimal system settings on the positioning performance, the signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) was investigated. The present work proved the basic concept of the proposed approach as an element of future scan automation. (c) 2009 Wiley-Liss, Inc.

How automatic is the hand's automatic pilot? Evidence from dual-task studies.

PubMed

McIntosh, Robert D; Mulroue, Amy; Brockmole, James R

2010-10-01

The ability to correct reaching movements for changes in target position has been described as the hand's 'automatic pilot'. These corrections are preconscious and occur by default in double-step reaching tasks, even if the goal is to react to the target jump in some other way, for instance by stopping the movement (STOP instruction). Nonetheless, corrections are strongly modulated by conscious intention: participants make more corrections when asked to follow the target (GO instruction) and can suppress them when explicitly asked not to follow the target (NOGO instruction). We studied the influence of a cognitively demanding (auditory 1-back) task upon correction behaviour under GO, STOP and NOGO instructions. Correction rates under the STOP instruction were unaffected by cognitive load, consistent with the assumption that they reflect the default behaviour of the automatic pilot. Correction rates under the GO instruction were also unaffected, suggesting that minimal cognitive resources are required to enhance online correction. By contrast, cognitive load impeded the ability to suppress online corrections under the NOGO instruction. These data reveal a constitutional bias in the automatic pilot system: intentional suppression of the default correction behaviour is cognitively demanding, but enhancement towards greater responsiveness is seemingly effortless.

Management of natural resources through automatic cartographic inventory

NASA Technical Reports Server (NTRS)

Rey, P.; Gourinard, Y.; Cambou, F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Over those parts of the ARNICA test site where ERTS-1 data were available, the search for correspondences between images and ground truth acquired by the vegetation and geology maps was quite positive. The probability of recognition of soil use types can be estimated at: (1) 100% for water plans, rivers, canals, swamplands, and wetlands; (2) 80%-100% for the major types of forestry, farmland zones, moorlands and pasturelands, and urbanization; (3) 20%-50% for communication lines; (4) 60%-80% for forestry species and organization of agricultural areas; (5) 40%-60% for finer discrimination between forest types and more accurate identification of cultivations; (6) 60%-90% for major geological features. These percentages will be improved upon as soon as it is possible to use the repetitive imagery. An early use of automatic cartography using ERTS-1 imagery was made possible for pine forests in the Central Pyrenees, the densitometric signature of which were particularly significant. Important observations were made in related fields of water resources, snow survey, estuary dynamics, and meteorology.

Music-Elicited Emotion Identification Using Optical Flow Analysis of Human Face

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Smirnova, Z. N.

2015-05-01

Human emotion identification from image sequences is highly demanded nowadays. The range of possible applications can vary from an automatic smile shutter function of consumer grade digital cameras to Biofied Building technologies, which enables communication between building space and residents. The highly perceptual nature of human emotions leads to the complexity of their classification and identification. The main question arises from the subjective quality of emotional classification of events that elicit human emotions. A variety of methods for formal classification of emotions were developed in musical psychology. This work is focused on identification of human emotions evoked by musical pieces using human face tracking and optical flow analysis. Facial feature tracking algorithm used for facial feature speed and position estimation is presented. Facial features were extracted from each image sequence using human face tracking with local binary patterns (LBP) features. Accurate relative speeds of facial features were estimated using optical flow analysis. Obtained relative positions and speeds were used as the output facial emotion vector. The algorithm was tested using original software and recorded image sequences. The proposed technique proves to give a robust identification of human emotions elicited by musical pieces. The estimated models could be used for human emotion identification from image sequences in such fields as emotion based musical background or mood dependent radio.

Automatic Identification & Classification of Surgical Margin Status from Pathology Reports Following Prostate Cancer Surgery

PubMed Central

D’Avolio, Leonard W.; Litwin, Mark S.; Rogers, Selwyn O.; Bui, Alex A. T.

2007-01-01

Prostate cancer removal surgeries that result in tumor found at the surgical margin, otherwise known as a positive surgical margin, have a significantly higher chance of biochemical recurrence and clinical progression. To support clinical outcomes assessment a system was designed to automatically identify, extract, and classify key phrases from pathology reports describing this outcome. Heuristics and boundary detection were used to extract phrases. Phrases were then classified using support vector machines into one of three classes: ‘positive (involved) margins,’ ‘negative (uninvolved) margins,’ and ‘not-applicable or definitive.’ A total of 851 key phrases were extracted from a sample of 782 reports produced between 1996 and 2006 from two major hospitals. Despite differences in reporting style, at least 1 sentence containing a diagnosis was extracted from 780 of the 782 reports (99.74%). Of the 851 sentences extracted, 97.3% contained diagnoses. Overall accuracy of automated classification of extracted sentences into the three categories was 97.18%. PMID:18693818

[Research on automatic external defibrillator based on DSP].

PubMed

Jing, Jun; Ding, Jingyan; Zhang, Wei; Hong, Wenxue

2012-10-01

Electrical defibrillation is the most effective way to treat the ventricular tachycardia (VT) and ventricular fibrillation (VF). An automatic external defibrillator based on DSP is introduced in this paper. The whole design consists of the signal collection module, the microprocessor controlingl module, the display module, the defibrillation module and the automatic recognition algorithm for VF and non VF, etc. This automatic external defibrillator has achieved goals such as ECG signal real-time acquisition, ECG wave synchronous display, data delivering to U disk and automatic defibrillate when shockable rhythm appears, etc.

Precision about the automatic emotional brain.

PubMed

Vuilleumier, Patrik

2015-01-01

The question of automaticity in emotion processing has been debated under different perspectives in recent years. Satisfying answers to this issue will require a better definition of automaticity in terms of relevant behavioral phenomena, ecological conditions of occurrence, and a more precise mechanistic account of the underlying neural circuits.

Automatic comparison of striation marks and automatic classification of shoe prints

NASA Astrophysics Data System (ADS)

Geradts, Zeno J.; Keijzer, Jan; Keereweer, Isaac

1995-09-01

A database for toolmarks (named TRAX) and a database for footwear outsole designs (named REBEZO) have been developed on a PC. The databases are filled with video-images and administrative data about the toolmarks and the footwear designs. An algorithm for the automatic comparison of the digitized striation patterns has been developed for TRAX. The algorithm appears to work well for deep and complete striation marks and will be implemented in TRAX. For REBEZO some efforts have been made to the automatic classification of outsole patterns. The algorithm first segments the shoeprofile. Fourier-features are selected for the separate elements and are classified with a neural network. In future developments information on invariant moments of the shape and rotation angle will be included in the neural network.

Crop identification technology assessment for remote sensing (CITARS). Volume 10: Interpretation of results

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Feiveson, A. H.; Hall, F. G.; Bauer, M. E.; Davis, B. J.; Malila, W. A.; Rice, D. P.

1975-01-01

The CITARS was an experiment designed to quantitatively evaluate crop identification performance for corn and soybeans in various environments using a well-defined set of automatic data processing (ADP) techniques. Each technique was applied to data acquired to recognize and estimate proportions of corn and soybeans. The CITARS documentation summarizes, interprets, and discusses the crop identification performances obtained using (1) different ADP procedures; (2) a linear versus a quadratic classifier; (3) prior probability information derived from historic data; (4) local versus nonlocal recognition training statistics and the associated use of preprocessing; (5) multitemporal data; (6) classification bias and mixed pixels in proportion estimation; and (7) data with differnt site characteristics, including crop, soil, atmospheric effects, and stages of crop maturity.

Identification of the chemical constituents of Chinese medicine Yi-Xin-Shu capsule by molecular feature orientated precursor ion selection and tandem mass spectrometry structure elucidation.

PubMed

Wang, Hong-ping; Chen, Chang; Liu, Yan; Yang, Hong-Jun; Wu, Hong-Wei; Xiao, Hong-Bin

2015-11-01

The incomplete identification of the chemical components of traditional Chinese medicinal formula has been one of the bottlenecks in the modernization of traditional Chinese medicine. Tandem mass spectrometry has been widely used for the identification of chemical substances. Current automatic tandem mass spectrometry acquisition, where precursor ions were selected according to their signal intensity, encounters a drawback in chemical substances identification when samples contain many overlapping signals. Compounds in minor or trace amounts could not be identified because most tandem mass spectrometry information was lost. Herein, a molecular feature orientated precursor ion selection and tandem mass spectrometry structure elucidation method for complex Chinese medicine chemical constituent analysis was developed. The precursor ions were selected according to their two-dimensional characteristics of retention times and mass-to-charge ratio ranges from herbal compounds, so that all precursor ions from herbal compounds were included and more minor chemical constituents in Chinese medicine were identified. Compared to the conventional automatic tandem mass spectrometry setups, the approach is novel and can overcome the drawback for chemical substances identification. As an example, 276 compounds from the Chinese Medicine of Yi-Xin-Shu capsule were identified. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic sample Dewar for MX beam-line

DOE Office of Scientific and Technical Information (OSTI.GOV)

Charignon, T.; Tanchon, J.; Trollier, T.

2014-01-29

It is very common for crystals of large biological macromolecules to show considerable variation in quality of their diffraction. In order to increase the number of samples that are tested for diffraction quality before any full data collections at the ESRF*, an automatic sample Dewar has been implemented. Conception and performances of the Dewar are reported in this paper. The automatic sample Dewar has 240 samples capability with automatic loading/unloading ports. The storing Dewar is capable to work with robots and it can be integrated in a full automatic MX** beam-line. The samples are positioned in the front of themore » loading/unloading ports with and automatic rotating plate. A view port has been implemented for data matrix camera reading on each sample loaded in the Dewar. At last, the Dewar is insulated with polyurethane foam that keeps the liquid nitrogen consumption below 1.6 L/h. At last, the static insulation also makes vacuum equipment and maintenance unnecessary. This Dewar will be useful for increasing the number of samples tested in synchrotrons.« less

Image simulation for automatic license plate recognition

NASA Astrophysics Data System (ADS)

Bala, Raja; Zhao, Yonghui; Burry, Aaron; Kozitsky, Vladimir; Fillion, Claude; Saunders, Craig; Rodríguez-Serrano, José

2012-01-01

Automatic license plate recognition (ALPR) is an important capability for traffic surveillance applications, including toll monitoring and detection of different types of traffic violations. ALPR is a multi-stage process comprising plate localization, character segmentation, optical character recognition (OCR), and identification of originating jurisdiction (i.e. state or province). Training of an ALPR system for a new jurisdiction typically involves gathering vast amounts of license plate images and associated ground truth data, followed by iterative tuning and optimization of the ALPR algorithms. The substantial time and effort required to train and optimize the ALPR system can result in excessive operational cost and overhead. In this paper we propose a framework to create an artificial set of license plate images for accelerated training and optimization of ALPR algorithms. The framework comprises two steps: the synthesis of license plate images according to the design and layout for a jurisdiction of interest; and the modeling of imaging transformations and distortions typically encountered in the image capture process. Distortion parameters are estimated by measurements of real plate images. The simulation methodology is successfully demonstrated for training of OCR.

ANNUAL REPORT-AUTOMATIC INDEXING AND ABSTRACTING.

ERIC Educational Resources Information Center

Lockheed Missiles and Space Co., Palo Alto, CA. Electronic Sciences Lab.

THE INVESTIGATION IS CONCERNED WITH THE DEVELOPMENT OF AUTOMATIC INDEXING, ABSTRACTING, AND EXTRACTING SYSTEMS. BASIC INVESTIGATIONS IN ENGLISH MORPHOLOGY, PHONETICS, AND SYNTAX ARE PURSUED AS NECESSARY MEANS TO THIS END. IN THE FIRST SECTION THE THEORY AND DESIGN OF THE "SENTENCE DICTIONARY" EXPERIMENT IN AUTOMATIC EXTRACTION IS OUTLINED. SOME OF…

14 CFR 29.1329 - Automatic pilot system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... is automatic synchronization, each system must have a means to readily indicate to the pilot the... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 29.1329 - Automatic pilot system.

