An automatic approach for 3D registration of CT scans

NASA Astrophysics Data System (ADS)

Hu, Yang; Saber, Eli; Dianat, Sohail; Vantaram, Sreenath Rao; Abhyankar, Vishwas

2012-03-01

CT (Computed tomography) is a widely employed imaging modality in the medical field. Normally, a volume of CT scans is prescribed by a doctor when a specific region of the body (typically neck to groin) is suspected of being abnormal. The doctors are required to make professional diagnoses based upon the obtained datasets. In this paper, we propose an automatic registration algorithm that helps healthcare personnel to automatically align corresponding scans from 'Study' to 'Atlas'. The proposed algorithm is capable of aligning both 'Atlas' and 'Study' into the same resolution through 3D interpolation. After retrieving the scanned slice volume in the 'Study' and the corresponding volume in the original 'Atlas' dataset, a 3D cross correlation method is used to identify and register various body parts.

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.

Method and system for entering data within a flight plan entry field

NASA Technical Reports Server (NTRS)

Gibbs, Michael J. (Inventor); Van Omen, Debi (Inventor); Adams, Michael B. (Inventor); Chase, Karl L. (Inventor); Lewis, Daniel E. (Inventor); McCrobie, Daniel E. (Inventor)

2005-01-01

The present invention provides systems, apparatus and methods for entering data into a flight plan entry field which facilitates the display and editing of aircraft flight-plan data. In one embodiment, the present invention provides a method for entering multiple waypoint and procedure identifiers at once within a single a flight plan entry field. In another embodiment, the present invention provides for the partial entry of any waypoint or procedure identifiers, and thereafter relating the identifiers with an aircraft's flight management system to anticipate the complete text entry for display. In yet another embodiment, the present invention discloses a method to automatically provide the aircraft operator with selectable prioritized arrival and approach routing identifiers by a single manual selection. In another embodiment, the present invention is a method for providing the aircraft operator with selectable alternate patterns to a new runway.

Automatic detection and classification of damage zone(s) for incorporating in digital image correlation technique

NASA Astrophysics Data System (ADS)

Bhattacharjee, Sudipta; Deb, Debasis

2016-07-01

Digital image correlation (DIC) is a technique developed for monitoring surface deformation/displacement of an object under loading conditions. This method is further refined to make it capable of handling discontinuities on the surface of the sample. A damage zone is referred to a surface area fractured and opened in due course of loading. In this study, an algorithm is presented to automatically detect multiple damage zones in deformed image. The algorithm identifies the pixels located inside these zones and eliminate them from FEM-DIC processes. The proposed algorithm is successfully implemented on several damaged samples to estimate displacement fields of an object under loading conditions. This study shows that displacement fields represent the damage conditions reasonably well as compared to regular FEM-DIC technique without considering the damage zones.

Developing a Satellite Based Automatic System for Crop Monitoring: Kenya's Great Rift Valley, A Case Study

NASA Astrophysics Data System (ADS)

Lucciani, Roberto; Laneve, Giovanni; Jahjah, Munzer; Mito, Collins

2016-08-01

The crop growth stage represents essential information for agricultural areas management. In this study we investigate the feasibility of a tool based on remotely sensed satellite (Landsat 8) imagery, capable of automatically classify crop fields and how much resolution enhancement based on pan-sharpening techniques and phenological information extraction, useful to create decision rules that allow to identify semantic class to assign to an object, can effectively support the classification process. Moreover we investigate the opportunity to extract vegetation health status information from remotely sensed assessment of the equivalent water thickness (EWT). Our case study is the Kenya's Great Rift valley, in this area a ground truth campaign was conducted during August 2015 in order to collect crop fields GPS measurements, leaf area index (LAI) and chlorophyll samples.

Development and testing of a portable wind sensitive directional air sampler

NASA Technical Reports Server (NTRS)

Deyo, J.; Toma, J.; King, R. B.

1975-01-01

A portable wind sensitive directional air sampler was developed as part of an air pollution source identification system. The system is designed to identify sources of air pollution based on the directional collection of field air samples and their analysis for TSP and trace element characteristics. Sources can be identified by analyzing the data on the basis of pattern recognition concepts. The unit, designated Air Scout, receives wind direction signals from an associated wind vane. Air samples are collected on filter slides using a standard high volume air sampler drawing air through a porting arrangement which tracks the wind direction and permits collection of discrete samples. A preset timer controls the length of time each filter is in the sampling position. At the conclusion of the sampling period a new filter is automatically moved into sampling position displacing the previous filter to a storage compartment. Thus the Air Scout may be set up at a field location, loaded with up to 12 filter slides, and left to acquire air samples automatically, according to the wind, at any timer interval desired from 1 to 30 hours.

A preliminary architecture for building communication software from traffic captures

NASA Astrophysics Data System (ADS)

Acosta, Jaime C.; Estrada, Pedro

2017-05-01

Security analysts are tasked with identifying and mitigating network service vulnerabilities. A common problem associated with in-depth testing of network protocols is the availability of software that communicates across disparate protocols. Many times, the software required to communicate with these services is not publicly available. Developing this software is a time-consuming undertaking that requires expertise and understanding of the protocol specification. The work described in this paper aims at developing a software package that is capable of automatically creating communication clients by using packet capture (pcap) and TShark dissectors. Currently, our focus is on simple protocols with fixed fields. The methodologies developed as part of this work will extend to other complex protocols such as the Gateway Load Balancing Protocol (GLBP), Port Aggregation Protocol (PAgP), and Open Shortest Path First (OSPF). Thus far, we have architected a modular pipeline for an automatic traffic-based software generator. We start the transformation of captured network traffic by employing TShark to convert packets into a Packet Details Markup Language (PDML) file. The PDML file contains a parsed, textual, representation of the packet data. Then, we extract field data, types, along with inter and intra-packet dependencies. This information is then utilized to construct an XML file that encompasses the protocol state machine and field vocabulary. Finally, this XML is converted into executable code. Using our methodology, and as a starting point, we have succeeded in automatically generating software that communicates with other hosts using an automatically generated Internet Control Message Protocol (ICMP) client program.

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.

Bayesian Analysis Of HMI Solar Image Observables And Comparison To TSI Variations And MWO Image Observables

NASA Astrophysics Data System (ADS)

Parker, D. G.; Ulrich, R. K.; Beck, J.

2014-12-01

We have previously applied the Bayesian automatic classification system AutoClass to solar magnetogram and intensity images from the 150 Foot Solar Tower at Mount Wilson to identify classes of solar surface features associated with variations in total solar irradiance (TSI) and, using those identifications, modeled TSI time series with improved accuracy (r > 0.96). (Ulrich, et al, 2010) AutoClass identifies classes by a two-step process in which it: (1) finds, without human supervision, a set of class definitions based on specified attributes of a sample of the image data pixels, such as magnetic field and intensity in the case of MWO images, and (2) applies the class definitions thus found to new data sets to identify automatically in them the classes found in the sample set. HMI high resolution images capture four observables-magnetic field, continuum intensity, line depth and line width-in contrast to MWO's two observables-magnetic field and intensity. In this study, we apply AutoClass to the HMI observables for images from May, 2010 to June, 2014 to identify solar surface feature classes. We use contemporaneous TSI measurements to determine whether and how variations in the HMI classes are related to TSI variations and compare the characteristic statistics of the HMI classes to those found from MWO images. We also attempt to derive scale factors between the HMI and MWO magnetic and intensity observables. The ability to categorize automatically surface features in the HMI images holds out the promise of consistent, relatively quick and manageable analysis of the large quantity of data available in these images. Given that the classes found in MWO images using AutoClass have been found to improve modeling of TSI, application of AutoClass to the more complex HMI images should enhance understanding of the physical processes at work in solar surface features and their implications for the solar-terrestrial environment. Ulrich, R.K., Parker, D, Bertello, L. and Boyden, J. 2010, Solar Phys. , 261 , 11.

An improved schlieren method for measurement and automatic reconstruction of the far-field focal spot

PubMed Central

Wang, Zhengzhou; Hu, Bingliang; Yin, Qinye

2017-01-01

The schlieren method of measuring far-field focal spots offers many advantages at the Shenguang III laser facility such as low cost and automatic laser-path collimation. However, current methods of far-field focal spot measurement often suffer from low precision and efficiency when the final focal spot is merged manually, thereby reducing the accuracy of reconstruction. In this paper, we introduce an improved schlieren method to construct the high dynamic-range image of far-field focal spots and improve the reconstruction accuracy and efficiency. First, a detection method based on weak light beam sampling and magnification imaging was designed; images of the main and side lobes of the focused laser irradiance in the far field were obtained using two scientific CCD cameras. Second, using a self-correlation template matching algorithm, a circle the same size as the schlieren ball was dug from the main lobe cutting image and used to change the relative region of the main lobe cutting image within a 100×100 pixel region. The position that had the largest correlation coefficient between the side lobe cutting image and the main lobe cutting image when a circle was dug was identified as the best matching point. Finally, the least squares method was used to fit the center of the side lobe schlieren small ball, and the error was less than 1 pixel. The experimental results show that this method enables the accurate, high-dynamic-range measurement of a far-field focal spot and automatic image reconstruction. Because the best matching point is obtained through image processing rather than traditional reconstruction methods based on manual splicing, this method is less sensitive to the efficiency of focal-spot reconstruction and thus offers better experimental precision. PMID:28207758

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

NASA Technical Reports Server (NTRS)

Messmore, J.; Copeland, G. E.; Levy, G. F.

1975-01-01

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95%), and progress is being made towards identifying the mapped spectral classes.

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

NASA Technical Reports Server (NTRS)

Messmore, J.; Copeland, G. E.; Levy, G. F.

1975-01-01

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95 percent), and progress is being made towards identifying the mapped spectral classes.

Wheat cultivation: Identification and estimation of areas using LANDSAT data

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Mendonca, F. J.; Cottrell, D. A.; Tardin, A. T.; Lee, D. C. L.; Shimabukuro, Y. E.; Moreira, M. A.; Delimaefernandocelsosoaresmaia, A. M.

1981-01-01

The feasibility of using automatically processed multispectral data obtained from LANDSAT to identify wheat and estimate the areas planted with this grain was investigated. Three 20 km by 40 km segments in a wheat growing region of Rio Grande do Sul were aerially photographed using type 2443 Aerochrome film. Three maps corresponding to each segment were obtained from the analysis of the photographs which identified wheat, barley, fallow land, prepared soil, forests, and reforested land. Using basic information about the fields and maps made from the photographed areas, an automatic classification of wheat was made using MSS data from two different periods: July to September and July to October 1979. Results show that orbital data is not only useful in characterizing the growth of wheat, but also provides information of the intensity and extent of adverse climate which affects cultivation. The temporal and spatial characteristics of LANDSAR data are also demonstrated.

Use of automatic extraction of LANDSAT data defining areas of ilmenite in the forest of the state of Pernambuco. [Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Mattoso, S. D. Q.; Paradella, W. R.; Meneses, P. R.

1979-01-01

The author has identified the following significant results. Classification results point out 600 alarm areas of high potentiality of titanium occurrence. Almost 80 of these 600 alarm areas were checked by field work, and in 56 of them, titanium occurrences were confirmed and four new ore deposits were found.

Tree-structured sensor fusion architecture for distributed sensor networks

NASA Astrophysics Data System (ADS)

Iyengar, S. Sitharama; Kashyap, Rangasami L.; Madan, Rabinder N.; Thomas, Daryl D.

1990-10-01

An assessment of numerous activities in the field of multisensor target recognition reveals several trends and conditions which are cause for concern. .These concerns are analyzed in terms of their potential impact on the ultimate employment of automatic target recognition in military systems. Suggestions for additional investigation and guidance for current activities are presented with respect to some of the identified concerns.

A Review of Automatic Methods Based on Image Processing Techniques for Tuberculosis Detection from Microscopic Sputum Smear Images.

PubMed

Panicker, Rani Oomman; Soman, Biju; Saini, Gagan; Rajan, Jeny

2016-01-01

Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis. It primarily affects the lungs, but it can also affect other parts of the body. TB remains one of the leading causes of death in developing countries, and its recent resurgences in both developed and developing countries warrant global attention. The number of deaths due to TB is very high (as per the WHO report, 1.5 million died in 2013), although most are preventable if diagnosed early and treated. There are many tools for TB detection, but the most widely used one is sputum smear microscopy. It is done manually and is often time consuming; a laboratory technician is expected to spend at least 15 min per slide, limiting the number of slides that can be screened. Many countries, including India, have a dearth of properly trained technicians, and they often fail to detect TB cases due to the stress of a heavy workload. Automatic methods are generally considered as a solution to this problem. Attempts have been made to develop automatic approaches to identify TB bacteria from microscopic sputum smear images. In this paper, we provide a review of automatic methods based on image processing techniques published between 1998 and 2014. The review shows that the accuracy of algorithms for the automatic detection of TB increased significantly over the years and gladly acknowledges that commercial products based on published works also started appearing in the market. This review could be useful to researchers and practitioners working in the field of TB automation, providing a comprehensive and accessible overview of methods of this field of research.

System for analysis of LANDSAT agricultural data: Automatic computer-assisted proportion estimation of local areas

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Kauth, R. J.; Thomas, G. S.

1976-01-01

The author has identified the following significant results. A conceptual man machine system framework was created for a large scale agricultural remote sensing system. The system is based on and can grow out of the local recognition mode of LACIE, through a gradual transition wherein computer support functions supplement and replace AI functions. Local proportion estimation functions are broken into two broad classes: (1) organization of the data within the sample segment; and (2) identification of the fields or groups of fields in the sample segment.

Poster — Thur Eve — 70: Automatic lung bronchial and vessel bifurcations detection algorithm for deformable image registration assessment

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

Labine, Alexandre; Carrier, Jean-François; Bedwani, Stéphane

2014-08-15

Purpose: To investigate an automatic bronchial and vessel bifurcations detection algorithm for deformable image registration (DIR) assessment to improve lung cancer radiation treatment. Methods: 4DCT datasets were acquired and exported to Varian treatment planning system (TPS) EclipseTM for contouring. The lungs TPS contour was used as the prior shape for a segmentation algorithm based on hierarchical surface deformation that identifies the deformed lungs volumes of the 10 breathing phases. Hounsfield unit (HU) threshold filter was applied within the segmented lung volumes to identify blood vessels and airways. Segmented blood vessels and airways were skeletonised using a hierarchical curve-skeleton algorithm basedmore » on a generalized potential field approach. A graph representation of the computed skeleton was generated to assign one of three labels to each node: the termination node, the continuation node or the branching node. Results: 320 ± 51 bifurcations were detected in the right lung of a patient for the 10 breathing phases. The bifurcations were visually analyzed. 92 ± 10 bifurcations were found in the upper half of the lung and 228 ± 45 bifurcations were found in the lower half of the lung. Discrepancies between ten vessel trees were mainly ascribed to large deformation and in regions where the HU varies. Conclusions: We established an automatic method for DIR assessment using the morphological information of the patient anatomy. This approach allows a description of the lung's internal structure movement, which is needed to validate the DIR deformation fields for accurate 4D cancer treatment planning.« less

Automated Detection of Salt Marsh Platforms : a Topographic Method

NASA Astrophysics Data System (ADS)

Goodwin, G.; Mudd, S. M.; Clubb, F. J.

2017-12-01

Monitoring the topographic evolution of coastal marshes is a crucial step toward improving the management of these valuable landscapes under the pressure of relative sea level rise and anthropogenic modification. However, determining their geometrically complex boundaries currently relies on spectral vegetation detection methods or requires labour-intensive field surveys and digitisation.We propose a novel method to reproducibly isolate saltmarsh scarps and platforms from a DEM. Field observations and numerical models show that saltmarshes mature into sub-horizontal platforms delineated by sub-vertical scarps: based on this premise, we identify scarps as lines of local maxima on a slope*relief raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. Non-dimensional search parameters allow batch-processing of data without recalibration. We test our method using lidar-derived DEMs of six saltmarshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and automatic segregation exceeds 90% for resolutions of 1m, with all but one sites maintaining this performance for resolutions up to 3.5m. For resolutions of 1m, automatically detected platforms are comparable in surface area and elevation distribution to digitised platforms. We also find that our method allows the accurate detection of local bloc failures 3 times larger than the DEM resolution.Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, automatic detection classifies them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method would benefit from a combination with existing creek detection algorithms. Fallen blocs and pioneer zones are inconsistently identified, particularly in macro-tidal marshes, leading to differences between digitisation and the automated method: this also suggests that these areas must be carefully considered when analysing erosion and accretion processes. Ultimately, we have shown that automatic detection of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.

[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.

Uav-Based Automatic Tree Growth Measurement for Biomass Estimation

NASA Astrophysics Data System (ADS)

Karpina, M.; Jarząbek-Rychard, M.; Tymków, P.; Borkowski, A.

2016-06-01

Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

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...

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.

Assessment of Automatically Exported Clinical Data from a Hospital Information System for Clinical Research in Multiple Myeloma.

PubMed

Torres, Viviana; Cerda, Mauricio; Knaup, Petra; Löpprich, Martin

2016-01-01

An important part of the electronic information available in Hospital Information System (HIS) has the potential to be automatically exported to Electronic Data Capture (EDC) platforms for improving clinical research. This automation has the advantage of reducing manual data transcription, a time consuming and prone to errors process. However, quantitative evaluations of the process of exporting data from a HIS to an EDC system have not been reported extensively, in particular comparing with manual transcription. In this work an assessment to study the quality of an automatic export process, focused in laboratory data from a HIS is presented. Quality of the laboratory data was assessed in two types of processes: (1) a manual process of data transcription, and (2) an automatic process of data transference. The automatic transference was implemented as an Extract, Transform and Load (ETL) process. Then, a comparison was carried out between manual and automatic data collection methods. The criteria to measure data quality were correctness and completeness. The manual process had a general error rate of 2.6% to 7.1%, obtaining the lowest error rate if data fields with a not clear definition were removed from the analysis (p < 10E-3). In the case of automatic process, the general error rate was 1.9% to 12.1%, where lowest error rate is obtained when excluding information missing in the HIS but transcribed to the EDC from other physical sources. The automatic ETL process can be used to collect laboratory data for clinical research if data in the HIS as well as physical documentation not included in HIS, are identified previously and follows a standardized data collection protocol.

From gaze cueing to perspective taking: Revisiting the claim that we automatically compute where or what other people are looking at

PubMed Central

Bukowski, Henryk; Hietanen, Jari K.; Samson, Dana

2015-01-01

ABSTRACT Two paradigms have shown that people automatically compute what or where another person is looking at. In the visual perspective-taking paradigm, participants judge how many objects they see; whereas, in the gaze cueing paradigm, participants identify a target. Unlike in the former task, in the latter task, the influence of what or where the other person is looking at is only observed when the other person is presented alone before the task-relevant objects. We show that this discrepancy across the two paradigms is not due to differences in visual settings (Experiment 1) or available time to extract the directional information (Experiment 2), but that it is caused by how attention is deployed in response to task instructions (Experiment 3). Thus, the mere presence of another person in the field of view is not sufficient to compute where/what that person is looking at, which qualifies the claimed automaticity of such computations. PMID:26924936

From gaze cueing to perspective taking: Revisiting the claim that we automatically compute where or what other people are looking at.

PubMed

Bukowski, Henryk; Hietanen, Jari K; Samson, Dana

2015-09-14

Two paradigms have shown that people automatically compute what or where another person is looking at. In the visual perspective-taking paradigm, participants judge how many objects they see; whereas, in the gaze cueing paradigm, participants identify a target. Unlike in the former task, in the latter task, the influence of what or where the other person is looking at is only observed when the other person is presented alone before the task-relevant objects. We show that this discrepancy across the two paradigms is not due to differences in visual settings (Experiment 1) or available time to extract the directional information (Experiment 2), but that it is caused by how attention is deployed in response to task instructions (Experiment 3). Thus, the mere presence of another person in the field of view is not sufficient to compute where/what that person is looking at, which qualifies the claimed automaticity of such computations.

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…

A new fast scanning system for the measurement of large angle tracks in nuclear emulsions

NASA Astrophysics Data System (ADS)

Alexandrov, A.; Buonaura, A.; Consiglio, L.; D'Ambrosio, N.; De Lellis, G.; Di Crescenzo, A.; Di Marco, N.; Galati, G.; Lauria, A.; Montesi, M. C.; Pupilli, F.; Shchedrina, T.; Tioukov, V.; Vladymyrov, M.

2015-11-01

Nuclear emulsions have been widely used in particle physics to identify new particles through the observation of their decays thanks to their unique spatial resolution. Nevertheless, before the advent of automatic scanning systems, the emulsion analysis was very demanding in terms of well trained manpower. Due to this reason, they were gradually replaced by electronic detectors, until the '90s, when automatic microscopes started to be developed in Japan and in Europe. Automatic scanning was essential to conceive large scale emulsion-based neutrino experiments like CHORUS, DONUT and OPERA. Standard scanning systems have been initially designed to recognize tracks within a limited angular acceptance (θ lesssim 30°) where θ is the track angle with respect to a line perpendicular to the emulsion plane. In this paper we describe the implementation of a novel fast automatic scanning system aimed at extending the track recognition to the full angular range and improving the present scanning speed. Indeed, nuclear emulsions do not have any intrinsic limit to detect particle direction. Such improvement opens new perspectives to use nuclear emulsions in several fields in addition to large scale neutrino experiments, like muon radiography, medical applications and dark matter directional detection.

Reliability Testing on the CTI-Cryogenic 1 Watt Integral Cooler (HD- 1033C/UA)

DTIC Science & Technology

1989-09-01

SUBJECT TERMS (Continue on reverse if necessary and identify by block numbe) FIELD GROUP SUB- GROUP Cryocooler, Stirling Cycle, Cryogenics 19, ABSTRCT...the Army. C2NVEO also maintains configuration management control of the forward-looking infrared (FLIR) Common Module coolers used in thermal imagers... controlled high/low temperature chamber. * A microprocessor which was programmed to automatically cycle the temperature in the chamber in accordance

Battle Staff Operations: Synchronization of Planning at Battalion and Brigade Level

DTIC Science & Technology

1989-06-02

tactical employment of the tank and mechanized infantry battalion task force. In consonance with Airland Battle doctrine, the document emphasizes ...letter entitled *Emphasis on Rapid Estimates and Decisions on the Atomic Battlefield.’ Emphasizing the increased tempo of the post war mechanized army...If so, a copy of the message is automatically canted to the user(s) identified in the distribution field. Queries are messages retrived records from

Waterway Performance Monitoring via Automatic Identification System (AIS) Data

DTIC Science & Technology

2013-08-01

Transceivers onboard the vessels broadcast the 4 AIS signal containing position, heading, speed, and other identifying information to shore- based 5 towers...Great Lakes system based 31 on the voyage histories reconstructed with the Destination field from the AIS static reports. In 32 spite of the much... Information Systems for Estimating Coastal Maritime Risk. 38 Transportation Research Record: Journal of the Transportation Research Board, No. 2222, 39 TRB

Skeletonization of Gridded Potential-Field Images

NASA Astrophysics Data System (ADS)

Gao, L.; Morozov, I. B.

2012-12-01

A new approach to skeletonization was developed for gridded potential-field data. Generally, skeletonization is a pattern-recognition technique allowing automatic recognition of near-linear features in the images, measurement of their parameters, and analyzing them for similarities. Our approach decomposes the images into arbitrarily-oriented "wavelets" characterized by positive or negative amplitudes, orientation angles, spatial dimensions, polarities, and other attributes. Orientations of the wavelets are obtained by scanning the azimuths to detect the strike direction of each anomaly. The wavelets are connected according to the similarities of these attributes, which leads to a "skeleton" map of the potential-field data. In addition, 2-D filtering is conducted concurrently with the wavelet-identification process, which allows extracting parameters of background trends and reduces the adverse effects of low-frequency background (which is often strong in potential-field maps) on skeletonization.. By correlating the neighboring wavelets, linear anomalies are identified and characterized. The advantages of this algorithm are the generality and isotropy of feature detection, as well as being specifically designed for gridded data. With several options for background-trend extraction, the stability for identification of lineaments is improved and optimized. The algorithm is also integrated in a powerful processing system which allows combining it with numerous other tools, such as filtering, computation of analytical signal, empirical mode decomposition, and various types of plotting. The method is applied to potential-field data for the Western Canada Sedimentary Basin, in a study area which extends from southern Saskatchewan into southwestern Manitoba. The target is the structure of crystalline basement beneath Phanerozoic sediments. The examples illustrate that skeletonization aid in the interpretation of complex structures at different scale lengths. The results indicate that this method is useful for identifying structures in complex geophysical images and for automatic extraction of their attributes as well as for quantitative characterization and analysis of potential-field images. Skeletonized potential-field images should also be useful for inversion.

Database Design for the Evaluation of On-shore and Off-Shore Storm Characteristics over East Central Florida

NASA Technical Reports Server (NTRS)

Simpson, Amy A.; Wilson, Jennifer G.; Brown, Robert G.

2015-01-01

Data from multiple sources is needed to investigate lightning characteristics over differing terrain (on-shore vs. off-shore) by comparing natural cloud-to-ground lightning behavior differences depending on the characteristics of attachment mediums. The KSC Lightning Research Database (KLRD) was created to reduce manual data entry time and aid research by combining information from various data sources into a single record for each unique lightning event of interest. The KLRD uses automatic data handling functions to import data from a lightning detection network and identify and record lighting events of interest. Additional automatic functions import data from the NASA Buoy 41009 (located approximately 20 miles off the coast) and the KSC Electric Field Mill network, then match these electric field mill values to the corresponding lightning events. The KLRD calculates distances between each lightning event and the various electric field mills, aids in identifying the location type for each stroke (i.e., on-shore vs. off-shore, etc.), provides statistics on the number of strokes per flash, and produces customizable reports for quick retrieval and logical display of data. Data from February 2014 to date covers 48 unique storm dates with 2295 flashes containing 5700 strokes, of which 2612 are off-shore and 1003 are on-shore. The number of strokes per flash ranges from 1 to 22. The ratio of single to subsequent stroke flashes is 1.29 for off-shore strokes and 2.19 for on-shore strokes.

Automatic Classification of Time-variable X-Ray Sources

NASA Astrophysics Data System (ADS)

Lo, Kitty K.; Farrell, Sean; Murphy, Tara; Gaensler, B. M.

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ~97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7-500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.

Automatic analysis of stereoscopic satellite image pairs for determination of cloud-top height and structure

NASA Technical Reports Server (NTRS)

Hasler, A. F.; Strong, J.; Woodward, R. H.; Pierce, H.

1991-01-01

Results are presented on an automatic stereo analysis of cloud-top heights from nearly simultaneous satellite image pairs from the GOES and NOAA satellites, using a massively parallel processor computer. Comparisons of computer-derived height fields and manually analyzed fields show that the automatic analysis technique shows promise for performing routine stereo analysis in a real-time environment, providing a useful forecasting tool by augmenting observational data sets of severe thunderstorms and hurricanes. Simulations using synthetic stereo data show that it is possible to automatically resolve small-scale features such as 4000-m-diam clouds to about 1500 m in the vertical.

Automatic control of solar power plants

NASA Astrophysics Data System (ADS)

Ermakov, V. S.; Dubilovich, V. M.

1982-02-01

The automatic control of the heliostat field of a 200-MW solar power plant is discussed. The advantages of the decentralized control principle with the solution of a number of individual problems in a single control center are emphasized. The basic requirements on heliostat construction are examined, and possible functional schemes for the automatic control of a heliostat field are described. It is proposed that groups of heliostats can be controlled from a single center and on the basis of a single algorithm.

Suspicious activity recognition in infrared imagery using Hidden Conditional Random Fields for outdoor perimeter surveillance

NASA Astrophysics Data System (ADS)

Rogotis, Savvas; Ioannidis, Dimosthenis; Tzovaras, Dimitrios; Likothanassis, Spiros

2015-04-01

The aim of this work is to present a novel approach for automatic recognition of suspicious activities in outdoor perimeter surveillance systems based on infrared video processing. Through the combination of size, speed and appearance based features, like the Center-Symmetric Local Binary Patterns, short-term actions are identified and serve as input, along with user location, for modeling target activities using the theory of Hidden Conditional Random Fields. HCRFs are used to directly link a set of observations to the most appropriate activity label and as such to discriminate high risk activities (e.g. trespassing) from zero risk activities (e.g loitering outside the perimeter). Experimental results demonstrate the effectiveness of our approach in identifying suspicious activities for video surveillance systems.

Return Difference Feedback Design for Robust Uncertainty Tolerance in Stochastic Multivariable Control Systems.

DTIC Science & Technology

1982-11-01

D- R136 495 RETURN DIFFERENCE FEEDBACK DESIGN FOR ROBUSTj/ UNCERTAINTY TOLERANCE IN STO..(U) UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES DEPT OF...State and ZIP Code) 7. b6 ADORESS (City. Staft and ZIP Code) Department of Electrical Engineering -’M Directorate of Mathematical & Information Systems ...13. SUBJECT TERMS Continur on rverse ineeesaty and identify by block nmber) FIELD GROUP SUE. GR. Systems theory; control; feedback; automatic control

Quantification of regional fat volume in rat MRI

NASA Astrophysics Data System (ADS)

Sacha, Jaroslaw P.; Cockman, Michael D.; Dufresne, Thomas E.; Trokhan, Darren

2003-05-01

Multiple initiatives in the pharmaceutical and beauty care industries are directed at identifying therapies for weight management. Body composition measurements are critical for such initiatives. Imaging technologies that can be used to measure body composition noninvasively include DXA (dual energy x-ray absorptiometry) and MRI (magnetic resonance imaging). Unlike other approaches, MRI provides the ability to perform localized measurements of fat distribution. Several factors complicate the automatic delineation of fat regions and quantification of fat volumes. These include motion artifacts, field non-uniformity, brightness and contrast variations, chemical shift misregistration, and ambiguity in delineating anatomical structures. We have developed an approach to deal practically with those challenges. The approach is implemented in a package, the Fat Volume Tool, for automatic detection of fat tissue in MR images of the rat abdomen, including automatic discrimination between abdominal and subcutaneous regions. We suppress motion artifacts using masking based on detection of implicit landmarks in the images. Adaptive object extraction is used to compensate for intensity variations. This approach enables us to perform fat tissue detection and quantification in a fully automated manner. The package can also operate in manual mode, which can be used for verification of the automatic analysis or for performing supervised segmentation. In supervised segmentation, the operator has the ability to interact with the automatic segmentation procedures to touch-up or completely overwrite intermediate segmentation steps. The operator's interventions steer the automatic segmentation steps that follow. This improves the efficiency and quality of the final segmentation. Semi-automatic segmentation tools (interactive region growing, live-wire, etc.) improve both the accuracy and throughput of the operator when working in manual mode. The quality of automatic segmentation has been evaluated by comparing the results of fully automated analysis to manual analysis of the same images. The comparison shows a high degree of correlation that validates the quality of the automatic segmentation approach.

Unsupervised segmentation of lung fields in chest radiographs using multiresolution fractal feature vector and deformable models.

PubMed

Lee, Wen-Li; Chang, Koyin; Hsieh, Kai-Sheng

2016-09-01

Segmenting lung fields in a chest radiograph is essential for automatically analyzing an image. We present an unsupervised method based on multiresolution fractal feature vector. The feature vector characterizes the lung field region effectively. A fuzzy c-means clustering algorithm is then applied to obtain a satisfactory initial contour. The final contour is obtained by deformable models. The results show the feasibility and high performance of the proposed method. Furthermore, based on the segmentation of lung fields, the cardiothoracic ratio (CTR) can be measured. The CTR is a simple index for evaluating cardiac hypertrophy. After identifying a suspicious symptom based on the estimated CTR, a physician can suggest that the patient undergoes additional extensive tests before a treatment plan is finalized.

Robust crop and weed segmentation under uncontrolled outdoor illumination.

PubMed

Jeon, Hong Y; Tian, Lei F; Zhu, Heping

2011-01-01

An image processing algorithm for detecting individual weeds was developed and evaluated. Weed detection processes included were normalized excessive green conversion, statistical threshold value estimation, adaptive image segmentation, median filter, morphological feature calculation and Artificial Neural Network (ANN). The developed algorithm was validated for its ability to identify and detect weeds and crop plants under uncontrolled outdoor illuminations. A machine vision implementing field robot captured field images under outdoor illuminations and the image processing algorithm automatically processed them without manual adjustment. The errors of the algorithm, when processing 666 field images, ranged from 2.1 to 2.9%. The ANN correctly detected 72.6% of crop plants from the identified plants, and considered the rest as weeds. However, the ANN identification rates for crop plants were improved up to 95.1% by addressing the error sources in the algorithm. The developed weed detection and image processing algorithm provides a novel method to identify plants against soil background under the uncontrolled outdoor illuminations, and to differentiate weeds from crop plants. Thus, the proposed new machine vision and processing algorithm may be useful for outdoor applications including plant specific direct applications (PSDA).

An Auto-Tuning PI Control System for an Open-Circuit Low-Speed Wind Tunnel Designed for Greenhouse Technology.

PubMed

Espinoza, Karlos; Valera, Diego L; Torres, José A; López, Alejandro; Molina-Aiz, Francisco D

2015-08-12

Wind tunnels are a key experimental tool for the analysis of airflow parameters in many fields of application. Despite their great potential impact on agricultural research, few contributions have dealt with the development of automatic control systems for wind tunnels in the field of greenhouse technology. The objective of this paper is to present an automatic control system that provides precision and speed of measurement, as well as efficient data processing in low-speed wind tunnel experiments for greenhouse engineering applications. The system is based on an algorithm that identifies the system model and calculates the optimum PI controller. The validation of the system was performed on a cellulose evaporative cooling pad and on insect-proof screens to assess its response to perturbations. The control system provided an accuracy of <0.06 m·s(-1) for airflow speed and <0.50 Pa for pressure drop, thus permitting the reproducibility and standardization of the tests. The proposed control system also incorporates a fully-integrated software unit that manages the tests in terms of airflow speed and pressure drop set points.

Analysis of contact zones from whole field isochromatics using reflection photoelasticity

NASA Astrophysics Data System (ADS)

Hariprasad, M. P.; Ramesh, K.

2018-06-01

This paper discusses the method for evaluating the unknown contact parameters by post processing the whole field fringe order data obtained from reflection photoelasticity in a nonlinear least squares sense. Recent developments in Twelve Fringe Photoelasticity (TFP) for fringe order evaluation from single isochromatics is utilized for the whole field fringe order evaluation. One of the issues in using TFP for reflection photoelasticity is the smudging of isochromatic data at the contact zone. This leads to error in identifying the origin of contact, which is successfully addressed by implementing a semi-automatic contact point refinement algorithm. The methodologies are initially verified for benchmark problems and demonstrated for two application problems of turbine blade and sheet pile contacting interfaces.

Field testing of a new flow-through directional passive air sampler applied to monitoring ambient nitrogen dioxide.