Code of Federal Regulations, 2010 CFR

2010-01-01

... is automatic synchronization, each system must have a means to readily indicate to the pilot the... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 29.1329 - Automatic pilot system.

Code of Federal Regulations, 2014 CFR

2014-01-01

... is automatic synchronization, each system must have a means to readily indicate to the pilot the... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 29.1329 - Automatic pilot system.

Code of Federal Regulations, 2013 CFR

2013-01-01

... is automatic synchronization, each system must have a means to readily indicate to the pilot the... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 29.1329 - Automatic pilot system.

Code of Federal Regulations, 2012 CFR

2012-01-01

... is automatic synchronization, each system must have a means to readily indicate to the pilot the... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

DOE PAGES

Benton, H. Paul; Ivanisevic, Julijana; Mahieu, Nathaniel G.; ...

2014-12-12

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometrymore » data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.« less

Identification of Velcro rales based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Chen, Xue; Shao, Jie; Long, Yingjiao; Que, Chengli; Zhang, Jue; Fang, Jing

2014-05-01

Velcro rales, as a kind of crackles, are relatively specific for lung fibrosis and usually the first clinical clue of interstitial lung disease (ILD). We proposed an automatic analytic tool based on Hilbert-Huang transform (HHT) for the computerized identification of Velcro rales. In particular, HHT was utilized to extract the energy weight in various frequency bands (EW) of crackles and to calculate the portion of crackles during late inspiration. Support vector machine (SVM) based on the HHT-derived measures was used to differentiate Velcro rales from other crackles. We found that there were significant differences in the extracted parameters between Velcro rales and other crackles, including EW, EW and the proportion of crackles that appeared during the late inspiration. The discrimination results obtained from SVM achieved a concordance rate up to 92.20%±1.80% as confirmed by the diagnosis from experienced physicians. For practical purpose, the proposed approach may have potential applications to improve the sensitivity and accuracy of auscultation and conduct automatic ILD diagnose system.

State Identification for Planetary Rovers: Learning and Recognition

NASA Technical Reports Server (NTRS)

Aycard, Olivier; Washington, Richard

1999-01-01

A planetary rover must be able to identify states where it should stop or change its plan. With limited and infrequent communication from ground, the rover must recognize states accurately. However, the sensor data is inherently noisy, so identifying the temporal patterns of data that correspond to interesting or important states becomes a complex problem. In this paper, we present an approach to state identification using second-order Hidden Markov Models. Models are trained automatically on a set of labeled training data; the rover uses those models to identify its state from the observed data. The approach is demonstrated on data from a planetary rover platform.

14 CFR 27.1329 - Automatic pilot system.

Code of Federal Regulations, 2014 CFR

2014-01-01

... automatic synchronization, each system must have a means to readily indicate to the pilot the alignment of... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 27.1329 - Automatic pilot system.

Code of Federal Regulations, 2010 CFR

2010-01-01

... automatic synchronization, each system must have a means to readily indicate to the pilot the alignment of... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 27.1329 - Automatic pilot system.

Code of Federal Regulations, 2013 CFR

2013-01-01

... automatic synchronization, each system must have a means to readily indicate to the pilot the alignment of... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 27.1329 - Automatic pilot system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... automatic synchronization, each system must have a means to readily indicate to the pilot the alignment of... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

14 CFR 27.1329 - Automatic pilot system.

Code of Federal Regulations, 2012 CFR

2012-01-01

... automatic synchronization, each system must have a means to readily indicate to the pilot the alignment of... that corrective action begins within a reasonable period of time. (e) If the automatic pilot integrates...

Validation of crowdsourced automatic rain gauge measurements in Amsterdam

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

2016-04-01

over time in most stations showed an underestimation of rainfall compared to the accumulative values found in the corresponding radar pixel of the reference. Special consideration is given to the identification of faulty measurements without the need to obtain additional meta-data, such as setup and surroundings. This validation will show the potential of crowdsourced automatic weather stations for future urban rainfall monitoring.

Polluter identification with spaceborne radar imagery, AIS and forward drift modeling.

PubMed

Longépé, N; Mouche, A A; Goacolou, M; Granier, N; Carrere, L; Lebras, J Y; Lozach, P; Besnard, S

2015-12-30

This study defines and assesses a new operational concept to identify the origin of pollution at sea, based on Synthetic Aperture Radar, Automatic Identification System, and a forward drift model. As opposed to traditional methodologies where the SAR detected pollution is backtracked in the past, our approach assumes that all the vessels pollute all along their way. Based on all the AIS data flows, the forward-tracked simulated pollutions are then compared to the detected pollution, and the potential polluter can be finally identified. Case studies are presented to showcase its usefulness in a variety of maritime situations with a focus on orphan pollutions in a dense traffic area. Out of the identification of the suspected polluters, the age and eventually the type of the pollution can be retrieved. Copyright © 2015 Elsevier Ltd. All rights reserved.

Channel Measurements for Automatic Vehicle Monitoring Systems

DOT National Transportation Integrated Search

1974-03-01

Co-channel and adjacent channel electromagnetic interference measurements were conducted on the Sierra Research Corp. and the Chicago Transit Authority automatic vehicle monitoring systems. These measurements were made to determine if the automatic v...

10 CFR 431.132 - Definitions concerning automatic commercial ice makers.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 3 2014-01-01 2014-01-01 false Definitions concerning automatic commercial ice makers... CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Automatic Commercial Ice Makers § 431.132 Definitions concerning automatic commercial ice makers. Automatic commercial ice maker means a factory-made assembly (not...

10 CFR 431.132 - Definitions concerning automatic commercial ice makers.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 3 2012-01-01 2012-01-01 false Definitions concerning automatic commercial ice makers... CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Automatic Commercial Ice Makers § 431.132 Definitions concerning automatic commercial ice makers. Automatic commercial ice maker means a factory-made assembly (not...

10 CFR 431.132 - Definitions concerning automatic commercial ice makers.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Definitions concerning automatic commercial ice makers... CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Automatic Commercial Ice Makers § 431.132 Definitions concerning automatic commercial ice makers. Automatic commercial ice maker means a factory-made assembly (not...

10 CFR 431.132 - Definitions concerning automatic commercial ice makers.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 3 2011-01-01 2011-01-01 false Definitions concerning automatic commercial ice makers... CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Automatic Commercial Ice Makers § 431.132 Definitions concerning automatic commercial ice makers. Automatic commercial ice maker means a factory-made assembly (not...

10 CFR 431.132 - Definitions concerning automatic commercial ice makers.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 3 2013-01-01 2013-01-01 false Definitions concerning automatic commercial ice makers... CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Automatic Commercial Ice Makers § 431.132 Definitions concerning automatic commercial ice makers. Automatic commercial ice maker means a factory-made assembly (not...

Automatic stereotyping against people with schizophrenia, schizoaffective and affective disorders

PubMed Central

Rüsch, Nicolas; Corrigan, Patrick W.; Todd, Andrew R.; Bodenhausen, Galen V.

2010-01-01

Similar to members of the public, people with mental illness may exhibit general negative automatic prejudice against their own group. However, it is unclear whether more specific negative stereotypes are automatically activated among diagnosed individuals and how such automatic stereotyping may be related to self-reported attitudes and emotional reactions. We therefore studied automatically activated reactions toward mental illness among 85 people with schizophrenia, schizoaffective or affective disorders as well as among 50 members of the general public, using a Lexical Decision Task to measure automatic stereotyping. Deliberately endorsed attitudes and emotional reactions were assessed by self-report. Independent of diagnosis, people with mental illness showed less negative automatic stereotyping than did members of the public. Among members of the public, stronger automatic stereotyping was associated with more self-reported shame about a potential mental illness and more anger toward stigmatized individuals. Reduced automatic stereotyping in the diagnosed group suggests that people with mental illness might not entirely internalize societal stigma. Among members of the public, automatic stereotyping predicted negative emotional reactions to people with mental illness. Initiatives to reduce the impact of public stigma and internalized stigma should take automatic stereotyping and related emotional aspects of stigma into account. PMID:20843560

Automatic Identification of Messages Related to Adverse Drug Reactions from Online User Reviews using Feature-based Classification.

PubMed

Liu, Jingfang; Zhang, Pengzhu; Lu, Yingjie

2014-11-01

User-generated medical messages on Internet contain extensive information related to adverse drug reactions (ADRs) and are known as valuable resources for post-marketing drug surveillance. The aim of this study was to find an effective method to identify messages related to ADRs automatically from online user reviews. We conducted experiments on online user reviews using different feature set and different classification technique. Firstly, the messages from three communities, allergy community, schizophrenia community and pain management community, were collected, the 3000 messages were annotated. Secondly, the N-gram-based features set and medical domain-specific features set were generated. Thirdly, three classification techniques, SVM, C4.5 and Naïve Bayes, were used to perform classification tasks separately. Finally, we evaluated the performance of different method using different feature set and different classification technique by comparing the metrics including accuracy and F-measure. In terms of accuracy, the accuracy of SVM classifier was higher than 0.8, the accuracy of C4.5 classifier or Naïve Bayes classifier was lower than 0.8; meanwhile, the combination feature sets including n-gram-based feature set and domain-specific feature set consistently outperformed single feature set. In terms of F-measure, the highest F-measure is 0.895 which was achieved by using combination feature sets and a SVM classifier. In all, we can get the best classification performance by using combination feature sets and SVM classifier. By using combination feature sets and SVM classifier, we can get an effective method to identify messages related to ADRs automatically from online user reviews.

Validation of automatic segmentation of ribs for NTCP modeling.

PubMed

Stam, Barbara; Peulen, Heike; Rossi, Maddalena M G; Belderbos, José S A; Sonke, Jan-Jakob

2016-03-01

Determination of a dose-effect relation for rib fractures in a large patient group has been limited by the time consuming manual delineation of ribs. Automatic segmentation could facilitate such an analysis. We determine the accuracy of automatic rib segmentation in the context of normal tissue complication probability modeling (NTCP). Forty-one patients with stage I/II non-small cell lung cancer treated with SBRT to 54 Gy in 3 fractions were selected. Using the 4DCT derived mid-ventilation planning CT, all ribs were manually contoured and automatically segmented. Accuracy of segmentation was assessed using volumetric, shape and dosimetric measures. Manual and automatic dosimetric parameters Dx and EUD were tested for equivalence using the Two One-Sided T-test (TOST), and assessed for agreement using Bland-Altman analysis. NTCP models based on manual and automatic segmentation were compared. Automatic segmentation was comparable with the manual delineation in radial direction, but larger near the costal cartilage and vertebrae. Manual and automatic Dx and EUD were significantly equivalent. The Bland-Altman analysis showed good agreement. The two NTCP models were very similar. Automatic rib segmentation was significantly equivalent to manual delineation and can be used for NTCP modeling in a large patient group. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Combining Phase Identification and Statistic Modeling for Automated Parallel Benchmark Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Ye; Ma, Xiaosong; Liu, Qing Gary

2015-01-01

Parallel application benchmarks are indispensable for evaluating/optimizing HPC software and hardware. However, it is very challenging and costly to obtain high-fidelity benchmarks reflecting the scale and complexity of state-of-the-art parallel applications. Hand-extracted synthetic benchmarks are time-and labor-intensive to create. Real applications themselves, while offering most accurate performance evaluation, are expensive to compile, port, reconfigure, and often plainly inaccessible due to security or ownership concerns. This work contributes APPRIME, a novel tool for trace-based automatic parallel benchmark generation. Taking as input standard communication-I/O traces of an application's execution, it couples accurate automatic phase identification with statistical regeneration of event parameters tomore » create compact, portable, and to some degree reconfigurable parallel application benchmarks. Experiments with four NAS Parallel Benchmarks (NPB) and three real scientific simulation codes confirm the fidelity of APPRIME benchmarks. They retain the original applications' performance characteristics, in particular the relative performance across platforms.« less