PubMed

Lin, Chun; McKenna, Paul; Timmis, Roger; Jones, Kevin C

2010-07-08

This paper reports the first field deployment and testing of a directional passive air sampler (DPAS) which can be used to cost-effectively identify and quantify air pollutants and their sources. The sampler was used for ambient nitrogen dioxide (NO(2)) over ten weeks from twelve directional sectors in an urban setting, and tested alongside an automatic chemiluminescent monitor. The time-integrated passive directional results were compared with the directional analysis of the active monitoring results using wind data recorded at a weather station. The DPAS discriminated air pollutant signals directionally. The attempts to derive quantitative data yielded reasonable results--usually within a factor of two of those obtained by the chemiluminescent analyser. Ultimately, whether DPAS approaches are adopted will depend on their reliability, added value and cost. It is argued that added value was obtained here from the DPAS approach applied in a routine monitoring situation, by identifying source sectors. Both the capital and running costs of DPAS were <5% of those for the automatic monitor. It is envisaged that different sorbents or sampling media will enable this rotatable DPAS design to be used for other airborne pollutants. In summary, there are reasons to be optimistic that directional passive air sampling, together with careful interpretation of results, will be of added value to air quality practitioners in future.

Automatic classification of time-variable X-ray sources

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

Lo, Kitty K.; Farrell, Sean; Murphy, Tara

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, andmore » other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ∼97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7–500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.« less

Design, Development, and Demonstration of a Prognostic and Diagnostics Health Monitoring System for the CROWS Platform

DTIC Science & Technology

2010-06-01

automatically appended onto the data packet by the CC2420 transceiver. The frame control field (FCF), data sequence number, and frame check sequence (FCS...by the CC2420 over the MAC protocol data unit (MPDU), i.e., the length field is not part of the FCS. This field is automatically generated and...verified by the CC2420 hardware when the AUTOCRC control bit is set in the MODEMCTRL0 control register’s field . If the FCS check indicates that a data

Exploratory field trial of motorcycle autonomous emergency braking (MAEB): Considerations on the acceptability of unexpected automatic decelerations.

PubMed

Savino, Giovanni; Pierini, Marco; Thompson, Jason; Fitzharris, Michael; Lenné, Michael G

2016-11-16

Autonomous emergency braking (AEB) acts to slow down a vehicle when an unavoidable impending collision is detected. In addition to documented benefits when applied to passenger cars, AEB has also shown potential when applied to motorcycles (MAEB). However, the feasibility of MAEB as practically applied to motorcycles in the real world is not well understood. In this study we performed a field trial involving 16 riders on a test motorcycle subjected to automatic decelerations, thus simulating MAEB activation. The tests were conducted along a rectilinear path at nominal speed of 40 km/h and with mean deceleration of 0.15 g (15% of full braking) deployed at random times. Riders were also exposed to one final undeclared brake activation with the aim of providing genuinely unexpected automatic braking events. Participants were consistently able to manage automatic decelerations of the vehicle with minor to moderate effort. Results of undeclared activations were consistent with those of standard runs. This study demonstrated the feasibility of a moderate automatic deceleration in a scenario of motorcycle travelling in a straight path, supporting the notion that the application of AEB on motorcycles is practicable. Furthermore, the proposed field trial can be used as a reference for future regulation or consumer tests in order to address safety and acceptability of unexpected automatic decelerations on a motorcycle.

UMEL: a new regression tool to identify measurement peaks in LIDAR/DIAL systems for environmental physics applications.

PubMed

Gelfusa, M; Gaudio, P; Malizia, A; Murari, A; Vega, J; Richetta, M; Gonzalez, S

2014-06-01

Recently, surveying large areas in an automatic way, for early detection of both harmful chemical agents and forest fires, has become a strategic objective of defence and public health organisations. The Lidar and Dial techniques are widely recognized as a cost-effective alternative to monitor large portions of the atmosphere. To maximize the effectiveness of the measurements and to guarantee reliable monitoring of large areas, new data analysis techniques are required. In this paper, an original tool, the Universal Multi Event Locator, is applied to the problem of automatically identifying the time location of peaks in Lidar and Dial measurements for environmental physics applications. This analysis technique improves various aspects of the measurements, ranging from the resilience to drift in the laser sources to the increase of the system sensitivity. The method is also fully general, purely software, and can therefore be applied to a large variety of problems without any additional cost. The potential of the proposed technique is exemplified with the help of data of various instruments acquired during several experimental campaigns in the field.

Automatic localization of the da Vinci surgical instrument tips in 3-D transrectal ultrasound.

PubMed

Mohareri, Omid; Ramezani, Mahdi; Adebar, Troy K; Abolmaesumi, Purang; Salcudean, Septimiu E

2013-09-01

Robot-assisted laparoscopic radical prostatectomy (RALRP) using the da Vinci surgical system is the current state-of-the-art treatment option for clinically confined prostate cancer. Given the limited field of view of the surgical site in RALRP, several groups have proposed the integration of transrectal ultrasound (TRUS) imaging in the surgical workflow to assist with accurate resection of the prostate and the sparing of the neurovascular bundles (NVBs). We previously introduced a robotic TRUS manipulator and a method for automatically tracking da Vinci surgical instruments with the TRUS imaging plane, in order to facilitate the integration of intraoperative TRUS in RALRP. Rapid and automatic registration of the kinematic frames of the da Vinci surgical system and the robotic TRUS probe manipulator is a critical component of the instrument tracking system. In this paper, we propose a fully automatic registration technique based on automatic 3-D TRUS localization of robot instrument tips pressed against the air-tissue boundary anterior to the prostate. The detection approach uses a multiscale filtering technique to identify and localize surgical instrument tips in the TRUS volume, and could also be used to detect other surface fiducials in 3-D ultrasound. Experiments have been performed using a tissue phantom and two ex vivo tissue samples to show the feasibility of the proposed methods. Also, an initial in vivo evaluation of the system has been carried out on a live anaesthetized dog with a da Vinci Si surgical system and a target registration error (defined as the root mean square distance of corresponding points after registration) of 2.68 mm has been achieved. Results show this method's accuracy and consistency for automatic registration of TRUS images to the da Vinci surgical system.

A non-parametric automatic blending methodology to estimate rainfall fields from rain gauge and radar data

NASA Astrophysics Data System (ADS)

Velasco-Forero, Carlos A.; Sempere-Torres, Daniel; Cassiraga, Eduardo F.; Jaime Gómez-Hernández, J.

2009-07-01

Quantitative estimation of rainfall fields has been a crucial objective from early studies of the hydrological applications of weather radar. Previous studies have suggested that flow estimations are improved when radar and rain gauge data are combined to estimate input rainfall fields. This paper reports new research carried out in this field. Classical approaches for the selection and fitting of a theoretical correlogram (or semivariogram) model (needed to apply geostatistical estimators) are avoided in this study. Instead, a non-parametric technique based on FFT is used to obtain two-dimensional positive-definite correlograms directly from radar observations, dealing with both the natural anisotropy and the temporal variation of the spatial structure of the rainfall in the estimated fields. Because these correlation maps can be automatically obtained at each time step of a given rainfall event, this technique might easily be used in operational (real-time) applications. This paper describes the development of the non-parametric estimator exploiting the advantages of FFT for the automatic computation of correlograms and provides examples of its application on a case study using six rainfall events. This methodology is applied to three different alternatives to incorporate the radar information (as a secondary variable), and a comparison of performances is provided. In particular, their ability to reproduce in estimated rainfall fields (i) the rain gauge observations (in a cross-validation analysis) and (ii) the spatial patterns of radar fields are analyzed. Results seem to indicate that the methodology of kriging with external drift [KED], in combination with the technique of automatically computing 2-D spatial correlograms, provides merged rainfall fields with good agreement with rain gauges and with the most accurate approach to the spatial tendencies observed in the radar rainfall fields, when compared with other alternatives analyzed.

Method and apparatus for telemetry adaptive bandwidth compression

NASA Technical Reports Server (NTRS)

Graham, Olin L.

1987-01-01

Methods and apparatus are provided for automatic and/or manual adaptive bandwidth compression of telemetry. An adaptive sampler samples a video signal from a scanning sensor and generates a sequence of sampled fields. Each field and range rate information from the sensor are hence sequentially transmitted to and stored in a multiple and adaptive field storage means. The field storage means then, in response to an automatic or manual control signal, transfers the stored sampled field signals to a video monitor in a form for sequential or simultaneous display of a desired number of stored signal fields. The sampling ratio of the adaptive sample, the relative proportion of available communication bandwidth allocated respectively to transmitted data and video information, and the number of fields simultaneously displayed are manually or automatically selectively adjustable in functional relationship to each other and detected range rate. In one embodiment, when relatively little or no scene motion is detected, the control signal maximizes sampling ratio and causes simultaneous display of all stored fields, thus maximizing resolution and bandwidth available for data transmission. When increased scene motion is detected, the control signal is adjusted accordingly to cause display of fewer fields. If greater resolution is desired, the control signal is adjusted to increase the sampling ratio.

Semantic Annotation of Complex Text Structures in Problem Reports

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Throop, David R.; Fleming, Land D.

2011-01-01

Text analysis is important for effective information retrieval from databases where the critical information is embedded in text fields. Aerospace safety depends on effective retrieval of relevant and related problem reports for the purpose of trend analysis. The complex text syntax in problem descriptions has limited statistical text mining of problem reports. The presentation describes an intelligent tagging approach that applies syntactic and then semantic analysis to overcome this problem. The tags identify types of problems and equipment that are embedded in the text descriptions. The power of these tags is illustrated in a faceted searching and browsing interface for problem report trending that combines automatically generated tags with database code fields and temporal information.

Bianchi identities and the automatic conservation of energy-momentum and angular momentum in general-relativistic field theories

NASA Astrophysics Data System (ADS)

Hehl, Friedrich W.; McCrea, J. Dermott

1986-03-01

Automatic conservation of energy-momentum and angular momentum is guaranteed in a gravitational theory if, via the field equations, the conservation laws for the material currents are reduced to the contracted Bianchi identities. We first execute an irreducible decomposition of the Bianchi identities in a Riemann-Cartan space-time. Then, starting from a Riemannian space-time with or without torsion, we determine those gravitational theories which have automatic conservation: general relativity and the Einstein-Cartan-Sciama-Kibble theory, both with cosmological constant, and the nonviable pseudoscalar model. The Poincaré gauge theory of gravity, like gauge theories of internal groups, has no automatic conservation in the sense defined above. This does not lead to any difficulties in principle. Analogies to 3-dimensional continuum mechanics are stressed throughout the article.

Use of AFIS for linking scenes of crime.

PubMed

Hefetz, Ido; Liptz, Yakir; Vaturi, Shaul; Attias, David

2016-05-01

Forensic intelligence can provide critical information in criminal investigations - the linkage of crime scenes. The Automatic Fingerprint Identification System (AFIS) is an example of a technological improvement that has advanced the entire forensic identification field to strive for new goals and achievements. In one example using AFIS, a series of burglaries into private apartments enabled a fingerprint examiner to search latent prints from different burglary scenes against an unsolved latent print database. Latent finger and palm prints coming from the same source were associated with over than 20 cases. Then, by forensic intelligence and profile analysis the offender's behavior could be anticipated. He was caught, identified, and arrested. It is recommended to perform an AFIS search of LT/UL prints against current crimes automatically as part of laboratory protocol and not by an examiner's discretion. This approach may link different crime scenes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The pull of the past: when do habits persist despite conflict with motives?

PubMed

Neal, David T; Wood, Wendy; Wu, Mengju; Kurlander, David

2011-11-01

To identify the factors that disrupt and maintain habit performance, two field experiments tested the conditions under which people eat out of habit, leading them to resist motivational influences. Habitual popcorn eaters at a cinema were minimally influenced by their hunger or how much they liked the food, and they ate equal amounts of stale and fresh popcorn. Yet, mechanisms of automaticity influenced habit performance: Participants ate out of habit, regardless of freshness, only when currently in the context associated with past performance (i.e., a cinema; Study 1) and only when eating in a way that allowed them to automatically execute the response cued by that context (i.e., eating with their dominant hand; Study 2). Across all conditions, participants with weaker cinema-popcorn-eating habits ate because of motivations such as liking for the popcorn. The findings reveal how habits resist conflicting motives and provide insight into promising mechanisms of habit change.

Longwall Guidance and Control Development

NASA Technical Reports Server (NTRS)

1982-01-01

The longwall guidance and control (G&C) system was evaluated to determine which systems and subsystems lent themselves to automatic control in the mining of coal. The upper coal/shale interface was identified as the reference for a vertical G&C system, with two sensors (the natural backgound and the sensitized pick) being used to locate and track this boundary. In order to insure a relatively smooth recession surface (roof and floor of the excavated seam), a last and present cut measuring instrument (acoustic sensor) was used. Potentiometers were used to measure elevations of the shearer arms. The intergration of these components comprised the vertical control system (pitch control). Yaw and roll control were incorporated into a face alignment system which was designed to keep the coal face normal to its external boundaries. Numerous tests, in the laboratory and in the field, have confirmed the feasibility of automatic horizon control, as well as determining the face alignment.

Automatic Multi-sensor Data Quality Checking and Event Detection for Environmental Sensing

NASA Astrophysics Data System (ADS)

LIU, Q.; Zhang, Y.; Zhao, Y.; Gao, D.; Gallaher, D. W.; Lv, Q.; Shang, L.

2017-12-01

With the advances in sensing technologies, large-scale environmental sensing infrastructures are pervasively deployed to continuously collect data for various research and application fields, such as air quality study and weather condition monitoring. In such infrastructures, many sensor nodes are distributed in a specific area and each individual sensor node is capable of measuring several parameters (e.g., humidity, temperature, and pressure), providing massive data for natural event detection and analysis. However, due to the dynamics of the ambient environment, sensor data can be contaminated by errors or noise. Thus, data quality is still a primary concern for scientists before drawing any reliable scientific conclusions. To help researchers identify potential data quality issues and detect meaningful natural events, this work proposes a novel algorithm to automatically identify and rank anomalous time windows from multiple sensor data streams. More specifically, (1) the algorithm adaptively learns the characteristics of normal evolving time series and (2) models the spatial-temporal relationship among multiple sensor nodes to infer the anomaly likelihood of a time series window for a particular parameter in a sensor node. Case studies using different data sets are presented and the experimental results demonstrate that the proposed algorithm can effectively identify anomalous time windows, which may resulted from data quality issues and natural events.

NEXUS: tracing the cosmic web connection

NASA Astrophysics Data System (ADS)

Cautun, Marius; van de Weygaert, Rien; Jones, Bernard J. T.

2013-02-01

We introduce the NEXUS algorithm for the identification of cosmic web environments: clusters, filaments, walls and voids. This is a multiscale and automatic morphological analysis tool that identifies all the cosmic structures in a scale free way, without preference for a certain size or shape. We develop the NEXUS method to incorporate the density, tidal field, velocity divergence and velocity shear as tracers of the cosmic web. We also present the NEXUS+ procedure which, taking advantage of a novel filtering of the density in logarithmic space, is very successful at identifying the filament and wall environments in a robust and natural way. To assess the algorithms we apply them to an N-body simulation. We find that all methods correctly identify the most prominent filaments and walls, while there are differences in the detection of the more tenuous structures. In general, the structures traced by the density and tidal fields are clumpier and more rugged than those present in the velocity divergence and velocity shear fields. We find that the NEXUS+ method captures much better the filamentary and wall networks and is successful in detecting even the fainter structures. We also confirm the efficiency of our methods by examining the dark matter particle and halo distributions.

Robust Crop and Weed Segmentation under Uncontrolled Outdoor Illumination

PubMed Central

Jeon, Hong Y.; Tian, Lei F.; Zhu, Heping

2011-01-01

An image processing algorithm for detecting individual weeds was developed and evaluated. Weed detection processes included were normalized excessive green conversion, statistical threshold value estimation, adaptive image segmentation, median filter, morphological feature calculation and Artificial Neural Network (ANN). The developed algorithm was validated for its ability to identify and detect weeds and crop plants under uncontrolled outdoor illuminations. A machine vision implementing field robot captured field images under outdoor illuminations and the image processing algorithm automatically processed them without manual adjustment. The errors of the algorithm, when processing 666 field images, ranged from 2.1 to 2.9%. The ANN correctly detected 72.6% of crop plants from the identified plants, and considered the rest as weeds. However, the ANN identification rates for crop plants were improved up to 95.1% by addressing the error sources in the algorithm. The developed weed detection and image processing algorithm provides a novel method to identify plants against soil background under the uncontrolled outdoor illuminations, and to differentiate weeds from crop plants. Thus, the proposed new machine vision and processing algorithm may be useful for outdoor applications including plant specific direct applications (PSDA). PMID:22163954

General relativity as the effective theory of GL(4,R) spontaneous symmetry breaking

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

Tomboulis, E. T.

2011-10-15

We assume a GL(4,R) space-time symmetry which is spontaneously broken to SO(3,1). We carry out the coset construction of the effective theory for the nonlinearly realized broken symmetry in terms of the Goldstone fields and matter fields transforming linearly under the unbroken Lorentz subgroup. We then identify functions of the Goldstone and matter fields that transform linearly also under the broken symmetry. Expressed in terms of these quantities the effective theory reproduces the vierbein formalism of general relativity with general coordinate invariance being automatically realized nonlinearly over GL(4,R). The coset construction makes no assumptions about any underlying theory that mightmore » be responsible for the assumed symmetry breaking. We give a brief discussion of the possibility of field theories with GL(4,R) rather than Lorentz space-time symmetry providing the underlying dynamics.« less

Template-based automatic extraction of the joint space of foot bones from CT scan

NASA Astrophysics Data System (ADS)

Park, Eunbi; Kim, Taeho; Park, Jinah

2016-03-01

Clean bone segmentation is critical in studying the joint anatomy for measuring the spacing between the bones. However, separation of the coupled bones in CT images is sometimes difficult due to ambiguous gray values coming from the noise and the heterogeneity of bone materials as well as narrowing of the joint space. For fine reconstruction of the individual local boundaries, manual operation is a common practice where the segmentation remains to be a bottleneck. In this paper, we present an automatic method for extracting the joint space by applying graph cut on Markov random field model to the region of interest (ROI) which is identified by a template of 3D bone structures. The template includes encoded articular surface which identifies the tight region of the high-intensity bone boundaries together with the fuzzy joint area of interest. The localized shape information from the template model within the ROI effectively separates the bones nearby. By narrowing the ROI down to the region including two types of tissue, the object extraction problem was reduced to binary segmentation and solved via graph cut. Based on the shape of a joint space marked by the template, the hard constraint was set by the initial seeds which were automatically generated from thresholding and morphological operations. The performance and the robustness of the proposed method are evaluated on 12 volumes of ankle CT data, where each volume includes a set of 4 tarsal bones (calcaneus, talus, navicular and cuboid).

An Auto-Tuning PI Control System for an Open-Circuit Low-Speed Wind Tunnel Designed for Greenhouse Technology

PubMed Central

Espinoza, Karlos; Valera, Diego L.; Torres, José A.; López, Alejandro; Molina-Aiz, Francisco D.

2015-01-01

Wind tunnels are a key experimental tool for the analysis of airflow parameters in many fields of application. Despite their great potential impact on agricultural research, few contributions have dealt with the development of automatic control systems for wind tunnels in the field of greenhouse technology. The objective of this paper is to present an automatic control system that provides precision and speed of measurement, as well as efficient data processing in low-speed wind tunnel experiments for greenhouse engineering applications. The system is based on an algorithm that identifies the system model and calculates the optimum PI controller. The validation of the system was performed on a cellulose evaporative cooling pad and on insect-proof screens to assess its response to perturbations. The control system provided an accuracy of <0.06 m·s−1 for airflow speed and <0.50 Pa for pressure drop, thus permitting the reproducibility and standardization of the tests. The proposed control system also incorporates a fully-integrated software unit that manages the tests in terms of airflow speed and pressure drop set points. PMID:26274962

An Automatic Portable Telecine Camera.

DTIC Science & Technology

1978-08-01

five television frames to achieve synchronous operation, that is about 0.2 second. 6.3 Video recorder noise imnunity The synchronisation pulse separator...display is filmed by a modified 16 am cine camera driven by a control unit in which the camera supply voltage is derived from the field synchronisation ...pulses of the video signal. Automatic synchronisation of the camera mechanism is achieved over a wide range of television field frequencies and the

Recognizing patterns of visual field loss using unsupervised machine learning

NASA Astrophysics Data System (ADS)

Yousefi, Siamak; Goldbaum, Michael H.; Zangwill, Linda M.; Medeiros, Felipe A.; Bowd, Christopher

2014-03-01

Glaucoma is a potentially blinding optic neuropathy that results in a decrease in visual sensitivity. Visual field abnormalities (decreased visual sensitivity on psychophysical tests) are the primary means of glaucoma diagnosis. One form of visual field testing is Frequency Doubling Technology (FDT) that tests sensitivity at 52 points within the visual field. Like other psychophysical tests used in clinical practice, FDT results yield specific patterns of defect indicative of the disease. We used Gaussian Mixture Model with Expectation Maximization (GEM), (EM is used to estimate the model parameters) to automatically separate FDT data into clusters of normal and abnormal eyes. Principal component analysis (PCA) was used to decompose each cluster into different axes (patterns). FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal (i.e., glaucomatous) FDT results, recruited from a university-based, longitudinal, multi-center, clinical study on glaucoma. The GEM input was the 52-point FDT threshold sensitivities for all eyes. The optimal GEM model separated the FDT fields into 3 clusters. Cluster 1 contained 94% normal fields (94% specificity) and clusters 2 and 3 combined, contained 77% abnormal fields (77% sensitivity). For clusters 1, 2 and 3 the optimal number of PCA-identified axes were 2, 2 and 5, respectively. GEM with PCA successfully separated FDT fields from healthy and glaucoma eyes and identified familiar glaucomatous patterns of loss.

Automatic multiple applicator electrophoresis

NASA Technical Reports Server (NTRS)

Grunbaum, B. W.

1977-01-01

Easy-to-use, economical device permits electrophoresis on all known supporting media. System includes automatic multiple-sample applicator, sample holder, and electrophoresis apparatus. System has potential applicability to fields of taxonomy, immunology, and genetics. Apparatus is also used for electrofocusing.

Distributed automatic control of technological processes in conditions of weightlessness

NASA Technical Reports Server (NTRS)

Kukhtenko, A. I.; Merkulov, V. I.; Samoylenko, Y. I.; Ladikov-Royev, Y. P.

1986-01-01

Some problems associated with the automatic control of liquid metal and plasma systems under conditions of weightlessness are examined, with particular reference to the problem of stability of liquid equilibrium configurations. The theoretical fundamentals of automatic control of processes in electrically conducting continuous media are outlined, and means of using electromagnetic fields for simulating technological processes in a space environment are discussed.

The Development of a Web-Based Assessment System to Identify Students' Misconception Automatically on Linear Kinematics with a Four-Tier Instrument Test

ERIC Educational Resources Information Center

Pujayanto, Pujayanto; Budiharti, Rini; Adhitama, Egy; Nuraini, Niken Rizky Amalia; Putri, Hanung Vernanda

2018-01-01

This research proposes the development of a web-based assessment system to identify students' misconception. The system, named WAS (web-based assessment system), can identify students' misconception profile on linear kinematics automatically after the student has finished the test. The test instrument was developed and validated. Items were…

[An automatic system controlled by microcontroller for carotid sinus perfusion].

PubMed

Yi, X L; Wang, M Y; Fan, Z Z; He, R R

2001-08-01

To establish a new method for controlling automatically the carotid perfusion pressure. A cheap practical automatic perfusion unit based on AT89C2051 micro controller was designed. The unit, LDB-M perfusion pump and the carotid sinus of an animal constituted an automatic perfusion system. This system was able to provide ramp and stepwise updown perfusion pattern and has been used in the research of baroreflex. It can insure the precision and reproducibility of perfusion pressure curve, and improve the technical level in corresponding medical field.

Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

PubMed

Grouin, Cyril; Zweigenbaum, Pierre

2013-01-01

In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

Biologically inspired EM image alignment and neural reconstruction.

PubMed

Knowles-Barley, Seymour; Butcher, Nancy J; Meinertzhagen, Ian A; Armstrong, J Douglas

2011-08-15

Three-dimensional reconstruction of consecutive serial-section transmission electron microscopy (ssTEM) images of neural tissue currently requires many hours of manual tracing and annotation. Several computational techniques have already been applied to ssTEM images to facilitate 3D reconstruction and ease this burden. Here, we present an alternative computational approach for ssTEM image analysis. We have used biologically inspired receptive fields as a basis for a ridge detection algorithm to identify cell membranes, synaptic contacts and mitochondria. Detected line segments are used to improve alignment between consecutive images and we have joined small segments of membrane into cell surfaces using a dynamic programming algorithm similar to the Needleman-Wunsch and Smith-Waterman DNA sequence alignment procedures. A shortest path-based approach has been used to close edges and achieve image segmentation. Partial reconstructions were automatically generated and used as a basis for semi-automatic reconstruction of neural tissue. The accuracy of partial reconstructions was evaluated and 96% of membrane could be identified at the cost of 13% false positive detections. An open-source reference implementation is available in the Supplementary information. seymour.kb@ed.ac.uk; douglas.armstrong@ed.ac.uk Supplementary data are available at Bioinformatics online.

Electronic surveillance and using administrative data to identify healthcare associated infections.

PubMed

Gastmeier, Petra; Behnke, Michael

2016-08-01

Traditional surveillance of healthcare associated infections (HCAI) is time consuming and error-prone. We have analysed literature of the past year to look at new developments in this field. It is divided into three parts: new algorithms for electronic surveillance, the use of administrative data for surveillance of HCAI, and the definition of new endpoints of surveillance, in accordance with an automatic surveillance approach. Most studies investigating electronic surveillance of HCAI have concentrated on bloodstream infection or surgical site infection. However, the lack of important parameters in hospital databases can lead to misleading results. The accuracy of administrative coding data was poor at identifying HCAI. New endpoints should be defined for automatic detection, with the most crucial step being to win clinicians' acceptance. Electronic surveillance with conventional endpoints is a successful method when hospital information systems implemented key changes and enhancements. One requirement is the access to systems for hospital administration and clinical databases.Although the primary source of data for HCAI surveillance is not administrative coding data, these are important components of a hospital-wide programme of automated surveillance. The implementation of new endpoints for surveillance is an approach which needs to be discussed further.

ADOPT: A tool for automatic detection of tectonic plates at the surface of convection models

NASA Astrophysics Data System (ADS)

Mallard, C.; Jacquet, B.; Coltice, N.

2017-08-01

Mantle convection models with plate-like behavior produce surface structures comparable to Earth's plate boundaries. However, analyzing those structures is a difficult task, since convection models produce, as on Earth, diffuse deformation and elusive plate boundaries. Therefore we present here and share a quantitative tool to identify plate boundaries and produce plate polygon layouts from results of numerical models of convection: Automatic Detection Of Plate Tectonics (ADOPT). This digital tool operates within the free open-source visualization software Paraview. It is based on image segmentation techniques to detect objects. The fundamental algorithm used in ADOPT is the watershed transform. We transform the output of convection models into a topographic map, the crest lines being the regions of deformation (plate boundaries) and the catchment basins being the plate interiors. We propose two generic protocols (the field and the distance methods) that we test against an independent visual detection of plate polygons. We show that ADOPT is effective to identify the smaller plates and to close plate polygons in areas where boundaries are diffuse or elusive. ADOPT allows the export of plate polygons in the standard OGR-GMT format for visualization, modification, and analysis under generic softwares like GMT or GPlates.

Adaptive Sensor Tuning for Seismic Event Detection in Environment with Electromagnetic Noise

NASA Astrophysics Data System (ADS)

Ziegler, Abra E.

The goal of this research is to detect possible microseismic events at a carbon sequestration site. Data recorded on a continuous downhole microseismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project, were evaluated using machine learning and reinforcement learning techniques to determine their effectiveness at seismic event detection on a dataset with electromagnetic noise. The data were recorded from a passive vertical monitoring array consisting of 16 levels of 3-component 15 Hz geophones installed in the field and continuously recording since January 2014. Electromagnetic and other noise recorded on the array has significantly impacted the utility of the data and it was necessary to characterize and filter the noise in order to attempt event detection. Traditional detection methods using short-term average/long-term average (STA/LTA) algorithms were evaluated and determined to be ineffective because of changing noise levels. To improve the performance of event detection and automatically and dynamically detect seismic events using effective data processing parameters, an adaptive sensor tuning (AST) algorithm developed by Sandia National Laboratories was utilized. AST exploits neuro-dynamic programming (reinforcement learning) trained with historic event data to automatically self-tune and determine optimal detection parameter settings. The key metric that guides the AST algorithm is consistency of each sensor with its nearest neighbors: parameters are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The effects that changes in neighborhood configuration have on signal detection were explored, as it was determined that neighborhood-based detections significantly reduce the number of both missed and false detections in ground-truthed data. The performance of the AST algorithm was quantitatively evaluated during a variety of noise conditions and seismic detections were identified using AST and compared to ancillary injection data. During a period of CO2 injection in a nearby well to the monitoring array, 82% of seismic events were accurately detected, 13% of events were missed, and 5% of detections were determined to be false. Additionally, seismic risk was evaluated from the stress field and faulting regime at FWU to determine the likelihood of pressure perturbations to trigger slip on previously mapped faults. Faults oriented NW-SE were identified as requiring the smallest pore pressure changes to trigger slip and faults oriented N-S will also potentially be reactivated although this is less likely.

Automatic Positioning System of Small Agricultural Robot

NASA Astrophysics Data System (ADS)

Momot, M. V.; Proskokov, A. V.; Natalchenko, A. S.; Biktimirov, A. S.

2016-08-01

The present article discusses automatic positioning systems of agricultural robots used in field works. The existing solutions in this area have been analyzed. The article proposes an original solution, which is easy to implement and is characterized by high- accuracy positioning.

Abbreviation definition identification based on automatic precision estimates.

PubMed

Sohn, Sunghwan; Comeau, Donald C; Kim, Won; Wilbur, W John

2008-09-25

The rapid growth of biomedical literature presents challenges for automatic text processing, and one of the challenges is abbreviation identification. The presence of unrecognized abbreviations in text hinders indexing algorithms and adversely affects information retrieval and extraction. Automatic abbreviation definition identification can help resolve these issues. However, abbreviations and their definitions identified by an automatic process are of uncertain validity. Due to the size of databases such as MEDLINE only a small fraction of abbreviation-definition pairs can be examined manually. An automatic way to estimate the accuracy of abbreviation-definition pairs extracted from text is needed. In this paper we propose an abbreviation definition identification algorithm that employs a variety of strategies to identify the most probable abbreviation definition. In addition our algorithm produces an accuracy estimate, pseudo-precision, for each strategy without using a human-judged gold standard. The pseudo-precisions determine the order in which the algorithm applies the strategies in seeking to identify the definition of an abbreviation. On the Medstract corpus our algorithm produced 97% precision and 85% recall which is higher than previously reported results. We also annotated 1250 randomly selected MEDLINE records as a gold standard. On this set we achieved 96.5% precision and 83.2% recall. This compares favourably with the well known Schwartz and Hearst algorithm. We developed an algorithm for abbreviation identification that uses a variety of strategies to identify the most probable definition for an abbreviation and also produces an estimated accuracy of the result. This process is purely automatic.

Discovering new events beyond the catalogue—application of empirical matched field processing to Salton Sea geothermal field seismicity

DOE PAGES

Wang, Jingbo; Templeton, Dennise C.; Harris, David B.

2015-07-30

Using empirical matched field processing (MFP), we compare 4 yr of continuous seismic data to a set of 195 master templates from within an active geothermal field and identify over 140 per cent more events than were identified using traditional detection and location techniques alone. In managed underground reservoirs, a substantial fraction of seismic events can be excluded from the official catalogue due to an inability to clearly identify seismic-phase onsets. Empirical MFP can improve the effectiveness of current seismic detection and location methodologies by using conventionally located events with higher signal-to-noise ratios as master events to define wavefield templatesmore » that could then be used to map normally discarded indistinct seismicity. Since MFP does not require picking, it can be carried out automatically and rapidly once suitable templates are defined. In this application, we extend MFP by constructing local-distance empirical master templates using Southern California Earthquake Data Center archived waveform data of events originating within the Salton Sea Geothermal Field. We compare the empirical templates to continuous seismic data collected between 1 January 2008 and 31 December 2011. The empirical MFP method successfully identifies 6249 additional events, while the original catalogue reported 4352 events. The majority of these new events are lower-magnitude events with magnitudes between M0.2–M0.8. Here, the increased spatial-temporal resolution of the microseismicity map within the geothermal field illustrates how empirical MFP, when combined with conventional methods, can significantly improve seismic network detection capabilities, which can aid in long-term sustainability and monitoring of managed underground reservoirs.« less

Wide-Field Imaging Telescope-0 (WIT0) with automatic observing system

NASA Astrophysics Data System (ADS)

Ji, Tae-Geun; Byeon, Seoyeon; Lee, Hye-In; Park, Woojin; Lee, Sang-Yun; Hwang, Sungyong; Choi, Changsu; Gibson, Coyne Andrew; Kuehne, John W.; Prochaska, Travis; Marshall, Jennifer L.; Im, Myungshin; Pak, Soojong

2018-01-01

We introduce Wide-Field Imaging Telescope-0 (WIT0), with an automatic observing system. It is developed for monitoring the variabilities of many sources at a time, e.g. young stellar objects and active galactic nuclei. It can also find the locations of transient sources such as a supernova or gamma-ray bursts. In 2017 February, we installed the wide-field 10-inch telescope (Takahashi CCA-250) as a piggyback system on the 30-inch telescope at the McDonald Observatory in Texas, US. The 10-inch telescope has a 2.35 × 2.35 deg field-of-view with a 4k × 4k CCD Camera (FLI ML16803). To improve the observational efficiency of the system, we developed a new automatic observing software, KAOS30 (KHU Automatic Observing Software for McDonald 30-inch telescope), which was developed by Visual C++ on the basis of a windows operating system. The software consists of four control packages: the Telescope Control Package (TCP), the Data Acquisition Package (DAP), the Auto Focus Package (AFP), and the Script Mode Package (SMP). Since it also supports the instruments that are using the ASCOM driver, the additional hardware installations become quite simplified. We commissioned KAOS30 in 2017 August and are in the process of testing. Based on the WIT0 experiences, we will extend KAOS30 to control multiple telescopes in future projects.

The Associate Principal Astronomer for AI Management of Automatic Telescopes

NASA Technical Reports Server (NTRS)

Henry, Gregory W.

1998-01-01

This research program in scheduling and management of automatic telescopes had the following objectives: 1. To field test the 1993 Automatic Telescope Instruction Set (ATIS93) programming language, which was specifically developed to allow real-time control of an automatic telescope via an artificial intelligence scheduler running on a remote computer. 2. To develop and test the procedures for two-way communication between a telescope controller and remote scheduler via the Internet. 3. To test various concepts in Al scheduling being developed at NASA Ames Research Center on an automatic telescope operated by Tennessee State University at the Fairborn Observatory site in southern Arizona. and 4. To develop a prototype software package, dubbed the Associate Principal Astronomer, for the efficient scheduling and management of automatic telescopes.

Research progress of on-line automatic monitoring of chemical oxygen demand (COD) of water

NASA Astrophysics Data System (ADS)

Cai, Youfa; Fu, Xing; Gao, Xiaolu; Li, Lianyin

2018-02-01

With the increasingly stricter control of pollutant emission in China, the on-line automatic monitoring of water quality is particularly urgent. The chemical oxygen demand (COD) is a comprehensive index to measure the contamination caused by organic matters, and thus it is taken as one important index of energy-saving and emission reduction in China’s “Twelve-Five” program. So far, the COD on-line automatic monitoring instrument has played an important role in the field of sewage monitoring. This paper reviews the existing methods to achieve on-line automatic monitoring of COD, and on the basis, points out the future trend of the COD on-line automatic monitoring instruments.

75 FR 68200 - Medical Devices; Radiology Devices; Reclassification of Full-Field Digital Mammography System

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-05

... exposure control, image processing and reconstruction programs, patient and equipment supports, component..., acquisition workstation, automatic exposure control, image processing and reconstruction programs, patient and... may include was revised by adding automatic exposure control, image processing and reconstruction...

Optical Automatic Car Identification (OACI) Field Test Program

DOT National Transportation Integrated Search

1976-05-01

The results of the Optical Automatic Car Identification (OACI) tests at Chicago conducted from August 16 to September 4, 1975 are presented. The main purpose of this test was to determine the suitability of optics as a principle of operation for an a...

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.

Automated Sensor Tuning for Seismic Event Detection at a Carbon Capture, Utilization, and Storage Site, Farnsworth Unit, Ochiltree County, Texas

NASA Astrophysics Data System (ADS)

Ziegler, A.; Balch, R. S.; Knox, H. A.; Van Wijk, J. W.; Draelos, T.; Peterson, M. G.

2016-12-01

We present results (e.g. seismic detections and STA/LTA detection parameters) from a continuous downhole seismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project. Specifically, we evaluate data from a passive vertical monitoring array consisting of 16 levels of 3-component 15Hz geophones installed in the field and continuously recording since January 2014. This detection database is directly compared to ancillary data (i.e. wellbore pressure) to determine if there is any relationship between seismic observables and CO2 injection and pressure maintenance in the field. Of particular interest is detection of relatively low-amplitude signals constituting long-period long-duration (LPLD) events that may be associated with slow shear-slip analogous to low frequency tectonic tremor. While this category of seismic event provides great insight into dynamic behavior of the pressurized subsurface, it is inherently difficult to detect. To automatically detect seismic events using effective data processing parameters, an automated sensor tuning (AST) algorithm developed by Sandia National Laboratories is being utilized. AST exploits ideas from neuro-dynamic programming (reinforcement learning) to automatically self-tune and determine optimal detection parameter settings. AST adapts in near real-time to changing conditions and automatically self-tune a signal detector to identify (detect) only signals from events of interest, leading to a reduction in the number of missed legitimate event detections and the number of false event detections. Funding for this project is provided by the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) through the Southwest Regional Partnership on Carbon Sequestration (SWP) under Award No. DE-FC26-05NT42591. Additional support has been provided by site operator Chaparral Energy, L.L.C. and Schlumberger Carbon Services. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

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…

When benefits outweigh costs: reconsidering "automatic" phonological recoding when reading aloud.

PubMed

Robidoux, Serje; Besner, Derek

2011-06-01

Skilled readers are slower to read aloud exception words (e.g., PINT) than regular words (e.g., MINT). In the case of exception words, sublexical knowledge competes with the correct pronunciation driven by lexical knowledge, whereas no such competition occurs for regular words. The dominant view is that the cost of this "regularity" effect is evidence that sublexical spelling-sound conversion is impossible to prevent (i.e., is "automatic"). This view has become so reified that the field rarely questions it. However, the results of simulations from the most successful computational models on the table suggest that the claim of "automatic" sublexical phonological recoding is premature given that there is also a benefit conferred by sublexical processing. Taken together with evidence from skilled readers that sublexical phonological recoding can be stopped, we suggest that the field is too narrowly focused when it asserts that sublexical phonological recoding is "automatic" and that a broader, more nuanced and contextually driven approach provides a more useful framework.

LAMOST OBSERVATIONS IN THE KEPLER FIELD: SPECTRAL CLASSIFICATION WITH THE MKCLASS CODE

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

Gray, R. O.; Corbally, C. J.; Cat, P. De

2016-01-15

The LAMOST-Kepler project was designed to obtain high-quality, low-resolution spectra of many of the stars in the Kepler field with the Large Sky Area Multi Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic telescope. To date 101,086 spectra of 80,447 objects over the entire Kepler field have been acquired. Physical parameters, radial velocities, and rotational velocities of these stars will be reported in other papers. In this paper we present MK spectral classifications for these spectra determined with the automatic classification code MKCLASS. We discuss the quality and reliability of the spectral types and present histograms showing the frequency of the spectralmore » types in the main table organized according to luminosity class. Finally, as examples of the use of this spectral database, we compute the proportion of A-type stars that are Am stars, and identify 32 new barium dwarf candidates.« less

An overview of animal science research 1945-2011 through science mapping analysis.

PubMed

Rodriguez-Ledesma, A; Cobo, M J; Lopez-Pujalte, C; Herrera-Viedma, E

2015-12-01

The conceptual structure of the field of Animal Science (AS) research is examined by means of a longitudinal science mapping analysis. The whole of the AS research field is analysed, revealing its conceptual evolution. To this end, an automatic approach to detecting and visualizing hidden themes or topics and their evolution across a consecutive span of years was applied to AS publications of the JCR category 'Agriculture, Dairy & Animal Science' during the period 1945-2011. This automatic approach was based on a coword analysis and combines performance analysis and science mapping. To observe the conceptual evolution of AS, six consecutive periods were defined: 1945-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2005 and 2006-2011. Research in AS was identified as having focused on ten main thematic areas: ANIMAL-FEEDING, SMALL-RUMINANTS, ANIMAL-REPRODUCTION, DAIRY-PRODUCTION, MEAT-QUALITY, SWINE-PRODUCTION, GENETICS-AND-ANIMAL-BREEDING, POULTRY, ANIMAL-WELFARE and GROWTH-FACTORS-AND-FATTY-ACIDS. The results show how genomic studies gain in weight and integrate with other thematic areas. The whole of AS research has become oriented towards an overall framework in which animal welfare, sustainable management and human health play a major role. All this would affect the future structure and management of livestock farming. © 2014 Blackwell Verlag GmbH.

The Potential of Automatic Word Comparison for Historical Linguistics.

PubMed

List, Johann-Mattis; Greenhill, Simon J; Gray, Russell D

2017-01-01

The amount of data from languages spoken all over the world is rapidly increasing. Traditional manual methods in historical linguistics need to face the challenges brought by this influx of data. Automatic approaches to word comparison could provide invaluable help to pre-analyze data which can be later enhanced by experts. In this way, computational approaches can take care of the repetitive and schematic tasks leaving experts to concentrate on answering interesting questions. Here we test the potential of automatic methods to detect etymologically related words (cognates) in cross-linguistic data. Using a newly compiled database of expert cognate judgments across five different language families, we compare how well different automatic approaches distinguish related from unrelated words. Our results show that automatic methods can identify cognates with a very high degree of accuracy, reaching 89% for the best-performing method Infomap. We identify the specific strengths and weaknesses of these different methods and point to major challenges for future approaches. Current automatic approaches for cognate detection-although not perfect-could become an important component of future research in historical linguistics.

The Potential of Automatic Word Comparison for Historical Linguistics

PubMed Central

Greenhill, Simon J.; Gray, Russell D.

2017-01-01

The amount of data from languages spoken all over the world is rapidly increasing. Traditional manual methods in historical linguistics need to face the challenges brought by this influx of data. Automatic approaches to word comparison could provide invaluable help to pre-analyze data which can be later enhanced by experts. In this way, computational approaches can take care of the repetitive and schematic tasks leaving experts to concentrate on answering interesting questions. Here we test the potential of automatic methods to detect etymologically related words (cognates) in cross-linguistic data. Using a newly compiled database of expert cognate judgments across five different language families, we compare how well different automatic approaches distinguish related from unrelated words. Our results show that automatic methods can identify cognates with a very high degree of accuracy, reaching 89% for the best-performing method Infomap. We identify the specific strengths and weaknesses of these different methods and point to major challenges for future approaches. Current automatic approaches for cognate detection—although not perfect—could become an important component of future research in historical linguistics. PMID:28129337

Automatic NMR field-frequency lock-pulsed phase locked loop approach.

PubMed

Kan, S; Gonord, P; Fan, M; Sauzade, M; Courtieu, J

1978-06-01

A self-contained deuterium frequency-field lock scheme for a high-resolution NMR spectrometer is described. It is based on phase locked loop techniques in which the free induction decay signal behaves as a voltage-controlled oscillator. By pulsing the spins at an offset frequency of a few hundred hertz and using a digital phase-frequency discriminator this method not only eliminates the usual phase, rf power, offset adjustments needed in conventional lock systems but also possesses the automatic pull-in characteristics that dispense with the use of field sweeps to locate the NMR line prior to closure of the lock loop.

Which Way Is the Flow?

NASA Technical Reports Server (NTRS)

Kao, David

1999-01-01

The line integral convolution (LIC) technique has been known to be an effective tool for depicting flow patterns in a given vector field. There have been many extensions to make it run faster and reveal useful flow information such as velocity magnitude, motion, and direction. There are also extensions to unsteady flows and 3D vector fields. Surprisingly, none of these extensions automatically highlight flow features, which often represent the most important and interesting physical flow phenomena. In this sketch, a method for highlighting flow direction in LIC images is presented. The method gives an intuitive impression of flow direction in the given vector field and automatically reveals saddle points in the flow.

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).

The Electronic McPhail Trap

PubMed Central

Potamitis, Ilyas; Rigakis, Iraklis; Fysarakis, Konstantinos

2014-01-01

Certain insects affect cultivations in a detrimental way. A notable case is the olive fruit fly (Bactrocera oleae (Rossi)), that in Europe alone causes billions of euros in crop-loss/per year. Pests can be controlled with aerial and ground bait pesticide sprays, the efficiency of which depends on knowing the time and location of insect infestations as early as possible. The inspection of traps is currently carried out manually. Automatic monitoring traps can enhance efficient monitoring of flying pests by identifying and counting targeted pests as they enter the trap. This work deals with the hardware setup of an insect trap with an embedded optoelectronic sensor that automatically records insects as they fly in the trap. The sensor responsible for detecting the insect is an array of phototransistors receiving light from an infrared LED. The wing-beat recording is based on the interruption of the emitted light due to the partial occlusion from insect's wings as they fly in the trap. We show that the recordings are of high quality paving the way for automatic recognition and transmission of insect detections from the field to a smartphone. This work emphasizes the hardware implementation of the sensor and the detection/counting module giving all necessary implementation details needed to construct it. PMID:25429412

Algorithm Summary and Evaluation: Automatic Implementation of Ringdown Analysis for Electromechanical Mode Identification from Phasor Measurements

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

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

2010-02-28

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 develops a recursive algorithm for implementing Prony analysis and proposed an oscillation detection method to detect ringdown data in real time. By automatically detecting 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. In addition, the proposed method is applied to field measurement data from WECC to show the performance of the proposed algorithm.« less

Markov random field based automatic image alignment for electron tomography.

PubMed

Amat, Fernando; Moussavi, Farshid; Comolli, Luis R; Elidan, Gal; Downing, Kenneth H; Horowitz, Mark

2008-03-01

We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.

The effects of presession manipulations on automatically maintained challenging behavior and task responding.

PubMed

Chung, Yi-Chieh; Cannella-Malone, Helen I

2010-11-01

This study examined the effects of presession exposure to attention, response blocking, attention with response blocking, and noninteraction conditions on subsequent engagement in automatically maintained challenging behavior and correct responding in four individuals with significant intellectual disabilities. Following a functional analysis, the effects of the four presession conditions were examined using multielement designs. Results varied across the 4 participants (e.g., presession noninteraction acted as an abolishing operation for 2 participants, but as an establishing operation for the other 2 participants). As such, both the results replicated and contradicted previous research examining the effects of motivating operations on automatically maintained challenging behavior. Although the results varied across participants, at least one condition resulting in a decrease in challenging behavior and an increase in correct responding were identified for each participant. These findings suggested that presession manipulations resulted in decreases in subsequent automatically maintained challenging behavior and simultaneous increases in correct responding might need to be individually identified when the maintaining contingencies cannot be identified.

Towards Automatically Aligning German Compounds with English Word Groups in an Example-Based Translation System.

ERIC Educational Resources Information Center

Jones, Daniel; Alexa, Melina

As part of the development of a completely sub-symbolic machine translation system, a method for automatically identifying German compounds was developed. Given a parallel bilingual corpus, German compounds are identified along with their English word groupings by statistical processing alone. The underlying principles and the design process are…

Graphonomics, Automaticity and Handwriting Assessment

ERIC Educational Resources Information Center

Tucha, Oliver; Tucha, Lara; Lange, Klaus W.

2008-01-01

A recent review of handwriting research in "Literacy" concluded that current curricula of handwriting education focus too much on writing style and neatness and neglect the aspect of handwriting automaticity. This conclusion is supported by evidence in the field of graphonomic research, where a range of experiments have been used to investigate…

Very Portable Remote Automatic Weather Stations

Treesearch

John R. Warren

1987-01-01

Remote Automatic Weather Stations (RAWS) were introduced to Forest Service and Bureau of Land Management field units in 1978 following development, test, and evaluation activities conducted jointly by the two agencies. The original configuration was designed for semi-permanent installation. Subsequently, a need for a more portable RAWS was expressed, and one was...

Research in Automatic Russian-English Scientific and Technical Lexicography. Final Report.

ERIC Educational Resources Information Center

Wayne State Univ., Detroit, MI.

Techniques of reversing English-Russian scientific and technical dictionaries into Russian-English versions through semi-automated compilation are described. Sections on manual and automatic processing discuss pre- and post-editing, the task program, updater (correction of errors and revision by specialist in a given field), the system employed…

DLA based compressed sensing for high resolution MR microscopy of neuronal tissue

NASA Astrophysics Data System (ADS)

Nguyen, Khieu-Van; Li, Jing-Rebecca; Radecki, Guillaume; Ciobanu, Luisa

2015-10-01

In this work we present the implementation of compressed sensing (CS) on a high field preclinical scanner (17.2 T) using an undersampling trajectory based on the diffusion limited aggregation (DLA) random growth model. When applied to a library of images this approach performs better than the traditional undersampling based on the polynomial probability density function. In addition, we show that the method is applicable to imaging live neuronal tissues, allowing significantly shorter acquisition times while maintaining the image quality necessary for identifying the majority of neurons via an automatic cell segmentation algorithm.

Manufacturing polymer thin films in a micro-gravity environment

NASA Technical Reports Server (NTRS)

Vera, Ivan

1987-01-01

This project represents Venezuela's first scientific experiment in space. The apparatus for the automatic casting of two polymer thin films will be contained in NASA's Payload No. G-559 of the Get Away Special program for a future orbital space flight in the U.S. Space Shuttle. Semi-permeable polymer membranes have important applications in a variety of fields, such as medicine, energy, and pharmaceuticals and in general fluid separation processes, such as reverse osmosis, ultrafiltration, and electrodialysis. The casting of semi-permeable membranes in space will help to identify the roles of convection in determining the structure of these membranes.

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.

Parsing Citations in Biomedical Articles Using Conditional Random Fields

PubMed Central

Zhang, Qing; Cao, Yong-Gang; Yu, Hong

2011-01-01

Citations are used ubiquitously in biomedical full-text articles and play an important role for representing both the rhetorical structure and the semantic content of the articles. As a result, text mining systems will significantly benefit from a tool that automatically extracts the content of a citation. In this study, we applied the supervised machine-learning algorithms Conditional Random Fields (CRFs) to automatically parse a citation into its fields (e.g., Author, Title, Journal, and Year). With a subset of html format open-access PubMed Central articles, we report an overall 97.95% F1-score. The citation parser can be accessed at: http://www.cs.uwm.edu/~qing/projects/cithit/index.html. PMID:21419403

A Machine Vision System for Automatically Grading Hardwood Lumber - (Proceedings)

Treesearch

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas H. Drayer; Joe G. Tront; Philip A. Araman; Robert L. Brisbon

1990-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

Large-field high-resolution mosaic movies

NASA Astrophysics Data System (ADS)

Hammerschlag, Robert H.; Sliepen, Guus; Bettonvil, Felix C. M.; Jägers, Aswin P. L.; Sütterlin, Peter; Martin, Sara F.

2012-09-01

Movies with fields-of-view larger than normal for high-resolution telescopes will give a better understanding of processes on the Sun, such as filament and active region developments and their possible interactions. New active regions can influence, by their emergence, their environment to the extent of possibly serving as an igniter of the eruption of a nearby filament. A method to create a large field-of-view is to join several fields-of-view into a mosaic. Fields are imaged quickly one after another using fast telescope-pointing. Such a pointing cycle has been automated at the Dutch Open Telescope (DOT), a high-resolution solar telescope located on the Canary Island La Palma. The observer can draw with the computer mouse the desired total field in the guider-telescope image of the whole Sun. The guider telescope is equipped with an H-alpha filter and electronic enhancement of contrast in the image for good visibility of filaments and prominences. The number and positions of the subfields are calculated automatically and represented by an array of bright points indicating the subfield centers inside the drawn rectangle of the total field on the computer screen with the whole-sun image. When the exposures start the telescope repeats automatically the sequence of subfields. Automatic production of flats is also programmed including defocusing and fast motion over the solar disk of the image field. For the first time mosaic movies were programmed from stored information on automated telescope motions from one field to the next. The mosaic movies fill the gap between whole-sun images with limited resolution of synoptic telescopes including space instruments and small-field high-cadence movies of high-resolution solar telescopes.

The Eras and Trends of Automatic Short Answer Grading

ERIC Educational Resources Information Center

Burrows, Steven; Gurevych, Iryna; Stein, Benno

2015-01-01

Automatic short answer grading (ASAG) is the task of assessing short natural language responses to objective questions using computational methods. The active research in this field has increased enormously of late with over 80 papers fitting a definition of ASAG. However, the past efforts have generally been ad-hoc and non-comparable until…

Automatic Generation of Customized, Model Based Information Systems for Operations Management.

DTIC Science & Technology

The paper discusses the need for developing a customized, model based system to support management decision making in the field of operations ... management . It provides a critique of the current approaches available, formulates a framework to classify logistics decisions, and suggests an approach for the automatic development of logistics systems. (Author)

INFORMATION STORAGE AND RETRIEVAL, REPORTS ON EVALUATION PROCEDURES AND RESULTS 1965-1967.

ERIC Educational Resources Information Center

SALTON, GERALD

A DETAILED ANALYSIS OF THE RETRIEVAL EVALUATION RESULTS OBTAINED WITH THE AUTOMATIC SMART DOCUMENT RETRIEVAL SYSTEM FOR DOCUMENT COLLECTIONS IN THE FIELDS OF AERODYNAMICS, COMPUTER SCIENCE, AND DOCUMENTATION IS GIVEN IN THIS REPORT. THE VARIOUS COMPONENTS OF FULLY AUTOMATIC DOCUMENT RETRIEVAL SYSTEMS ARE DISCUSSED IN DETAIL, INCLUDING THE FORMS OF…

Integration of wireless sensor networks into automatic irrigation scheduling of a center pivot

USDA-ARS?s Scientific Manuscript database

A six-span center pivot system was used as a platform for testing two wireless sensor networks (WSN) of infrared thermometers. The cropped field was a semi-circle, divided into six pie shaped sections of which three were irrigated manually and three were irrigated automatically based on the time tem...

Towards parsimony in habit measurement: Testing the convergent and predictive validity of an automaticity subscale of the Self-Report Habit Index

PubMed Central

2012-01-01

Background The twelve-item Self-Report Habit Index (SRHI) is the most popular measure of energy-balance related habits. This measure characterises habit by automatic activation, behavioural frequency, and relevance to self-identity. Previous empirical research suggests that the SRHI may be abbreviated with no losses in reliability or predictive utility. Drawing on recent theorising suggesting that automaticity is the ‘active ingredient’ of habit-behaviour relationships, we tested whether an automaticity-specific SRHI subscale could capture habit-based behaviour patterns in self-report data. Methods A content validity task was undertaken to identify a subset of automaticity indicators within the SRHI. The reliability, convergent validity and predictive validity of the automaticity item subset was subsequently tested in secondary analyses of all previous SRHI applications, identified via systematic review, and in primary analyses of four raw datasets relating to energy‐balance relevant behaviours (inactive travel, active travel, snacking, and alcohol consumption). Results A four-item automaticity subscale (the ‘Self-Report Behavioural Automaticity Index’; ‘SRBAI’) was found to be reliable and sensitive to two hypothesised effects of habit on behaviour: a habit-behaviour correlation, and a moderating effect of habit on the intention-behaviour relationship. Conclusion The SRBAI offers a parsimonious measure that adequately captures habitual behaviour patterns. The SRBAI may be of particular utility in predicting future behaviour and in studies tracking habit formation or disruption. PMID:22935297

Land use classification using texture information in ERTS-A MSS imagery

NASA Technical Reports Server (NTRS)

Haralick, R. M. (Principal Investigator); Shanmugam, K. S.; Bosley, R.

1973-01-01

The author has identified the following significant results. Preliminary digital analysis of ERTS-1 MSS imagery reveals that the textural features of the imagery are very useful for land use classification. A procedure for extracting the textural features of ERTS-1 imagery is presented and the results of a land use classification scheme based on the textural features are also presented. The land use classification algorithm using textural features was tested on a 5100 square mile area covered by part of an ERTS-1 MSS band 5 image over the California coastline. The image covering this area was blocked into 648 subimages of size 8.9 square miles each. Based on a color composite of the image set, a total of 7 land use categories were identified. These land use categories are: coastal forest, woodlands, annual grasslands, urban areas, large irrigated fields, small irrigated fields, and water. The automatic classifier was trained to identify the land use categories using only the textural characteristics of the subimages; 75 percent of the subimages were assigned correct identifications. Since texture and spectral features provide completely different kinds of information, a significant increase in identification accuracy will take place when both features are used together.

Utilizing automatic identification tracking systems to compile operational field and structure data : [research summary].

DOT National Transportation Integrated Search

2014-05-01

Thefederallymandatedmaterialsclearanceprocessrequiresstatetransportation : agenciestosubjectallconstructionfieldsamplestoqualitycontrol/assurancetestingin : ordertopassstandardizedstateinspections....

Quality Control of True Height Profiles Obtained Automatically from Digital Ionograms.

DTIC Science & Technology

1982-05-01

nece.,ssary and Identify by block number) Ionosphere Digisonde Electron Density Profile Ionogram Autoscaling ARTIST 2 , ABSTRACT (Continue on reverae...analysis technique currently used with the ionogram traces scaled automatically by the ARTIST software [Reinisch and Huang, 1983; Reinisch et al...19841, and the generalized polynomial analysis technique POLAN [Titheridge, 1985], using the same ARTIST -identified ionogram traces. 2. To determine how

Realization of the ergonomics design and automatic control of the fundus cameras

NASA Astrophysics Data System (ADS)

Zeng, Chi-liang; Xiao, Ze-xin; Deng, Shi-chao; Yu, Xin-ye

2012-12-01

The principles of ergonomics design in fundus cameras should be extending the agreeableness by automatic control. Firstly, a 3D positional numerical control system is designed for positioning the eye pupils of the patients who are doing fundus examinations. This system consists of a electronically controlled chin bracket for moving up and down, a lateral movement of binocular with the detector and the automatic refocusing of the edges of the eye pupils. Secondly, an auto-focusing device for the object plane of patient's fundus is designed, which collects the patient's fundus images automatically whether their eyes is ametropic or not. Finally, a moving visual target is developed for expanding the fields of the fundus images.

A Machine Vision System for Automatically Grading Hardwood Lumber - (Industrial Metrology)

Treesearch

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon

1992-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

Design of cylindrical pipe automatic welding control system based on STM32

NASA Astrophysics Data System (ADS)

Chen, Shuaishuai; Shen, Weicong

2018-04-01

The development of modern economy makes the demand for pipeline construction and construction rapidly increasing, and the pipeline welding has become an important link in pipeline construction. At present, there are still a large number of using of manual welding methods at home and abroad, and field pipe welding especially lacks miniature and portable automatic welding equipment. An automated welding system consists of a control system, which consisting of a lower computer control panel and a host computer operating interface, as well as automatic welding machine mechanisms and welding power systems in coordination with the control system. In this paper, a new control system of automatic pipe welding based on the control panel of the lower computer and the interface of the host computer is proposed, which has many advantages over the traditional automatic welding machine.

Automatic techniques for 3D reconstruction of critical workplace body postures from range imaging data

NASA Astrophysics Data System (ADS)

Westfeld, Patrick; Maas, Hans-Gerd; Bringmann, Oliver; Gröllich, Daniel; Schmauder, Martin

2013-11-01

The paper shows techniques for the determination of structured motion parameters from range camera image sequences. The core contribution of the work presented here is the development of an integrated least squares 3D tracking approach based on amplitude and range image sequences to calculate dense 3D motion vector fields. Geometric primitives of a human body model are fitted to time series of range camera point clouds using these vector fields as additional information. Body poses and motion information for individual body parts are derived from the model fit. On the basis of these pose and motion parameters, critical body postures are detected. The primary aim of the study is to automate ergonomic studies for risk assessments regulated by law, identifying harmful movements and awkward body postures in a workplace.

Segmentation of stereo terrain images

NASA Astrophysics Data System (ADS)

George, Debra A.; Privitera, Claudio M.; Blackmon, Theodore T.; Zbinden, Eric; Stark, Lawrence W.

2000-06-01

We have studied four approaches to segmentation of images: three automatic ones using image processing algorithms and a fourth approach, human manual segmentation. We were motivated toward helping with an important NASA Mars rover mission task -- replacing laborious manual path planning with automatic navigation of the rover on the Mars terrain. The goal of the automatic segmentations was to identify an obstacle map on the Mars terrain to enable automatic path planning for the rover. The automatic segmentation was first explored with two different segmentation methods: one based on pixel luminance, and the other based on pixel altitude generated through stereo image processing. The third automatic segmentation was achieved by combining these two types of image segmentation. Human manual segmentation of Martian terrain images was used for evaluating the effectiveness of the combined automatic segmentation as well as for determining how different humans segment the same images. Comparisons between two different segmentations, manual or automatic, were measured using a similarity metric, SAB. Based on this metric, the combined automatic segmentation did fairly well in agreeing with the manual segmentation. This was a demonstration of a positive step towards automatically creating the accurate obstacle maps necessary for automatic path planning and rover navigation.

Neurophysiological Pathways to Obesity: Below Awareness and Beyond Individual Control

PubMed Central

Cohen, Deborah A.

2008-01-01

A global obesity epidemic is occurring simultaneously with ongoing increases in the availability and salience of food in the environment. Obesity is increasing across all socioeconomic groups and educational levels and occurs even among individuals with the highest levels of education and expertise in nutrition and related fields. Given these circumstances, it is plausible that excessive food consumption occurs in ways that defy personal insight or are below individual awareness. The current food environment stimulates automatic reflexive responses that enhance the desire to eat and increase caloric intake, making it exceedingly difficult for individuals to resist, especially because they may not be aware of these influences. This article identifies 10 neurophysiological pathways that can lead people to make food choices subconsciously or, in some cases, automatically. These pathways include reflexive and uncontrollable neurohormonal responses to food images, cues, and smells; mirror neurons that cause people to imitate the eating behavior of others without awareness; and limited cognitive capacity to make informed decisions about food. Given that people have limited ability to shape the food environment individually and no ability to control automatic responses to food-related cues that are unconsciously perceived, it is incumbent upon society as a whole to regulate the food environment, including the number and types of food-related cues, portion sizes, food availability, and food advertising. PMID:18586908

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.

FRACTIONATING COLUMN PRODUCT COLLECTOR CONTROL

DOEpatents

Paxson, G.D. Jr.

1964-03-10

Means for detecting minute fluid products from a chemical separation column and for advancing a collector tube rack in order to automatically separate and collect successive fractionated products are described. A charge is imposed on the forming drops at the column orifice to create an electric field as the drop falls in the vicinity of a sensing plate. The field is detected by an electrometer tube coupled to the plate causing an output signal to actuate rotation of a collector turntable rack, thereby positioning new collectors under the orifice. The invention provides reliable automatic collection independent of drop size, rate of fall, or chemical composition. (AEC)

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 for patient CVD risk categorization by the evaluated methods ranged from 0.80 to 1.00. A publicly available standardized framework for the evaluation of (semi)automatic methods for CAC identification in cardiac CT is described. An evaluation of five (semi)automatic methods within this framework shows that automatic per patient CVD risk categorization is feasible. CAC lesions at ambiguous locations such as the coronary ostia remain challenging, but their detection had limited impact on CVD risk determination.

Director, Operational Test and Evaluation FY 2004 Annual Report

DTIC Science & Technology

2004-01-01

HIGH) Space Based Radar (SBR) Sensor Fuzed Weapon (SFW) P3I (CBU-97/B) Small Diameter Bomb (SDB) Secure Mobile Anti-Jam Reliable Tactical Terminal...detection, identification, and sampling capability for both fixed-site and mobile operations. The system must automatically detect and identify up to ten...staffing within the Services. SYSTEM DESCRIPTION AND MISSION The Services envision JCAD as a hand-held device that automatically detects, identifies, and

Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text

NASA Astrophysics Data System (ADS)

Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.

2015-12-01

We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction process. We will describe our experience and implementation of our system and share lessons learned from our development. We will also discuss ways in which this could be adapted to other science fields. [1] Funk et al., 2014. [2] Kang et al., 2014. [3] Utopia Documents, http://utopiadocs.com [4] Apache cTAKES, http://ctakes.apache.org

Automatic rice crop height measurement using a field server and digital image processing.

PubMed

Sritarapipat, Tanakorn; Rakwatin, Preesan; Kasetkasem, Teerasit

2014-01-07

Rice crop height is an important agronomic trait linked to plant type and yield potential. This research developed an automatic image processing technique to detect rice crop height based on images taken by a digital camera attached to a field server. The camera acquires rice paddy images daily at a consistent time of day. The images include the rice plants and a marker bar used to provide a height reference. The rice crop height can be indirectly measured from the images by measuring the height of the marker bar compared to the height of the initial marker bar. Four digital image processing steps are employed to automatically measure the rice crop height: band selection, filtering, thresholding, and height measurement. Band selection is used to remove redundant features. Filtering extracts significant features of the marker bar. The thresholding method is applied to separate objects and boundaries of the marker bar versus other areas. The marker bar is detected and compared with the initial marker bar to measure the rice crop height. Our experiment used a field server with a digital camera to continuously monitor a rice field located in Suphanburi Province, Thailand. The experimental results show that the proposed method measures rice crop height effectively, with no human intervention required.

ROTSE All-Sky Surveys for Variable Stars. I. Test Fields

NASA Astrophysics Data System (ADS)

Akerlof, C.; Amrose, S.; Balsano, R.; Bloch, J.; Casperson, D.; Fletcher, S.; Gisler, G.; Hills, J.; Kehoe, R.; Lee, B.; Marshall, S.; McKay, T.; Pawl, A.; Schaefer, J.; Szymanski, J.; Wren, J.

2000-04-01

The Robotic Optical Transient Search Experiment I (ROTSE-I) experiment has generated CCD photometry for the entire northern sky in two epochs nightly since 1998 March. These sky patrol data are a powerful resource for studies of astrophysical transients. As a demonstration project, we present first results of a search for periodic variable stars derived from ROTSE-I observations. Variable identification, period determination, and type classification are conducted via automatic algorithms. In a set of nine ROTSE-I sky patrol fields covering roughly 2000 deg2, we identify 1781 periodic variable stars with mean magnitudes between mv=10.0 and mv=15.5. About 90% of these objects are newly identified as variable. Examples of many familiar types are presented. All classifications for this study have been manually confirmed. The selection criteria for this analysis have been conservatively defined and are known to be biased against some variable classes. This preliminary study includes only 5.6% of the total ROTSE-I sky coverage, suggesting that the full ROTSE-I variable catalog will include more than 32,000 periodic variable stars.

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.

VizieR Online Data Catalog: Hubble Legacy Archive ACS grism data (Kuemmel+, 2011)

NASA Astrophysics Data System (ADS)

Kuemmel, M.; Rosati, P.; Fosbury, R.; Haase, J.; Hook, R. N.; Kuntschner, H.; Lombardi, M.; Micol, A.; Nilsson, K. K.; Stoehr, F.; Walsh, J. R.

2011-09-01

A public release of slitless spectra, obtained with ACS/WFC and the G800L grism, is presented. Spectra were automatically extracted in a uniform way from 153 archival fields (or "associations") distributed across the two Galactic caps, covering all observations to 2008. The ACS G800L grism provides a wavelength range of 0.55-1.00um, with a dispersion of 40Å/pixel and a resolution of ~80Å for point-like sources. The ACS G800L images and matched direct images were reduced with an automatic pipeline that handles all steps from archive retrieval, alignment and astrometric calibration, direct image combination, catalogue generation, spectral extraction and collection of metadata. The large number of extracted spectra (73,581) demanded automatic methods for quality control and an automated classification algorithm was trained on the visual inspection of several thousand spectra. The final sample of quality controlled spectra includes 47919 datasets (65% of the total number of extracted spectra) for 32149 unique objects, with a median iAB-band magnitude of 23.7, reaching 26.5 AB for the faintest objects. Each released dataset contains science-ready 1D and 2D spectra, as well as multi-band image cutouts of corresponding sources and a useful preview page summarising the direct and slitless data, astrometric and photometric parameters. This release is part of the continuing effort to enhance the content of the Hubble Legacy Archive (HLA) with highly processed data products which significantly facilitate the scientific exploitation of the Hubble data. In order to characterize the slitless spectra, emission-line flux and equivalent width sensitivity of the ACS data were compared with public ground-based spectra in the GOODS-South field. An example list of emission line galaxies with two or more identified lines is also included, covering the redshift range 0.2-4.6. Almost all redshift determinations outside of the GOODS fields are new. The scope of science projects possible with the ACS slitless release data is large, from studies of Galactic stars to searches for high redshift galaxies. (3 data files).

The Hubble Legacy Archive ACS grism data

NASA Astrophysics Data System (ADS)

Kümmel, M.; Rosati, P.; Fosbury, R.; Haase, J.; Hook, R. N.; Kuntschner, H.; Lombardi, M.; Micol, A.; Nilsson, K. K.; Stoehr, F.; Walsh, J. R.