Automatic Contour Tracking in Ultrasound Images

ERIC Educational Resources Information Center

Li, Min; Kambhamettu, Chandra; Stone, Maureen

2005-01-01

In this paper, a new automatic contour tracking system, EdgeTrak, for the ultrasound image sequences of human tongue is presented. The images are produced by a head and transducer support system (HATS). The noise and unrelated high-contrast edges in ultrasound images make it very difficult to automatically detect the correct tongue surfaces. In…

Performance of wavelet analysis and neural networks for pathological voices identification

NASA Astrophysics Data System (ADS)

Salhi, Lotfi; Talbi, Mourad; Abid, Sabeur; Cherif, Adnane

2011-09-01

Within the medical environment, diverse techniques exist to assess the state of the voice of the patient. The inspection technique is inconvenient for a number of reasons, such as its high cost, the duration of the inspection, and above all, the fact that it is an invasive technique. This study focuses on a robust, rapid and accurate system for automatic identification of pathological voices. This system employs non-invasive, non-expensive and fully automated method based on hybrid approach: wavelet transform analysis and neural network classifier. First, we present the results obtained in our previous study while using classic feature parameters. These results allow visual identification of pathological voices. Second, quantified parameters drifting from the wavelet analysis are proposed to characterise the speech sample. On the other hand, a system of multilayer neural networks (MNNs) has been developed which carries out the automatic detection of pathological voices. The developed method was evaluated using voice database composed of recorded voice samples (continuous speech) from normophonic or dysphonic speakers. The dysphonic speakers were patients of a National Hospital 'RABTA' of Tunis Tunisia and a University Hospital in Brussels, Belgium. Experimental results indicate a success rate ranging between 75% and 98.61% for discrimination of normal and pathological voices using the proposed parameters and neural network classifier. We also compared the average classification rate based on the MNN, Gaussian mixture model and support vector machines.

Automatically processed alpha-track radon monitor

DOEpatents

Langner, Jr., G. Harold

1993-01-01

An automatically processed alpha-track radon monitor is provided which includes a housing having an aperture allowing radon entry, and a filter that excludes the entry of radon daughters into the housing. A flexible track registration material is located within the housing that records alpha-particle emissions from the decay of radon and radon daughters inside the housing. The flexible track registration material is capable of being spliced such that the registration material from a plurality of monitors can be spliced into a single strip to facilitate automatic processing of the registration material from the plurality of monitors. A process for the automatic counting of radon registered by a radon monitor is also provided.

Automatically processed alpha-track radon monitor

DOEpatents

Langner, G.H. Jr.

1993-01-12

An automatically processed alpha-track radon monitor is provided which includes a housing having an aperture allowing radon entry, and a filter that excludes the entry of radon daughters into the housing. A flexible track registration material is located within the housing that records alpha-particle emissions from the decay of radon and radon daughters inside the housing. The flexible track registration material is capable of being spliced such that the registration material from a plurality of monitors can be spliced into a single strip to facilitate automatic processing of the registration material from the plurality of monitors. A process for the automatic counting of radon registered by a radon monitor is also provided.

Automatic Lamp and Fan Control Based on Microcontroller

NASA Astrophysics Data System (ADS)

Widyaningrum, V. T.; Pramudita, Y. D.

2018-01-01

In general, automation can be described as a process following pre-determined sequential steps with a little or without any human exertion. Automation is provided with the use of various sensors suitable to observe the production processes, actuators and different techniques and devices. In this research, the automation system developed is an automatic lamp and an automatic fan on the smart home. Both of these systems will be processed using an Arduino Mega 2560 microcontroller. A microcontroller is used to obtain values of physical conditions through sensors connected to it. In the automatic lamp system required sensors to detect the light of the LDR (Light Dependent Resistor) sensor. While the automatic fan system required sensors to detect the temperature of the DHT11 sensor. In tests that have been done lamps and fans can work properly. The lamp can turn on automatically when the light begins to darken, and the lamp can also turn off automatically when the light begins to bright again. In addition, it can concluded also that the readings of LDR sensors are placed outside the room is different from the readings of LDR sensors placed in the room. This is because the light intensity received by the existing LDR sensor in the room is blocked by the wall of the house or by other objects. Then for the fan, it can also turn on automatically when the temperature is greater than 25°C, and the fan speed can also be adjusted. The fan may also turn off automatically when the temperature is less than equal to 25°C.

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

PubMed

Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick

2017-11-03

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

Practical automatic Arabic license plate recognition system

NASA Astrophysics Data System (ADS)

Mohammad, Khader; Agaian, Sos; Saleh, Hani

2011-02-01

Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

Automated bow shock and radiation belt edge identification methods and their application for Cluster, THEMIS/ARTEMIS and Van Allen Probes data

NASA Astrophysics Data System (ADS)

Facsko, Gabor; Sibeck, David; Balogh, Tamas; Kis, Arpad; Wesztergom, Viktor

2017-04-01

The bow shock and the outer rim of the outer radiation belt are detected automatically by our algorithm developed as a part of the Boundary Layer Identification Code Cluster Active Archive project. The radiation belt positions are determined from energized electron measurements working properly onboard all Cluster spacecraft. For bow shock identification we use magnetometer data and, when available, ion plasma instrument data. In addition, electrostatic wave instrument electron density, spacecraft potential measurements and wake indicator auxiliary data are also used so the events can be identified by all Cluster probes in highly redundant way, as the magnetometer and these instruments are still operational in all spacecraft. The capability and performance of the bow shock identification algorithm were tested using known bow shock crossing determined manually from January 29, 2002 to February 3,. The verification enabled 70% of the bow shock crossings to be identified automatically. The method shows high flexibility and it can be applied to observations from various spacecraft. Now these tools have been applied to Time History of Events and Macroscale Interactions during Substorms (THEMIS)/Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) magnetic field, plasma and spacecraft potential observations to identify bow shock crossings; and to Van Allen Probes supra-thermal electron observations to identify the edges of the radiation belt. The outcomes of the algorithms are checked manually and the parameters used to search for bow shock identification are refined.

Surgical instrument similarity metrics and tray analysis for multi-sensor instrument identification

NASA Astrophysics Data System (ADS)

Glaser, Bernhard; Schellenberg, Tobias; Franke, Stefan; Dänzer, Stefan; Neumuth, Thomas

2015-03-01

A robust identification of the instrument currently used by the surgeon is crucial for the automatic modeling and analysis of surgical procedures. Various approaches for intra-operative surgical instrument identification have been presented, mostly based on radio-frequency identification (RFID) or endoscopic video analysis. A novel approach is to identify the instruments on the instrument table of the scrub nurse with a combination of video and weight information. In a previous article, we successfully followed this approach and applied it to multiple instances of an ear, nose and throat (ENT) procedure and the surgical tray used therein. In this article, we present a metric for the suitability of the instruments of a surgical tray for identification by video and weight analysis and apply it to twelve trays of four different surgical domains (abdominal surgery, neurosurgery, orthopedics and urology). The used trays were digitized at the central sterile services department of the hospital. The results illustrate that surgical trays differ in their suitability for the approach. In general, additional weight information can significantly contribute to the successful identification of surgical instruments. Additionally, for ten different surgical instruments, ten exemplars of each instrument were tested for their weight differences. The samples indicate high weight variability in instruments with identical brand and model number. The results present a new metric for approaches aiming towards intra-operative surgical instrument detection and imply consequences for algorithms exploiting video and weight information for identification purposes.

Who identifies with suicidal film characters? Determinants of identification with suicidal protagonists of drama films.

PubMed

Till, Benedikt; Herberth, Arno; Sonneck, Gernot; Vitouch, Peter; Niederkrotenthaler, Thomas

2013-06-01

Identification with a media character is an influential factor for the effects of a media product on the recipient, but still very little is known about this cognitive process. This study investigated to what extent identification of a recipient with the suicidal protagonist of a film drama is influenced by the similarity between them in terms of sex, age, and education as well as by the viewer's empathy and suicidality. Sixty adults were assigned randomly to one of two film groups. Both groups watched a drama that concluded with the tragic suicide of the protagonist. Identification, empathy, suicidality, as well as socio-demographic data were measured by questionnaires that were applied before and after the movie screening. Results indicated that identification was not associated with socio-demographic similarity or the viewer's suicidality. However, the greater the subjects' empathy was, the more they identified with the protagonist in one of the two films. This investigation provides evidence that challenges the common assumption that identification with a film character is automatically generated when viewer and protagonist are similar in terms of sex, age, education or attitude.

Text de-identification for privacy protection: a study of its impact on clinical text information content.

PubMed

Meystre, Stéphane M; Ferrández, Óscar; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2014-08-01

As more and more electronic clinical information is becoming easier to access for secondary uses such as clinical research, approaches that enable faster and more collaborative research while protecting patient privacy and confidentiality are becoming more important. Clinical text de-identification offers such advantages but is typically a tedious manual process. Automated Natural Language Processing (NLP) methods can alleviate this process, but their impact on subsequent uses of the automatically de-identified clinical narratives has only barely been investigated. In the context of a larger project to develop and investigate automated text de-identification for Veterans Health Administration (VHA) clinical notes, we studied the impact of automated text de-identification on clinical information in a stepwise manner. Our approach started with a high-level assessment of clinical notes informativeness and formatting, and ended with a detailed study of the overlap of select clinical information types and Protected Health Information (PHI). To investigate the informativeness (i.e., document type information, select clinical data types, and interpretation or conclusion) of VHA clinical notes, we used five different existing text de-identification systems. The informativeness was only minimally altered by these systems while formatting was only modified by one system. To examine the impact of de-identification on clinical information extraction, we compared counts of SNOMED-CT concepts found by an open source information extraction application in the original (i.e., not de-identified) version of a corpus of VHA clinical notes, and in the same corpus after de-identification. Only about 1.2-3% less SNOMED-CT concepts were found in de-identified versions of our corpus, and many of these concepts were PHI that was erroneously identified as clinical information. To study this impact in more details and assess how generalizable our findings were, we examined the overlap between

[Study on Intelligent Automatic Tracking Radiation Protection Curtain].

PubMed

Zhao, Longyang; Han, Jindong; Ou, Minjian; Chen, Jinlong

2015-09-01

In order to overcome the shortcomings of traditional X-ray inspection taking passive protection mode, this paper combines the automatic control technology, puts forward a kind of active protection X-ray equipment. The device of automatic detection of patients receiving X-ray irradiation part, intelligent adjustment in patients and shooting device between automatic tracking radiation protection device height. The device has the advantages of automatic adjustment, anti-radiation device, reduce the height of non-irradiated area X-ray radiation and improve the work efficiency. Testing by the professional organization, the device can decrease more than 90% of X-ray dose for patients with non-irradiated area.

Automatic Clustering Using FSDE-Forced Strategy Differential Evolution

NASA Astrophysics Data System (ADS)

Yasid, A.

2018-01-01

Clustering analysis is important in datamining for unsupervised data, cause no adequate prior knowledge. One of the important tasks is defining the number of clusters without user involvement that is known as automatic clustering. This study intends on acquiring cluster number automatically utilizing forced strategy differential evolution (AC-FSDE). Two mutation parameters, namely: constant parameter and variable parameter are employed to boost differential evolution performance. Four well-known benchmark datasets were used to evaluate the algorithm. Moreover, the result is compared with other state of the art automatic clustering methods. The experiment results evidence that AC-FSDE is better or competitive with other existing automatic clustering algorithm.

Automatic Brake Slack Adjusters on Transit Buses

DOT National Transportation Integrated Search

1985-04-01

The purpose of this report is to provide transit bus agencies with current information on automatic brake slack adjusters. Rather than a comprehensive statistical survey, this report is intended to provide an overview of the states of automatic slack...