2011-06-01

A public release of slitless spectra, obtained with ACS/WFC and the G800L grism, is presented. Spectra were automatically extracted in a uniform way from 153 archival fields (or "associations") distributed across the two Galactic caps, covering all observations to 2008. The ACS G800L grism provides a wavelength range of 0.55-1.00 μm, with a dispersion of 40 Å/pixel and a resolution of ~80 Å for point-like sources. The ACS G800L images and matched direct images were reduced with an automatic pipeline that handles all steps from archive retrieval, alignment and astrometric calibration, direct image combination, catalogue generation, spectral extraction and collection of metadata. The large number of extracted spectra (73,581) demanded automatic methods for quality control and an automated classification algorithm was trained on the visual inspection of several thousand spectra. The final sample of quality controlled spectra includes 47 919 datasets (65% of the total number of extracted spectra) for 32 149 unique objects, with a median iAB-band magnitude of 23.7, reaching 26.5 AB for the faintest objects. Each released dataset contains science-ready 1D and 2D spectra, as well as multi-band image cutouts of corresponding sources and a useful preview page summarising the direct and slitless data, astrometric and photometric parameters. This release is part of the continuing effort to enhance the content of the Hubble Legacy Archive (HLA) with highly processed data products which significantly facilitate the scientific exploitation of the Hubble data. In order to characterize the slitless spectra, emission-line flux and equivalent width sensitivity of the ACS data were compared with public ground-based spectra in the GOODS-South field. An example list of emission line galaxies with two or more identified lines is also included, covering the redshift range 0.2 - 4.6. Almost all redshift determinations outside of the GOODS fields are new. The scope of science projects possible with the ACS slitless release data is large, from studies of Galactic stars to searches for high redshift galaxies.

Deep Learning Methods for Quantifying Invasive Benthic Species in the Great Lakes

NASA Astrophysics Data System (ADS)

Billings, G.; Skinner, K.; Johnson-Roberson, M.

2017-12-01

In recent decades, invasive species such as the round goby and dreissenid mussels have greatly impacted the Great Lakes ecosystem. It is critical to monitor these species, model their distribution, and quantify the impacts on the native fisheries and surrounding ecosystem in order to develop an effective management response. However, data collection in underwater environments is challenging and expensive. Furthermore, the round goby is typically found in rocky habitats, which are inaccessible to standard survey techniques such as bottom trawling. In this work we propose a robotic system for visual data collection to automatically detect and quantify invasive round gobies and mussels in the Great Lakes. Robotic platforms equipped with cameras can perform efficient, cost-effective, low-bias benthic surveys. This data collection can be further optimized through automatic detection and annotation of the target species. Deep learning methods have shown success in image recognition tasks. However, these methods often rely on a labelled training dataset, with up to millions of labelled images. Hand labeling large numbers of images is expensive and often impracticable. Furthermore, data collected in the field may be sparse when only considering images that contain the objects of interest. It is easier to collect dense, clean data in controlled lab settings, but this data is not a realistic representation of real field environments. In this work, we propose a deep learning approach to generate a large set of labelled training data realistic of underwater environments in the field. To generate these images, first we draw random sample images of individual fish and mussels from a library of images captured in a controlled lab environment. Next, these randomly drawn samples will be automatically merged into natural background images. Finally, we will use a generative adversarial network (GAN) that incorporates constraints of the physical model of underwater light propagation to simulate the process of underwater image formation in various water conditions. The output of the GAN will be realistic looking annotated underwater images. This generated dataset of images will be used to train a classifier to identify round gobies and mussels in order to measure the biomass and abundance of these invasive species in the Great Lakes.

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.

DLA based compressed sensing for high resolution MR microscopy of neuronal tissue.

PubMed

Nguyen, Khieu-Van; Li, Jing-Rebecca; Radecki, Guillaume; Ciobanu, Luisa

2015-10-01

In this work we present the implementation of compressed sensing (CS) on a high field preclinical scanner (17.2 T) using an undersampling trajectory based on the diffusion limited aggregation (DLA) random growth model. When applied to a library of images this approach performs better than the traditional undersampling based on the polynomial probability density function. In addition, we show that the method is applicable to imaging live neuronal tissues, allowing significantly shorter acquisition times while maintaining the image quality necessary for identifying the majority of neurons via an automatic cell segmentation algorithm. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

ORAC-DR -- integral field spectroscopy data reduction

NASA Astrophysics Data System (ADS)

Todd, Stephen

ORAC-DR is a general-purpose automatic data-reduction pipeline environment. This document describes its use to reduce integral field unit (IFU) data collected at the United Kingdom Infrared Telescope (UKIRT) with the UIST instrument.

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

Automatic measurement of pennation angle and fascicle length of gastrocnemius muscles using real-time ultrasound imaging.

PubMed

Zhou, Guang-Quan; Chan, Phoebe; Zheng, Yong-Ping

2015-03-01

Muscle imaging is a promising field of research to understand the biological and bioelectrical characteristics of muscles through the observation of muscle architectural change. Sonomyography (SMG) is a technique which can quantify the real-time architectural change of muscles under different contractions and motions with ultrasound imaging. The pennation angle and fascicle length are two crucial SMG parameters to understand the contraction mechanics at muscle level, but they have to be manually detected on ultrasound images frame by frame. In this study, we proposed an automatic method to quantitatively identify pennation angle and fascicle length of gastrocnemius (GM) muscle based on multi-resolution analysis and line feature extraction, which could overcome the limitations of tedious and time-consuming manual measurement. The method started with convolving Gabor wavelet specially designed for enhancing the line-like structure detection in GM ultrasound image. The resulting image was then used to detect the fascicles and aponeuroses for calculating the pennation angle and fascicle length with the consideration of their distribution in ultrasound image. The performance of this method was tested on computer simulated images and experimental images in vivo obtained from normal subjects. Tests on synthetic images showed that the method could identify the fascicle orientation with an average error less than 0.1°. The result of in vivo experiment showed a good agreement between the results obtained by the automatic and the manual measurements (r=0.94±0.03; p<0.001, and r=0.95±0.02, p<0.001). Furthermore, a significant correlation between the ankle angle and pennation angle (r=0.89±0.05; p<0.001) and fascicle length (r=-0.90±0.04; p<0.001) was found for the ankle plantar flexion. This study demonstrated that the proposed method was able to automatically measure the pennation angle and fascicle length of GM ultrasound images, which made it feasible to investigate muscle-level mechanics more comprehensively in vivo. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Three-dimensional automated nanoparticle tracking using Mie scattering in an optical microscope.

PubMed

Gineste, J-M; Macko, P; Patterson, E A; Whelan, M P

2011-08-01

The forward scattering of light in a conventional inverted optical microscope by nanoparticles ranging in diameter from 10 to 50nm has been used to automatically and quantitatively identify and track their location in three-dimensions with a temporal resolution of 200ms. The standard deviation of the location of nominally stationary 50-nm-diameter nanoparticles was found to be about 50nm along the light path and about 5nm in the plane perpendicular to the light path. The method is based on oscillating the microscope objective along the light path using a piezo actuator and acquiring images with the condenser aperture closed to a minimum to enhance the effects of diffraction. Data processing in the time and spatial domains allowed the location of particles to be obtained automatically so that the technique has potential applications both in the processing of nanoparticles and in their use in a variety of fields including nanobiotechnology, pharmaceuticals and food processing where a simple optical microscope maybe preferred for a variety of reasons. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.

National Highway Safety Administration. Automatic collision notice field test summary.

PubMed

2001-10-01

From 1995 to 2000, the National Highway Traffic Safety Administration (NHTSA) sponsored an initiative to create and operate an Automatic Collision Notification (ACN) system on a demonstration basis in a rural area to provide faster and smarter emergency medical responses and in an attempt to save lives and reduce disabilities from injuries. This article is a brief summary of that demonstration.

Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents

DTIC Science & Technology

1997-11-01

status can sometimes be reflected in the infectious potential or drug resistance of those pathogens. For example, in Mycobacterium tuberculosis ... Mycobacterium tuberculosis , its antibiotic resistance and prediction of pathogenicity amongst Mycobacterium spp. based on signature lipid biomarkers ...TITLE AND SUBTITLE Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents 5a. CONTRACT NUMBER 5b

Pattern mining of user interaction logs for a post-deployment usability evaluation of a radiology PACS client.

PubMed

Jorritsma, Wiard; Cnossen, Fokie; Dierckx, Rudi A; Oudkerk, Matthijs; van Ooijen, Peter M A

2016-01-01

To perform a post-deployment usability evaluation of a radiology Picture Archiving and Communication System (PACS) client based on pattern mining of user interaction log data, and to assess the usefulness of this approach compared to a field study. All user actions performed on the PACS client were logged for four months. A data mining technique called closed sequential pattern mining was used to automatically extract frequently occurring interaction patterns from the log data. These patterns were used to identify usability issues with the PACS. The results of this evaluation were compared to the results of a field study based usability evaluation of the same PACS client. The interaction patterns revealed four usability issues: (1) the display protocols do not function properly, (2) the line measurement tool stays active until another tool is selected, rather than being deactivated after one use, (3) the PACS's built-in 3D functionality does not allow users to effectively perform certain 3D-related tasks, (4) users underuse the PACS's customization possibilities. All usability issues identified based on the log data were also found in the field study, which identified 48 issues in total. Post-deployment usability evaluation based on pattern mining of user interaction log data provides useful insights into the way users interact with the radiology PACS client. However, it reveals few usability issues compared to a field study and should therefore not be used as the sole method of usability evaluation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Marking airdromes

NASA Technical Reports Server (NTRS)

James, P

1922-01-01

Necessity of adopting for all aviation fields, civil or military, a single system of markers for giving the direction for starting and landing (with an automatic indicator of the direction of the wind) and of indicating the good part of the field.

Classification of Nortes in the Gulf of Mexico derived from wave energy maps

NASA Astrophysics Data System (ADS)

Appendini, C. M.; Hernández-Lasheras, J.

2016-02-01

Extreme wave climate in the Gulf of Mexico is determined by tropical cyclones and winds from the Central American Cold Surges, locally referred to as Nortes. While hurricanes can have catastrophic effects, extreme waves and storm surge from Nortes occur several times a year, and thus have greater impacts on human activities along the Mexican coast of the Gulf of Mexico. Despite the constant impacts from Nortes, there is no available classification that relates their characteristics (e.g. pressure gradients, wind speed), to the associated coastal impacts. This work presents a first approximation to characterize and classify Nortes, which is based on the assumption that the derived wave energy synthetizes information (i.e. wind intensity, direction and duration) of individual Norte events as they pass through the Gulf of Mexico. First, we developed an index to identify Nortes based on surface pressure differences of two locations. To validate the methodology we compared the events identified with other studies and available Nortes logs. Afterwards, we detected Nortes from the 1986/1987, 2008/2009 and 2009/2010 seasons and used their corresponding wind fields to derive the wave energy maps using a numerical wave model. We used the energy maps to classify the events into groups using manual (visual) and automatic classifications (principal component analysis and k-means). The manual classification identified 3 types of Nortes and the automatic classification identified 5, although 3 of them had a high degree of similarity. The principal component analysis indicated that all events have similar characteristics, as few components are necessary to explain almost all of the variance. The classification from the k-means indicated that 81% of analyzed Nortes affect the southeastern Gulf of Mexico, while a smaller percentage affects the northern Gulf of Mexico and even less affect the western Caribbean.

Automatic estimation of retinal nerve fiber bundle orientation in SD-OCT images using a structure-oriented smoothing filter

NASA Astrophysics Data System (ADS)

Ghafaryasl, Babak; Baart, Robert; de Boer, Johannes F.; Vermeer, Koenraad A.; van Vliet, Lucas J.

2017-02-01

Optical coherence tomography (OCT) yields high-resolution, three-dimensional images of the retina. A better understanding of retinal nerve fiber bundle (RNFB) trajectories in combination with visual field data may be used for future diagnosis and monitoring of glaucoma. However, manual tracing of these bundles is a tedious task. In this work, we present an automatic technique to estimate the orientation of RNFBs from volumetric OCT scans. Our method consists of several steps, starting from automatic segmentation of the RNFL. Then, a stack of en face images around the posterior nerve fiber layer interface was extracted. The image showing the best visibility of RNFB trajectories was selected for further processing. After denoising the selected en face image, a semblance structure-oriented filter was applied to probe the strength of local linear structure in a discrete set of orientations creating an orientation space. Gaussian filtering along the orientation axis in this space is used to find the dominant orientation. Next, a confidence map was created to supplement the estimated orientation. This confidence map was used as pixel weight in normalized convolution to regularize the semblance filter response after which a new orientation estimate can be obtained. Finally, after several iterations an orientation field corresponding to the strongest local orientation was obtained. The RNFB orientations of six macular scans from three subjects were estimated. For all scans, visual inspection shows a good agreement between the estimated orientation fields and the RNFB trajectories in the en face images. Additionally, a good correlation between the orientation fields of two scans of the same subject was observed. Our method was also applied to a larger field of view around the macula. Manual tracing of the RNFB trajectories shows a good agreement with the automatically obtained streamlines obtained by fiber tracking.

Automatic classification of seismic events within a regional seismograph network

NASA Astrophysics Data System (ADS)

Tiira, Timo; Kortström, Jari; Uski, Marja

2015-04-01

A fully automatic method for seismic event classification within a sparse regional seismograph network is presented. The tool is based on a supervised pattern recognition technique, Support Vector Machine (SVM), trained here to distinguish weak local earthquakes from a bulk of human-made or spurious seismic events. The classification rules rely on differences in signal energy distribution between natural and artificial seismic sources. Seismic records are divided into four windows, P, P coda, S, and S coda. For each signal window STA is computed in 20 narrow frequency bands between 1 and 41 Hz. The 80 discrimination parameters are used as a training data for the SVM. The SVM models are calculated for 19 on-line seismic stations in Finland. The event data are compiled mainly from fully automatic event solutions that are manually classified after automatic location process. The station-specific SVM training events include 11-302 positive (earthquake) and 227-1048 negative (non-earthquake) examples. The best voting rules for combining results from different stations are determined during an independent testing period. Finally, the network processing rules are applied to an independent evaluation period comprising 4681 fully automatic event determinations, of which 98 % have been manually identified as explosions or noise and 2 % as earthquakes. The SVM method correctly identifies 94 % of the non-earthquakes and all the earthquakes. The results imply that the SVM tool can identify and filter out blasts and spurious events from fully automatic event solutions with a high level of confidence. The tool helps to reduce work-load in manual seismic analysis by leaving only ~5 % of the automatic event determinations, i.e. the probable earthquakes for more detailed seismological analysis. The approach presented is easy to adjust to requirements of a denser or wider high-frequency network, once enough training examples for building a station-specific data set are available.

Developing Automatic Water Table Control System for Reducing Greenhouse Gas Emissions from Paddy Fields

NASA Astrophysics Data System (ADS)

Arif, C.; Fauzan, M. I.; Satyanto, K. S.; Budi, I. S.; Masaru, M.

2018-05-01

Water table in rice fields play important role to mitigate greenhouse gas (GHG) emissions from paddy fields. Continuous flooding by maintenance water table 2-5 cm above soil surface is not effective and release more GHG emissions. System of Rice Intensification (SRI) as alternative rice farming apply intermittent irrigation by maintaining lower water table is proven can reduce GHG emissions reducing productivity significantly. The objectives of this study were to develop automatic water table control system for SRI application and then evaluate the performances. The control system was developed based on fuzzy logic algorithms using the mini PC of Raspberry Pi. Based on laboratory and field tests, the developed system was working well as indicated by lower MAPE (mean absolute percentage error) values. MAPE values for simulation and field tests were 16.88% and 15.80%, respectively. This system can save irrigation water up to 42.54% without reducing productivity significantly when compared to manual irrigation systems.

Counting the number of Feynman graphs in QCD

NASA Astrophysics Data System (ADS)

Kaneko, T.

2018-05-01

Information about the number of Feynman graphs for a given physical process in a given field theory is especially useful for confirming the result of a Feynman graph generator used in an automatic system of perturbative calculations. A method of counting the number of Feynman graphs with weight of symmetry factor was established based on zero-dimensional field theory, and was used in scalar theories and QED. In this article this method is generalized to more complicated models by direct calculation of generating functions on a computer algebra system. This method is applied to QCD with and without counter terms, where many higher order are being calculated automatically.

Automated water monitor system field demonstration test report. Volume 2: Technical summary

NASA Technical Reports Server (NTRS)

Brooks, R. L.; Jeffers, E. L.; Perreira, J.; Poel, J. D.; Nibley, D.; Nuss, R. H.

1981-01-01

The NASA Automatic Water Monitor System was installed in a water reclamation facility to evaluate the technical and cost feasibility of producing high quality reclaimed water. Data gathered during this field demonstration test are reported.

Automatic Evaluations and Exercising: Systematic Review and Implications for Future Research.

PubMed

Schinkoeth, Michaela; Antoniewicz, Franziska

2017-01-01

The general purpose of this systematic review was to summarize, structure and evaluate the findings on automatic evaluations of exercising. Studies were eligible for inclusion if they reported measuring automatic evaluations of exercising with an implicit measure and assessed some kind of exercise variable. Fourteen nonexperimental and six experimental studies (out of a total N = 1,928) were identified and rated by two independent reviewers. The main study characteristics were extracted and the grade of evidence for each study evaluated. First, results revealed a large heterogeneity in the applied measures to assess automatic evaluations of exercising and the exercise variables. Generally, small to large-sized significant relations between automatic evaluations of exercising and exercise variables were identified in the vast majority of studies. The review offers a systematization of the various examined exercise variables and prompts to differentiate more carefully between actually observed exercise behavior (proximal exercise indicator) and associated physiological or psychological variables (distal exercise indicator). Second, a lack of transparent reported reflections on the differing theoretical basis leading to the use of specific implicit measures was observed. Implicit measures should be applied purposefully, taking into consideration the individual advantages or disadvantages of the measures. Third, 12 studies were rated as providing first-grade evidence (lowest grade of evidence), five represent second-grade and three were rated as third-grade evidence. There is a dramatic lack of experimental studies, which are essential for illustrating the cause-effect relation between automatic evaluations of exercising and exercise and investigating under which conditions automatic evaluations of exercising influence behavior. Conclusions about the necessity of exercise interventions targeted at the alteration of automatic evaluations of exercising should therefore not be drawn too hastily.

Automatic Evaluations and Exercising: Systematic Review and Implications for Future Research

PubMed Central

Schinkoeth, Michaela; Antoniewicz, Franziska

2017-01-01

The general purpose of this systematic review was to summarize, structure and evaluate the findings on automatic evaluations of exercising. Studies were eligible for inclusion if they reported measuring automatic evaluations of exercising with an implicit measure and assessed some kind of exercise variable. Fourteen nonexperimental and six experimental studies (out of a total N = 1,928) were identified and rated by two independent reviewers. The main study characteristics were extracted and the grade of evidence for each study evaluated. First, results revealed a large heterogeneity in the applied measures to assess automatic evaluations of exercising and the exercise variables. Generally, small to large-sized significant relations between automatic evaluations of exercising and exercise variables were identified in the vast majority of studies. The review offers a systematization of the various examined exercise variables and prompts to differentiate more carefully between actually observed exercise behavior (proximal exercise indicator) and associated physiological or psychological variables (distal exercise indicator). Second, a lack of transparent reported reflections on the differing theoretical basis leading to the use of specific implicit measures was observed. Implicit measures should be applied purposefully, taking into consideration the individual advantages or disadvantages of the measures. Third, 12 studies were rated as providing first-grade evidence (lowest grade of evidence), five represent second-grade and three were rated as third-grade evidence. There is a dramatic lack of experimental studies, which are essential for illustrating the cause-effect relation between automatic evaluations of exercising and exercise and investigating under which conditions automatic evaluations of exercising influence behavior. Conclusions about the necessity of exercise interventions targeted at the alteration of automatic evaluations of exercising should therefore not be drawn too hastily. PMID:29250022

Comparison between manual scaling and Autoscala automatic scaling applied to Sodankylä Geophysical Observatory ionograms

NASA Astrophysics Data System (ADS)

Enell, Carl-Fredrik; Kozlovsky, Alexander; Turunen, Tauno; Ulich, Thomas; Välitalo, Sirkku; Scotto, Carlo; Pezzopane, Michael

2016-03-01

This paper presents a comparison between standard ionospheric parameters manually and automatically scaled from ionograms recorded at the high-latitude Sodankylä Geophysical Observatory (SGO, ionosonde SO166, 64.1° geomagnetic latitude), located in the vicinity of the auroral oval. The study is based on 2610 ionograms recorded during the period June-December 2013. The automatic scaling was made by means of the Autoscala software. A few typical examples are shown to outline the method, and statistics are presented regarding the differences between manually and automatically scaled values of F2, F1, E and sporadic E (Es) layer parameters. We draw the conclusions that: 1. The F2 parameters scaled by Autoscala, foF2 and M(3000)F2, are reliable. 2. F1 is identified by Autoscala in significantly fewer cases (about 50 %) than in the manual routine, but if identified the values of foF1 are reliable. 3. Autoscala frequently (30 % of the cases) detects an E layer when the manual scaling process does not. When identified by both methods, the Autoscala E-layer parameters are close to those manually scaled, foE agreeing to within 0.4 MHz. 4. Es and parameters of Es identified by Autoscala are in many cases different from those of the manual scaling. Scaling of Es at auroral latitudes is often a difficult task.

Automated Assessment of Child Vocalization Development Using LENA

ERIC Educational Resources Information Center

Richards, Jeffrey A.; Xu, Dongxin; Gilkerson, Jill; Yapanel, Umit; Gray, Sharmistha; Paul, Terrance

2017-01-01

Purpose: To produce a novel, efficient measure of children's expressive vocal development on the basis of automatic vocalization assessment (AVA), child vocalizations were automatically identified and extracted from audio recordings using Language Environment Analysis (LENA) System technology. Method: Assessment was based on full-day audio…

Using Automatic Code Generation in the Attitude Control Flight Software Engineering Process

NASA Technical Reports Server (NTRS)

McComas, David; O'Donnell, James R., Jr.; Andrews, Stephen F.

1999-01-01

This paper presents an overview of the attitude control subsystem flight software development process, identifies how the process has changed due to automatic code generation, analyzes each software development phase in detail, and concludes with a summary of our lessons learned.

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

Code of Federal Regulations, 2010 CFR

2010-10-01

... 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, 2013 CFR

2013-10-01

... 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, 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...

Synthesis of actual knowledge on machine-tool monitoring methods and equipment

NASA Astrophysics Data System (ADS)

Tanguy, J. C.

1988-06-01

Problems connected with the automatic supervision of production were studied. Many different automatic control devices are now able to identify defects in the tools, but the solutions proposed to detect optimal limits in the utilization of a tool are not satisfactory.

10 CFR Appendix J1 to Subpart B of... - Uniform Test Method for Measuring the Energy Consumption of Automatic and Semi-Automatic Clothes...

Code of Federal Regulations, 2014 CFR

2014-01-01

... clothes washer design can achieve spin speeds in the 500g range. When this matrix is repeated 3 times, a...) or an equivalent extractor with same basket design (i.e. diameter, length, volume, and hole... materially inaccurate comparative data, field testing may be appropriate for establishing an acceptable test...

10 CFR Appendix J1 to Subpart B of... - Uniform Test Method for Measuring the Energy Consumption of Automatic and Semi-Automatic Clothes...

Code of Federal Regulations, 2013 CFR

2013-01-01

.... The 500g requirement will only be used if a clothes washer design can achieve spin speeds in the 500g... Products, P.O. Box 5127, Toledo, OH 43611) or an equivalent extractor with same basket design (i.e... provide materially inaccurate comparative data, field testing may be appropriate for establishing an...

Automatic Generation of Rasch-Calibrated Items: Figural Matrices Test GEOM and Endless-Loops Test EC

ERIC Educational Resources Information Center

Arendasy, Martin

2005-01-01

The future of test construction for certain psychological ability domains that can be analyzed well in a structured manner may lie--at the very least for reasons of test security--in the field of automatic item generation. In this context, a question that has not been explicitly addressed is whether it is possible to embed an item response theory…

Gated high speed optical detector

NASA Technical Reports Server (NTRS)

Green, S. I.; Carson, L. M.; Neal, G. W.

1973-01-01

The design, fabrication, and test of two gated, high speed optical detectors for use in high speed digital laser communication links are discussed. The optical detectors used a dynamic crossed field photomultiplier and electronics including dc bias and RF drive circuits, automatic remote synchronization circuits, automatic gain control circuits, and threshold detection circuits. The equipment is used to detect binary encoded signals from a mode locked neodynium laser.

Identification of Active Galactic Nuclei through HST optical variability in the GOODS South field

NASA Astrophysics Data System (ADS)

Pouliasis, Ektoras; Georgantopoulos; Bonanos, A.; HCV Team

2016-08-01

This work aims to identify AGN in the GOODS South deep field through optical variability. This method can easily identify low-luminosity AGN. In particular, we use images in the z-band obtained from the Hubble Space Telescope with the ACS/WFC camera over 5 epochs separated by ~45 days. Aperture photometry has been performed using SExtractor to extract the lightcurves. Several variability indices, such as the median absolute deviation, excess variance, and sigma were applied to automatically identify the variable sources. After removing artifacts, stars and supernovae from the variable selected sample and keeping only those sources with known photometric or spectroscopic redshift, the optical variability was compared to variability in other wavelengths (X-rays, mid-IR, radio). This multi-wavelength study provides important constraints on the structure and the properties of the AGN and their relation to their hosts. This work is a part of the validation of the Hubble Catalog of Variables (HCV) project, which has been launched at the National Observatory of Athens by ESA, and aims to identify all sources (pointlike and extended) showing variability, based on the Hubble Source Catalog (HSC, Whitmore et al. 2015). The HSC version 1 was released in February 2015 and includes 80 million sources imaged with the WFPC2, ACS/WFC, WFC3/UVIS and WFC3/IR cameras.

Collaboration spotting for dental science.

PubMed

Leonardi, E; Agocs, A; Fragkiskos, S; Kasfikis, N; Le Goff, J M; Cristalli, M P; Luzzi, V; Polimeni, A

2014-10-06

The goal of the Collaboration Spotting project is to create an automatic system to collect information about publications and patents related to a given technology, to identify the key players involved, and to highlight collaborations and related technologies. The collected information can be visualized in a web browser as interactive graphical maps showing in an intuitive way the players and their collaborations (Sociogram) and the relations among the technologies (Technogram). We propose to use the system to study technologies related to Dental Science. In order to create a Sociogram, we create a logical filter based on a set of keywords related to the technology under study. This filter is used to extract a list of publications from the Web of Science™ database. The list is validated by an expert in the technology and sent to CERN where it is inserted in the Collaboration Spotting database. Here, an automatic software system uses the data to generate the final maps. We studied a set of recent technologies related to bone regeneration procedures of oro--maxillo--facial critical size defects, namely the use of Porous HydroxyApatite (HA) as a bone substitute alone (bone graft) or as a tridimensional support (scaffold) for insemination and differentiation ex--vivo of Mesenchymal Stem Cells. We produced the Sociograms for these technologies and the resulting maps are now accessible on--line. The Collaboration Spotting system allows the automatic creation of interactive maps to show the current and historical state of research on a specific technology. These maps are an ideal tool both for researchers who want to assess the state--of--the--art in a given technology, and for research organizations who want to evaluate their contribution to the technological development in a given field. We demonstrated that the system can be used for Dental Science and produced the maps for an initial set of technologies in this field. We now plan to enlarge the set of mapped technologies in order to make the Collaboration Spotting system a useful reference tool for Dental Science research.

Collaboration Spotting for oral medicine.

PubMed

Leonardi, E; Agocs, A; Fragkiskos, S; Kasfikis, N; Le Goff, J M; Cristalli, M P; Luzzi, V; Polimeni, A

2014-09-01

The goal of the Collaboration Spotting project is to create an automatic system to collect information about publications and patents related to a given technology, to identify the key players involved, and to highlight collaborations and related technologies. The collected information can be visualized in a web browser as interactive graphical maps showing in an intuitive way the players and their collaborations (Sociogram) and the relations among the technologies (Technogram). We propose to use the system to study technologies related to oral medicine. In order to create a sociogram, we create a logical filter based on a set of keywords related to the technology under study. This filter is used to extract a list of publications from the Web of Science™ database. The list is validated by an expert in the technology and sent to CERN where it is inserted in the Collaboration Spotting database. Here, an automatic software system uses the data to generate the final maps. We studied a set of recent technologies related to bone regeneration procedures of oro-maxillo-facial critical size defects, namely the use of porous hydroxyapatite (HA) as a bone substitute alone (bone graft) or as a tridimensional support (scaffold) for insemination and differentiation ex vivo of mesenchymal stem cells. We produced the sociograms for these technologies and the resulting maps are now accessible on-line. The Collaboration Spotting system allows the automatic creation of interactive maps to show the current and historical state of research on a specific technology. These maps are an ideal tool both for researchers who want to assess the state-of-the-art in a given technology, and for research organizations who want to evaluate their contribution to the technological development in a given field. We demonstrated that the system can be used in oral medicine as is produced the maps for an initial set of technologies in this field. We now plan to enlarge the set of mapped technologies in order to make the Collaboration Spotting system a useful reference tool for oral medicine research.

A field demonstration of energy conservation using occupancy sensor lighting control in equipment rooms

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

Dagle, J.E.

1992-09-01

The Pacific Northwest Laboratory identified energy savings potential of automatic equipment-room lighting controls, which was demonstrated by the field experiment described in this report. Occupancy sensor applications have gained popularity in recent years due to improved technology that enhances reliability and reduces cost. Automatic lighting control using occupancy sensors has been accepted as an energy-conservation measure because it reduces wasted lighting. This study focused on lighting control for equipment rooms, which have inherent conditions ideal for automatic lighting control, i.e., an area which is seldom occupied, multiple users of the area who would not know if others are in themore » room when they leave, and high lighting energy intensity in the area. Two rooms were selected for this study: a small equipment room in the basement of the 337 Building, and a large equipment area in the upper level of the 329 Building. The rooms were selected to demonstrate the various degrees of complexity which may be encountered in equipment rooms throughout the Hanford Site. The 337 Building equipment-room test case demonstrated a 97% reduction in lighting energy consumption, with an annual energy savings of $184. Including lamp-replacement savings, a total savings of $306 per year is offset by an initial installation cost of $1,100. The installation demonstrates a positive net present value of $2,858 when the lamp-replacement costs are included in a life-cycle analysis. This also corresponds to a 4.0-year payback period. The 329 Building equipment-room installation resulted in a 92% reduction in lighting energy consumption. This corresponds to annual energy savings of $1,372, and a total annual savings of $2,104 per year including lamp-replacement savings. The life-cycle cost analysis shows a net present value of $15,855, with a 5.8-year payback period.« less

Culture, attribution and automaticity: a social cognitive neuroscience view

PubMed Central

Morris, Michael W.

2010-01-01

A fundamental challenge facing social perceivers is identifying the cause underlying other people’s behavior. Evidence indicates that East Asian perceivers are more likely than Western perceivers to reference the social context when attributing a cause to a target person’s actions. One outstanding question is whether this reflects a culture’s influence on automatic or on controlled components of causal attribution. After reviewing behavioral evidence that culture can shape automatic mental processes as well as controlled reasoning, we discuss the evidence in favor of cultural differences in automatic and controlled components of causal attribution more specifically. We contend that insights emerging from social cognitive neuroscience research can inform this debate. After introducing an attribution framework popular among social neuroscientists, we consider findings relevant to the automaticity of attribution, before speculating how one could use a social neuroscience approach to clarify whether culture affects automatic, controlled or both types of attribution processes. PMID:20460302

Automatic alignment of double optical paths in excimer laser amplifier

NASA Astrophysics Data System (ADS)

Wang, Dahui; Zhao, Xueqing; Hua, Hengqi; Zhang, Yongsheng; Hu, Yun; Yi, Aiping; Zhao, Jun

2013-05-01

A kind of beam automatic alignment method used for double paths amplification in the electron pumped excimer laser system is demonstrated. In this way, the beams from the amplifiers can be transferred along the designated direction and accordingly irradiate on the target with high stabilization and accuracy. However, owing to nonexistence of natural alignment references in excimer laser amplifiers, two cross-hairs structure is used to align the beams. Here, one crosshair put into the input beam is regarded as the near-field reference while the other put into output beam is regarded as the far-field reference. The two cross-hairs are transmitted onto Charge Coupled Devices (CCD) by image-relaying structures separately. The errors between intersection points of two cross-talk images and centroid coordinates of actual beam are recorded automatically and sent to closed loop feedback control mechanism. Negative feedback keeps running until preset accuracy is reached. On the basis of above-mentioned design, the alignment optical path is built and the software is compiled, whereafter the experiment of double paths automatic alignment in electron pumped excimer laser amplifier is carried through. Meanwhile, the related influencing factors and the alignment precision are analyzed. Experimental results indicate that the alignment system can achieve the aiming direction of automatic aligning beams in short time. The analysis shows that the accuracy of alignment system is 0.63μrad and the beam maximum restoration error is 13.75μm. Furthermore, the bigger distance between the two cross-hairs, the higher precision of the system is. Therefore, the automatic alignment system has been used in angular multiplexing excimer Main Oscillation Power Amplification (MOPA) system and can satisfy the requirement of beam alignment precision on the whole.

Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations

PubMed Central

Langenkämper, Daniel; Jakobi, Tobias; Feld, Dustin; Jelonek, Lukas; Goesmann, Alexander; Nattkemper, Tim W.

2016-01-01

Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures. PMID:26904094

Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations.

PubMed

Langenkämper, Daniel; Jakobi, Tobias; Feld, Dustin; Jelonek, Lukas; Goesmann, Alexander; Nattkemper, Tim W

2016-01-01

Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures.

Wireless tracking of cotton modules. Part I: Automatic message triggering

USDA-ARS?s Scientific Manuscript database

The ability to map profit across a cotton field would enable producers to see where money is being made or lost on their farms and to implement precise field management practices to ensure the highest return possible on each portion of a field. To this end, a wireless module-tracking system was rec...

Performance of Control System Using Microcontroller for Sea Water Circulation

NASA Astrophysics Data System (ADS)

Indriani, A.; Witanto, Y.; Pratama, A. S.; Supriyadi; Hendra; Tanjung, A.

2018-02-01

Now a day control system is very important rule for any process. Control system have been used in the automatic system. Automatic system can be seen in the industrial filed, mechanical field, electrical field and etc. In industrial and mechanical field, control system are used for control of motion component such as motor, conveyor, machine, control of process made of product, control of system and soon. In electrical field, control system can met for control of electrical system as equipment or part electrical like fan, rice cooker, refrigerator, air conditioner and etc. Control system are used for control of temperature and circulation gas, air and water. Control system of temperature and circulation of water also can be used for fisher community. Control system can be create by using microcontroller, PLC and other automatic program [1][2]. In this paper we will focus on the close loop system by using microcontroller Arduino Mega to control of temperature and circulation of sea water for fisher community. Performance control system is influenced by control equipment, sensor sensitivity, test condition, environment and others. The temperature sensor is measured using the DS18S20 and the sea water clarity sensor for circulation indicator with turbidity sensor. From the test results indicated that this control system can circulate sea water and maintain the temperature and clarity of seawater in a short time.

Examination of the semi-automatic calculation technique of vegetation cover rate by digital camera images.

NASA Astrophysics Data System (ADS)

Takemine, S.; Rikimaru, A.; Takahashi, K.