Automatic safety rod for reactors

DOEpatents

Germer, John H.

1988-01-01

An automatic safety rod for a nuclear reactor containing neutron absorbing material and designed to be inserted into a reactor core after a loss-of-core flow. Actuation is based upon either a sudden decrease in core pressure drop or the pressure drop decreases below a predetermined minimum value. The automatic control rod includes a pressure regulating device whereby a controlled decrease in operating pressure due to reduced coolant flow does not cause the rod to drop into the core.

Automatic image enhancement based on multi-scale image decomposition

NASA Astrophysics Data System (ADS)

Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong

2014-01-01

In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.

Speaker gender identification based on majority vote classifiers

NASA Astrophysics Data System (ADS)

Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

2017-03-01

Speaker gender identification is considered among the most important tools in several multimedia applications namely in automatic speech recognition, interactive voice response systems and audio browsing systems. Gender identification systems performance is closely linked to the selected feature set and the employed classification model. Typical techniques are based on selecting the best performing classification method or searching optimum tuning of one classifier parameters through experimentation. In this paper, we consider a relevant and rich set of features involving pitch, MFCCs as well as other temporal and frequency-domain descriptors. Five classification models including decision tree, discriminant analysis, nave Bayes, support vector machine and k-nearest neighbor was experimented. The three best perming classifiers among the five ones will contribute by majority voting between their scores. Experimentations were performed on three different datasets spoken in three languages: English, German and Arabic in order to validate language independency of the proposed scheme. Results confirm that the presented system has reached a satisfying accuracy rate and promising classification performance thanks to the discriminating abilities and diversity of the used features combined with mid-level statistics.

Observed use of automatic seat belts in 1987 cars.

PubMed

Williams, A F; Wells, J K; Lund, A K; Teed, N

1989-10-01

Usage of the automatic belt systems supplied by six large-volume automobile manufacturers to meet the federal requirements for automatic restraints were observed in suburban Washington, D.C., Chicago, Los Angeles, and Philadelphia. The different belt systems studied were: Ford and Toyota (motorized, nondetachable automatic shoulder belt), Nissan (motorized, detachable shoulder belt), VW and Chrysler (nonmotorized, detachable shoulder belt), and GM (nonmotorized detachable lap and shoulder belt). Use of automatic belts was significantly greater than manual belt use in otherwise comparable late-model cars for all manufacturers except Chrysler; in Chrysler cars, automatic belt use was significantly lower than manual belt use. The automatic shoulder belts provided by Ford, Nissan, Toyota, and VW increased use rates to about 90%. Because use rates were lower in Ford cars with manual belts, their increase was greater. GM cars had the smallest increase in use rates; however, lap belt use was highest in GM cars. The other manufacturers supply knee bolsters to supplement shoulder belt protection; all--except VW--also provide manual lap belts, which were used by about half of those who used the automatic shoulder belt. The results indicate that some manufacturers have been more successful than others in providing automatic belt systems that result in high use that, in turn, will mean fewer deaths and injuries in those cars.

Automatic rapid attachable warhead section

DOEpatents

Trennel, A.J.

1994-05-10

Disclosed are a method and apparatus for automatically selecting warheads or reentry vehicles from a storage area containing a plurality of types of warheads or reentry vehicles, automatically selecting weapon carriers from a storage area containing at least one type of weapon carrier, manipulating and aligning the selected warheads or reentry vehicles and weapon carriers, and automatically coupling the warheads or reentry vehicles with the weapon carriers such that coupling of improperly selected warheads or reentry vehicles with weapon carriers is inhibited. Such inhibition enhances safety of operations and is achieved by a number of means including computer control of the process of selection and coupling and use of connectorless interfaces capable of assuring that improperly selected items will be rejected or rendered inoperable prior to coupling. Also disclosed are a method and apparatus wherein the stated principles pertaining to selection, coupling and inhibition are extended to apply to any item-to-be-carried and any carrying assembly. 10 figures.

Automatic rapid attachable warhead section

DOEpatents

Trennel, Anthony J.

1994-05-10

Disclosed are a method and apparatus for (1) automatically selecting warheads or reentry vehicles from a storage area containing a plurality of types of warheads or reentry vehicles, (2) automatically selecting weapon carriers from a storage area containing at least one type of weapon carrier, (3) manipulating and aligning the selected warheads or reentry vehicles and weapon carriers, and (4) automatically coupling the warheads or reentry vehicles with the weapon carriers such that coupling of improperly selected warheads or reentry vehicles with weapon carriers is inhibited. Such inhibition enhances safety of operations and is achieved by a number of means including computer control of the process of selection and coupling and use of connectorless interfaces capable of assuring that improperly selected items will be rejected or rendered inoperable prior to coupling. Also disclosed are a method and apparatus wherein the stated principles pertaining to selection, coupling and inhibition are extended to apply to any item-to-be-carried and any carrying assembly.

Automatic, semi-automatic and manual validation of urban drainage data.

PubMed

Branisavljević, N; Prodanović, D; Pavlović, D

2010-01-01

Advances in sensor technology and the possibility of automated long distance data transmission have made continuous measurements the preferable way of monitoring urban drainage processes. Usually, the collected data have to be processed by an expert in order to detect and mark the wrong data, remove them and replace them with interpolated data. In general, the first step in detecting the wrong, anomaly data is called the data quality assessment or data validation. Data validation consists of three parts: data preparation, validation scores generation and scores interpretation. This paper will present the overall framework for the data quality improvement system, suitable for automatic, semi-automatic or manual operation. The first two steps of the validation process are explained in more detail, using several validation methods on the same set of real-case data from the Belgrade sewer system. The final part of the validation process, which is the scores interpretation, needs to be further investigated on the developed system.

AUTOMATIC MASS SPECTROMETER

DOEpatents

Hanson, M.L.; Tabor, C.D. Jr.

1961-12-01

A mass spectrometer for analyzing the components of a gas is designed which is capable of continuous automatic operation such as analysis of samples of process gas from a continuous production system where the gas content may be changing. (AEC)

Automatic Gain Control in Compact Spectrometers.

PubMed

Protopopov, Vladimir

2016-03-01

An image intensifier installed in the optical path of a compact spectrometer may act not only as a fast gating unit, which is widely used for time-resolved measurements, but also as a variable attenuator-amplifier in a continuous wave mode. This opens the possibility of an automatic gain control, a new feature in spectroscopy. With it, the user is relieved from the necessity to manually adjust signal level at a certain value that it is done automatically by means of an electronic feedback loop. It is even more important that automatic gain control is done without changing exposure time, which is an additional benefit in time-resolved experiments. The concept, algorithm, design considerations, and experimental results are presented. © The Author(s) 2016.

30 CFR 75.523-3 - Automatic emergency-parking brakes.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic emergency-parking brakes. 75.523-3...-3 Automatic emergency-parking brakes. (a) Except for personnel carriers, rubber-tired, self... with automatic emergency-parking brakes in accordance with the following schedule. (1) On and after May...

30 CFR 75.523-3 - Automatic emergency-parking brakes.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Automatic emergency-parking brakes. 75.523-3...-3 Automatic emergency-parking brakes. (a) Except for personnel carriers, rubber-tired, self... with automatic emergency-parking brakes in accordance with the following schedule. (1) On and after May...

Automatic P-S phase picking procedure based on Kurtosis: Vanuatu region case study

NASA Astrophysics Data System (ADS)

Baillard, C.; Crawford, W. C.; Ballu, V.; Hibert, C.

2012-12-01

Automatic P and S phase picking is indispensable for large seismological data sets. Robust algorithms, based on short term and long term average ratio comparison (Allen, 1982), are commonly used for event detection, but further improvements can be made in phase identification and picking. We present a picking scheme using consecutively Kurtosis-derived Characteristic Functions (CF) and Eigenvalue decompositions on 3-component seismic data to independently pick P and S arrivals. When computed over a sliding window of the signal, a sudden increase in the CF reveals a transition from a gaussian to a non-gaussian distribution, characterizing the phase onset (Saragiotis, 2002). One advantage of the method is that it requires much fewer adjustable parameters than competing methods. We modified the Kurtosis CF to improve pick precision, by computing the CF over several frequency bandwidths, window sizes and smoothing parameters. Once phases were picked, we determined the onset type (P or S) using polarization parameters (rectilinearity, azimuth and dip) calculated using Eigenvalue decompositions of the covariance matrix (Cichowicz, 1993). Finally, we removed bad picks using a clustering procedure and the signal-to-noise ratio (SNR). The pick quality index was also assigned based on the SNR value. Amplitude calculation is integrated into the procedure to enable automatic magnitude calculation. We applied this procedure to data from a network of 30 wideband seismometers (including 10 oceanic bottom seismometers) in Vanuatu that ran for 10 months from May 2008 to February 2009. We manually picked the first 172 events of June, whose local magnitudes range from 0.7 to 3.7. We made a total of 1601 picks, 1094 P and 507 S. We then applied our automatic picking to the same dataset. 70% of the manually picked onsets were picked automatically. For P-picks, the difference between manual and automatic picks is 0.01 ± 0.08 s overall; for the best quality picks (quality index 0: 64

[Terahertz Spectroscopic Identification with Deep Belief Network].

PubMed

Ma, Shuai; Shen, Tao; Wang, Rui-qi; Lai, Hua; Yu, Zheng-tao

2015-12-01

Feature extraction and classification are the key issues of terahertz spectroscopy identification. Because many materials have no apparent absorption peaks in the terahertz band, it is difficult to extract theirs terahertz spectroscopy feature and identify. To this end, a novel of identify terahertz spectroscopy approach with Deep Belief Network (DBN) was studied in this paper, which combines the advantages of DBN and K-Nearest Neighbors (KNN) classifier. Firstly, cubic spline interpolation and S-G filter were used to normalize the eight kinds of substances (ATP, Acetylcholine Bromide, Bifenthrin, Buprofezin, Carbazole, Bleomycin, Buckminster and Cylotriphosphazene) terahertz transmission spectra in the range of 0.9-6 THz. Secondly, the DBN model was built by two restricted Boltzmann machine (RBM) and then trained layer by layer using unsupervised approach. Instead of using handmade features, the DBN was employed to learn suitable features automatically with raw input data. Finally, a KNN classifier was applied to identify the terahertz spectrum. Experimental results show that using the feature learned by DBN can identify the terahertz spectrum of different substances with the recognition rate of over 90%, which demonstrates that the proposed method can automatically extract the effective features of terahertz spectrum. Furthermore, this KNN classifier was compared with others (BP neural network, SOM neural network and RBF neural network). Comparisons showed that the recognition rate of KNN classifier is better than the other three classifiers. Using the approach that automatic extract terahertz spectrum features by DBN can greatly reduce the workload of feature extraction. This proposed method shows a promising future in the application of identifying the mass terahertz spectroscopy.

Grinding Parts For Automatic Welding

NASA Technical Reports Server (NTRS)

Burley, Richard K.; Hoult, William S.

1989-01-01

Rollers guide grinding tool along prospective welding path. Skatelike fixture holds rotary grinder or file for machining large-diameter rings or ring segments in preparation for welding. Operator grasps handles to push rolling fixture along part. Rollers maintain precise dimensional relationship so grinding wheel cuts precise depth. Fixture-mounted grinder machines surface to quality sufficient for automatic welding; manual welding with attendant variations and distortion not necessary. Developed to enable automatic welding of parts, manual welding of which resulted in weld bead permeated with microscopic fissures.

21 CFR 211.68 - Automatic, mechanical, and electronic equipment.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 4 2011-04-01 2011-04-01 false Automatic, mechanical, and electronic equipment. 211.68 Section 211.68 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN... Equipment § 211.68 Automatic, mechanical, and electronic equipment. (a) Automatic, mechanical, or electronic...

21 CFR 211.68 - Automatic, mechanical, and electronic equipment.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 4 2012-04-01 2012-04-01 false Automatic, mechanical, and electronic equipment. 211.68 Section 211.68 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN... Equipment § 211.68 Automatic, mechanical, and electronic equipment. (a) Automatic, mechanical, or electronic...

30 CFR 75.1404 - Automatic brakes; speed reduction gear.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic brakes; speed reduction gear. 75.1404... Automatic brakes; speed reduction gear. [Statutory Provisions] Each locomotive and haulage car used in an... permit automatic brakes, locomotives and haulage cars shall be subject to speed reduction gear, or other...

30 CFR 75.1404 - Automatic brakes; speed reduction gear.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Automatic brakes; speed reduction gear. 75.1404... Automatic brakes; speed reduction gear. [Statutory Provisions] Each locomotive and haulage car used in an... permit automatic brakes, locomotives and haulage cars shall be subject to speed reduction gear, or other...

MARZ: Manual and automatic redshifting software

NASA Astrophysics Data System (ADS)

Hinton, S. R.; Davis, Tamara M.; Lidman, C.; Glazebrook, K.; Lewis, G. F.

2016-04-01

The Australian Dark Energy Survey (OzDES) is a 100-night spectroscopic survey underway on the Anglo-Australian Telescope using the fibre-fed 2-degree-field (2dF) spectrograph. We have developed a new redshifting application MARZ with greater usability, flexibility, and the capacity to analyse a wider range of object types than the RUNZ software package previously used for redshifting spectra from 2dF. MARZ is an open-source, client-based, Javascript web-application which provides an intuitive interface and powerful automatic matching capabilities on spectra generated from the AAOmega spectrograph to produce high quality spectroscopic redshift measurements. The software can be run interactively or via the command line, and is easily adaptable to other instruments and pipelines if conforming to the current FITS file standard is not possible. Behind the scenes, a modified version of the AUTOZ cross-correlation algorithm is used to match input spectra against a variety of stellar and galaxy templates, and automatic matching performance for OzDES spectra has increased from 54% (RUNZ) to 91% (MARZ). Spectra not matched correctly by the automatic algorithm can be easily redshifted manually by cycling automatic results, manual template comparison, or marking spectral features.

Shaping electromagnetic waves using software-automatically-designed metasurfaces.

PubMed

Zhang, Qian; Wan, Xiang; Liu, Shuo; Yuan Yin, Jia; Zhang, Lei; Jun Cui, Tie

2017-06-15

We present a fully digital procedure of designing reflective coding metasurfaces to shape reflected electromagnetic waves. The design procedure is completely automatic, controlled by a personal computer. In details, the macro coding units of metasurface are automatically divided into several types (e.g. two types for 1-bit coding, four types for 2-bit coding, etc.), and each type of the macro coding units is formed by discretely random arrangement of micro coding units. By combining an optimization algorithm and commercial electromagnetic software, the digital patterns of the macro coding units are optimized to possess constant phase difference for the reflected waves. The apertures of the designed reflective metasurfaces are formed by arranging the macro coding units with certain coding sequence. To experimentally verify the performance, a coding metasurface is fabricated by automatically designing two digital 1-bit unit cells, which are arranged in array to constitute a periodic coding metasurface to generate the required four-beam radiations with specific directions. Two complicated functional metasurfaces with circularly- and elliptically-shaped radiation beams are realized by automatically designing 4-bit macro coding units, showing excellent performance of the automatic designs by software. The proposed method provides a smart tool to realize various functional devices and systems automatically.

Automatic soldering machine

NASA Technical Reports Server (NTRS)

Stein, J. A.

1974-01-01

Fully-automatic tube-joint soldering machine can be used to make leakproof joints in aluminum tubes of 3/16 to 2 in. in diameter. Machine consists of temperature-control unit, heater transformer and heater head, vibrator, and associated circuitry controls, and indicators.

Multi-stage robust scheme for citrus identification from high resolution airborne images

NASA Astrophysics Data System (ADS)

Amorós-López, Julia; Izquierdo Verdiguier, Emma; Gómez-Chova, Luis; Muñoz-Marí, Jordi; Zoilo Rodríguez-Barreiro, Jorge; Camps-Valls, Gustavo; Calpe-Maravilla, Javier

2008-10-01

Identification of land cover types is one of the most critical activities in remote sensing. Nowadays, managing land resources by using remote sensing techniques is becoming a common procedure to speed up the process while reducing costs. However, data analysis procedures should satisfy the accuracy figures demanded by institutions and governments for further administrative actions. This paper presents a methodological scheme to update the citrus Geographical Information Systems (GIS) of the Comunidad Valenciana autonomous region, Spain). The proposed approach introduces a multi-stage automatic scheme to reduce visual photointerpretation and ground validation tasks. First, an object-oriented feature extraction process is carried out for each cadastral parcel from very high spatial resolution (VHR) images (0.5m) acquired in the visible and near infrared. Next, several automatic classifiers (decision trees, multilayer perceptron, and support vector machines) are trained and combined to improve the final accuracy of the results. The proposed strategy fulfills the high accuracy demanded by policy makers by means of combining automatic classification methods with visual photointerpretation available resources. A level of confidence based on the agreement between classifiers allows us an effective management by fixing the quantity of parcels to be reviewed. The proposed methodology can be applied to similar problems and applications.

Development of an optimal filter substrate for the identification of small microplastic particles in food by micro-Raman spectroscopy.

PubMed

Oßmann, Barbara E; Sarau, George; Schmitt, Sebastian W; Holtmannspötter, Heinrich; Christiansen, Silke H; Dicke, Wilhelm

2017-06-01

When analysing microplastics in food, due to toxicological reasons it is important to achieve clear identification of particles down to a size of at least 1 μm. One reliable, optical analytical technique allowing this is micro-Raman spectroscopy. After isolation of particles via filtration, analysis is typically performed directly on the filter surface. In order to obtain high qualitative Raman spectra, the material of the membrane filters should not show any interference in terms of background and Raman signals during spectrum acquisition. To facilitate the usage of automatic particle detection, membrane filters should also show specific optical properties. In this work, beside eight different, commercially available membrane filters, three newly designed metal-coated polycarbonate membrane filters were tested to fulfil these requirements. We found that aluminium-coated polycarbonate membrane filters had ideal characteristics as a substrate for micro-Raman spectroscopy. Its spectrum shows no or minimal interference with particle spectra, depending on the laser wavelength. Furthermore, automatic particle detection can be applied when analysing the filter surface under dark-field illumination. With this new membrane filter, analytics free of interference of microplastics down to a size of 1 μm becomes possible. Thus, an important size class of these contaminants can now be visualized and spectrally identified. Graphical abstract A newly developed aluminium coated polycarbonate membrane filter enables automatic particle detection and generation of high qualitative Raman spectra allowing identification of small microplastics.

46 CFR 171.118 - Automatic ventilators and side ports.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 7 2011-10-01 2011-10-01 false Automatic ventilators and side ports. 171.118 Section... SPECIAL RULES PERTAINING TO VESSELS CARRYING PASSENGERS Openings in the Side of a Vessel Below the Bulkhead or Weather Deck § 171.118 Automatic ventilators and side ports. (a) An automatic ventilator must...

46 CFR 171.118 - Automatic ventilators and side ports.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 7 2010-10-01 2010-10-01 false Automatic ventilators and side ports. 171.118 Section... SPECIAL RULES PERTAINING TO VESSELS CARRYING PASSENGERS Openings in the Side of a Vessel Below the Bulkhead or Weather Deck § 171.118 Automatic ventilators and side ports. (a) An automatic ventilator must...

46 CFR 171.118 - Automatic ventilators and side ports.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 7 2014-10-01 2014-10-01 false Automatic ventilators and side ports. 171.118 Section... SPECIAL RULES PERTAINING TO VESSELS CARRYING PASSENGERS Openings in the Side of a Vessel Below the Bulkhead or Weather Deck § 171.118 Automatic ventilators and side ports. (a) An automatic ventilator must...

46 CFR 171.118 - Automatic ventilators and side ports.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 7 2012-10-01 2012-10-01 false Automatic ventilators and side ports. 171.118 Section... SPECIAL RULES PERTAINING TO VESSELS CARRYING PASSENGERS Openings in the Side of a Vessel Below the Bulkhead or Weather Deck § 171.118 Automatic ventilators and side ports. (a) An automatic ventilator must...

46 CFR 171.118 - Automatic ventilators and side ports.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 7 2013-10-01 2013-10-01 false Automatic ventilators and side ports. 171.118 Section... SPECIAL RULES PERTAINING TO VESSELS CARRYING PASSENGERS Openings in the Side of a Vessel Below the Bulkhead or Weather Deck § 171.118 Automatic ventilators and side ports. (a) An automatic ventilator must...

Presentation video retrieval using automatically recovered slide and spoken text

NASA Astrophysics Data System (ADS)

Cooper, Matthew

2013-03-01

Video is becoming a prevalent medium for e-learning. Lecture videos contain text information in both the presentation slides and lecturer's speech. This paper examines the relative utility of automatically recovered text from these sources for lecture video retrieval. To extract the visual information, we automatically detect slides within the videos and apply optical character recognition to obtain their text. Automatic speech recognition is used similarly to extract spoken text from the recorded audio. We perform controlled experiments with manually created ground truth for both the slide and spoken text from more than 60 hours of lecture video. We compare the automatically extracted slide and spoken text in terms of accuracy relative to ground truth, overlap with one another, and utility for video retrieval. Results reveal that automatically recovered slide text and spoken text contain different content with varying error profiles. Experiments demonstrate that automatically extracted slide text enables higher precision video retrieval than automatically recovered spoken text.

Automatic identification of variables in epidemiological datasets using logic regression.

PubMed

Lorenz, Matthias W; Abdi, Negin Ashtiani; Scheckenbach, Frank; Pflug, Anja; Bülbül, Alpaslan; Catapano, Alberico L; Agewall, Stefan; Ezhov, Marat; Bots, Michiel L; Kiechl, Stefan; Orth, Andreas

2017-04-13

For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

10 CFR 1045.38 - Automatic declassification prohibition.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Automatic declassification prohibition. (a) Documents containing RD and FRD remain classified until a... Energy Act, no date or event for automatic declassification ever applies to RD and FRD documents, even if such documents also contain NSI. (c) E.O. 12958 acknowledges that RD and FRD are exempt from all...

10 CFR 1045.38 - Automatic declassification prohibition.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Automatic declassification prohibition. (a) Documents containing RD and FRD remain classified until a... Energy Act, no date or event for automatic declassification ever applies to RD and FRD documents, even if such documents also contain NSI. (c) E.O. 12958 acknowledges that RD and FRD are exempt from all...

10 CFR 1045.38 - Automatic declassification prohibition.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Automatic declassification prohibition. (a) Documents containing RD and FRD remain classified until a... Energy Act, no date or event for automatic declassification ever applies to RD and FRD documents, even if such documents also contain NSI. (c) E.O. 12958 acknowledges that RD and FRD are exempt from all...

10 CFR 1045.38 - Automatic declassification prohibition.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Automatic declassification prohibition. (a) Documents containing RD and FRD remain classified until a... Energy Act, no date or event for automatic declassification ever applies to RD and FRD documents, even if such documents also contain NSI. (c) E.O. 12958 acknowledges that RD and FRD are exempt from all...

10 CFR 1045.38 - Automatic declassification prohibition.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Automatic declassification prohibition. (a) Documents containing RD and FRD remain classified until a... Energy Act, no date or event for automatic declassification ever applies to RD and FRD documents, even if such documents also contain NSI. (c) E.O. 12958 acknowledges that RD and FRD are exempt from all...