The rice is one of the staple foods in the world High quality rice production requires periodically collecting rice growth data to control the growth of rice The height of plant the number of stem the color of leaf is well known parameters to indicate rice growth Rice growth diagnosis method based on these parameters is used operationally in Japan although collecting these parameters by field survey needs a lot of labor and time Recently a laborsaving method for rice growth diagnosis is proposed which is based on vegetation cover rate of rice Vegetation cover rate of rice is calculated based on discriminating rice plant areas in a digital camera image which is photographed in nadir direction Discrimination of rice plant areas in the image was done by the automatic binarization processing However in the case of vegetation cover rate calculation method depending on the automatic binarization process there is a possibility to decrease vegetation cover rate against growth of rice In this paper a calculation method of vegetation cover rate was proposed which based on the automatic binarization process and referred to the growth hysteresis information For several images obtained by field survey during rice growing season vegetation cover rate was calculated by the conventional automatic binarization processing and the proposed method respectively And vegetation cover rate of both methods was compared with reference value obtained by visual interpretation As a result of comparison the accuracy of discriminating rice plant areas was increased by the proposed

Individual differences in automatic emotion regulation affect the asymmetry of the LPP component.

PubMed

Zhang, Jing; Zhou, Renlai

2014-01-01

The main goal of this study was to investigate how automatic emotion regulation altered the hemispheric asymmetry of ERPs elicited by emotion processing. We examined the effect of individual differences in automatic emotion regulation on the late positive potential (LPP) when participants were viewing blocks of positive high arousal, positive low arousal, negative high arousal and negative low arousal pictures from International affect picture system (IAPS). Two participant groups were categorized by the Emotion Regulation-Implicit Association Test which has been used in previous research to identify two groups of participants with automatic emotion control and with automatic emotion express. The main finding was that automatic emotion express group showed a right dominance of the LPP component at posterior electrodes, especially in high arousal conditions. But no right dominance of the LPP component was observed for automatic emotion control group. We also found the group with automatic emotion control showed no differences in the right posterior LPP amplitude between high- and low-arousal emotion conditions, while the participants with automatic emotion express showed larger LPP amplitude in the right posterior in high-arousal conditions compared to low-arousal conditions. This result suggested that AER (Automatic emotion regulation) modulated the hemispheric asymmetry of LPP on posterior electrodes and supported the right hemisphere hypothesis.

21 CFR 892.1715 - Full-field digital mammography system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... planar digital x-ray images of the entire breast. This generic type of device may include digital mammography acquisition software, full-field digital image receptor, acquisition workstation, automatic exposure control, image processing and reconstruction programs, patient and equipment supports, component...

21 CFR 892.1715 - Full-field digital mammography system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... planar digital x-ray images of the entire breast. This generic type of device may include digital mammography acquisition software, full-field digital image receptor, acquisition workstation, automatic exposure control, image processing and reconstruction programs, patient and equipment supports, component...

21 CFR 892.1715 - Full-field digital mammography system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... planar digital x-ray images of the entire breast. This generic type of device may include digital mammography acquisition software, full-field digital image receptor, acquisition workstation, automatic exposure control, image processing and reconstruction programs, patient and equipment supports, component...

21 CFR 892.1715 - Full-field digital mammography system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... planar digital x-ray images of the entire breast. This generic type of device may include digital mammography acquisition software, full-field digital image receptor, acquisition workstation, automatic exposure control, image processing and reconstruction programs, patient and equipment supports, component...

SMART operational field test evaluation : scheduler survey report : final report

DOT National Transportation Integrated Search

1997-06-01

The Suburban Mobility Authority for Regional Transportation (SMART) has installed an automatic scheduling and dispatch system (ASD) in Southeast Michigan in accordance with their plans to implement ITS as a site for an operational field test. The pur...

Shape design sensitivity analysis and optimization of three dimensional elastic solids using geometric modeling and automatic regridding. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Yao, Tse-Min; Choi, Kyung K.

1987-01-01

An automatic regridding method and a three dimensional shape design parameterization technique were constructed and integrated into a unified theory of shape design sensitivity analysis. An algorithm was developed for general shape design sensitivity analysis of three dimensional eleastic solids. Numerical implementation of this shape design sensitivity analysis method was carried out using the finite element code ANSYS. The unified theory of shape design sensitivity analysis uses the material derivative of continuum mechanics with a design velocity field that represents shape change effects over the structural design. Automatic regridding methods were developed by generating a domain velocity field with boundary displacement method. Shape design parameterization for three dimensional surface design problems was illustrated using a Bezier surface with boundary perturbations that depend linearly on the perturbation of design parameters. A linearization method of optimization, LINRM, was used to obtain optimum shapes. Three examples from different engineering disciplines were investigated to demonstrate the accuracy and versatility of this shape design sensitivity analysis method.

Automatic welding systems gain world-wide acceptance

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

Ives, G. Jr.

1979-04-01

Five automatic welding systems are currently available for commercial use, marketed by three US companies - CRC Automatic Welding Co., H.C. Price Co., and Diametrics Inc. - as well as by Belgium's S.A. Arcos Co. (the Orbimatic welding device) and France's Societe Serimer. The pioneer and leader of the field, CRC has served on 52 projects since 1969, including the 56-in. Orenburg line in the USSR. In comparison, the other systems have seen only limited activity. The Orbimatic welder has been used in the Netherlands and other Western European countries on projects with up to 42-in.-diameter pipe. The H.C. Pricemore » welder proved successful in North Sea construction and last year in Mexico's Troncal Sistema Nacional de Gas. The Diametrics welder relies on the electric flash-butt system used on large-diameter projects in the USSR. The most recent entry into the commerical market, France's Serimer completed field testing last year. Four other welders have recently been announced but are not yet commercially available.« less

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.

An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

PubMed

Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

2017-08-01

Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

TU-F-BRF-03: Effect of Radiation Therapy Planning Scan Registration On the Dose in Lung Cancer Patient CT Scans

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

Cunliffe, A; Contee, C; White, B

Purpose: To characterize the effect of deformable registration of serial computed tomography (CT) scans on the radiation dose calculated from a treatment planning scan. Methods: Eighteen patients who received curative doses (≥60Gy, 2Gy/fraction) of photon radiation therapy for lung cancer treatment were retrospectively identified. For each patient, a diagnostic-quality pre-therapy (4–75 days) CT scan and a treatment planning scan with an associated dose map calculated in Pinnacle were collected. To establish baseline correspondence between scan pairs, a researcher manually identified anatomically corresponding landmark point pairs between the two scans. Pre-therapy scans were co-registered with planning scans (and associated dose maps)more » using the Plastimatch demons and Fraunhofer MEVIS deformable registration algorithms. Landmark points in each pretherapy scan were automatically mapped to the planning scan using the displacement vector field output from both registration algorithms. The absolute difference in planned dose (|ΔD|) between manually and automatically mapped landmark points was calculated. Using regression modeling, |ΔD| was modeled as a function of the distance between manually and automatically matched points (registration error, E), the dose standard deviation (SD-dose) in the eight-pixel neighborhood, and the registration algorithm used. Results: 52–92 landmark point pairs (median: 82) were identified in each patient's scans. Average |ΔD| across patients was 3.66Gy (range: 1.2–7.2Gy). |ΔD| was significantly reduced by 0.53Gy using Plastimatch demons compared with Fraunhofer MEVIS. |ΔD| increased significantly as a function of E (0.39Gy/mm) and SD-dose (2.23Gy/Gy). Conclusion: An average error of <4Gy in radiation dose was introduced when points were mapped between CT scan pairs using deformable registration. Dose differences following registration were significantly increased when the Fraunhofer MEVIS registration algorithm was used, spatial registration errors were larger, and dose gradient was higher (i.e., higher SD-dose). To our knowledge, this is the first study to directly compute dose errors following deformable registration of lung CT scans.« less

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.

PubMed

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Yan, Bin; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

PubMed Central

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition. PMID:26380294

Systems and methods for automatically identifying and linking names in digital resources

DOEpatents

Parker, Charles T.; Lyons, Catherine M.; Roston, Gerald P.; Garrity, George M.

2017-06-06

The present invention provides systems and methods for automatically identifying name-like-strings in digital resources, matching these name-like-string against a set of names held in an expertly curated database, and for those name-like-strings found in said database, enhancing the content by associating additional matter with the name, wherein said matter includes information about the names that is held within said database and pointers to other digital resources which include the same name and it synonyms.

Quantitative evaluation of 3D mouse behaviors and motor function in the open-field after spinal cord injury using markerless motion tracking.

PubMed

Sheets, Alison L; Lai, Po-Lun; Fisher, Lesley C; Basso, D Michele

2013-01-01

Thousands of scientists strive to identify cellular mechanisms that could lead to breakthroughs in developing ameliorative treatments for debilitating neural and muscular conditions such as spinal cord injury (SCI). Most studies use rodent models to test hypotheses, and these are all limited by the methods available to evaluate animal motor function. This study's goal was to develop a behavioral and locomotor assessment system in a murine model of SCI that enables quantitative kinematic measurements to be made automatically in the open-field by applying markerless motion tracking approaches. Three-dimensional movements of eight naïve, five mild, five moderate, and four severe SCI mice were recorded using 10 cameras (100 Hz). Background subtraction was used in each video frame to identify the animal's silhouette, and the 3D shape at each time was reconstructed using shape-from-silhouette. The reconstructed volume was divided into front and back halves using k-means clustering. The animal's front Center of Volume (CoV) height and whole-body CoV speed were calculated and used to automatically classify animal behaviors including directed locomotion, exploratory locomotion, meandering, standing, and rearing. More detailed analyses of CoV height, speed, and lateral deviation during directed locomotion revealed behavioral differences and functional impairments in animals with mild, moderate, and severe SCI when compared with naïve animals. Naïve animals displayed the widest variety of behaviors including rearing and crossing the center of the open-field, the fastest speeds, and tallest rear CoV heights. SCI reduced the range of behaviors, and decreased speed (r = .70 p<.005) and rear CoV height (r = .65 p<.01) were significantly correlated with greater lesion size. This markerless tracking approach is a first step toward fundamentally changing how rodent movement studies are conducted. By providing scientists with sensitive, quantitative measurement methods, subjectivity and human error is reduced, potentially providing insights leading to breakthroughs in treating human disease.

Quantitative Evaluation of 3D Mouse Behaviors and Motor Function in the Open-Field after Spinal Cord Injury Using Markerless Motion Tracking

PubMed Central

Sheets, Alison L.; Lai, Po-Lun; Fisher, Lesley C.; Basso, D. Michele

2013-01-01

Thousands of scientists strive to identify cellular mechanisms that could lead to breakthroughs in developing ameliorative treatments for debilitating neural and muscular conditions such as spinal cord injury (SCI). Most studies use rodent models to test hypotheses, and these are all limited by the methods available to evaluate animal motor function. This study’s goal was to develop a behavioral and locomotor assessment system in a murine model of SCI that enables quantitative kinematic measurements to be made automatically in the open-field by applying markerless motion tracking approaches. Three-dimensional movements of eight naïve, five mild, five moderate, and four severe SCI mice were recorded using 10 cameras (100 Hz). Background subtraction was used in each video frame to identify the animal’s silhouette, and the 3D shape at each time was reconstructed using shape-from-silhouette. The reconstructed volume was divided into front and back halves using k-means clustering. The animal’s front Center of Volume (CoV) height and whole-body CoV speed were calculated and used to automatically classify animal behaviors including directed locomotion, exploratory locomotion, meandering, standing, and rearing. More detailed analyses of CoV height, speed, and lateral deviation during directed locomotion revealed behavioral differences and functional impairments in animals with mild, moderate, and severe SCI when compared with naïve animals. Naïve animals displayed the widest variety of behaviors including rearing and crossing the center of the open-field, the fastest speeds, and tallest rear CoV heights. SCI reduced the range of behaviors, and decreased speed (r = .70 p<.005) and rear CoV height (r = .65 p<.01) were significantly correlated with greater lesion size. This markerless tracking approach is a first step toward fundamentally changing how rodent movement studies are conducted. By providing scientists with sensitive, quantitative measurement methods, subjectivity and human error is reduced, potentially providing insights leading to breakthroughs in treating human disease. PMID:24058586

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.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: SHARPs - Space-Weather HMI Active Region Patches

NASA Astrophysics Data System (ADS)

Bobra, M. G.; Sun, X.; Hoeksema, J. T.; Turmon, M.; Liu, Y.; Hayashi, K.; Barnes, G.; Leka, K. D.

2014-09-01

A new data product from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) called Space-weather HMI Active Region Patches ( SHARPs) is now available. SDO/HMI is the first space-based instrument to map the full-disk photospheric vector magnetic field with high cadence and continuity. The SHARP data series provide maps in patches that encompass automatically tracked magnetic concentrations for their entire lifetime; map quantities include the photospheric vector magnetic field and its uncertainty, along with Doppler velocity, continuum intensity, and line-of-sight magnetic field. Furthermore, keywords in the SHARP data series provide several parameters that concisely characterize the magnetic-field distribution and its deviation from a potential-field configuration. These indices may be useful for active-region event forecasting and for identifying regions of interest. The indices are calculated per patch and are available on a twelve-minute cadence. Quick-look data are available within approximately three hours of observation; definitive science products are produced approximately five weeks later. SHARP data are available at jsoc.stanford.edu and maps are available in either of two different coordinate systems. This article describes the SHARP data products and presents examples of SHARP data and parameters.

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.

AISLE: an automatic volumetric segmentation method for the study of lung allometry.

PubMed

Ren, Hongliang; Kazanzides, Peter

2011-01-01

We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.

An automatic locating system for cloud-to-ground lightning. [which utilizes a microcomputer

NASA Technical Reports Server (NTRS)

Krider, E. P.; Pifer, A. E.; Uman, M. A.

1980-01-01

Automatic locating systems which respond to cloud to ground lightning and which discriminate against cloud discharges and background noise are described. Subsystems of the locating system, which include the direction finder and the position analyzer, are discussed. The direction finder senses the electromagnetic fields radiated by lightning on two orthogonal magnetic loop antennas and on a flat plate electric antenna. The position analyzer is a preprogrammed microcomputer system which automatically computes, maps, and records lightning locations in real time using data inputs from the direction finder. The use of the locating systems for wildfire management and fire weather forecasting is discussed.

An Automated Method for Navigation Assessment for Earth Survey Sensors Using Island Targets

NASA Technical Reports Server (NTRS)

Patt, F. S.; Woodward, R. H.; Gregg, W. W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalogue of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean colour sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Automated navigation assessment for earth survey sensors using island targets

NASA Technical Reports Server (NTRS)

Patt, Frederick S.; Woodward, Robert H.; Gregg, Watson W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalog of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean color sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

On the question of the necessity of implementation of automatic control systems in timber industry

NASA Astrophysics Data System (ADS)

Khasanov, E. R.; Zelenkov, P. V.; Petrosyan, M. O.; Murygin, A. V.; Laptenor, V. D.

2016-04-01

The paper considers the necessity of implementation of automatic control systems on the level of forest farms management and timber industry. Main areas of activity, which currently subjected to automation, are revealed. Objectives, which solved by implementation of APCS, are identified.

Automaticity and Attentional Processes in Aging.

ERIC Educational Resources Information Center

Madden, David J.; Mitchell, David B.

In recent research, two qualitatively different classes of mental operations have been identified. The performance of one type of cognitive task requires attention, in the sense of mental effort, for its execution, while the second type can be performed automatically, independent of attentional control. Further research has shown that automatic…

Concept development of automatic guidance for rotorcraft obstacle avoidance

NASA Technical Reports Server (NTRS)

Cheng, Victor H. L.

1990-01-01

The automatic guidance of rotorcraft for obstacle avoidance in nap-of-the-earth flight is studied. A hierarchical breakdown of the guidance components is used to identify the functional requirements. These requirements and anticipated sensor capabilities lead to a preliminary guidance concept, which has been evaluated via computer simulations.

Automatic Construction of English/Chinese Parallel Corpora.

ERIC Educational Resources Information Center

Yang, Christopher C.; Li, Kar Wing

2003-01-01

Discussion of multilingual corpora and cross-lingual information retrieval focuses on research that constructed English/Chinese parallel corpus automatically from the World Wide Web. Presents an alignment method which is based on dynamic programming to identify one-to-one Chinese and English title pairs and discusses results of experiments…

10 CFR Appendix J1 to Subpart B of... - Uniform Test Method for Measuring the Energy Consumption of Automatic and Semi-Automatic Clothes...

Code of Federal Regulations, 2011 CFR

2011-01-01

.... The 500g requirement will only be used if a clothes washer design can achieve spin speeds in the 500g... Products, P.O. Box 5127, Toledo, OH 43611) or an equivalent extractor with same basket design (i.e... characteristics as to provide materially inaccurate comparative data, field testing may be appropriate for...

10 CFR Appendix J1 to Subpart B of... - Uniform Test Method for Measuring the Energy Consumption of Automatic and Semi-Automatic Clothes...

Code of Federal Regulations, 2012 CFR

2012-01-01

.... The 500g requirement will only be used if a clothes washer design can achieve spin speeds in the 500g... Products, P.O. Box 5127, Toledo, OH 43611) or an equivalent extractor with same basket design (i.e... characteristics as to provide materially inaccurate comparative data, field testing may be appropriate for...

Exploring the Thermal Limits of IR-Based Automatic Whale Detection (ETAW)

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Exploring the thermal limits of IR-based automatic whale ...marine mammals are entering a predefined exclusion zone. Marine mammal observers usually scan the ship’s environs for whales using binoculars or the...Hence, in combination with the whales ’ prolonged dives, sighting opportunities are rare, which, in addition to the limited field of view and finite

Quality Control of The Miniature Exoplanet Radio Velocity Array(MINERVA)

NASA Astrophysics Data System (ADS)

Rivera García, Kevin O.; Eastman, Jason D.

2017-01-01

The MINiature Exoplanet Radial Velocity Array, also known as MINERVA , is a network of four robotic 0.7 meter telescopes that is conducting a Radial Velocity survey of the nearest, brightest stars in search of small and rocky exoplanets. The robotic telescope array is located in Fred Lawrence Whipple Observatory in Arizona. MINERVA began science operations in 2015 and we are constantly improving its observing efficiency. We will describe performance statistics that we have developed in Python to proactively identify problems before they impede observations. We have written code to monitor the pointing error for each telescope to ensure it will always be able to acquire a target in the 3 arcminute field of view of its acquisition camera, but there are still some issues that need to be identified. The end goal for this research is to automatically address any common malfunction that may cause the observation to fail and ultimately improve our observing efficiency.

Automatic yield-line analysis of slabs using discontinuity layout optimization

PubMed Central

Gilbert, Matthew; He, Linwei; Smith, Colin C.; Le, Canh V.

2014-01-01

The yield-line method of analysis is a long established and extremely effective means of estimating the maximum load sustainable by a slab or plate. However, although numerous attempts to automate the process of directly identifying the critical pattern of yield-lines have been made over the past few decades, to date none has proved capable of reliably analysing slabs of arbitrary geometry. Here, it is demonstrated that the discontinuity layout optimization (DLO) procedure can successfully be applied to such problems. The procedure involves discretization of the problem using nodes inter-connected by potential yield-line discontinuities, with the critical layout of these then identified using linear programming. The procedure is applied to various benchmark problems, demonstrating that highly accurate solutions can be obtained, and showing that DLO provides a truly systematic means of directly and reliably automatically identifying yield-line patterns. Finally, since the critical yield-line patterns for many problems are found to be quite complex in form, a means of automatically simplifying these is presented. PMID:25104905

Automatic Network Fingerprinting through Single-Node Motifs

PubMed Central

Echtermeyer, Christoph; da Fontoura Costa, Luciano; Rodrigues, Francisco A.; Kaiser, Marcus

2011-01-01

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs—a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks. PMID:21297963

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.

Taxonomic classification of soils using digital information from LANDSAT data. Huayllamarca and eucaliptus areas. M.S. Thesis - Bolivia Univ.

NASA Technical Reports Server (NTRS)

Quiroga, S. Q.

1977-01-01

The applicability of LANDSAT digital information to soil mapping is described. A compilation of all cartographic information and bibliography of the study area is made. LANDSAT MSS images on a scale of 1:250,000 are interpreted and a physiographic map with legend is prepared. The study area is inspected and a selection of the sample areas is made. A digital map of the different soil units is produced and the computer mapping units are checked against the soil units encountered in the field. The soil boundaries obtained by automatic mapping were not substantially changed by field work. The accuracy of the automatic mapping is rather high.

Magsat investigation. [Canadian shield

NASA Technical Reports Server (NTRS)

Hall, D. H. (Principal Investigator)

1980-01-01

A computer program was prepared for modeling segments of the Earth's crust allowing for heterogeneity in magnetization in calculating the Earth's field at Magsat heights. This permits investigation of a large number of possible models in assessing the magnetic signatures of subprovinces of the Canadian shield. The fit between the model field and observed fields is optimized in a semi-automatic procedure.

Developing Predictive Models for Algal Bloom Occurrence and Identifying Factors Controlling their Occurrence in the Charlotte County and Surroundings

NASA Astrophysics Data System (ADS)

Karki, S.; Sultan, M.; Elkadiri, R.; Chouinard, K.

2017-12-01

Numerous occurrences of harmful algal blooms (Karenia Brevis) were reported from Southwest Florida along the coast of Charlotte County, Florida. We are developing data-driven (remote sensing, field, and meteorological data) models to accomplish the following: (1) identify the factors controlling bloom development, (2) forecast bloom occurrences, and (3) make recommendations for monitoring variables that are found to be most indicative of algal bloom occurrences and for identifying optimum locations for monitoring stations. To accomplish these three tasks we completed/are working on the following steps. Firstly, we developed an automatic system for downloading and processing of ocean color data acquired through MODIS Terra and MODIS Aqua products using SeaDAS ocean color processing software. Examples of extracted variables include: chlorophyll a (OC3M), chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel- Maritorena (GSM), sea surface temperature (SST), Secchi disk depth, euphotic depth, turbidity index, wind direction and speed, colored dissolved organic material (CDOM). Secondly we are developing a GIS database and a web-based GIS to host the generated remote sensing-based products in addition to relevant meteorological and field data. Examples of the meteorological and field inputs include: precipitation amount and rates, concentrations of nitrogen, phosphorous, fecal coliform and Dissolved Oxygen (DO). Thirdly, we are constructing and validating a multivariate regression model and an artificial neural network model to simulate past algal bloom occurrences using the compiled archival remote sensing, meteorological, and field data. The validated model will then be used to predict the timing and location of algal bloom occurrences. The developed system, upon completion, could enhance the decision making process, improve the citizen's quality of life, and strengthen the local economy.

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

Shimizu, Y; Yoon, Y; Iwase, K

Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints thatmore » could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprints for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system because they are less affected by positioning differences during imaging.« less

Human factors process failure modes and effects analysis (HF PFMEA) software tool

NASA Technical Reports Server (NTRS)

Chandler, Faith T. (Inventor); Relvini, Kristine M. (Inventor); Shedd, Nathaneal P. (Inventor); Valentino, William D. (Inventor); Philippart, Monica F. (Inventor); Bessette, Colette I. (Inventor)

2011-01-01

Methods, computer-readable media, and systems for automatically performing Human Factors Process Failure Modes and Effects Analysis for a process are provided. At least one task involved in a process is identified, where the task includes at least one human activity. The human activity is described using at least one verb. A human error potentially resulting from the human activity is automatically identified, the human error is related to the verb used in describing the task. A likelihood of occurrence, detection, and correction of the human error is identified. The severity of the effect of the human error is identified. The likelihood of occurrence, and the severity of the risk of potential harm is identified. The risk of potential harm is compared with a risk threshold to identify the appropriateness of corrective measures.

An automatic method to generate domain-specific investigator networks using PubMed abstracts.

PubMed

Yu, Wei; Yesupriya, Ajay; Wulf, Anja; Qu, Junfeng; Gwinn, Marta; Khoury, Muin J

2007-06-20

Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70-90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network. We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks.

An automatic method to generate domain-specific investigator networks using PubMed abstracts

PubMed Central

Yu, Wei; Yesupriya, Ajay; Wulf, Anja; Qu, Junfeng; Gwinn, Marta; Khoury, Muin J

2007-01-01

Background Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. Results We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70–90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network. Conclusion We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks. PMID:17584920

Automatic evidence retrieval for systematic reviews.

PubMed

Choong, Miew Keen; Galgani, Filippo; Dunn, Adam G; Tsafnat, Guy

2014-10-01

Snowballing involves recursively pursuing relevant references cited in the retrieved literature and adding them to the search results. Snowballing is an alternative approach to discover additional evidence that was not retrieved through conventional search. Snowballing's effectiveness makes it best practice in systematic reviews despite being time-consuming and tedious. Our goal was to evaluate an automatic method for citation snowballing's capacity to identify and retrieve the full text and/or abstracts of cited articles. Using 20 review articles that contained 949 citations to journal or conference articles, we manually searched Microsoft Academic Search (MAS) and identified 78.0% (740/949) of the cited articles that were present in the database. We compared the performance of the automatic citation snowballing method against the results of this manual search, measuring precision, recall, and F1 score. The automatic method was able to correctly identify 633 (as proportion of included citations: recall=66.7%, F1 score=79.3%; as proportion of citations in MAS: recall=85.5%, F1 score=91.2%) of citations with high precision (97.7%), and retrieved the full text or abstract for 490 (recall=82.9%, precision=92.1%, F1 score=87.3%) of the 633 correctly retrieved citations. The proposed method for automatic citation snowballing is accurate and is capable of obtaining the full texts or abstracts for a substantial proportion of the scholarly citations in review articles. By automating the process of citation snowballing, it may be possible to reduce the time and effort of common evidence surveillance tasks such as keeping trial registries up to date and conducting systematic reviews.

Detection of buried magnetic objects by a SQUID gradiometer system

NASA Astrophysics Data System (ADS)

Meyer, Hans-Georg; Hartung, Konrad; Linzen, Sven; Schneider, Michael; Stolz, Ronny; Fried, Wolfgang; Hauspurg, Sebastian

2009-05-01

We present a magnetic detection system based on superconducting gradiometric sensors (SQUID gradiometers). The system provides a unique fast mapping of large areas with a high resolution of the magnetic field gradient as well as the local position. A main part of this work is the localization and classification of magnetic objects in the ground by automatic interpretation of geomagnetic field gradients, measured by the SQUID system. In accordance with specific features the field is decomposed into segments, which allow inferences to possible objects in the ground. The global consideration of object describing properties and their optimization using error minimization methods allows the reconstruction of superimposed features and detection of buried objects. The analysis system of measured geomagnetic fields works fully automatically. By a given surface of area-measured gradients the algorithm determines within numerical limits the absolute position of objects including depth with sub-pixel accuracy and allows an arbitrary position and attitude of sources. Several SQUID gradiometer data sets were used to show the applicability of the analysis algorithm.

A magnetic field measurement technique using a miniature transducer

NASA Technical Reports Server (NTRS)

Fales, C. L., Jr.; Breckenridge, R. A.; Debnam, W. J., Jr.

1974-01-01

The development, fabrication, and application of a magnetometer are described. The magnetometer has a miniature transducer and is capable of automatic scanning. The magnetometer described here is capable of detecting static magnetic fields as low as 1.6 A/m and its transducer has an active area 0.64 mm by 0.76 mm. Thin and rugged, the transducer uses wire, 0.05 mm in diameter, which is plated with a magnetic film, enabling measurement of transverse magnetic fields as close as 0.08 mm from a surface. The magnetometer, which is simple to operate and has a fast response, uses an inexpensive clip-on milliammeter (commonly found in most laboratories) for driving and processing the electrical signals and readout. A specially designed transducer holding mechanism replaces the XY recorder ink pen; this mechanism provides the basis for an automatic scanning technique. The instrument has been applied to the measurements of magnetic fields arising from remanent magnetization in experimental plated-wire memory planes and regions of magnetic activity in geological rock specimens.

Preliminary clinical evaluation of semi-automated nailfold capillaroscopy in the assessment of patients with Raynaud's phenomenon.

PubMed

Murray, Andrea K; Feng, Kaiyan; Moore, Tonia L; Allen, Phillip D; Taylor, Christopher J; Herrick, Ariane L

2011-08-01

  Nailfold capillaroscopy is well established in screening patients with Raynaud's phenomenon for underlying SSc-spectrum disorders, by identifying abnormal capillaries. Our aim was to compare semi-automatic feature measurement from newly developed software with manual measurements, and determine the degree to which semi-automated data allows disease group classification.   Images from 46 healthy controls, 21 patients with PRP and 49 with SSc were preprocessed, and semi-automated measurements of intercapillary distance and capillary width, tortuosity, and derangement were performed. These were compared with manual measurements. Features were used to classify images into the three subject groups.   Comparison of automatic and manual measures for distance, width, tortuosity, and derangement had correlations of r=0.583, 0.624, 0.495 (p<0.001), and 0.195 (p=0.040). For automatic measures, correlations were found between width and intercapillary distance, r=0.374, and width and tortuosity, r=0.573 (p<0.001). Significant differences between subject groups were found for all features (p<0.002). Overall, 75% of images correctly matched clinical classification using semi-automated features, compared with 71% for manual measurements.   Semi-automatic and manual measurements of distance, width, and tortuosity showed moderate (but statistically significant) correlations. Correlation for derangement was weaker. Semi-automatic measurements are faster than manual measurements. Semi-automatic parameters identify differences between groups, and are as good as manual measurements for between-group classification. © 2011 John Wiley & Sons Ltd.

Coupling a regional warning system to a semantic engine on online news for enhancing landslide prediction

NASA Astrophysics Data System (ADS)

Battistini, Alessandro; Rosi, Ascanio; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

2017-04-01

Landslide inventories are basic data for large scale landslide modelling, e.g. they are needed to calibrate and validate rainfall thresholds, physically based models and early warning systems. The setting up of landslide inventories with traditional methods (e.g. remote sensing, field surveys and manual retrieval of data from technical reports and local newspapers) is time consuming. The objective of this work is to automatically set up a landslide inventory using a state-of-the art semantic engine based on data mining on online news (Battistini et al., 2013) and to evaluate if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds. The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was set up for the Tuscany region (23,000 km2, Italy). The inventory was compared with the outputs of the regional landslide early warning system based on rainfall thresholds, and a good correspondence was found: e.g. 84% of the events reported in the news is correctly identified by the model. In addition, the cases of not correspondence were forwarded to the rainfall threshold developers, which used these inputs to update some of the thresholds. On the basis of the results obtained, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the internet channel using an appropriate semantic engine. We also automated the validation procedure, which is based on a comparison between forecasts and reported events. We verified that our approach can be automatically used for a near real time validation of the warning system and for a semi-automatic update of the rainfall thresholds, which could lead to an improvement of the forecasting effectiveness of the warning system. In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum human intervention. References: Battistini, A., Segoni, S., Manzo, G., Catani, F., Casagli, N. (2013). Web data mining for automatic inventory of geohazards at national scale. Applied Geography, 43, 147-158.

Trust, control strategies and allocation of function in human-machine systems.

PubMed

Lee, J; Moray, N

1992-10-01

As automated controllers supplant human intervention in controlling complex systems, the operators' role often changes from that of an active controller to that of a supervisory controller. Acting as supervisors, operators can choose between automatic and manual control. Improperly allocating function between automatic and manual control can have negative consequences for the performance of a system. Previous research suggests that the decision to perform the job manually or automatically depends, in part, upon the trust the operators invest in the automatic controllers. This paper reports an experiment to characterize the changes in operators' trust during an interaction with a semi-automatic pasteurization plant, and investigates the relationship between changes in operators' control strategies and trust. A regression model identifies the causes of changes in trust, and a 'trust transfer function' is developed using time series analysis to describe the dynamics of trust. Based on a detailed analysis of operators' strategies in response to system faults we suggest a model for the choice between manual and automatic control, based on trust in automatic controllers and self-confidence in the ability to control the system manually.

Agricultural land use mapping. [Pennsylvania, Montana, and Texas

NASA Technical Reports Server (NTRS)

Mcmurtry, G. J.; Petersen, G. W. (Principal Investigator); Wilson, A. D.

1973-01-01

The author has identified the following significant results. Agricultural areas were selected or analysis in southeastern Pennsylvania, north central Montana, and southern Texas. These three sites represent a broad range of soils, soil parent materials, climate, modes of agricultural operation, crops, and field sizes. In each of these three sites, ERTS-1 digital data were processed to determine the feasibility of automatically mapping agricultural land use. In Pennsylvania, forest land, cultivated land, and water were separable within a 25,000 acre area. Four classes of water were also classified and identified, using ground truth. A less complex land use pattern was analyzed in Hill County, Montana. A land use map was prepared shown alternating patterns of summer fallow and stubble fields. The location of farmsteads could be inferred, along with that of a railroad line. A river and a creek flowing into the river were discernible. Six categories of water, related to sediment content and depth, were defined in the reservoir held by the Fresno dam. These classifications were completed on a 150 square mile area. Analysis of the data from Texas is in its formative stages. A test site has been selected and a brightness map has been produced.

Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learning.

PubMed

DeChant, Chad; Wiesner-Hanks, Tyr; Chen, Siyuan; Stewart, Ethan L; Yosinski, Jason; Gore, Michael A; Nelson, Rebecca J; Lipson, Hod

2017-11-01

Northern leaf blight (NLB) can cause severe yield loss in maize; however, scouting large areas to accurately diagnose the disease is time consuming and difficult. We demonstrate a system capable of automatically identifying NLB lesions in field-acquired images of maize plants with high reliability. This approach uses a computational pipeline of convolutional neural networks (CNNs) that addresses the challenges of limited data and the myriad irregularities that appear in images of field-grown plants. Several CNNs were trained to classify small regions of images as containing NLB lesions or not; their predictions were combined into separate heat maps, then fed into a final CNN trained to classify the entire image as containing diseased plants or not. The system achieved 96.7% accuracy on test set images not used in training. We suggest that such systems mounted on aerial- or ground-based vehicles can help in automated high-throughput plant phenotyping, precision breeding for disease resistance, and reduced pesticide use through targeted application across a variety of plant and disease categories.

An automatic agricultural zone classification procedure for crop inventory satellite images

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Kux, H. J.; Velasco, F. R. D.; Deoliveira, M. O. B.

1982-01-01

A classification procedure for assessing crop areal proportion in multispectral scanner image is discussed. The procedure is into four parts: labeling; classification; proportion estimation; and evaluation. The procedure also has the following characteristics: multitemporal classification; the need for a minimum field information; and verification capability between automatic classification and analyst labeling. The processing steps and the main algorithms involved are discussed. An outlook on the future of this technology is also presented.

A general graphical user interface for automatic reliability modeling

NASA Technical Reports Server (NTRS)

Liceaga, Carlos A.; Siewiorek, Daniel P.

1991-01-01

Reported here is a general Graphical User Interface (GUI) for automatic reliability modeling of Processor Memory Switch (PMS) structures using a Markov model. This GUI is based on a hierarchy of windows. One window has graphical editing capabilities for specifying the system's communication structure, hierarchy, reconfiguration capabilities, and requirements. Other windows have field texts, popup menus, and buttons for specifying parameters and selecting actions. An example application of the GUI is given.

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.