46 CFR 58.25-30 - Automatic restart.

Code of Federal Regulations, 2014 CFR

2014-10-01

... auxiliary steering gear and each power actuating system must restart automatically when electrical power is... 46 Shipping 2 2014-10-01 2014-10-01 false Automatic restart. 58.25-30 Section 58.25-30 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING MAIN AND AUXILIARY MACHINERY...

46 CFR 58.25-30 - Automatic restart.

Code of Federal Regulations, 2013 CFR

2013-10-01

... auxiliary steering gear and each power actuating system must restart automatically when electrical power is... 46 Shipping 2 2013-10-01 2013-10-01 false Automatic restart. 58.25-30 Section 58.25-30 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING MAIN AND AUXILIARY MACHINERY...

46 CFR 58.25-30 - Automatic restart.

Code of Federal Regulations, 2012 CFR

2012-10-01

... auxiliary steering gear and each power actuating system must restart automatically when electrical power is... 46 Shipping 2 2012-10-01 2012-10-01 false Automatic restart. 58.25-30 Section 58.25-30 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING MAIN AND AUXILIARY MACHINERY...

46 CFR 58.25-30 - Automatic restart.

Code of Federal Regulations, 2011 CFR

2011-10-01

... auxiliary steering gear and each power actuating system must restart automatically when electrical power is... 46 Shipping 2 2011-10-01 2011-10-01 false Automatic restart. 58.25-30 Section 58.25-30 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING MAIN AND AUXILIARY MACHINERY...

46 CFR 58.25-30 - Automatic restart.

Code of Federal Regulations, 2010 CFR

2010-10-01

... auxiliary steering gear and each power actuating system must restart automatically when electrical power is... 46 Shipping 2 2010-10-01 2010-10-01 false Automatic restart. 58.25-30 Section 58.25-30 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING MAIN AND AUXILIARY MACHINERY...

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2010 CFR

2010-07-01

... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.23... function automatically at a methane content of the mine atmosphere between 1.0 to 1.5 volume percent and at all higher concentrations of methane. (c) It is recommended that the automatic warning device be...

Automatic Item Generation of Probability Word Problems

ERIC Educational Resources Information Center

Holling, Heinz; Bertling, Jonas P.; Zeuch, Nina

2009-01-01

Mathematical word problems represent a common item format for assessing student competencies. Automatic item generation (AIG) is an effective way of constructing many items with predictable difficulties, based on a set of predefined task parameters. The current study presents a framework for the automatic generation of probability word problems…

Enhancing Automaticity through Task-Based Language Learning

ERIC Educational Resources Information Center

De Ridder, Isabelle; Vangehuchten, Lieve; Gomez, Marta Sesena

2007-01-01

In general terms automaticity could be defined as the subconscious condition wherein "we perform a complex series of tasks very quickly and efficiently, without having to think about the various components and subcomponents of action involved" (DeKeyser 2001: 125). For language learning, Segalowitz (2003) characterised automaticity as a…

Crystal identification for a dual-layer-offset LYSO based PET system via Lu-176 background radiation and mean shift algorithm

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Ma, Tianyu; Xu, Tianpeng; Zeng, Ming; Gu, Yu; Dai, Tiantian; Liu, Yaqiang

2018-01-01

Modern positron emission tomography (PET) detectors are made from pixelated scintillation crystal arrays and readout by Anger logic. The interaction position of the gamma-ray should be assigned to a crystal using a crystal position map or look-up table. Crystal identification is a critical procedure for pixelated PET systems. In this paper, we propose a novel crystal identification method for a dual-layer-offset LYSO based animal PET system via Lu-176 background radiation and mean shift algorithm. Single photon event data of the Lu-176 background radiation are acquired in list-mode for 3 h to generate a single photon flood map (SPFM). Coincidence events are obtained from the same data using time information to generate a coincidence flood map (CFM). The CFM is used to identify the peaks of the inner layer using the mean shift algorithm. The response of the inner layer is deducted from the SPFM by subtracting CFM. Then, the peaks of the outer layer are also identified using the mean shift algorithm. The automatically identified peaks are manually inspected by a graphical user interface program. Finally, a crystal position map is generated using a distance criterion based on these peaks. The proposed method is verified on the animal PET system with 48 detector blocks on a laptop with an Intel i7-5500U processor. The total runtime for whole system peak identification is 67.9 s. Results show that the automatic crystal identification has 99.98% and 99.09% accuracy for the peaks of the inner and outer layers of the whole system respectively. In conclusion, the proposed method is suitable for the dual-layer-offset lutetium based PET system to perform crystal identification instead of external radiation sources.

49 CFR 236.504 - Operation interconnected with automatic block-signal system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Operation interconnected with automatic block... Operation interconnected with automatic block-signal system. (a) A continuous inductive automatic train stop or train control system shall operate in connection with an automatic block signal system and shall...

An automatic brain tumor segmentation tool.

PubMed

Diaz, Idanis; Boulanger, Pierre; Greiner, Russell; Hoehn, Bret; Rowe, Lindsay; Murtha, Albert

2013-01-01

This paper introduces an automatic brain tumor segmentation method (ABTS) for segmenting multiple components of brain tumor using four magnetic resonance image modalities. ABTS's four stages involve automatic histogram multi-thresholding and morphological operations including geodesic dilation. Our empirical results, on 16 real tumors, show that ABTS works very effectively, achieving a Dice accuracy compared to expert segmentation of 81% in segmenting edema and 85% in segmenting gross tumor volume (GTV).

Chemical etching for automatic processing of integrated circuits

NASA Technical Reports Server (NTRS)

Kennedy, B. W.

1981-01-01

Chemical etching for automatic processing of integrated circuits is discussed. The wafer carrier and loading from a receiving air track into automatic furnaces and unloading onto a sending air track are included.

30 CFR 75.1403-4 - Criteria-Automatic elevators.

Code of Federal Regulations, 2010 CFR

2010-07-01

... appropriate on automatic elevators which will automatically shut-off the power and apply the brakes in the... telephone or other effective communication system by which aid or assistance can be obtained promptly. ...

Automated Microbiological Detection/Identification System

PubMed Central

Aldridge, C.; Jones, P. W.; Gibson, S.; Lanham, J.; Meyer, M.; Vannest, R.; Charles, R.

1977-01-01

An automated, computerized system, the AutoMicrobic System, has been developed for the detection, enumeration, and identification of bacteria and yeasts in clinical specimens. The biological basis for the system resides in lyophilized, highly selective and specific media enclosed in wells of a disposable plastic cuvette; introduction of a suitable specimen rehydrates and inoculates the media in the wells. An automated optical system monitors, and the computer interprets, changes in the media, with enumeration and identification results automatically obtained in 13 h. Sixteen different selective media were developed and tested with a variety of seeded (simulated) and clinical specimens. The AutoMicrobic System has been extensively tested with urine specimens, using a urine test kit (Identi-Pak) that contains selective media for Escherichia coli, Proteus species, Pseudomonas aeruginosa, Klebsiella-Enterobacter species, Serratia species, Citrobacter freundii, group D enterococci, Staphylococcus aureus, and yeasts (Candida species and Torulopsis glabrata). The system has been tested with 3,370 seeded urine specimens and 1,486 clinical urines. Agreement with simultaneous conventional (manual) cultures, at levels of 70,000 colony-forming units per ml (or more), was 92% or better for seeded specimens; clinical specimens yielded results of 93% or better for all organisms except P. aeruginosa, where agreement was 86%. System expansion in progress includes antibiotic susceptibility testing and compatibility with most types of clinical specimens. Images PMID:334798

Yuma proving grounds automatic UXO detection using biomorphic robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tilden, M.W.

1996-07-01

The current variety and dispersion of Unexploded Ordnance (UXO) is a daunting technological problem for current sensory and extraction techniques. The bottom line is that the only way to insure a live UXO has been found and removed is to step on it. As this is an upsetting proposition for biological organisms like animals, farmers, or Yuma field personnel, this paper details a non-biological approach to developing inexpensive, automatic machines that will find, tag, and may eventually remove UXO from a variety of terrains by several proposed methods. The Yuma proving grounds (Arizona) has been pelted with bombs, mines, missiles,more » and shells since the 1940s. The idea of automatic machines that can clean up after such testing is an old one but as yet unrealized because of the daunting cost, power and complexity requirements of capable robot mechanisms. A researcher at Los Alamos National Laboratory has invented and developed a new variety of living robots that are solar powered, legged, autonomous, adaptive to massive damage, and very inexpensive. This technology, called Nervous Networks (Nv), allows for the creation of capable walking mechanisms (known as Biomorphic robots, or Biomechs for short) that rather than work from task principles use instead a survival-based design philosophy. This allows Nv based machines to continue doing work even after multiple limbs and sensors have been removed or damaged, and to dynamically negotiate complex terrains as an emergent property of their operation (fighting to proceed, as it were). They are not programmed, and indeed, the twelve transistor Nv controller keeps their electronic cost well below that of most pocket radios. It is suspected that advanced forms of these machines in huge numbers may be an interesting, capable solution to the problem of general and specific UXO identification, tagging, and removal.« less

Automatic identification of the number of food items in a meal using clustering techniques based on the monitoring of swallowing and chewing.

PubMed

Lopez-Meyer, Paulo; Schuckers, Stephanie; Makeyev, Oleksandr; Fontana, Juan M; Sazonov, Edward

2012-09-01

The number of distinct foods consumed in a meal is of significant clinical concern in the study of obesity and other eating disorders. This paper proposes the use of information contained in chewing and swallowing sequences for meal segmentation by food types. Data collected from experiments of 17 volunteers were analyzed using two different clustering techniques. First, an unsupervised clustering technique, Affinity Propagation (AP), was used to automatically identify the number of segments within a meal. Second, performance of the unsupervised AP method was compared to a supervised learning approach based on Agglomerative Hierarchical Clustering (AHC). While the AP method was able to obtain 90% accuracy in predicting the number of food items, the AHC achieved an accuracy >95%. Experimental results suggest that the proposed models of automatic meal segmentation may be utilized as part of an integral application for objective Monitoring of Ingestive Behavior in free living conditions.

Identification of the heart wall and chamber based on temporal change of ultrasonic scatterer distribution

NASA Astrophysics Data System (ADS)

Takahashi, Kohei; Taki, Hirofumi; Kanai, Hiroshi

2017-07-01

In most current methods for evaluating the cardiac function by ultrasound, the heart wall area is identified manually by an examiner. To eliminate examiner dependence and to improve usability, an automatic heart wall identification method is desirable. Identification based on only echogenicity often fails because of low echogenicity of some areas of the heart wall. In the present study, to determine more essential features, we focused on the relative temporal change of ultrasonic scatterer distribution and proposed three features for identification of the heart wall and the chamber: cross-correlation of RF signals, that of envelopes, and spatial dispersion of movement vectors in small regions. In an in vivo experiment, using echogenicity and the three features, we identified the heart wall and the chamber in the left ventricular long-axis view, resulting in criteria of separability J of 1.69, 1.40, and 3.02 using these features compared with the result of 0.979 using echogenicity.

Automatic Operation For A Robot Lawn Mower

NASA Astrophysics Data System (ADS)

Huang, Y. Y.; Cao, Z. L.; Oh, S. J.; Kattan, E. U.; Hall, E. L.

1987-02-01

A domestic mobile robot, lawn mower, which performs the automatic operation mode, has been built up in the Center of Robotics Research, University of Cincinnati. The robot lawn mower automatically completes its work with the region filling operation, a new kind of path planning for mobile robots. Some strategies for region filling of path planning have been developed for a partly-known or a unknown environment. Also, an advanced omnidirectional navigation system and a multisensor-based control system are used in the automatic operation. Research on the robot lawn mower, especially on the region filling of path planning, is significant in industrial and agricultural applications.

Exposure to violent video games increases automatic aggressiveness.

PubMed

Uhlmann, Eric; Swanson, Jane

2004-02-01

The effects of exposure to violent video games on automatic associations with the self were investigated in a sample of 121 students. Playing the violent video game Doom led participants to associate themselves with aggressive traits and actions on the Implicit Association Test. In addition, self-reported prior exposure to violent video games predicted automatic aggressive self-concept, above and beyond self-reported aggression. Results suggest that playing violent video games can lead to the automatic learning of aggressive self-views.

What is automatized during perceptual categorization?

PubMed Central

Roeder, Jessica L.; Ashby, F. Gregory

2016-01-01

An experiment is described that tested whether stimulus-response associations or an abstract rule are automatized during extensive practice at perceptual categorization. Twenty-seven participants each completed 12,300 trials of perceptual categorization, either on rule-based (RB) categories that could be learned explicitly or information-integration (II) categories that required procedural learning. Each participant practiced predominantly on a primary category structure, but every third session they switched to a secondary structure that used the same stimuli and responses. Half the stimuli retained their same response on the primary and secondary categories (the congruent stimuli) and half switched responses (the incongruent stimuli). Several results stood out. First, performance on the primary categories met the standard criteria of automaticity by the end of training. Second, for the primary categories in the RB condition, accuracy and response time (RT) were identical on congruent and incongruent stimuli. In contrast, for the primary II categories, accuracy was higher and RT was lower for congruent than for incongruent stimuli. These results are consistent with the hypothesis that rules are automatized in RB tasks, whereas stimulus-response associations are automatized in II tasks. A cognitive neuroscience theory is proposed that accounts for these results. PMID:27232521

Automatic attention to emotional stimuli: neural correlates.

PubMed

Carretié, Luis; Hinojosa, José A; Martín-Loeches, Manuel; Mercado, Francisco; Tapia, Manuel

2004-08-01

We investigated the capability of emotional and nonemotional visual stimulation to capture automatic attention, an aspect of the interaction between cognitive and emotional processes that has received scant attention from researchers. Event-related potentials were recorded from 37 subjects using a 60-electrode array, and were submitted to temporal and spatial principal component analyses to detect and quantify the main components, and to source localization software (LORETA) to determine their spatial origin. Stimuli capturing automatic attention were of three types: emotionally positive, emotionally negative, and nonemotional pictures. Results suggest that initially (P1: 105 msec after stimulus), automatic attention is captured by negative pictures, and not by positive or nonemotional ones. Later (P2: 180 msec), automatic attention remains captured by negative pictures, but also by positive ones. Finally (N2: 240 msec), attention is captured only by positive and nonemotional stimuli. Anatomically, this sequence is characterized by decreasing activation of the visual association cortex (VAC) and by the growing involvement, from dorsal to ventral areas, of the anterior cingulate cortex (ACC). Analyses suggest that the ACC and not the VAC is responsible for experimental effects described above. Intensity, latency, and location of neural activity related to automatic attention thus depend clearly on the stimulus emotional content and on its associated biological importance. Copyright 2004 Wiley-Liss, Inc.

Effectiveness of sequential automatic-manual home respiratory polygraphy scoring.

PubMed

Masa, Juan F; Corral, Jaime; Pereira, Ricardo; Duran-Cantolla, Joaquin; Cabello, Marta; Hernández-Blasco, Luis; Monasterio, Carmen; Alonso-Fernandez, Alberto; Chiner, Eusebi; Vázquez-Polo, Francisco-José; Montserrat, Jose M

2013-04-01

Automatic home respiratory polygraphy (HRP) scoring functions can potentially confirm the diagnosis of sleep apnoea-hypopnoea syndrome (SAHS) (obviating technician scoring) in a substantial number of patients. The result would have important management and cost implications. The aim of this study was to determine the diagnostic cost-effectiveness of a sequential HRP scoring protocol (automatic and then manual for residual cases) compared with manual HRP scoring, and with in-hospital polysomnography. We included suspected SAHS patients in a multicentre study and assigned them to home and hospital protocols at random. We constructed receiver operating characteristic (ROC) curves for manual and automatic scoring. Diagnostic agreement for several cut-off points was explored and costs for two equally effective alternatives were calculated. Of 366 randomised patients, 348 completed the protocol. Manual scoring produced better ROC curves than automatic scoring. There was no sensitive automatic or subsequent manual HRP apnoea-hypopnoea index (AHI) cut-off point. The specific cut-off points for automatic and subsequent manual HRP scorings (AHI >25 and >20, respectively) had a specificity of 93% for automatic and 94% for manual scorings. The costs of manual protocol were 9% higher than sequential HRP protocol; these were 69% and 64%, respectively, of the cost of the polysomnography. A sequential HRP scoring protocol is a cost-effective alternative to polysomnography, although with limited cost savings compared to HRP manual scoring.

Automatic cell identification and visualization using digital holographic microscopy with head mounted augmented reality devices.

PubMed

O'Connor, Timothy; Rawat, Siddharth; Markman, Adam; Javidi, Bahram

2018-03-01

We propose a compact imaging system that integrates an augmented reality head mounted device with digital holographic microscopy for automated cell identification and visualization. A shearing interferometer is used to produce holograms of biological cells, which are recorded using customized smart glasses containing an external camera. After image acquisition, segmentation is performed to isolate regions of interest containing biological cells in the field-of-view, followed by digital reconstruction of the cells, which is used to generate a three-dimensional (3D) pseudocolor optical path length profile. Morphological features are extracted from the cell's optical path length map, including mean optical path length, coefficient of variation, optical volume, projected area, projected area to optical volume ratio, cell skewness, and cell kurtosis. Classification is performed using the random forest classifier, support vector machines, and K-nearest neighbor, and the results are compared. Finally, the augmented reality device displays the cell's pseudocolor 3D rendering of its optical path length profile, extracted features, and the identified cell's type or class. The proposed system could allow a healthcare worker to quickly visualize cells using augmented reality smart glasses and extract the relevant information for rapid diagnosis. To the best of our knowledge, this is the first report on the integration of digital holographic microscopy with augmented reality devices for automated cell identification and visualization.

Automatic welding of stainless steel tubing

NASA Technical Reports Server (NTRS)

Clautice, W. E.

1978-01-01

The use of automatic welding for making girth welds in stainless steel tubing was investigated as well as the reduction in fabrication costs resulting from the elimination of radiographic inspection. Test methodology, materials, and techniques are discussed, and data sheets for individual tests are included. Process variables studied include welding amperes, revolutions per minute, and shielding gas flow. Strip chart recordings, as a definitive method of insuring weld quality, are studied. Test results, determined by both radiographic and visual inspection, are presented and indicate that once optimum welding procedures for specific sizes of tubing are established, and the welding machine operations are certified, then the automatic tube welding process produces good quality welds repeatedly, with a high degree of reliability. Revised specifications for welding tubing using the automatic process and weld visual inspection requirements at the Kennedy Space Center are enumerated.

Automatic morphological classification of galaxy images

PubMed Central

Shamir, Lior

2009-01-01

We describe an image analysis supervised learning algorithm that can automatically classify galaxy images. The algorithm is first trained using a manually classified images of elliptical, spiral, and edge-on galaxies. A large set of image features is extracted from each image, and the most informative features are selected using Fisher scores. Test images can then be classified using a simple Weighted Nearest Neighbor rule such that the Fisher scores are used as the feature weights. Experimental results show that galaxy images from Galaxy Zoo can be classified automatically to spiral, elliptical and edge-on galaxies with accuracy of ~90% compared to classifications carried out by the author. Full compilable source code of the algorithm is available for free download, and its general-purpose nature makes it suitable for other uses that involve automatic image analysis of celestial objects. PMID:20161594

Automatic recognition of coronal type II radio bursts: The ARBIS 2 method and first observations

NASA Astrophysics Data System (ADS)

Lobzin, Vasili; Cairns, Iver; Robinson, Peter; Steward, Graham; Patterson, Garth

Major space weather events such as solar flares and coronal mass ejections are usually accompa-nied by solar radio bursts, which can potentially be used for real-time space weather forecasts. Type II radio bursts are produced near the local plasma frequency and its harmonic by fast electrons accelerated by a shock wave moving through the corona and solar wind with a typi-cal speed of 1000 km s-1 . The coronal bursts have dynamic spectra with frequency gradually falling with time and durations of several minutes. We present a new method developed to de-tect type II coronal radio bursts automatically and describe its implementation in an extended Automated Radio Burst Identification System (ARBIS 2). Preliminary tests of the method with spectra obtained in 2002 show that the performance of the current implementation is quite high, ˜ 80%, while the probability of false positives is reasonably low, with one false positive per 100-200 hr for high solar activity and less than one false event per 10000 hr for low solar activity periods. The first automatically detected coronal type II radio bursts are also presented. ARBIS 2 is now operational with IPS Radio and Space Services, providing email alerts and event lists internationally.

Automatic Grading of Spreadsheet and Database Skills

ERIC Educational Resources Information Center

Kovacic, Zlatko J.; Green, John Steven

2012-01-01

Growing enrollment in distance education has increased student-to-lecturer ratios and, therefore, increased the workload of the lecturer. This growing enrollment has resulted in mounting efforts to develop automatic grading systems in an effort to reduce this workload. While research in the design and development of automatic grading systems has a…

Identification and on-line monitoring of reduced sulphur species (RSS) by voltammetry in oxic waters.

PubMed

Superville, Pierre-Jean; Pižeta, Ivanka; Omanović, Dario; Billon, Gabriel

2013-08-15

Based on automatic on-line measurements on the Deûle River that showed daily variation of a peak around -0.56V (vs Ag|AgCl 3M), identification of Reduced Sulphur Species (RSS) in oxic waters was performed applying cathodic stripping voltammetry (CSV) with the hanging mercury drop electrode (HMDE). Pseudopolarographic studies accompanied with increasing concentrations of copper revealed the presence of elemental sulphur S(0), thioacetamide (TA) and reduced glutathione (GSH) as the main sulphur compounds in the Deûle River. In order to resolve these three species, a simple procedure was developed and integrated in an automatic on-line monitoring system. During one week monitoring with hourly measurements, GSH and S(0) exhibited daily cycles whereas no consequential pattern was observed for TA. Copyright © 2013 Elsevier B.V. All rights reserved.

Automatic Control of Silicon Melt Level

NASA Technical Reports Server (NTRS)

Duncan, C. S.; Stickel, W. B.

1982-01-01

A new circuit, when combined with melt-replenishment system and melt level sensor, offers continuous closed-loop automatic control of melt-level during web growth. Installed on silicon-web furnace, circuit controls melt-level to within 0.1 mm for as long as 8 hours. Circuit affords greater area growth rate and higher web quality, automatic melt-level control also allows semiautomatic growth of web over long periods which can greatly reduce costs.

Support for Debugging Automatically Parallelized Programs

NASA Technical Reports Server (NTRS)

Hood, Robert; Jost, Gabriele; Biegel, Bryan (Technical Monitor)

2001-01-01

This viewgraph presentation provides information on the technical aspects of debugging computer code that has been automatically converted for use in a parallel computing system. Shared memory parallelization and distributed memory parallelization entail separate and distinct challenges for a debugging program. A prototype system has been developed which integrates various tools for the debugging of automatically parallelized programs including the CAPTools Database which provides variable definition information across subroutines as well as array distribution information.

33 CFR 164.03 - Incorporation by reference.

Code of Federal Regulations, 2014 CFR

2014-07-01

... radiocommunication equipment and systems—Automatic identification systems (AIS)—part 2: Class A shipborne equipment of the universal automatic identification system (AIS)—Operational and performance requirements..., Recommendation on Performance Standards for a Universal Shipborne Automatic Identification System (AIS), adopted...

33 CFR 164.03 - Incorporation by reference.

Code of Federal Regulations, 2012 CFR

2012-07-01

... radiocommunication equipment and systems—Automatic identification systems (AIS)—part 2: Class A shipborne equipment of the universal automatic identification system (AIS)—Operational and performance requirements..., Recommendation on Performance Standards for a Universal Shipborne Automatic Identification System (AIS), adopted...