A semi-automatic annotation tool for cooking video

NASA Astrophysics Data System (ADS)

Bianco, Simone; Ciocca, Gianluigi; Napoletano, Paolo; Schettini, Raimondo; Margherita, Roberto; Marini, Gianluca; Gianforme, Giorgio; Pantaleo, Giuseppe

2013-03-01

In order to create a cooking assistant application to guide the users in the preparation of the dishes relevant to their profile diets and food preferences, it is necessary to accurately annotate the video recipes, identifying and tracking the foods of the cook. These videos present particular annotation challenges such as frequent occlusions, food appearance changes, etc. Manually annotate the videos is a time-consuming, tedious and error-prone task. Fully automatic tools that integrate computer vision algorithms to extract and identify the elements of interest are not error free, and false positive and false negative detections need to be corrected in a post-processing stage. We present an interactive, semi-automatic tool for the annotation of cooking videos that integrates computer vision techniques under the supervision of the user. The annotation accuracy is increased with respect to completely automatic tools and the human effort is reduced with respect to completely manual ones. The performance and usability of the proposed tool are evaluated on the basis of the time and effort required to annotate the same video sequences.

Automated reconstruction of standing posture panoramas from multi-sector long limb x-ray images

NASA Astrophysics Data System (ADS)

Miller, Linzey; Trier, Caroline; Ben-Zikri, Yehuda K.; Linte, Cristian A.

2016-03-01

Due to the digital X-ray imaging system's limited field of view, several individual sector images are required to capture the posture of an individual in standing position. These images are then "stitched together" to reconstruct the standing posture. We have created an image processing application that automates the stitching, therefore minimizing user input, optimizing workflow, and reducing human error. The application begins with pre-processing the input images by removing artifacts, filtering out isolated noisy regions, and amplifying a seamless bone edge. The resulting binary images are then registered together using a rigid-body intensity based registration algorithm. The identified registration transformations are then used to map the original sector images into the panorama image. Our method focuses primarily on the use of the anatomical content of the images to generate the panoramas as opposed to using external markers employed to aid with the alignment process. Currently, results show robust edge detection prior to registration and we have tested our approach by comparing the resulting automatically-stitched panoramas to the manually stitched panoramas in terms of registration parameters, target registration error of homologous markers, and the homogeneity of the digitally subtracted automatically- and manually-stitched images using 26 patient datasets.

Software development for a gamma-ray burst rapid-response observatory in the US Virgin Islands.

NASA Astrophysics Data System (ADS)

Davis, K. A.; Giblin, T. W.; Neff, J. E.; Hakkila, J.; Hartmann, D.

2004-12-01

The site is situated near the crest of Crown Mountain on the island of St. Thomas in the US Virgin Islands. The observing site is strategically located 65 W longitude, placing it as the most eastern GRB-dedicated observing site in the western hemisphere. The observatory has a 0.5 m robotic telescope and a Marconi 4240 2048 by 2048 CCD with BVRI filters. The field of view is identical to that of the XRT onboard Swift, 19 by 19 arc minutes. The telescope is operated through the Talon telescope control software. The observatory is notified of a burst trigger through the GRB Coordinates Network (GCN). This GCN notification is received through a socket connection to the control computer on site. A Perl script passes this information to the Talon software, which automatically interrupts concurrent observations and inserts a new GRB observing schedule. Once the observations are made the resulting images are then analyzed in IRAF. A source extraction is necessary to identify known sources and the optical transient. The system is being calibrated for automatic GRB response and is expected to be ready to follow up Swift observations. This work has been supported by NSF and NASA-EPSCoR.

Myocardial perfusion assessment with contrast echocardiography

NASA Astrophysics Data System (ADS)

Desco, Manuel; Ledesma-Carbayo, Maria J.; Santos, Andres; Garcia-Fernandez, Miguel A.; Marcos-Alberca, Pedro; Malpica, Norberto; Antoranz, Jose C.; Garcia-Barreno, Pedro

2001-05-01

Assessment of intramyocardial perfusion by contrast echocardiography is a promising new technique that allows to obtain quantitative parameters for the assessment of ischemic disease. In this work, a new methodology and a software prototype developed for this task are presented. It has been validated with Coherent Contrast Imaging (CCI) images acquired with an Acuson Sequoia scanner. Contrast (Optison microbubbles) is injected continuously during the scan. 150 images are acquired using low mechanical index U/S pulses. A burst of high mechanical index pulses is used to destroy bubbles, thus allowing to detect the contrast wash-in. The stud is performed in two conditions: rest and pharmacologically induced stress. The software developed allows to visualized the study (cine) and to select several ROIs within the heart wall. The position of these ROIs along the cardiac cycle is automatically corrected on the basis of the gradient field, and they can also be manually corrected in case the automatic procedure fails. Time curves are analyzed according to a parametric model that incorporates both contrast inflow rate and cyclic variations. Preliminary clinical results on 80 patients have allowed us to identify normal and pathological patterns and to establish the correlation of quantitative parameters with the real diagnosis.

Exploiting range imagery: techniques and applications

NASA Astrophysics Data System (ADS)

Armbruster, Walter

2009-07-01

Practically no applications exist for which automatic processing of 2D intensity imagery can equal human visual perception. This is not the case for range imagery. The paper gives examples of 3D laser radar applications, for which automatic data processing can exceed human visual cognition capabilities and describes basic processing techniques for attaining these results. The examples are drawn from the fields of helicopter obstacle avoidance, object detection in surveillance applications, object recognition at high range, multi-object-tracking, and object re-identification in range image sequences. Processing times and recognition performances are summarized. The techniques used exploit the bijective continuity of the imaging process as well as its independence of object reflectivity, emissivity and illumination. This allows precise formulations of the probability distributions involved in figure-ground segmentation, feature-based object classification and model based object recognition. The probabilistic approach guarantees optimal solutions for single images and enables Bayesian learning in range image sequences. Finally, due to recent results in 3D-surface completion, no prior model libraries are required for recognizing and re-identifying objects of quite general object categories, opening the way to unsupervised learning and fully autonomous cognitive systems.

Short non-coding RNAs as bacteria species identifiers detected by surface plasmon resonance enhanced common path interferometry

NASA Astrophysics Data System (ADS)

Greef, Charles; Petropavlovskikh, Viatcheslav; Nilsen, Oyvind; Khattatov, Boris; Plam, Mikhail; Gardner, Patrick; Hall, John

2008-04-01

Small non-coding RNA sequences have recently been discovered as unique identifiers of certain bacterial species, raising the possibility that they can be used as highly specific Biowarfare Agent detection markers in automated field deployable integrated detection systems. Because they are present in high abundance they could allow genomic based bacterial species identification without the need for pre-assay amplification. Further, a direct detection method would obviate the need for chemical labeling, enabling a rapid, efficient, high sensitivity mechanism for bacterial detection. Surface Plasmon Resonance enhanced Common Path Interferometry (SPR-CPI) is a potentially market disruptive, high sensitivity dual technology that allows real-time direct multiplex measurement of biomolecule interactions, including small molecules, nucleic acids, proteins, and microbes. SPR-CPI measures differences in phase shift of reflected S and P polarized light under Total Internal Reflection (TIR) conditions at a surface, caused by changes in refractive index induced by biomolecular interactions within the evanescent field at the TIR interface. The measurement is performed on a microarray of discrete 2-dimensional areas functionalized with biomolecule capture reagents, allowing simultaneous measurement of up to 100 separate analytes. The optical beam encompasses the entire microarray, allowing a solid state detector system with no scanning requirement. Output consists of simultaneous voltage measurements proportional to the phase differences resulting from the refractive index changes from each microarray feature, and is automatically processed and displayed graphically or delivered to a decision making algorithm, enabling a fully automatic detection system capable of rapid detection and quantification of small nucleic acids at extremely sensitive levels. Proof-of-concept experiments on model systems and cell culture samples have demonstrated utility of the system, and efforts are in progress for full development and deployment of the device. The technology has broad applicability as a universal detection platform for BWA detection, medical diagnostics, and drug discovery research, and represents a new class of instrumentation as a rapid, high sensitivity, label-free methodology.

Semi-Automatic Determination of Rockfall Trajectories

PubMed Central

Volkwein, Axel; Klette, Johannes

2014-01-01

In determining rockfall trajectories in the field, it is essential to calibrate and validate rockfall simulation software. This contribution presents an in situ device and a complementary Local Positioning System (LPS) that allow the determination of parts of the trajectory. An assembly of sensors (herein called rockfall sensor) is installed in the falling block recording the 3D accelerations and rotational velocities. The LPS automatically calculates the position of the block along the slope over time based on Wi-Fi signals emitted from the rockfall sensor. The velocity of the block over time is determined through post-processing. The setup of the rockfall sensor is presented followed by proposed calibration and validation procedures. The performance of the LPS is evaluated by means of different experiments. The results allow for a quality analysis of both the obtained field data and the usability of the rockfall sensor for future/further applications in the field. PMID:25268916

Hough transform for clustered microcalcifications detection in full-field digital mammograms

NASA Astrophysics Data System (ADS)

Fanizzi, A.; Basile, T. M. A.; Losurdo, L.; Amoroso, N.; Bellotti, R.; Bottigli, U.; Dentamaro, R.; Didonna, V.; Fausto, A.; Massafra, R.; Moschetta, M.; Tamborra, P.; Tangaro, S.; La Forgia, D.

2017-09-01

Many screening programs use mammography as principal diagnostic tool for detecting breast cancer at a very early stage. Despite the efficacy of the mammograms in highlighting breast diseases, the detection of some lesions is still doubtless for radiologists. In particular, the extremely minute and elongated salt-like particles of microcalcifications are sometimes no larger than 0.1 mm and represent approximately half of all cancer detected by means of mammograms. Hence the need for automatic tools able to support radiologists in their work. Here, we propose a computer assisted diagnostic tool to support radiologists in identifying microcalcifications in full (native) digital mammographic images. The proposed CAD system consists of a pre-processing step, that improves contrast and reduces noise by applying Sobel edge detection algorithm and Gaussian filter, followed by a microcalcification detection step performed by exploiting the circular Hough transform. The procedure performance was tested on 200 images coming from the Breast Cancer Digital Repository (BCDR), a publicly available database. The automatically detected clusters of microcalcifications were evaluated by skilled radiologists which asses the validity of the correctly identified regions of interest as well as the system error in case of missed clustered microcalcifications. The system performance was evaluated in terms of Sensitivity and False Positives per images (FPi) rate resulting comparable to the state-of-art approaches. The proposed model was able to accurately predict the microcalcification clusters obtaining performances (sensibility = 91.78% and FPi rate = 3.99) which favorably compare to other state-of-the-art approaches.

Estimation of prenatal aorta intima-media thickness in ultrasound examination

NASA Astrophysics Data System (ADS)

Veronese, Elisa; Poletti, Enea; Cosmi, Erich; Grisan, Enrico

2012-03-01

Prenatal events such as intrauterine growth restriction have been shown to be associated with an increased thickness of abdominal aorta in the fetus. Therefore the measurement of abdominal aortic intima-media thickness (aIMT) has been recently considered a sensitive marker of artherosclerosis risk. To date measure of aortic diameter and of aIMT has been performed manually on US fetal images, thus being susceptible to intra- and inter- operator variability. This work introduces an automatic algorithm that identifies abdominal aorta and estimates its diameter and aIMT from videos recorded during routine third trimester ultrasonographic fetal biometry. Firstly, in each frame, the algorithm locates and segments the region corresponding to aorta by means of an active contour driven by two different external forces: a static vector field convolution force and a dynamic pressure force. Then, in each frame, the mean diameter of the vessel is computed, to reconstruct the cardiac cycle: in fact, we expect the diameter to have a sinusoidal trend, according to the heart rate. From the obtained sinusoid, we identify the frames corresponding to the end diastole and to the end systole. Finally, in these frames we assess the aIMT. According to its definition, we consider as aIMT the distance between the leading edge of the blood-intima interface, and the leading edge of the media-adventitia interface on the far wall of the vessel. The correlation between end-diastole and end-systole aIMT automatic and manual measures is 0.90 and 0.84 respectively.

Segmentation, Splitting, and Classification of Overlapping Bacteria in Microscope Images for Automatic Bacterial Vaginosis Diagnosis.

PubMed

Song, Youyi; He, Liang; Zhou, Feng; Chen, Siping; Ni, Dong; Lei, Baiying; Wang, Tianfu

2017-07-01

Quantitative analysis of bacterial morphotypes in the microscope images plays a vital role in diagnosis of bacterial vaginosis (BV) based on the Nugent score criterion. However, there are two main challenges for this task: 1) It is quite difficult to identify the bacterial regions due to various appearance, faint boundaries, heterogeneous shapes, low contrast with the background, and small bacteria sizes with regards to the image. 2) There are numerous bacteria overlapping each other, which hinder us to conduct accurate analysis on individual bacterium. To overcome these challenges, we propose an automatic method in this paper to diagnose BV by quantitative analysis of bacterial morphotypes, which consists of a three-step approach, i.e., bacteria regions segmentation, overlapping bacteria splitting, and bacterial morphotypes classification. Specifically, we first segment the bacteria regions via saliency cut, which simultaneously evaluates the global contrast and spatial weighted coherence. And then Markov random field model is applied for high-quality unsupervised segmentation of small object. We then decompose overlapping bacteria clumps into markers, and associate a pixel with markers to identify evidence for eventual individual bacterium splitting. Next, we extract morphotype features from each bacterium to learn the descriptors and to characterize the types of bacteria using an Adaptive Boosting machine learning framework. Finally, BV diagnosis is implemented based on the Nugent score criterion. Experiments demonstrate that our proposed method achieves high accuracy and efficiency in computation for BV diagnosis.

Documents Similarity Measurement Using Field Association Terms.

ERIC Educational Resources Information Center

Atlam, El-Sayed; Fuketa, M.; Morita, K.; Aoe, Jun-ichi

2003-01-01

Discussion of text analysis and information retrieval and measurement of document similarity focuses on a new text manipulation system called FA (field association)-Sim that is useful for retrieving information in large heterogeneous texts and for recognizing content similarity in text excerpts. Discusses recall and precision, automatic indexing…

Automatic single questionnaire intensity (SQI, EMS98 scale) estimation using ranking models built on the existing BCSF database

NASA Astrophysics Data System (ADS)

Schlupp, A.; Sira, C.; Schmitt, K.; Schaming, M.

2013-12-01

In charge of intensity estimations in France, BCSF has collected and manually analyzed more than 47000 online individual macroseismic questionnaires since 2000 up to intensity VI. These macroseismic data allow us to estimate one SQI value (Single Questionnaire Intensity) for each form following the EMS98 scale. The reliability of the automatic intensity estimation is important as they are today used for automatic shakemaps communications and crisis management. Today, the automatic intensity estimation at BCSF is based on the direct use of thumbnails selected on a menu by the witnesses. Each thumbnail corresponds to an EMS-98 intensity value, allowing us to quickly issue an intensity map of the communal intensity by averaging the SQIs at each city. Afterwards an expert, to determine a definitive SQI, manually analyzes each form. This work is time consuming and not anymore suitable considering the increasing number of testimonies at BCSF. Nevertheless, it can take into account incoherent answers. We tested several automatic methods (USGS algorithm, Correlation coefficient, Thumbnails) (Sira et al. 2013, IASPEI) and compared them with 'expert' SQIs. These methods gave us medium score (between 50 to 60% of well SQI determined and 35 to 40% with plus one or minus one intensity degree). The best fit was observed with the thumbnails. Here, we present new approaches based on 3 statistical ranking methods as 1) Multinomial logistic regression model, 2) Discriminant analysis DISQUAL and 3) Support vector machines (SVMs). The two first methods are standard methods, while the third one is more recent. Theses methods could be applied because the BCSF has already in his database more then 47000 forms and because their questions and answers are well adapted for a statistical analysis. The ranking models could then be used as automatic method constrained on expert analysis. The performance of the automatic methods and the reliability of the estimated SQI can be evaluated thanks to the fact that each definitive BCSF SQIs is determined by an expert analysis. We compare the SQIs obtained by these methods from our database and discuss the coherency and variations between automatic and manual processes. These methods lead to high scores with up to 85% of the forms well classified and most of the remaining forms classified with only a shift of one intensity degree. This allows us to use the ranking methods as the best automatic methods to fast SQIs estimation and to produce fast shakemaps. The next step, to improve the use of these methods, will be to identify explanations for the forms not classified at the correct value and a way to select the few remaining forms that should be analyzed by the expert. Note that beyond intensity VI, on-line questionnaires are insufficient and a field survey is indispensable to estimate intensity. For such survey, in France, BCSF leads a macroseismic intervention group (GIM).

[Stimulation parameters for automatic examination of color vision].

PubMed

Sommerhalder, J; Pelizzone, M; Roth, A

1997-05-01

We have developed a polyvalent computer controlled instrument, which uses the "two equation method" (Rayleigh and Moreland equations) to measure human colour vision. This "colorimeter" (or anomaloscope) was used to determine the influence of some important stimulation parameters. The influence of stimulus exposure time, observation field size, absolute stimulus luminance, saturation and luminance mismatches between mixture and reference stimuli were measured on our computer controlled colorimeter. All subjects were normal observers. 1) An exposure time of 2s was found to be optimal for clinical work. 2) The Moreland equation on a 7 degrees observation field yields results in which population variability is comparable to a Rayleigh equation on a 2 degrees field. 3) A retinal illuminance between 40 and 1000 trolands can be used for automated Moreland matches. 4) The saturation of the reference field for the Moreland match can be preset to a fixed value. 5) It is important to vary automatically the radiance of the reference field to provide an approximate luminance match as the ratio of primaries in the mixture field is changed. These measurements allows us to determine optimal conditions for automated colour vision examinations and to make recommendations for an international standard.

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.

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PubMed

Narayan, Sreenath; Kalhan, Satish C; Wilson, David L

2013-05-01

To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. Copyright © 2012 Wiley Periodicals, Inc.

Automatic health record review to help prioritize gravely ill Social Security disability applicants.

PubMed

Abbott, Kenneth; Ho, Yen-Yi; Erickson, Jennifer

2017-07-01

Every year, thousands of patients die waiting for disability benefits from the Social Security Administration. Some qualify for expedited service under the Compassionate Allowance (CAL) initiative, but CAL software focuses exclusively on information from a single form field. This paper describes the development of a supplemental process for identifying some overlooked but gravely ill applicants, through automatic annotation of health records accompanying new claims. We explore improved prioritization instead of fully autonomous claims approval. We developed a sample of claims containing medical records at the moment of arrival in a single office. A series of tools annotated both patient records and public Web page descriptions of CAL medical conditions. We trained random forests to identify CAL patients and validated each model with 10-fold cross validation. Our main model, a general CAL classifier, had an area under the receiver operating characteristic curve of 0.915. Combining this classifier with existing software improved sensitivity from 0.960 to 0.994, detecting every deceased patient, but reducing positive predictive value to 0.216. True positive CAL identification is a priority, given CAL patient mortality. Mere prioritization of the false positives would not create a meaningful burden in terms of manual review. Death certificate data suggest the presence of truly ill patients among putative false positives. To a limited extent, it is possible to identify gravely ill Social Security disability applicants by analyzing annotations of unstructured electronic health records, and the level of identification is sufficient to be useful in prioritizing case reviews. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the US.

SOMBI: Bayesian identification of parameter relations in unstructured cosmological data

NASA Astrophysics Data System (ADS)

Frank, Philipp; Jasche, Jens; Enßlin, Torsten A.

2016-11-01

This work describes the implementation and application of a correlation determination method based on self organizing maps and Bayesian inference (SOMBI). SOMBI aims to automatically identify relations between different observed parameters in unstructured cosmological or astrophysical surveys by automatically identifying data clusters in high-dimensional datasets via the self organizing map neural network algorithm. Parameter relations are then revealed by means of a Bayesian inference within respective identified data clusters. Specifically such relations are assumed to be parametrized as a polynomial of unknown order. The Bayesian approach results in a posterior probability distribution function for respective polynomial coefficients. To decide which polynomial order suffices to describe correlation structures in data, we include a method for model selection, the Bayesian information criterion, to the analysis. The performance of the SOMBI algorithm is tested with mock data. As illustration we also provide applications of our method to cosmological data. In particular, we present results of a correlation analysis between galaxy and active galactic nucleus (AGN) properties provided by the SDSS catalog with the cosmic large-scale-structure (LSS). The results indicate that the combined galaxy and LSS dataset indeed is clustered into several sub-samples of data with different average properties (for example different stellar masses or web-type classifications). The majority of data clusters appear to have a similar correlation structure between galaxy properties and the LSS. In particular we revealed a positive and linear dependency between the stellar mass, the absolute magnitude and the color of a galaxy with the corresponding cosmic density field. A remaining subset of data shows inverted correlations, which might be an artifact of non-linear redshift distortions.

A semantic graph-based approach to biomedical summarisation.

PubMed

Plaza, Laura; Díaz, Alberto; Gervás, Pablo

2011-09-01

Access to the vast body of research literature that is available in biomedicine and related fields may be improved by automatic summarisation. This paper presents a method for summarising biomedical scientific literature that takes into consideration the characteristics of the domain and the type of documents. To address the problem of identifying salient sentences in biomedical texts, concepts and relations derived from the Unified Medical Language System (UMLS) are arranged to construct a semantic graph that represents the document. A degree-based clustering algorithm is then used to identify different themes or topics within the text. Different heuristics for sentence selection, intended to generate different types of summaries, are tested. A real document case is drawn up to illustrate how the method works. A large-scale evaluation is performed using the recall-oriented understudy for gisting-evaluation (ROUGE) metrics. The results are compared with those achieved by three well-known summarisers (two research prototypes and a commercial application) and two baselines. Our method significantly outperforms all summarisers and baselines. The best of our heuristics achieves an improvement in performance of almost 7.7 percentage units in the ROUGE-1 score over the LexRank summariser (0.7862 versus 0.7302). A qualitative analysis of the summaries also shows that our method succeeds in identifying sentences that cover the main topic of the document and also considers other secondary or "satellite" information that might be relevant to the user. The method proposed is proved to be an efficient approach to biomedical literature summarisation, which confirms that the use of concepts rather than terms can be very useful in automatic summarisation, especially when dealing with highly specialised domains. Copyright © 2011 Elsevier B.V. All rights reserved.

Improved automatic adjustment of density and contrast in FCR system using neural network

NASA Astrophysics Data System (ADS)

Takeo, Hideya; Nakajima, Nobuyoshi; Ishida, Masamitsu; Kato, Hisatoyo

1994-05-01

FCR system has an automatic adjustment of image density and contrast by analyzing the histogram of image data in the radiation field. Advanced image recognition methods proposed in this paper can improve the automatic adjustment performance, in which neural network technology is used. There are two methods. Both methods are basically used 3-layer neural network with back propagation. The image data are directly input to the input-layer in one method and the histogram data is input in the other method. The former is effective to the imaging menu such as shoulder joint in which the position of interest region occupied on the histogram changes by difference of positioning and the latter is effective to the imaging menu such as chest-pediatrics in which the histogram shape changes by difference of positioning. We experimentally confirm the validity of these methods (about the automatic adjustment performance) as compared with the conventional histogram analysis methods.

Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping.

PubMed

Sadeghi-Tehran, Pouria; Virlet, Nicolas; Sabermanesh, Kasra; Hawkesford, Malcolm J

2017-01-01

Accurately segmenting vegetation from the background within digital images is both a fundamental and a challenging task in phenotyping. The performance of traditional methods is satisfactory in homogeneous environments, however, performance decreases when applied to images acquired in dynamic field environments. In this paper, a multi-feature learning method is proposed to quantify vegetation growth in outdoor field conditions. The introduced technique is compared with the state-of the-art and other learning methods on digital images. All methods are compared and evaluated with different environmental conditions and the following criteria: (1) comparison with ground-truth images, (2) variation along a day with changes in ambient illumination, (3) comparison with manual measurements and (4) an estimation of performance along the full life cycle of a wheat canopy. The method described is capable of coping with the environmental challenges faced in field conditions, with high levels of adaptiveness and without the need for adjusting a threshold for each digital image. The proposed method is also an ideal candidate to process a time series of phenotypic information throughout the crop growth acquired in the field. Moreover, the introduced method has an advantage that it is not limited to growth measurements only but can be applied on other applications such as identifying weeds, diseases, stress, etc.

Automatic Segmentation of Drosophila Neural Compartments Using GAL4 Expression Data Reveals Novel Visual Pathways.

PubMed

Panser, Karin; Tirian, Laszlo; Schulze, Florian; Villalba, Santiago; Jefferis, Gregory S X E; Bühler, Katja; Straw, Andrew D

2016-08-08

Identifying distinct anatomical structures within the brain and developing genetic tools to target them are fundamental steps for understanding brain function. We hypothesize that enhancer expression patterns can be used to automatically identify functional units such as neuropils and fiber tracts. We used two recent, genome-scale Drosophila GAL4 libraries and associated confocal image datasets to segment large brain regions into smaller subvolumes. Our results (available at https://strawlab.org/braincode) support this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. The basis for the structural assignment is clustering of voxels based on patterns of enhancer expression. These initial clusters are agglomerated to make hierarchical predictions of structure. We applied the algorithm to central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 11 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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.

An effective automatic procedure for testing parameter identifiability of HIV/AIDS models.

PubMed

Saccomani, Maria Pia

2011-08-01

Realistic HIV models tend to be rather complex and many recent models proposed in the literature could not yet be analyzed by traditional identifiability testing techniques. In this paper, we check a priori global identifiability of some of these nonlinear HIV models taken from the recent literature, by using a differential algebra algorithm based on previous work of the author. The algorithm is implemented in a software tool, called DAISY (Differential Algebra for Identifiability of SYstems), which has been recently released (DAISY is freely available on the web site http://www.dei.unipd.it/~pia/ ). The software can be used to automatically check global identifiability of (linear and) nonlinear models described by polynomial or rational differential equations, thus providing a general and reliable tool to test global identifiability of several HIV models proposed in the literature. It can be used by researchers with a minimum of mathematical background.

77 FR 74647 - Application(s) for Duty-Free Entry of Scientific Instruments

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-17

... an AFM tip to measure the electromagnetic near-field of optical antennas, plasmonics in metals and... field-aligned Ion Cyclotron RF antenna, which is used to automatically follow the load variation in real time and make the antenna system load tolerant. The instrument's unique specifications are its...

An Experiment of GMPLS-Based Dispersion Compensation Control over In-Field Fibers

NASA Astrophysics Data System (ADS)

Seno, Shoichiro; Horiuchi, Eiichi; Yoshida, Sota; Sugihara, Takashi; Onohara, Kiyoshi; Kamei, Misato; Baba, Yoshimasa; Kubo, Kazuo; Mizuochi, Takashi

As ROADMs (Reconfigurable Optical Add/Drop Multiplexers) are becoming widely used in metro/core networks, distributed control of wavelength paths by extended GMPLS (Generalized MultiProtocol Label Switching) protocols has attracted much attention. For the automatic establishment of an arbitrary wavelength path satisfying dynamic traffic demands over a ROADM or WXC (Wavelength Cross Connect)-based network, precise determination of chromatic dispersion over the path and optimized assignment of dispersion compensation capabilities at related nodes are essential. This paper reports an experiment over in-field fibers where GMPLS-based control was applied for the automatic discovery of chromatic dispersion, path computation, and wavelength path establishment with dynamic adjustment of variable dispersion compensation. The GMPLS-based control scheme, which the authors called GMPLS-Plus, extended GMPLS's distributed control architecture with attributes for automatic discovery, advertisement, and signaling of chromatic dispersion. In this experiment, wavelength paths with distances of 24km and 360km were successfully established and error-free data transmission was verified. The experiment also confirmed path restoration with dynamic compensation adjustment upon fiber failure.

Automatic Image Registration of Multimodal Remotely Sensed Data with Global Shearlet Features

NASA Technical Reports Server (NTRS)

Murphy, James M.; Le Moigne, Jacqueline; Harding, David J.

2015-01-01

Automatic image registration is the process of aligning two or more images of approximately the same scene with minimal human assistance. Wavelet-based automatic registration methods are standard, but sometimes are not robust to the choice of initial conditions. That is, if the images to be registered are too far apart relative to the initial guess of the algorithm, the registration algorithm does not converge or has poor accuracy, and is thus not robust. These problems occur because wavelet techniques primarily identify isotropic textural features and are less effective at identifying linear and curvilinear edge features. We integrate the recently developed mathematical construction of shearlets, which is more effective at identifying sparse anisotropic edges, with an existing automatic wavelet-based registration algorithm. Our shearlet features algorithm produces more distinct features than wavelet features algorithms; the separation of edges from textures is even stronger than with wavelets. Our algorithm computes shearlet and wavelet features for the images to be registered, then performs least squares minimization on these features to compute a registration transformation. Our algorithm is two-staged and multiresolution in nature. First, a cascade of shearlet features is used to provide a robust, though approximate, registration. This is then refined by registering with a cascade of wavelet features. Experiments across a variety of image classes show an improved robustness to initial conditions, when compared to wavelet features alone.

Automatic Image Registration of Multi-Modal Remotely Sensed Data with Global Shearlet Features

PubMed Central

Murphy, James M.; Le Moigne, Jacqueline; Harding, David J.

2017-01-01

Automatic image registration is the process of aligning two or more images of approximately the same scene with minimal human assistance. Wavelet-based automatic registration methods are standard, but sometimes are not robust to the choice of initial conditions. That is, if the images to be registered are too far apart relative to the initial guess of the algorithm, the registration algorithm does not converge or has poor accuracy, and is thus not robust. These problems occur because wavelet techniques primarily identify isotropic textural features and are less effective at identifying linear and curvilinear edge features. We integrate the recently developed mathematical construction of shearlets, which is more effective at identifying sparse anisotropic edges, with an existing automatic wavelet-based registration algorithm. Our shearlet features algorithm produces more distinct features than wavelet features algorithms; the separation of edges from textures is even stronger than with wavelets. Our algorithm computes shearlet and wavelet features for the images to be registered, then performs least squares minimization on these features to compute a registration transformation. Our algorithm is two-staged and multiresolution in nature. First, a cascade of shearlet features is used to provide a robust, though approximate, registration. This is then refined by registering with a cascade of wavelet features. Experiments across a variety of image classes show an improved robustness to initial conditions, when compared to wavelet features alone. PMID:29123329

Automatic Classification of Extensive Aftershock Sequences Using Empirical Matched Field Processing

NASA Astrophysics Data System (ADS)

Gibbons, Steven J.; Harris, David B.; Kværna, Tormod; Dodge, Douglas A.

2013-04-01

The aftershock sequences that follow large earthquakes create considerable problems for data centers attempting to produce comprehensive event bulletins in near real-time. The greatly increased number of events which require processing can overwhelm analyst resources and reduce the capacity for analyzing events of monitoring interest. This exacerbates a potentially reduced detection capability at key stations, due the noise generated by the sequence, and a deterioration in the quality of the fully automatic preliminary event bulletins caused by the difficulty in associating the vast numbers of closely spaced arrivals over the network. Considerable success has been enjoyed by waveform correlation methods for the automatic identification of groups of events belonging to the same geographical source region, facilitating the more time-efficient analysis of event ensembles as opposed to individual events. There are, however, formidable challenges associated with the automation of correlation procedures. The signal generated by a very large earthquake seldom correlates well enough with the signals generated by far smaller aftershocks for a correlation detector to produce statistically significant triggers at the correct times. Correlation between events within clusters of aftershocks is significantly better, although the issues of when and how to initiate new pattern detectors are still being investigated. Empirical Matched Field Processing (EMFP) is a highly promising method for detecting event waveforms suitable as templates for correlation detectors. EMFP is a quasi-frequency-domain technique that calibrates the spatial structure of a wavefront crossing a seismic array in a collection of narrow frequency bands. The amplitude and phase weights that result are applied in a frequency-domain beamforming operation that compensates for scattering and refraction effects not properly modeled by plane-wave beams. It has been demonstrated to outperform waveform correlation as a classifier of ripple-fired mining blasts since the narrowband procedure is insensitive to differences in the source-time functions. For sequences in which the spectral content and time-histories of the signals from the main shock and aftershocks vary greatly, the spatial structure calibrated by EMFP is an invariant that permits reliable detection of events in the specific source region. Examples from the 2005 Kashmir and 2011 Van earthquakes demonstrate how EMFP templates from the main events detect arrivals from the aftershock sequences with high sensitivity and exceptionally low false alarm rates. Classical waveform correlation detectors are demonstrated to fail for these examples. Even arrivals with SNR below unity can produce significant EMFP triggers as the spatial pattern of the incoming wavefront is identified, leading to robust detections at a greater number of stations and potentially more reliable automatic bulletins. False EMFP triggers are readily screened by scanning a space of phase shifts relative to the imposed template. EMFP has the potential to produce a rapid and robust overview of the evolving aftershock sequence such that correlation and subspace detectors can be applied semi-autonomously, with well-chosen parameter specifications, to identify and classify clusters of very closely spaced aftershocks.

Effects of voluntary and automatic control of center of pressure sway during quiet standing.

PubMed

Ueta, Kozo; Okada, Yohei; Nakano, Hideki; Osumi, Michihiro; Morioka, Shu

2015-01-01

The authors investigated the effects of voluntary and automatic control on the spatial variables (envelope area, maximal amplitude, and root mean square [RMS]) of center of pressure (COP) displacement during quiet standing and identified differences in their postural control strategies (mean velocity [MV], mean power frequency [MPF], and power density). COP data were recorded under relaxed (experimental control), still (voluntary control), and dual (automatic control) conditions. RMS was significantly lower in the still and dual conditions than in the relaxed condition. MV, MPF, and power density were significantly higher in the still condition than in the dual condition. These results indicate that both voluntary and automatic control decrease the spatial variables of COP displacement; however, their postural control strategies are different.

Automatic Registration of GF4 Pms: a High Resolution Multi-Spectral Sensor on Board a Satellite on Geostationary Orbit

NASA Astrophysics Data System (ADS)

Gao, M.; Li, J.

2018-04-01

Geometric correction is an important preprocessing process in the application of GF4 PMS image. The method of geometric correction that is based on the manual selection of geometric control points is time-consuming and laborious. The more common method, based on a reference image, is automatic image registration. This method involves several steps and parameters. For the multi-spectral sensor GF4 PMS, it is necessary for us to identify the best combination of parameters and steps. This study mainly focuses on the following issues: necessity of Rational Polynomial Coefficients (RPC) correction before automatic registration, base band in the automatic registration and configuration of GF4 PMS spatial resolution.

Automatic recognition and analysis of synapses. [in brain tissue

NASA Technical Reports Server (NTRS)

Ungerleider, J. A.; Ledley, R. S.; Bloom, F. E.

1976-01-01

An automatic system for recognizing synaptic junctions would allow analysis of large samples of tissue for the possible classification of specific well-defined sets of synapses based upon structural morphometric indices. In this paper the three steps of our system are described: (1) cytochemical tissue preparation to allow easy recognition of the synaptic junctions; (2) transmitting the tissue information to a computer; and (3) analyzing each field to recognize the synapses and make measurements on them.

Automatic Docking System Sensor Design, Test, and Mission Performance

NASA Technical Reports Server (NTRS)

Jackson, John L.; Howard, Richard T.; Cole, Helen J.

1998-01-01

The Video Guidance Sensor is a key element of an automatic rendezvous and docking program administered by NASA that was flown on STS-87 in November of 1997. The system used laser illumination of a passive target in the field of view of an on-board camera and processed the video image to determine the relative position and attitude between the target and the sensor. Comparisons of mission results with theoretical models and laboratory measurements will be discussed.

Automatic translation among spoken languages

NASA Technical Reports Server (NTRS)

Walter, Sharon M.; Costigan, Kelly

1994-01-01

The Machine Aided Voice Translation (MAVT) system was developed in response to the shortage of experienced military field interrogators with both foreign language proficiency and interrogation skills. Combining speech recognition, machine translation, and speech generation technologies, the MAVT accepts an interrogator's spoken English question and translates it into spoken Spanish. The spoken Spanish response of the potential informant can then be translated into spoken English. Potential military and civilian applications for automatic spoken language translation technology are discussed in this paper.

Building the Joint Battlespace Infosphere. Volume 1: Summary

DTIC Science & Technology

1999-12-17

portable devices , including wearable computer technology for mobile or field application 7.1.4.4.3 The Far Term (2009) The technology will be...graphic on a 2-D map image, or change the list of weapons to be loaded on an F/A-18, or sound an audible alarm in conjunction with flashing red...information automatically through a subscribe process. (3) At the same time, published information can be automatically changed into a new representation or

Automated Grading of Rough Hardwood Lumber

Treesearch

Richard W. Conners; Tai-Hoon Cho; Philip A. Araman

1989-01-01

Any automatic hardwood grading system must have two components. The first of these is a computer vision system for locating and identifying defects on rough lumber. The second is a system for automatically grading boards based on the output of the computer vision system. This paper presents research results aimed at developing the first of these components. The...

Automatic machine learning based prediction of cardiovascular events in lung cancer screening data

NASA Astrophysics Data System (ADS)

de Vos, Bob D.; de Jong, Pim A.; Wolterink, Jelmer M.; Vliegenthart, Rozemarijn; Wielingen, Geoffrey V. F.; Viergever, Max A.; Išgum, Ivana

2015-03-01

Calcium burden determined in CT images acquired in lung cancer screening is a strong predictor of cardiovascular events (CVEs). This study investigated whether subjects undergoing such screening who are at risk of a CVE can be identified using automatic image analysis and subject characteristics. Moreover, the study examined whether these individuals can be identified using solely image information, or if a combination of image and subject data is needed. A set of 3559 male subjects undergoing Dutch-Belgian lung cancer screening trial was included. Low-dose non-ECG synchronized chest CT images acquired at baseline were analyzed (1834 scanned in the University Medical Center Groningen, 1725 in the University Medical Center Utrecht). Aortic and coronary calcifications were identified using previously developed automatic algorithms. A set of features describing number, volume and size distribution of the detected calcifications was computed. Age of the participants was extracted from image headers. Features describing participants' smoking status, smoking history and past CVEs were obtained. CVEs that occurred within three years after the imaging were used as outcome. Support vector machine classification was performed employing different feature sets using sets of only image features, or a combination of image and subject related characteristics. Classification based solely on the image features resulted in the area under the ROC curve (Az) of 0.69. A combination of image and subject features resulted in an Az of 0.71. The results demonstrate that subjects undergoing lung cancer screening who are at risk of CVE can be identified using automatic image analysis. Adding subject information slightly improved the performance.

Automatic Evidence Retrieval for Systematic Reviews

PubMed Central

Choong, Miew Keen; Galgani, Filippo; Dunn, Adam G

2014-01-01

Background Snowballing involves recursively pursuing relevant references cited in the retrieved literature and adding them to the search results. Snowballing is an alternative approach to discover additional evidence that was not retrieved through conventional search. Snowballing’s effectiveness makes it best practice in systematic reviews despite being time-consuming and tedious. Objective Our goal was to evaluate an automatic method for citation snowballing’s capacity to identify and retrieve the full text and/or abstracts of cited articles. Methods Using 20 review articles that contained 949 citations to journal or conference articles, we manually searched Microsoft Academic Search (MAS) and identified 78.0% (740/949) of the cited articles that were present in the database. We compared the performance of the automatic citation snowballing method against the results of this manual search, measuring precision, recall, and F1 score. Results The automatic method was able to correctly identify 633 (as proportion of included citations: recall=66.7%, F1 score=79.3%; as proportion of citations in MAS: recall=85.5%, F1 score=91.2%) of citations with high precision (97.7%), and retrieved the full text or abstract for 490 (recall=82.9%, precision=92.1%, F1 score=87.3%) of the 633 correctly retrieved citations. Conclusions The proposed method for automatic citation snowballing is accurate and is capable of obtaining the full texts or abstracts for a substantial proportion of the scholarly citations in review articles. By automating the process of citation snowballing, it may be possible to reduce the time and effort of common evidence surveillance tasks such as keeping trial registries up to date and conducting systematic reviews. PMID:25274020

Understanding the role of injury/illness sensitivity and anxiety sensitivity in (automatic) pain processing: an examination using the extrinsic affective simon task.

PubMed

Vancleef, Linda M G; Peters, Madelon L; Gilissen, Susan M P; De Jong, Peter J

2007-07-01

Three fundamental fears are assumed to underlie psychopathology: Anxiety Sensitivity (AS), Injury/illness sensitivity (IS), and Fear of Negative Evaluation (FNE). Both AS and IS may form risk factors for the development and exacerbation of chronic pain. The current research examines the relation between these fears and automatic threat appraisal for pain-related stimuli. Study 1 (n=48) additionally examined content-specific associations of AS and FNE with the automatic threat appraisal of, respectively, panic and social evaluative cues. Study 2 (n=60) additionally focused on the association of IS and AS with the engagement in health protecting behavior, and the use of health care services. Both studies found evidence for an automatic threat appraisal of aversive stimuli. Study 2 demonstrated a positive association between the automatic threat appraisal for pain-related stimuli and individuals' IS levels. IS was found to be the single best predictor of the tendency to engage in health protecting behavior, whereas AS was the single best predictor of the reported use of health care services. This study contributes to the field of knowledge on putative risk factors for chronic pain. Results demonstrate an automatic threat appraisal toward pain-related stimuli that is related to vulnerability traits for pain. This automatic threat appraisal might initiate relatively spontaneous (nonstrategic) pain-maintaining behavioral responses.

Use of Semi-Autonomous Tools for ISS Commanding and Monitoring

NASA Technical Reports Server (NTRS)

Brzezinski, Amy S.

2014-01-01

As the International Space Station (ISS) has moved into a utilization phase, operations have shifted to become more ground-based with fewer mission control personnel monitoring and commanding multiple ISS systems. This shift to fewer people monitoring more systems has prompted use of semi-autonomous console tools in the ISS Mission Control Center (MCC) to help flight controllers command and monitor the ISS. These console tools perform routine operational procedures while keeping the human operator "in the loop" to monitor and intervene when off-nominal events arise. Two such tools, the Pre-positioned Load (PPL) Loader and Automatic Operators Recorder Manager (AutoORM), are used by the ISS Communications RF Onboard Networks Utilization Specialist (CRONUS) flight control position. CRONUS is responsible for simultaneously commanding and monitoring the ISS Command & Data Handling (C&DH) and Communications and Tracking (C&T) systems. PPL Loader is used to uplink small pieces of frequently changed software data tables, called PPLs, to ISS computers to support different ISS operations. In order to uplink a PPL, a data load command must be built that contains multiple user-input fields. Next, a multiple step commanding and verification procedure must be performed to enable an onboard computer for software uplink, uplink the PPL, verify the PPL has incorporated correctly, and disable the computer for software uplink. PPL Loader provides different levels of automation in both building and uplinking these commands. In its manual mode, PPL Loader automatically builds the PPL data load commands but allows the flight controller to verify and save the commands for future uplink. In its auto mode, PPL Loader automatically builds the PPL data load commands for flight controller verification, but automatically performs the PPL uplink procedure by sending commands and performing verification checks while notifying CRONUS of procedure step completion. If an off-nominal condition occurs during procedure execution, PPL Loader notifies CRONUS through popup messages, allowing CRONUS to examine the situation and choose an option of how PPL loader should proceed with the procedure. The use of PPL Loader to perform frequent, routine PPL uplinks offloads CRONUS to better monitor two ISS systems. It also reduces procedure performance time and decreases risk of command errors. AutoORM identifies ISS communication outage periods and builds commands to lock, playback, and unlock ISS Operations Recorder files. Operation Recorder files are circular buffer files of continually recorded ISS telemetry data. Sections of these files can be locked from further writing, be played back to capture telemetry data that occurred during an ISS loss of signal (LOS) period, and then be unlocked for future recording use. Downlinked Operation Recorder files are used by mission support teams for data analysis, especially if failures occur during LOS. The commands to lock, playback, and unlock Operations Recorder files are encompassed in three different operational procedures and contain multiple user-input fields. AutoORM provides different levels of automation for building and uplinking the commands to lock, playback, and unlock Operations Recorder files. In its automatic mode, AutoORM automatically detects ISS LOS periods, then generates and uplinks the commands to lock, playback, and unlock Operations Recorder files when MCC regains signal with ISS. AutoORM also features semi-autonomous and manual modes which integrate CRONUS more into the command verification and uplink process. AutoORMs ability to automatically detect ISS LOS periods and build the necessary commands to preserve, playback, and release recorded telemetry data greatly offloads CRONUS to perform more high-level cognitive tasks, such as mission planning and anomaly troubleshooting. Additionally, since Operations Recorder commands contain numerical time input fields which are tedious for a human to manually build, AutoORM's ability to automatically build commands reduces operational command errors. PPL Loader and AutoORM demonstrate principles of semi-autonomous operational tools that will benefit future space mission operations. Both tools employ different levels of automation to perform simple and routine procedures, thereby offloading human operators to perform higher-level cognitive tasks. Because both tools provide procedure execution status and highlight off-nominal indications, the flight controller is able to intervene during procedure execution if needed. Semi-autonomous tools and systems that can perform routine procedures, yet keep human operators informed of execution, will be essential in future long-duration missions where the onboard crew will be solely responsible for spacecraft monitoring and control.

Crustal Fracturing Field and Presence of Fluid as Revealed by Seismic Anisotropy

NASA Astrophysics Data System (ADS)

Pastori, M.; Piccinini, D.; de Gori, P.; Margheriti, L.; Barchi, M. R.; di Bucci, D.

2010-12-01

In the last three years, we developed, tested and improved an automatic analysis code (Anisomat+) to calculate the shear wave splitting parameters, fast polarization direction (φ) and delay time (∂t). The code is a set of MatLab scripts able to retrieve crustal anisotropy parameters from three-component seismic recording of local earthquakes using horizontal component cross-correlation method. The analysis procedure consists in choosing an appropriate frequency range, that better highlights the signal containing the shear waves, and a length of time window on the seismogram centered on the S arrival (the temporal window contains at least one cycle of S wave). The code was compared to other two automatic analysis code (SPY and SHEBA) and tested on three Italian areas (Val d’Agri, Tiber Valley and L’Aquila surrounding) along the Apennine mountains. For each region we used the anisotropic parameters resulting from the automatic computation as a tool to determine the fracture field geometries connected with the active stress field. We compare the temporal variations of anisotropic parameters to the evolution of vp/vs ratio for the same seismicity. The anisotropic fast directions are used to define the active stress field (EDA model), finding a general consistence between fast direction and main stress indicators (focal mechanism and borehole break-out). The magnitude of delay time is used to define the fracture field intensity finding higher value in the volume where micro-seismicity occurs. Furthermore we studied temporal variations of anisotropic parameters and vp/vs ratio in order to explain if fluids play an important role in the earthquake generation process. The close association of anisotropic and vp/vs parameters variations and seismicity rate changes supports the hypothesis that the background seismicity is influenced by the fluctuation of pore fluid pressure in the rocks.

Effectiveness of an automatic manual wheelchair braking system in the prevention of falls.

PubMed

Martorello, Laura; Swanson, Edward

2006-01-01

The purpose of this study was to evaluate the effectiveness of an automatic manual wheelchair braking system in the reduction of falls for patients at high risk of falls while transferring to and from a manual wheelchair. The study design was a normative survey carried out through the use of a written questionnaire sent to 60 skilled nursing facilities to collect data from the medical charts, which identified patients at high risk for falls who used an automatic wheelchair braking system. The facilities participating in the study identified a frequency of falls of high-risk patients while transferring to and from the wheelchair ranging from 2 to 10 per year, with a median fall rate per facility of 4 falls. One year after the installation of the automatic wheelchair braking system, participating facilities demonstrated a reduction of zero to three falls during transfers by high-risk patients, with a median fall rate of zero falls. This represents a statistically significant reduction of 78% in the fall rate of high-risk patients while transferring to and from the wheelchair, t (18) = 6.39, p < .0001. Incident reports of falls to and from manual wheelchairs were reviewed retrospectively for a 1-year period. This study suggests that high-risk fallers transferring to or from manual wheelchairs sustained significantly fewer falls when the Steddy Mate automatic braking system for manual wheelchairs was installed. The application of the automatic braking system allows clients, families/caregivers, and facility personnel an increased safety factor for the reduction of falls from the wheelchair.

Identification of damage in plates using full-field measurement with a continuously scanning laser Doppler vibrometer system

NASA Astrophysics Data System (ADS)

Chen, Da-Ming; Xu, Y. F.; Zhu, W. D.

2018-05-01

An effective and reliable damage identification method for plates with a continuously scanning laser Doppler vibrometer (CSLDV) system is proposed. A new constant-speed scan algorithm is proposed to create a two-dimensional (2D) scan trajectory and automatically scan a whole plate surface. Full-field measurement of the plate can be achieved by applying the algorithm to the CSLDV system. Based on the new scan algorithm, the demodulation method is extended from one dimension for beams to two dimensions for plates to obtain a full-field operating deflection shape (ODS) of the plate from velocity response measured by the CSLDV system. The full-field ODS of an associated undamaged plate is obtained by using polynomials with proper orders to fit the corresponding full-field ODS from the demodulation method. A curvature damage index (CDI) using differences between curvatures of ODSs (CODSs) associated with ODSs that are obtained by the demodulation method and the polynomial fit is proposed to identify damage. An auxiliary CDI obtained by averaging CDIs at different excitation frequencies is defined to further assist damage identification. An experiment of an aluminum plate with damage in the form of 10.5% thickness reduction in a damage area of 0.86% of the whole scan area is conducted to investigate the proposed method. Six frequencies close to natural frequencies of the plate and one randomly selected frequency are used as sinusoidal excitation frequencies. Two 2D scan trajectories, i.e., a horizontally moving 2D scan trajectory and a vertically moving 2D scan trajectory, are used to obtain ODSs, CODSs, and CDIs of the plate. The damage is successfully identified near areas with consistently high values of CDIs at different excitation frequencies along the two 2D scan trajectories; the damage area is also identified by auxiliary CDIs.

A Fast, Automatic Segmentation Algorithm for Locating and Delineating Touching Cell Boundaries in Imaged Histopathology

PubMed Central

Qi, Xin; Xing, Fuyong; Foran, David J.; Yang, Lin

2013-01-01

Summary Background Automated analysis of imaged histopathology specimens could potentially provide support for improved reliability in detection and classification in a range of investigative and clinical cancer applications. Automated segmentation of cells in the digitized tissue microarray (TMA) is often the prerequisite for quantitative analysis. However overlapping cells usually bring significant challenges for traditional segmentation algorithms. Objectives In this paper, we propose a novel, automatic algorithm to separate overlapping cells in stained histology specimens acquired using bright-field RGB imaging. Methods It starts by systematically identifying salient regions of interest throughout the image based upon their underlying visual content. The segmentation algorithm subsequently performs a quick, voting based seed detection. Finally, the contour of each cell is obtained using a repulsive level set deformable model using the seeds generated in the previous step. We compared the experimental results with the most current literature, and the pixel wise accuracy between human experts' annotation and those generated using the automatic segmentation algorithm. Results The method is tested with 100 image patches which contain more than 1000 overlapping cells. The overall precision and recall of the developed algorithm is 90% and 78%, respectively. We also implement the algorithm on GPU. The parallel implementation is 22 times faster than its C/C++ sequential implementation. Conclusion The proposed overlapping cell segmentation algorithm can accurately detect the center of each overlapping cell and effectively separate each of the overlapping cells. GPU is proven to be an efficient parallel platform for overlapping cell segmentation. PMID:22526139

Interconnecting smartphone, image analysis server, and case report forms in clinical trials for automatic skin lesion tracking in clinical trials

NASA Astrophysics Data System (ADS)

Haak, Daniel; Doma, Aliaa; Gombert, Alexander; Deserno, Thomas M.

2016-03-01

Today, subject's medical data in controlled clinical trials is captured digitally in electronic case report forms (eCRFs). However, eCRFs only insufficiently support integration of subject's image data, although medical imaging is looming large in studies today. For bed-side image integration, we present a mobile application (App) that utilizes the smartphone-integrated camera. To ensure high image quality with this inexpensive consumer hardware, color reference cards are placed in the camera's field of view next to the lesion. The cards are used for automatic calibration of geometry, color, and contrast. In addition, a personalized code is read from the cards that allows subject identification. For data integration, the App is connected to an communication and image analysis server that also holds the code-study-subject relation. In a second system interconnection, web services are used to connect the smartphone with OpenClinica, an open-source, Food and Drug Administration (FDA)-approved electronic data capture (EDC) system in clinical trials. Once the photographs have been securely stored on the server, they are released automatically from the mobile device. The workflow of the system is demonstrated by an ongoing clinical trial, in which photographic documentation is frequently performed to measure the effect of wound incision management systems. All 205 images, which have been collected in the study so far, have been correctly identified and successfully integrated into the corresponding subject's eCRF. Using this system, manual steps for the study personnel are reduced, and, therefore, errors, latency and costs decreased. Our approach also increases data security and privacy.

Perceptual organization, visual attention, and objecthood.

PubMed

Kimchi, Ruth; Yeshurun, Yaffa; Spehar, Branka; Pirkner, Yossef

2016-09-01

We have previously demonstrated that the mere organization of some elements in the visual field into an object attracts attention automatically. Here, we explored three different aspects of this automatic attentional capture: (a) Does the attentional capture by an object involve a spatial component? (b) Which Gestalt organization factors suffice for an object to capture attention? (c) Does the strength of organization affect the object's ability to capture attention? Participants viewed multi-elements displays and either identified the color of one element or responded to a Vernier target. On some trials, a subset of the elements grouped by Gestalt factors into an object that was irrelevant to the task and not predictive of the target. An object effect - faster performance for targets within the object than for targets outside the object - was found even when the target appeared after the object offset, and was sensitive to target-object distance, suggesting that the capture of attention by an object is accompanied by a deployment of attention to the object location. Object effects of similar magnitude were found for objects grouped by a combination of factors (collinearity, closure, and symmetry, or closure and symmetry) or by a single factor when it was collinearity, but not symmetry, suggesting that collinearity, or closure combined with symmetry, suffices for automatic capture of attention by an object, but symmetry does not. Finally, the strength of grouping in modal completion, manipulated by varying contrast polarity between and within elements, affected the effectiveness of the attentional capture by the induced object. Copyright © 2015 Elsevier Ltd. All rights reserved.

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 casting and mechanism of formation of semi-permeable polymer membranes in a microgravity environment

NASA Astrophysics Data System (ADS)

Vera, I.

The National Electric Company of Venezuela, C.A.D.A.F.E., is sponsoring the development of this experiment which represents Venezuela's first scientific experiment in space. The apparatus for the automatic casting of polymer thin films will be contained in NASA's payload No. G-559 of the Get Away Special program for a future orbital space flight in the U.S. Space Shuttle. Semi-permeable polymer membranes have important applications in a variety of fields, such as medecine, energy, and pharmaceuticals, and in general fluid separation processes such as reverse osmosis, ultra-filtration, and electro-dialysis. The casting of semi-permeable membranes in space will help to identify the roles of convection in determining the strucutre of these membranes.

Semantic Information Extraction of Lanes Based on Onboard Camera Videos

NASA Astrophysics Data System (ADS)

Tang, L.; Deng, T.; Ren, C.

2018-04-01

In the field of autonomous driving, semantic information of lanes is very important. This paper proposes a method of automatic detection of lanes and extraction of semantic information from onboard camera videos. The proposed method firstly detects the edges of lanes by the grayscale gradient direction, and improves the Probabilistic Hough transform to fit them; then, it uses the vanishing point principle to calculate the lane geometrical position, and uses lane characteristics to extract lane semantic information by the classification of decision trees. In the experiment, 216 road video images captured by a camera mounted onboard a moving vehicle were used to detect lanes and extract lane semantic information. The results show that the proposed method can accurately identify lane semantics from video images.

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.

Difficulty identifying feelings and automatic activation in the fusiform gyrus in response to facial emotion.

PubMed

Eichmann, Mischa; Kugel, Harald; Suslow, Thomas

2008-12-01

Difficulties in identifying and differentiating one's emotions are a central characteristic of alexithymia. In the present study, automatic activation of the fusiform gyrus to facial emotion was investigated as a function of alexithymia as assessed by the 20-item Toronto Alexithymia Scale. During 3 Tesla fMRI scanning, pictures of faces bearing sad, happy, and neutral expressions masked by neutral faces were presented to 22 healthy adults who also responded to the Toronto Alexithymia Scale. The fusiform gyrus was selected as the region of interest, and voxel values of this region were extracted, summarized as means, and tested among the different conditions (sad, happy, and neutral faces). Masked sad facial emotions were associated with greater bilateral activation of the fusiform gyrus than masked neutral faces. The subscale, Difficulty Identifying Feelings, was negatively correlated with the neural response of the fusiform gyrus to masked sad faces. The correlation results suggest that automatic hyporesponsiveness of the fusiform gyrus to negative emotion stimuli may reflect problems in recognizing one's emotions in everyday life.

Automated regional analysis of B-mode ultrasound images of skeletal muscle movement

PubMed Central

Darby, John; Costen, Nicholas; Loram, Ian D.

2012-01-01

To understand the functional significance of skeletal muscle anatomy, a method of quantifying local shape changes in different tissue structures during dynamic tasks is required. Taking advantage of the good spatial and temporal resolution of B-mode ultrasound imaging, we describe a method of automatically segmenting images into fascicle and aponeurosis regions and tracking movement of features, independently, in localized portions of each tissue. Ultrasound images (25 Hz) of the medial gastrocnemius muscle were collected from eight participants during ankle joint rotation (2° and 20°), isometric contractions (1, 5, and 50 Nm), and deep knee bends. A Kanade-Lucas-Tomasi feature tracker was used to identify and track any distinctive and persistent features within the image sequences. A velocity field representation of local movement was then found and subdivided between fascicle and aponeurosis regions using segmentations from a multiresolution active shape model (ASM). Movement in each region was quantified by interpolating the effect of the fields on a set of probes. ASM segmentation results were compared with hand-labeled data, while aponeurosis and fascicle movement were compared with results from a previously documented cross-correlation approach. ASM provided good image segmentations (<1 mm average error), with fully automatic initialization possible in sequences from seven participants. Feature tracking provided similar length change results to the cross-correlation approach for small movements, while outperforming it in larger movements. The proposed method provides the potential to distinguish between active and passive changes in muscle shape and model strain distributions during different movements/conditions and quantify nonhomogeneous strain along aponeuroses. PMID:22033532

Use of airborne imaging spectrometer data to map minerals associated with hydrothermally altered rocks in the northern grapevine mountains, Nevada, and California

USGS Publications Warehouse

Kruse, F.A.

1988-01-01

Three flightlines of Airborne Imaging Spectrometer (AIS) data, acquired over the northern Grapevine Mountains, Nevada, and California, were used to map minerals associated with hydrothermally altered rocks. The data were processed to remove vertical striping, normalized using an equal area normalization, and reduced to reflectance relative to an average spectrum derived from the data. An algorithm was developed to automatically calculate the absorption band parameters band position, band depth, and band width for the strongest absorption feature in each pixel. These parameters were mapped into an intensity, hue, saturation (IHS) color system to produce a single color image that summarized the absorption band information, This image was used to map areas of potential alteration based upon the predicted relationships between the color image and mineral absorption band. Individual AIS spectra for these areas were then examined to identify specific minerals. Two types of alteration were mapped with the AIS data. Areas of quartz-sericite-pyrite alteration were identified based upon a strong absorption feature near 2.21 ??m, a weak shoulder near 2.25 ??m, and a weak absorption band near 2.35 ??m caused by sericite (fine-grained muscovite). Areas of argillic alteration were defined based on the presence of montmorillonite, identified by a weak to moderate absorption feature near 2.21 ??m and the absence of the 2.35 ??m band. Montmorillonite could not be identified in mineral mixtures. Calcite and dolomite were identified based on sharp absorption features near 2.34 and 2.32 ??m, respectively. Areas of alteration identified using the AIS data corresponded well with areas mapped using field mapping, field reflectance spectra, and laboratory spectral measurements. ?? 1988.

The "Sigmoid Sniffer” and the "Advanced Automated Solar Filament Detection and Characterization Code” Modules

NASA Astrophysics Data System (ADS)

Raouafi, Noureddine; Bernasconi, P. N.; Georgoulis, M. K.

2010-05-01

We present two pattern recognition algorithms, the "Sigmoid Sniffer” and the "Advanced Automated Solar Filament Detection and Characterization Code,” that are among the Feature Finding modules of the Solar Dynamic Observatory: 1) Coronal sigmoids visible in X-rays and the EUV are the result of highly twisted magnetic fields. They can occur anywhere on the solar disk and are closely related to solar eruptive activity (e.g., flares, CMEs). Their appearance is typically synonym of imminent solar eruptions, so they can serve as a tool to forecast solar activity. Automatic X-ray sigmoid identification offers an unbiased way of detecting short-to-mid term CME precursors. The "Sigmoid Sniffer” module is capable of automatically detecting sigmoids in full-disk X-ray images and determining their chirality, as well as other characteristics. It uses multiple thresholds to identify persistent bright structures on a full-disk X-ray image of the Sun. We plan to apply the code to X-ray images from Hinode/XRT, as well as on SDO/AIA images. When implemented in a near real-time environment, the Sigmoid Sniffer could allow 3-7 day forecasts of CMEs and their potential to cause major geomagnetic storms. 2)The "Advanced Automated Solar Filament Detection and Characterization Code” aims to identify, classify, and track solar filaments in full-disk Hα images. The code can reliably identify filaments; determine their chirality and other relevant parameters like filament area, length, and average orientation with respect to the equator. It is also capable of tracking the day-by-day evolution of filaments as they traverse the visible disk. The code was tested by analyzing daily Hα images taken at the Big Bear Solar Observatory from mid-2000 to early-2005. It identified and established the chirality of thousands of filaments without human intervention.

Image analysis for skeletal evaluation of carpal bones

NASA Astrophysics Data System (ADS)

Ko, Chien-Chuan; Mao, Chi-Wu; Lin, Chi-Jen; Sun, Yung-Nien

1995-04-01

The assessment of bone age is an important field to the pediatric radiology. It provides very important information for treatment and prediction of skeletal growth in a developing child. So far, various computerized algorithms for automatically assessing the skeletal growth have been reported. Most of these methods made attempt to analyze the phalangeal growth. The most fundamental step in these automatic measurement methods is the image segmentation that extracts bones from soft-tissue and background. These automatic segmentation methods of hand radiographs can roughly be categorized into two main approaches that are edge and region based methods. This paper presents a region-based carpal-bone segmentation approach. It is organized into four stages: contrast enhancement, moment-preserving thresholding, morphological processing, and region-growing labeling.

Astrometrica: Astrometric data reduction of CCD images

NASA Astrophysics Data System (ADS)

Raab, Herbert

2012-03-01

Astrometrica is an interactive software tool for scientific grade astrometric data reduction of CCD images. The current version of the software is for the Windows 32bit operating system family. Astrometrica reads FITS (8, 16 and 32 bit integer files) and SBIG image files. The size of the images is limited only by available memory. It also offers automatic image calibration (Dark Frame and Flat Field correction), automatic reference star identification, automatic moving object detection and identification, and access to new-generation star catalogs (PPMXL, UCAC 3 and CMC-14), in addition to online help and other features. Astrometrica is shareware, available for use for a limited period of time (100 days) for free; special arrangements can be made for educational projects.

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.

Use of an automatic resistivity system for detecting abandoned mine workings

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

Peters, W.R.; Burdick, R.G.

1983-01-01

A high-resolution earth resistivity system has been designed and constructed for use as a means of detecting abandoned coal mine workings. The automatic pole-dipole earth resistivity technique has already been applied to the detection of subsurface voids for military applications. The hardware and software of the system are described, together with applications for surveying and mapping abandoned coal mine workings. Field tests are presented to illustrate the detection of both air-filled and water-filled mine workings.

Filmless Radiographic System for Field Use.

DTIC Science & Technology

1988-02-12

electronic circuits. The receptor assembly contains the x-ray grid , cassette holder or EPID panel and the sensor panel for the automatic exposure control... Grid lines were still resolved. The appearance of fine details was altered but most of the diagnostic value was retained. The choice of the screens must...A 6:1, 60 lines per inch grid is mounted to the frame on the x-ray entrance side. II.F.4. Ion Chamber The ion chamber is used by the automatic

Automatic Concept-Based Query Expansion Using Term Relational Pathways Built from a Collection-Specific Association Thesaurus

ERIC Educational Resources Information Center

Lyall-Wilson, Jennifer Rae

2013-01-01

The dissertation research explores an approach to automatic concept-based query expansion to improve search engine performance. It uses a network-based approach for identifying the concept represented by the user's query and is founded on the idea that a collection-specific association thesaurus can be used to create a reasonable representation of…

Automatic license plate reader: a solution to avoiding vehicle pursuit

NASA Astrophysics Data System (ADS)

Jordan, Stanley K.

1997-01-01

The Massachusetts Governor's Auto Theft Strike Force has tested an automatic license plate reader (LPR) to recover stolen cars and catch car thieves, without vehicle pursuit. Experiments were conducted at the Sumner Tunnel in Boston, and proved the feasibility of a LPR for identifying stolen cars instantly. The same technology can be applied to other law-enforcement objectives.

Use of Automatic Interaction Detector in Monitoring Faculty Salaries. AIR 1983 Annual Forum Paper.

ERIC Educational Resources Information Center

Cohen, Margaret E.

A university's use of the Automatic Interaction Detector (AID) to monitor faculty salary data is described. The first step consists of examining a tree diagram and summary table produced by AID. The tree is used to identify the characteristics of faculty at different salary levels. The table is used to determine the explanatory power of the…

Growth in Rapid Automatized Naming from Grades K to 8 in Children with Math or Reading Disabilities

ERIC Educational Resources Information Center

Mazzocco, Michèle M. M.; Grimm, Kevin J.

2013-01-01

Rapid automatized naming (RAN) is widely used to identify reading disabilities (RD) and has recently been considered a potential predictor of risk for mathematics learning disabilities (MLD). Here we longitudinally examine RAN performance from Grades K to 8, to view how growth on RAN response time differs for children with RD versus MLD. Across…

Automatic photointerpretation for land use management in Minnesota

NASA Technical Reports Server (NTRS)

Swanlund, G. D. (Principal Investigator); Kirvida, L.; Cheung, M.; Pile, D.; Zirkle, R.

1974-01-01

The author has identified the following significant results. Automatic photointerpretation techniques were utilized to evaluate the feasibility of data for land use management. It was shown that ERTS-1 MSS data can produce thematic maps of adequate resolution and accuracy to update land use maps. In particular, five typical land use areas were mapped with classification accuracies ranging from 77% to over 90%.

[Design of Adjustable Magnetic Field Generating Device in the Capsule Endoscope Tracking System].

PubMed

Ruan, Chao; Guo, Xudong; Yang, Fei

2015-08-01

The capsule endoscope swallowed from the mouth into the digestive system can capture the images of important gastrointestinal tract regions. It can compensate for the blind spot of traditional endoscopic techniques. It enables inspection of the digestive system without discomfort or need for sedation. However, currently available clinical capsule endoscope has some limitations such as the diagnostic information being not able to correspond to the orientation in the body, since the doctor is unable to control the capsule motion and orientation. To solve the problem, it is significant to track the position and orientation of the capsule in the human body. This study presents an AC excitation wireless tracking method in the capsule endoscope, and the sensor embedded in the capsule can measure the magnetic field generated by excitation coil. And then the position and orientation of the capsule can be obtained by solving a magnetic field inverse problem. Since the magnetic field decays with distance dramatically, the dynamic range of the received signal spans three orders of magnitude, we designed an adjustable alternating magnetic field generating device. The device can adjust the strength of the alternating magnetic field automatically through the feedback signal from the sensor. The prototype experiment showed that the adjustable magnetic field generating device was feasible. It could realize the automatic adjustment of the magnetic field strength successfully, and improve the tracking accuracy.

Automatic segmentation and classification of gestational sac based on mean sac diameter using medical ultrasound image

NASA Astrophysics Data System (ADS)

Khazendar, Shan; Farren, Jessica; Al-Assam, Hisham; Sayasneh, Ahmed; Du, Hongbo; Bourne, Tom; Jassim, Sabah A.

2014-05-01

Ultrasound is an effective multipurpose imaging modality that has been widely used for monitoring and diagnosing early pregnancy events. Technology developments coupled with wide public acceptance has made ultrasound an ideal tool for better understanding and diagnosing of early pregnancy. The first measurable signs of an early pregnancy are the geometric characteristics of the Gestational Sac (GS). Currently, the size of the GS is manually estimated from ultrasound images. The manual measurement involves multiple subjective decisions, in which dimensions are taken in three planes to establish what is known as Mean Sac Diameter (MSD). The manual measurement results in inter- and intra-observer variations, which may lead to difficulties in diagnosis. This paper proposes a fully automated diagnosis solution to accurately identify miscarriage cases in the first trimester of pregnancy based on automatic quantification of the MSD. Our study shows a strong positive correlation between the manual and the automatic MSD estimations. Our experimental results based on a dataset of 68 ultrasound images illustrate the effectiveness of the proposed scheme in identifying early miscarriage cases with classification accuracies comparable with those of domain experts using K nearest neighbor classifier on automatically estimated MSDs.

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.

A dual-systems perspective on addiction: contributions from neuroimaging and cognitive training.

PubMed

McClure, Samuel M; Bickel, Warren K

2014-10-01

Dual-systems theories explain lapses in self-control in terms of a conflict between automatic and deliberative modes of behavioral control. Numerous studies have now tested whether the brain areas that control behavior are organized in a manner consistent with dual-systems models. Brain regions directly associated with the mesolimbic dopamine system, the nucleus accumbens and ventromedial prefrontal cortex in particular, capture some of the features assumed by automatic processing. Regions in the lateral prefrontal cortex are more closely linked to deliberative processing and the exertion of self-control in the suppression of impulses. While identifying these regions crudely supports dual-systems theories, important modifications to what constitutes automatic and deliberative behavioral control are also suggested. Experiments have identified various means by which automatic processes may be sculpted. Additional work decomposes deliberative processes into component functions such as generalized working memory, reappraisal of emotional stimuli, and prospection. The importance of deconstructing dual-systems models into specific cognitive processes is clear for understanding and treating addiction. We discuss intervention possibilities suggested by recent research, and focus in particular on cognitive training approaches to bolster deliberative control processes that may aid quit attempts. © 2014 New York Academy of Sciences.