33 CFR 164.03 - Incorporation by reference.

Code of Federal Regulations, 2013 CFR

2013-07-01

... radiocommunication equipment and systems—Automatic identification systems (AIS)—part 2: Class A shipborne equipment of the universal automatic identification system (AIS)—Operational and performance requirements..., Recommendation on Performance Standards for a Universal Shipborne Automatic Identification System (AIS), adopted...

Automatic Payroll Deposit System.

ERIC Educational Resources Information Center

Davidson, D. B.

1979-01-01

The Automatic Payroll Deposit System in Yakima, Washington's Public School District No. 7, directly transmits each employee's salary amount for each pay period to a bank or other financial institution. (Author/MLF)

FAMA: Fast Automatic MOOG Analysis

NASA Astrophysics Data System (ADS)

Magrini, Laura; Randich, Sofia; Friel, Eileen; Spina, Lorenzo; Jacobson, Heather; Cantat-Gaudin, Tristan; Donati, Paolo; Baglioni, Roberto; Maiorca, Enrico; Bragaglia, Angela; Sordo, Rosanna; Vallenari, Antonella

2014-02-01

FAMA (Fast Automatic MOOG Analysis), written in Perl, computes the atmospheric parameters and abundances of a large number of stars using measurements of equivalent widths (EWs) automatically and independently of any subjective approach. Based on the widely-used MOOG code, it simultaneously searches for three equilibria, excitation equilibrium, ionization balance, and the relationship between logn(FeI) and the reduced EWs. FAMA also evaluates the statistical errors on individual element abundances and errors due to the uncertainties in the stellar parameters. Convergence criteria are not fixed "a priori" but instead are based on the quality of the spectra.

Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning.

PubMed

Norouzzadeh, Mohammad Sadegh; Nguyen, Anh; Kosmala, Margaret; Swanson, Alexandra; Palmer, Meredith S; Packer, Craig; Clune, Jeff

2018-06-19

Having accurate, detailed, and up-to-date information about the location and behavior of animals in the wild would improve our ability to study and conserve ecosystems. We investigate the ability to automatically, accurately, and inexpensively collect such data, which could help catalyze the transformation of many fields of ecology, wildlife biology, zoology, conservation biology, and animal behavior into "big data" sciences. Motion-sensor "camera traps" enable collecting wildlife pictures inexpensively, unobtrusively, and frequently. However, extracting information from these pictures remains an expensive, time-consuming, manual task. We demonstrate that such information can be automatically extracted by deep learning, a cutting-edge type of artificial intelligence. We train deep convolutional neural networks to identify, count, and describe the behaviors of 48 species in the 3.2 million-image Snapshot Serengeti dataset. Our deep neural networks automatically identify animals with >93.8% accuracy, and we expect that number to improve rapidly in years to come. More importantly, if our system classifies only images it is confident about, our system can automate animal identification for 99.3% of the data while still performing at the same 96.6% accuracy as that of crowdsourced teams of human volunteers, saving >8.4 y (i.e., >17,000 h at 40 h/wk) of human labeling effort on this 3.2 million-image dataset. Those efficiency gains highlight the importance of using deep neural networks to automate data extraction from camera-trap images, reducing a roadblock for this widely used technology. Our results suggest that deep learning could enable the inexpensive, unobtrusive, high-volume, and even real-time collection of a wealth of information about vast numbers of animals in the wild. Copyright © 2018 the Author(s). Published by PNAS.

Using RFID Positioning Technology to Construct an Automatic Rehabilitation Scheduling Mechanism.

PubMed

Wang, Ching-Sheng; Hung, Lun-Ping; Yen, Neil Y

2016-01-01

Accurately and efficiently identifying the location of patients during the course of rehabilitation is an important issue. Wireless transmission technology can reach this goal. Tracking technologies such as RFID (Radio frequency identification) can support process improvement and improve efficiencies of rehabilitation. There are few published models or methods to solve the problem of positioning and apply this technology in the rehabilitation center. We propose a mechanism to enhance the accuracy of positioning technology and provide information about turns and obstacles on the path; and user-centered services based on location-aware to enhanced quality care in rehabilitation environment. This paper outlines the requirements and the role of RFID in assisting rehabilitation environment. A prototype RFID hospital support tool is established. It is designed to provide assistance for monitoring rehabilitation patients. It can simultaneously calculate the rehabilitant's location and the duration of treatment, and automatically record the rehabilitation course of the rehabilitant, so as to improve the management efficiency of the rehabilitation program.

A PC-based computer package for automatic detection and location of earthquakes: Application to a seismic network in eastern sicity (Italy)

NASA Astrophysics Data System (ADS)

Patanè, Domenico; Ferrari, Ferruccio; Giampiccolo, Elisabetta; Gresta, Stefano

Few automated data acquisition and processing systems operate on mainframes, some run on UNIX-based workstations and others on personal computers, equipped with either DOS/WINDOWS or UNIX-derived operating systems. Several large and complex software packages for automatic and interactive analysis of seismic data have been developed in recent years (mainly for UNIX-based systems). Some of these programs use a variety of artificial intelligence techniques. The first operational version of a new software package, named PC-Seism, for analyzing seismic data from a local network is presented in Patanè et al. (1999). This package, composed of three separate modules, provides an example of a new generation of visual object-oriented programs for interactive and automatic seismic data-processing running on a personal computer. In this work, we mainly discuss the automatic procedures implemented in the ASDP (Automatic Seismic Data-Processing) module and real time application to data acquired by a seismic network running in eastern Sicily. This software uses a multi-algorithm approach and a new procedure MSA (multi-station-analysis) for signal detection, phase grouping and event identification and location. It is designed for an efficient and accurate processing of local earthquake records provided by single-site and array stations. Results from ASDP processing of two different data sets recorded at Mt. Etna volcano by a regional network are analyzed to evaluate its performance. By comparing the ASDP pickings with those revised manually, the detection and subsequently the location capabilities of this software are assessed. The first data set is composed of 330 local earthquakes recorded in the Mt. Etna erea during 1997 by the telemetry analog seismic network. The second data set comprises about 970 automatic locations of more than 2600 local events recorded at Mt. Etna during the last eruption (July 2001) at the present network. For the former data set, a comparison of the

The algorithm for automatic detection of the calibration object

NASA Astrophysics Data System (ADS)

Artem, Kruglov; Irina, Ugfeld

2017-06-01

The problem of the automatic image calibration is considered in this paper. The most challenging task of the automatic calibration is a proper detection of the calibration object. The solving of this problem required the appliance of the methods and algorithms of the digital image processing, such as morphology, filtering, edge detection, shape approximation. The step-by-step process of the development of the algorithm and its adopting to the specific conditions of the log cuts in the image's background is presented. Testing of the automatic calibration module was carrying out under the conditions of the production process of the logging enterprise. Through the tests the average possibility of the automatic isolating of the calibration object is 86.1% in the absence of the type 1 errors. The algorithm was implemented in the automatic calibration module within the mobile software for the log deck volume measurement.

Automatic spatiotemporal matching of detected pleural thickenings

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

Methods for automatically analyzing humpback song units.

PubMed

Rickwood, Peter; Taylor, Andrew

2008-03-01

This paper presents mathematical techniques for automatically extracting and analyzing bioacoustic signals. Automatic techniques are described for isolation of target signals from background noise, extraction of features from target signals and unsupervised classification (clustering) of the target signals based on these features. The only user-provided inputs, other than raw sound, is an initial set of signal processing and control parameters. Of particular note is that the number of signal categories is determined automatically. The techniques, applied to hydrophone recordings of humpback whales (Megaptera novaeangliae), produce promising initial results, suggesting that they may be of use in automated analysis of not only humpbacks, but possibly also in other bioacoustic settings where automated analysis is desirable.

Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

NASA Astrophysics Data System (ADS)

Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

2016-04-01

Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

Hypertensive retinopathy identification through retinal fundus image using backpropagation neural network

NASA Astrophysics Data System (ADS)

Syahputra, M. F.; Amalia, C.; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Nurdin; Andayani, U.

2018-03-01

Hypertension or high blood pressure can cause damage of blood vessels in the retina of eye called hypertensive retinopathy (HR). In the event Hypertension, it will cause swelling blood vessels and a decrese in retina performance. To detect HR in patients body, it is usually performed through physical examination of opthalmoscope which is still conducted manually by an ophthalmologist. Certainly, in such a manual manner, takes a ong time for a doctor to detetct HR on aa patient based on retina fundus iamge. To overcome ths problem, a method is needed to identify the image of retinal fundus automatically. In this research, backpropagation neural network was used as a method for retinal fundus identification. The steps performed prior to identification were pre-processing (green channel, contrast limited adapative histogram qualization (CLAHE), morphological close, background exclusion, thresholding and connected component analysis), feature extraction using zoning. The results show that the proposed method is able to identify retinal fundus with an accuracy of 95% with maximum epoch of 1500.

Automatization of hardware configuration for plasma diagnostic system

NASA Astrophysics Data System (ADS)

Wojenski, A.; Pozniak, K. T.; Kasprowicz, G.; Kolasinski, P.; Krawczyk, R. D.; Zabolotny, W.; Linczuk, P.; Chernyshova, M.; Czarski, T.; Malinowski, K.

2016-09-01

Soft X-ray plasma measurement systems are mostly multi-channel, high performance systems. In case of the modular construction it is necessary to perform sophisticated system discovery in parallel with automatic system configuration. In the paper the structure of the modular system designed for tokamak plasma soft X-ray measurements is described. The concept of the system discovery and further automatic configuration is also presented. FCS application (FMC/ FPGA Configuration Software) is used for running sophisticated system setup with automatic verification of proper configuration. In order to provide flexibility of further system configurations (e.g. user setup), common communication interface is also described. The approach presented here is related to the automatic system firmware building presented in previous papers. Modular construction and multichannel measurements are key requirement in term of SXR diagnostics with use of GEM detectors.

Approach for the Development of a Framework for the Identification of Activities of Daily Living Using Sensors in Mobile Devices.

PubMed

Pires, Ivan Miguel; Garcia, Nuno M; Pombo, Nuno; Flórez-Revuelta, Francisco; Spinsante, Susanna

2018-02-21

Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking into account several concepts, including data acquisition, data processing, data fusion, and pattern recognition. These concepts can be mapped onto different modules of the framework. The proposed framework should perform the identification of ADL without Internet connection, performing these tasks locally on the mobile device, taking in account the hardware and software limitations of these devices. The main purpose of this paper is to present a new approach for the creation of a framework for the recognition of ADL, analyzing the allowed sensors available in the mobile devices, and the existing methods available in the literature.

Approach for the Development of a Framework for the Identification of Activities of Daily Living Using Sensors in Mobile Devices

PubMed Central

Pombo, Nuno

2018-01-01

Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking into account several concepts, including data acquisition, data processing, data fusion, and pattern recognition. These concepts can be mapped onto different modules of the framework. The proposed framework should perform the identification of ADL without Internet connection, performing these tasks locally on the mobile device, taking in account the hardware and software limitations of these devices. The main purpose of this paper is to present a new approach for the creation of a framework for the recognition of ADL, analyzing the allowed sensors available in the mobile devices, and the existing methods available in the literature. PMID:29466316

Automatic safety rod for reactors. [LMFBR

DOEpatents

Germer, J.H.

1982-03-23

An automatic safety rod for a nuclear reactor containing neutron absorbing material and designed to be inserted into a reactor core after a loss-of-flow. Actuation is based upon either a sudden decrease in core pressure drop or the pressure drop decreases below a predetermined minimum value. The automatic control rod includes a pressure regulating device whereby a controlled decrease in operating pressure due to reduced coolant flow does not cause the rod to drop into the core.