A dual-systems perspective on addiction: contributions from neuroimaging and cognitive training

PubMed Central

McClure, Samuel M.; Bickel, Warren K.

2014-01-01

Dual-systems theories explain lapses in self-control in terms of a conflict between automatic and deliberative modes of behavioral control. Numerous studies have now tested whether the brain areas that control behavior are organized in a manner consistent with dual-systems models. Brain regions directly associated with the mesolimbic dopamine system, the nucleus accumbens (NAcc) and ventromedial prefrontal cortex (vmPFC) in particular, capture some of the features assumed by automatic processing. Regions in the lateral prefrontal cortex (lPFC) are more closely linked to deliberative processing and the exertion of self-control in the suppression of impulses. While identifying these regions crudely supports dual-system theories, important modifications to what constitutes automatic and deliberative behavioral control are also suggested. Experiments have identified various means by which automatic processes may be sculpted. Additional work decomposes deliberative processes into component functions such as generalized working memory, reappraisal of emotional stimuli, and prospection. The importance of deconstructing dual-systems models into specific cognitive processes is clear for understanding and treating addiction. We discuss intervention possibilities suggested by recent research, and focus in particular on cognitive training approaches to bolster deliberative control processes that may aid quit attempts. PMID:25336389

Detecting cell division of Pseudomonas aeruginosa bacteria from bright-field microscopy images with hidden conditional random fields.

PubMed

Ong, Lee-Ling S; Xinghua Zhang; Kundukad, Binu; Dauwels, Justin; Doyle, Patrick; Asada, H Harry

2016-08-01

An approach to automatically detect bacteria division with temporal models is presented. To understand how bacteria migrate and proliferate to form complex multicellular behaviours such as biofilms, it is desirable to track individual bacteria and detect cell division events. Unlike eukaryotic cells, prokaryotic cells such as bacteria lack distinctive features, causing bacteria division difficult to detect in a single image frame. Furthermore, bacteria may detach, migrate close to other bacteria and may orientate themselves at an angle to the horizontal plane. Our system trains a hidden conditional random field (HCRF) model from tracked and aligned bacteria division sequences. The HCRF model classifies a set of image frames as division or otherwise. The performance of our HCRF model is compared with a Hidden Markov Model (HMM). The results show that a HCRF classifier outperforms a HMM classifier. From 2D bright field microscopy data, it is a challenge to separate individual bacteria and associate observations to tracks. Automatic detection of sequences with bacteria division will improve tracking accuracy.

Automated eye blink detection and correction method for clinical MR eye imaging.

PubMed

Wezel, Joep; Garpebring, Anders; Webb, Andrew G; van Osch, Matthias J P; Beenakker, Jan-Willem M

2017-07-01

To implement an on-line monitoring system to detect eye blinks during ocular MRI using field probes, and to reacquire corrupted k-space lines by means of an automatic feedback system integrated with the MR scanner. Six healthy subjects were scanned on a 7 Tesla MRI whole-body system using a custom-built receive coil. Subjects were asked to blink multiple times during the MR-scan. The local magnetic field changes were detected with an external fluorine-based field probe which was positioned close to the eye. The eye blink produces a field shift greater than a threshold level, this was communicated in real-time to the MR system which immediately reacquired the motion-corrupted k-space lines. The uncorrected images, using the original motion-corrupted data, showed severe artifacts, whereas the corrected images, using the reacquired data, provided an image quality similar to images acquired without blinks. Field probes can successfully detect eye blinks during MRI scans. By automatically reacquiring the eye blink-corrupted data, high quality MR-images of the eye can be acquired. Magn Reson Med 78:165-171, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

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).

Efficient Semi-Automatic 3D Segmentation for Neuron Tracing in Electron Microscopy Images

PubMed Central

Jones, Cory; Liu, Ting; Cohan, Nathaniel Wood; Ellisman, Mark; Tasdizen, Tolga

2015-01-01

0.1. Background In the area of connectomics, there is a significant gap between the time required for data acquisition and dense reconstruction of the neural processes contained in the same dataset. Automatic methods are able to eliminate this timing gap, but the state-of-the-art accuracy so far is insufficient for use without user corrections. If completed naively, this process of correction can be tedious and time consuming. 0.2. New Method We present a new semi-automatic method that can be used to perform 3D segmentation of neurites in EM image stacks. It utilizes an automatic method that creates a hierarchical structure for recommended merges of superpixels. The user is then guided through each predicted region to quickly identify errors and establish correct links. 0.3. Results We tested our method on three datasets with both novice and expert users. Accuracy and timing were compared with published automatic, semi-automatic, and manual results. 0.4. Comparison with Existing Methods Post-automatic correction methods have also been used in [1] and [2]. These methods do not provide navigation or suggestions in the manner we present. Other semi-automatic methods require user input prior to the automatic segmentation such as [3] and [4] and are inherently different than our method. 0.5. Conclusion Using this method on the three datasets, novice users achieved accuracy exceeding state-of-the-art automatic results, and expert users achieved accuracy on par with full manual labeling but with a 70% time improvement when compared with other examples in publication. PMID:25769273

An Automatic Phase-Change Detection Technique for Colloidal Hard Sphere Suspensions

NASA Technical Reports Server (NTRS)

McDowell, Mark; Gray, Elizabeth; Rogers, Richard B.

2005-01-01

Colloidal suspensions of monodisperse spheres are used as physical models of thermodynamic phase transitions and as precursors to photonic band gap materials. However, current image analysis techniques are not able to distinguish between densely packed phases within conventional microscope images, which are mainly characterized by degrees of randomness or order with similar grayscale value properties. Current techniques for identifying the phase boundaries involve manually identifying the phase transitions, which is very tedious and time consuming. We have developed an intelligent machine vision technique that automatically identifies colloidal phase boundaries. The algorithm utilizes intelligent image processing techniques that accurately identify and track phase changes vertically or horizontally for a sequence of colloidal hard sphere suspension images. This technique is readily adaptable to any imaging application where regions of interest are distinguished from the background by differing patterns of motion over time.

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 either accelerometer position. Machine learning techniques can be used for automatic activity recognition, as they provide very accurate activity recognition, significantly more accurate than when keeping a diary. Identification of jogging periods in adolescents can be performed using only one accelerometer. Performance-wise there is no significant benefit from using accelerometers on both locations.

SU-G-JeP2-03: Automatic Quantification of MLC Positional Accuracy in An MRI Guided Radiotherapy System

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

Li, X; Studenski, M; Yang, F

Purpose: MRI-guided-radiotherapy (MRIGRT) systems lack many features of traditional Linac based RT systems and specialized tests need to be developed to evaluate MLC performance. This work describes automatic tools for the analysis of positional accuracy of an MLC equipped MRIGRT system. Methods: This MLC analysis tool was developed for the MRIdian™ RT system which has three Co-60 equipped treatment heads each with a double focused MLC containing 30 leaf pairs, leaf thickness is 1.05cm defined at isocenter (SAD 105 cm). For MLC positional analysis a picket fence test was performed using a 25.4cm × 25.4cm Gafchromic™ RTQA2 film placed betweenmore » 5cm solidwater and a 30cm × 30cm × 1cm jigwire phantom with seven embedded parallel metal strips 4cm apart. A plan was generated to deliver 2Gy per field and seven 23.1cm × 2cm fields centered over each wire in the phantom. For each leaf pair the center of the radiation profile was determined by fitting the horizontal profile with a Gaussian model and determining the center of the FWHM. This was compared with the metal strip location to determine any deviation. The following metrics were used to evaluate the deviations per gantry angle including maximum, minimum, mean, Kurtosis, and skewness. Results: The identified maximum/mean leaf deviations are, 1.32/0.55 mm for gantry 0°, 1.59/0.76 mm for gantry 90°, and 1.19/0.39 mm for gantry 270°. The percentage of leaf deviation less than 1mm are 90.0% at 0°, 74.6% at 90°, and 97.0% at 270°. Kurtosis/skewness of the leaf deviation are 2.41/0.14 at 0°, 2.53/0.23 at 90°, 3.33/0.83 at 270°, respectively. Conclusion: This work presents an automatic tool for evaluation of the MLC position accuracy of the MRIdian™ radiotherapy system which can be used to benchmark the performance of the MLC system for each treatment head and track the results longitudinally.« less

Comparison of an automatic analysis and a manual analysis of conjunctival microcirculation in a sheep model of haemorrhagic shock.

PubMed

Arnemann, Philip-Helge; Hessler, Michael; Kampmeier, Tim; Morelli, Andrea; Van Aken, Hugo Karel; Westphal, Martin; Rehberg, Sebastian; Ertmer, Christian

2016-12-01

Life-threatening diseases of critically ill patients are known to derange microcirculation. Automatic analysis of microcirculation would provide a bedside diagnostic tool for microcirculatory disorders and allow immediate therapeutic decisions based upon microcirculation analysis. After induction of general anaesthesia and instrumentation for haemodynamic monitoring, haemorrhagic shock was induced in ten female sheep by stepwise blood withdrawal of 3 × 10 mL per kilogram body weight. Before and after the induction of haemorrhagic shock, haemodynamic variables, samples for blood gas analysis, and videos of conjunctival microcirculation were obtained by incident dark field illumination microscopy. Microcirculatory videos were analysed (1) manually with AVA software version 3.2 by an experienced user and (2) automatically by AVA software version 4.2 for total vessel density (TVD), perfused vessel density (PVD) and proportion of perfused vessels (PPV). Correlation between the two analysis methods was examined by intraclass correlation coefficient and Bland-Altman analysis. The induction of haemorrhagic shock decreased the mean arterial pressure (from 87 ± 11 to 40 ± 7 mmHg; p < 0.001); stroke volume index (from 38 ± 14 to 20 ± 5 ml·m -2 ; p = 0.001) and cardiac index (from 2.9 ± 0.9 to 1.8 ± 0.5 L·min -1 ·m -2 ; p < 0.001) and increased the heart rate (from 72 ± 9 to 87 ± 11 bpm; p < 0.001) and lactate concentration (from 0.9 ± 0.3 to 2.0 ± 0.6 mmol·L -1 ; p = 0.001). Manual analysis showed no change in TVD (17.8 ± 4.2 to 17.8 ± 3.8 mm*mm -2 ; p = 0.993), whereas PVD (from 15.6 ± 4.6 to 11.5 ± 6.5 mm*mm -2 ; p = 0.041) and PPV (from 85.9 ± 11.8 to 62.7 ± 29.6%; p = 0.017) decreased significantly. Automatic analysis was not able to identify these changes. Correlation analysis showed a poor correlation between the analysis methods and a wide spread of values in Bland-Altman analysis. As characteristic changes in microcirculation during ovine haemorrhagic shock were not detected by automatic analysis and correlation between automatic and manual analyses (current gold standard) was poor, the use of the investigated software for automatic analysis of microcirculation cannot be recommended in its current version at least in the investigated model. Further improvements in automatic vessel detection are needed before its routine use.

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-prostatectomy patients has been validated by PSA and pharmacokinetic constants analysis showing that it generates clinically relevant volumes.« less

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.

Preparing a collection of radiology examinations for distribution and retrieval.

PubMed

Demner-Fushman, Dina; Kohli, Marc D; Rosenman, Marc B; Shooshan, Sonya E; Rodriguez, Laritza; Antani, Sameer; Thoma, George R; McDonald, Clement J

2016-03-01

Clinical documents made available for secondary use play an increasingly important role in discovery of clinical knowledge, development of research methods, and education. An important step in facilitating secondary use of clinical document collections is easy access to descriptions and samples that represent the content of the collections. This paper presents an approach to developing a collection of radiology examinations, including both the images and radiologist narrative reports, and making them publicly available in a searchable database. The authors collected 3996 radiology reports from the Indiana Network for Patient Care and 8121 associated images from the hospitals' picture archiving systems. The images and reports were de-identified automatically and then the automatic de-identification was manually verified. The authors coded the key findings of the reports and empirically assessed the benefits of manual coding on retrieval. The automatic de-identification of the narrative was aggressive and achieved 100% precision at the cost of rendering a few findings uninterpretable. Automatic de-identification of images was not quite as perfect. Images for two of 3996 patients (0.05%) showed protected health information. Manual encoding of findings improved retrieval precision. Stringent de-identification methods can remove all identifiers from text radiology reports. DICOM de-identification of images does not remove all identifying information and needs special attention to images scanned from film. Adding manual coding to the radiologist narrative reports significantly improved relevancy of the retrieved clinical documents. The de-identified Indiana chest X-ray collection is available for searching and downloading from the National Library of Medicine (http://openi.nlm.nih.gov/). Published by Oxford University Press on behalf of the American Medical Informatics Association 2015. This work is written by US Government employees and is in the public domain in the US.

Tackling non-linearities with the effective field theory of dark energy and modified gravity

NASA Astrophysics Data System (ADS)

Frusciante, Noemi; Papadomanolakis, Georgios

2017-12-01

We present the extension of the effective field theory framework to the mildly non-linear scales. The effective field theory approach has been successfully applied to the late time cosmic acceleration phenomenon and it has been shown to be a powerful method to obtain predictions about cosmological observables on linear scales. However, mildly non-linear scales need to be consistently considered when testing gravity theories because a large part of the data comes from those scales. Thus, non-linear corrections to predictions on observables coming from the linear analysis can help in discriminating among different gravity theories. We proceed firstly by identifying the necessary operators which need to be included in the effective field theory Lagrangian in order to go beyond the linear order in perturbations and then we construct the corresponding non-linear action. Moreover, we present the complete recipe to map any single field dark energy and modified gravity models into the non-linear effective field theory framework by considering a general action in the Arnowitt-Deser-Misner formalism. In order to illustrate this recipe we proceed to map the beyond-Horndeski theory and low-energy Hořava gravity into the effective field theory formalism. As a final step we derived the 4th order action in term of the curvature perturbation. This allowed us to identify the non-linear contributions coming from the linear order perturbations which at the next order act like source terms. Moreover, we confirm that the stability requirements, ensuring the positivity of the kinetic term and the speed of propagation for scalar mode, are automatically satisfied once the viability of the theory is demanded at linear level. The approach we present here will allow to construct, in a model independent way, all the relevant predictions on observables at mildly non-linear scales.

Effects of Image Compression on Automatic Count of Immunohistochemically Stained Nuclei in Digital Images

PubMed Central

López, Carlos; Lejeune, Marylène; Escrivà, Patricia; Bosch, Ramón; Salvadó, Maria Teresa; Pons, Lluis E.; Baucells, Jordi; Cugat, Xavier; Álvaro, Tomás; Jaén, Joaquín

2008-01-01

This study investigates the effects of digital image compression on automatic quantification of immunohistochemical nuclear markers. We examined 188 images with a previously validated computer-assisted analysis system. A first group was composed of 47 images captured in TIFF format, and other three contained the same images converted from TIFF to JPEG format with 3×, 23× and 46× compression. Counts of TIFF format images were compared with the other three groups. Overall, differences in the count of the images increased with the percentage of compression. Low-complexity images (≤100 cells/field, without clusters or with small-area clusters) had small differences (<5 cells/field in 95–100% of cases) and high-complexity images showed substantial differences (<35–50 cells/field in 95–100% of cases). Compression does not compromise the accuracy of immunohistochemical nuclear marker counts obtained by computer-assisted analysis systems for digital images with low complexity and could be an efficient method for storing these images. PMID:18755997

Detection of Thermal Erosion Gullies from High-Resolution Images Using Deep Learning

NASA Astrophysics Data System (ADS)

Huang, L.; Liu, L.; Jiang, L.; Zhang, T.; Sun, Y.

2017-12-01

Thermal erosion gullies, one type of thermokarst landforms, develop due to thawing of ice-rich permafrost. Mapping the location and extent of thermal erosion gullies can help understand the spatial distribution of thermokarst landforms and their temporal evolution. Remote sensing images provide an effective way for mapping thermokarst landforms, especially thermokarst lakes. However, thermal erosion gullies are challenging to map from remote sensing images due to their small sizes and significant variations in geometric/radiometric properties. It is feasible to manually identify these features, as a few previous studies have carried out. However manual methods are labor-intensive, therefore, cannot be used for a large study area. In this work, we conduct automatic mapping of thermal erosion gullies from high-resolution images by using Deep Learning. Our study area is located in Eboling Mountain (Qinghai, China). Within a 6 km2 peatland area underlain by ice-rich permafrost, at least 20 thermal erosional gullies are well developed. The image used is a 15-cm-resolution Digital Orthophoto Map (DOM) generated in July 2016. First, we extracted 14 gully patches and ten non-gully patches as training data. And we performed image augmentation. Next, we fine-tuned the pre-trained model of DeepLab, a deep-learning algorithm for semantic image segmentation based on Deep Convolutional Neural Networks. Then, we performed inference on the whole DOM and obtained intermediate results in forms of polygons for all identified gullies. At last, we removed misidentified polygons based on a few pre-set criteria on the size and shape of each polygon. Our final results include 42 polygons. Validated against field measurements using GPS, most of the gullies are detected correctly. There are 20 false detections due to the small number and low quality of training images. We also found three new gullies that missed in the field observations. This study shows that (1) despite a challenging mapping task, DeepLab can detect small, irregular-shaped thermal erosion gullies with high accuracy. (2) Automatic detection is critical for mapping thermal erosion gully since manual mapping or field work may miss some targets even in a relatively small region. (3) The quantity and quality of training data are crucial for detection accuracy.

Automatically Detecting Likely Edits in Clinical Notes Created Using Automatic Speech Recognition

PubMed Central

Lybarger, Kevin; Ostendorf, Mari; Yetisgen, Meliha

2017-01-01

The use of automatic speech recognition (ASR) to create clinical notes has the potential to reduce costs associated with note creation for electronic medical records, but at current system accuracy levels, post-editing by practitioners is needed to ensure note quality. Aiming to reduce the time required to edit ASR transcripts, this paper investigates novel methods for automatic detection of edit regions within the transcripts, including both putative ASR errors but also regions that are targets for cleanup or rephrasing. We create detection models using logistic regression and conditional random field models, exploring a variety of text-based features that consider the structure of clinical notes and exploit the medical context. Different medical text resources are used to improve feature extraction. Experimental results on a large corpus of practitioner-edited clinical notes show that 67% of sentence-level edits and 45% of word-level edits can be detected with a false detection rate of 15%. PMID:29854187

Semi-automatic brain tumor segmentation by constrained MRFs using structural trajectories.

PubMed

Zhao, Liang; Wu, Wei; Corso, Jason J

2013-01-01

Quantifying volume and growth of a brain tumor is a primary prognostic measure and hence has received much attention in the medical imaging community. Most methods have sought a fully automatic segmentation, but the variability in shape and appearance of brain tumor has limited their success and further adoption in the clinic. In reaction, we present a semi-automatic brain tumor segmentation framework for multi-channel magnetic resonance (MR) images. This framework does not require prior model construction and only requires manual labels on one automatically selected slice. All other slices are labeled by an iterative multi-label Markov random field optimization with hard constraints. Structural trajectories-the medical image analog to optical flow and 3D image over-segmentation are used to capture pixel correspondences between consecutive slices for pixel labeling. We show robustness and effectiveness through an evaluation on the 2012 MICCAI BRATS Challenge Dataset; our results indicate superior performance to baselines and demonstrate the utility of the constrained MRF formulation.

Automatic updating and 3D modeling of airport information from high resolution images using GIS and LIDAR data

NASA Astrophysics Data System (ADS)

Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng

2007-11-01

As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.

Semi Automatic Ontology Instantiation in the domain of Risk Management

NASA Astrophysics Data System (ADS)

Makki, Jawad; Alquier, Anne-Marie; Prince, Violaine

One of the challenging tasks in the context of Ontological Engineering is to automatically or semi-automatically support the process of Ontology Learning and Ontology Population from semi-structured documents (texts). In this paper we describe a Semi-Automatic Ontology Instantiation method from natural language text, in the domain of Risk Management. This method is composed from three steps 1 ) Annotation with part-of-speech tags, 2) Semantic Relation Instances Extraction, 3) Ontology instantiation process. It's based on combined NLP techniques using human intervention between steps 2 and 3 for control and validation. Since it heavily relies on linguistic knowledge it is not domain dependent which is a good feature for portability between the different fields of risk management application. The proposed methodology uses the ontology of the PRIMA1 project (supported by the European community) as a Generic Domain Ontology and populates it via an available corpus. A first validation of the approach is done through an experiment with Chemical Fact Sheets from Environmental Protection Agency2.

Do automatic reactions elicited by thoughts of romantic partner, mother, and self relate to adult romantic attachment?

PubMed

Zayas, Vivian; Shoda, Yuichi

2005-08-01

Three studies tested the expectation that automatic reactions elicited by the mental representation of one's current romantic partner, mother, and self relate to adult romantic attachment. Adult romantic attachment was assessed using multiple measures, and individual differences in automatic reactions were assessed by the Implicit Association Test (IAT). Studies 1 and 2 showed that automatic reactions elicited by thoughts of current romantic partner, but not by thoughts of self, were related to adult romantic attachment assessed at a specific (i.e., within one's current romantic relationship) and general level (i.e., across all romantic relationships). The pattern of results was stronger among individuals identified as attachment-schematic. Studies 2 and 3 showed that automatic reactions elicited by thoughts of one's mother were related to adult romantic attachment assessed at a general level. In all three studies, results did not differ depending on how adult romantic attachment was conceptualized (four styles vs. two dimensions).

Carotid stenosis assessment with multi-detector CT angiography: comparison between manual and automatic segmentation methods.

PubMed

Zhu, Chengcheng; Patterson, Andrew J; Thomas, Owen M; Sadat, Umar; Graves, Martin J; Gillard, Jonathan H

2013-04-01

Luminal stenosis is used for selecting the optimal management strategy for patients with carotid artery disease. The aim of this study is to evaluate the reproducibility of carotid stenosis quantification using manual and automated segmentation methods using submillimeter through-plane resolution Multi-Detector CT angiography (MDCTA). 35 patients having carotid artery disease with >30 % luminal stenosis as identified by carotid duplex imaging underwent contrast enhanced MDCTA. Two experienced CT readers quantified carotid stenosis from axial source images, reconstructed maximum intensity projection (MIP) and 3D-carotid geometry which was automatically segmented by an open-source toolkit (Vascular Modelling Toolkit, VMTK) using NASCET criteria. Good agreement among the measurement using axial images, MIP and automatic segmentation was observed. Automatic segmentation methods show better inter-observer agreement between the readers (intra-class correlation coefficient (ICC): 0.99 for diameter stenosis measurement) than manual measurement of axial (ICC = 0.82) and MIP (ICC = 0.86) images. Carotid stenosis quantification using an automatic segmentation method has higher reproducibility compared with manual methods.

FURTHER ANALYSIS OF SUBTYPES OF AUTOMATICALLY REINFORCED SIB: A REPLICATION AND QUANTITATIVE ANALYSIS OF PUBLISHED DATASETS

PubMed Central

Hagopian, Louis P.; Rooker, Griffin W.; Zarcone, Jennifer R.; Bonner, Andrew C.; Arevalo, Alexander R.

2017-01-01

Hagopian, Rooker, and Zarcone (2015) evaluated a model for subtyping automatically reinforced self-injurious behavior (SIB) based on its sensitivity to changes in functional analysis conditions and the presence of self-restraint. The current study tested the generality of the model by applying it to all datasets of automatically reinforced SIB published from 1982 to 2015. We identified 49 datasets that included sufficient data to permit subtyping. Similar to the original study, Subtype-1 SIB was generally amenable to treatment using reinforcement alone, whereas Subtype-2 SIB was not. Conclusions could not be drawn about Subtype-3 SIB due to the small number of datasets. Nevertheless, the findings support the generality of the model and suggest that sensitivity of SIB to disruption by alternative reinforcement is an important dimension of automatically reinforced SIB. Findings also suggest that automatically reinforced SIB should no longer be considered a single category and that additional research is needed to better understand and treat Subtype-2 SIB. PMID:28032344

Defeaturing CAD models using a geometry-based size field and facet-based reduction operators.

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

Quadros, William Roshan; Owen, Steven James

2010-04-01

We propose a method to automatically defeature a CAD model by detecting irrelevant features using a geometry-based size field and a method to remove the irrelevant features via facet-based operations on a discrete representation. A discrete B-Rep model is first created by obtaining a faceted representation of the CAD entities. The candidate facet entities are then marked for reduction by using a geometry-based size field. This is accomplished by estimating local mesh sizes based on geometric criteria. If the field value at a facet entity goes below a user specified threshold value then it is identified as an irrelevant featuremore » and is marked for reduction. The reduction of marked facet entities is primarily performed using an edge collapse operator. Care is taken to retain a valid geometry and topology of the discrete model throughout the procedure. The original model is not altered as the defeaturing is performed on a separate discrete model. Associativity between the entities of the discrete model and that of original CAD model is maintained in order to decode the attributes and boundary conditions applied on the original CAD entities onto the mesh via the entities of the discrete model. Example models are presented to illustrate the effectiveness of the proposed approach.« less

Data-driven automated acoustic analysis of human infant vocalizations using neural network tools.

PubMed

Warlaumont, Anne S; Oller, D Kimbrough; Buder, Eugene H; Dale, Rick; Kozma, Robert

2010-04-01

Acoustic analysis of infant vocalizations has typically employed traditional acoustic measures drawn from adult speech acoustics, such as f(0), duration, formant frequencies, amplitude, and pitch perturbation. Here an alternative and complementary method is proposed in which data-derived spectrographic features are central. 1-s-long spectrograms of vocalizations produced by six infants recorded longitudinally between ages 3 and 11 months are analyzed using a neural network consisting of a self-organizing map and a single-layer perceptron. The self-organizing map acquires a set of holistic, data-derived spectrographic receptive fields. The single-layer perceptron receives self-organizing map activations as input and is trained to classify utterances into prelinguistic phonatory categories (squeal, vocant, or growl), identify the ages at which they were produced, and identify the individuals who produced them. Classification performance was significantly better than chance for all three classification tasks. Performance is compared to another popular architecture, the fully supervised multilayer perceptron. In addition, the network's weights and patterns of activation are explored from several angles, for example, through traditional acoustic measurements of the network's receptive fields. Results support the use of this and related tools for deriving holistic acoustic features directly from infant vocalization data and for the automatic classification of infant vocalizations.

Automatic Selection of Multiple Images in the Frontier Field Clusters

NASA Astrophysics Data System (ADS)

Mahler, Guillaume; Richard, Johan; Patricio, Vera; Clément, Benjamin; Lagattuta, David

2015-08-01

Probing the central mass distribution of massive galaxy clusters is an important step towards mapping the overall distribution of their dark matter content. Thanks to gravitational lensing and the appearance of multiple images, we can constrain the inner region of galaxy clusters with a high precision. The Frontier Fields (FF) provide us with the deepest HST data ever in such clusters. Currently, most multiple-image systems are found by eye, yet in the FF, we expect hundreds to exist.Thus, In order to deal with such huge amounts of data, we need to method develop an automated detection method.I present a new tool to perform this task, MISE (Multiple Images SEarcher), a program which identifies multiple images by combining their specific properties. In particular, multiple images must: a) have similar colors, b) have similar surface brightnesses, and c) appear in locations predicted by a specific lensing configuration.I will describe the tuning and performances of MISE on both the FF clusters and the simulated clusters HERA and ARES. MISE allows us to not confirm multiple images identified visually, but also detect new multiple-image candidates in MACS0416 and A2744, giving us additional constraints on the mass distribution in these clusters. A spectroscopic follow-up of these candidates is currently underway with MUSE.

How wind turbines affect the performance of seismic monitoring stations and networks

NASA Astrophysics Data System (ADS)

Neuffer, Tobias; Kremers, Simon

2017-12-01

In recent years, several minor seismic events were observed in the apparently aseismic region of the natural gas fields in Northern Germany. A seismic network was installed in the region consisting of borehole stations with sensor depths up to 200 m and surface stations to monitor induced seismicity. After installation of the network in 2012, an increasing number of wind turbines was established in proximity (<5 km) to several stations, thereby influencing the local noise conditions. This study demonstrates the impact of wind turbines on seismic noise level in a frequency range of 1-10 Hz at the monitoring sites with correlation to wind speed, based on the calculation of power spectral density functions and I95 values of waveforms over a time period of 4 yr. It could be shown that higher wind speeds increase the power spectral density amplitudes at distinct frequencies in the considered frequency band, depending on height as well as number and type of influencing wind turbines. The azimuthal direction of incoming Rayleigh waves at a surface station was determined to identify the noise sources. The analysis of the perturbed wave field showed that Rayleigh waves with backazimuths pointing to wind turbines in operation are dominating the wave field in a frequency band of 3-4 Hz. Additional peaks in a frequency range of 1-4 Hz could be attributed to turbine tower eigenfrequencies of various turbine manufactures with the hub height as defining parameter. Moreover, the influence of varying noise levels at a station on the ability to automatically detect seismic events was investigated. The increased noise level in correlation to higher wind speeds at the monitoring sites deteriorates the station's recording quality inhibiting the automatic detection of small seismic events. As a result, functionality and task fulfilment of the seismic monitoring network is more and more limited by the increasing number of nearby wind turbines.

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.

Investigation of possible causes for human-performance degradation during microgravity flight

NASA Technical Reports Server (NTRS)

Schroeder, James E.; Tuttle, Megan L.

1992-01-01

The results of the first year of a three year study of the effects of microgravity on human performance are given. Test results show support for the hypothesis that the effects of microgravity can be studied indirectly on Earth by measuring performance in an altered gravitational field. The hypothesis was that an altered gravitational field could disrupt performance on previously automated behaviors if gravity was a critical part of the stimulus complex controlling those behaviors. In addition, it was proposed that performance on secondary cognitive tasks would also degrade, especially if the subject was provided feedback about degradation on the previously automated task. In the initial experimental test of these hypotheses, there was little statistical support. However, when subjects were categorized as high or low in automated behavior, results for the former group supported the hypotheses. The predicted interaction between body orientation and level of workload in their joint effect on performance in the secondary cognitive task was significant for the group high in automatized behavior and receiving feedback, but no such interventions were found for the group high in automatized behavior but not receiving feedback, or the group low in automatized behavior.

Evaluation of Automatic Item Generation Utilities in Formative Assessment Application for Korean High School Students

ERIC Educational Resources Information Center

Choi, Jaehwa; Kim, HeeKyoung; Pak, Seohong

2018-01-01

The recent interests in research in the assessment field have been rapidly shifting from decision-maker-centered assessments to learner-centered assessments (i.e., diagnostic and/or formative assessments). In particular, it is a very important research topic in this field to analyze how these learner-centered assessments are developed more…

INSTRUMENTATION AND AUTOMATIC CONTROL, SUGGESTED TECHNIQUES FOR DETERMINING COURSES OF STUDY IN VOCATIONAL AND TECHNICAL EDUCATION PROGRAMS.

ERIC Educational Resources Information Center

WEINSTEIN, EMANUEL

THE PURPOSE OF THIS GUIDE IS TO HELP THE STATES ORGANIZE AND OPERATE EDUCATIONAL PROGRAMS FOR OCCUPATIONS IN THE FIELD OF INSTRUMENTATION. CHAPTER TITLES ARE--(1) INSTRUMENTATIONS--PAST, PRESENT, AND FUTURE, (2) THE OCCUPATIONAL FIELD, (3) WORK ACTIVITIES (DESIGN, FABRICATION, MAINTENANCE, REPAIR, AND SERVICE), (4) TRAINING REQUIREMENTS, AND (5)…

A data variance technique for automated despiking of magnetotelluric data with a remote reference

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

Kappler, K.

2011-02-15

The magnetotelluric method employs co-located surface measurements of electric and magnetic fields to infer the local electrical structure of the earth. The frequency-dependent 'apparent resistivity' curves can be inaccurate at long periods if input data are contaminated - even when robust remote reference techniques are employed. Data despiking prior to processing can result in significantly more reliable estimates of long period apparent resistivities. This paper outlines a two-step method of automatic identification and replacement for spike-like contamination of magnetotelluric data; based on the simultaneity of natural electric and magnetic field variations at distant sites. This simultaneity is exploited both tomore » identify windows in time when the array data are compromised, and to generate synthetic data that replace observed transient noise spikes. In the first step, windows in data time series containing spikes are identified via intersite comparison of channel 'activity' - such as the variance of differenced data within each window. In the second step, plausible data for replacement of flagged windows is calculated by Wiener filtering coincident data in clean channels. The Wiener filters - which express the time-domain relationship between various array channels - are computed using an uncontaminated segment of array training data. Examples are shown where the algorithm is applied to artificially contaminated data, and to real field data. In both cases all spikes are successfully identified. In the case of implanted artificial noise, the synthetic replacement time series are very similar to the original recording. In all cases, apparent resistivity and phase curves obtained by processing the despiked data are much improved over curves obtained from raw data.« less

Using nanoinformatics methods for automatically identifying relevant nanotoxicology entities from the literature.

PubMed

García-Remesal, Miguel; García-Ruiz, Alejandro; Pérez-Rey, David; de la Iglesia, Diana; Maojo, Víctor

2013-01-01

Nanoinformatics is an emerging research field that uses informatics techniques to collect, process, store, and retrieve data, information, and knowledge on nanoparticles, nanomaterials, and nanodevices and their potential applications in health care. In this paper, we have focused on the solutions that nanoinformatics can provide to facilitate nanotoxicology research. For this, we have taken a computational approach to automatically recognize and extract nanotoxicology-related entities from the scientific literature. The desired entities belong to four different categories: nanoparticles, routes of exposure, toxic effects, and targets. The entity recognizer was trained using a corpus that we specifically created for this purpose and was validated by two nanomedicine/nanotoxicology experts. We evaluated the performance of our entity recognizer using 10-fold cross-validation. The precisions range from 87.6% (targets) to 93.0% (routes of exposure), while recall values range from 82.6% (routes of exposure) to 87.4% (toxic effects). These results prove the feasibility of using computational approaches to reliably perform different named entity recognition (NER)-dependent tasks, such as for instance augmented reading or semantic searches. This research is a "proof of concept" that can be expanded to stimulate further developments that could assist researchers in managing data, information, and knowledge at the nanolevel, thus accelerating research in nanomedicine.

Manifestation of the synergetic mechanism in the implementation of automatic processing of scientific documents

NASA Astrophysics Data System (ADS)

Chizhacovsky, Valentin; Popescu, Anatol N.; Russu, Vladimir

2005-02-01

This article is dedicated to the problem of the presence in the natural language and in the cognitive-verbal human activity of an interior mechanisms of reproduction and self regulation which will help us solve problem by the automatic documents. We have attributed to these mechanisms the property of being synergetic. The above expressed thought has been confirmed at the implementation of the automatic processing of scientific articles, published in the German specialized magazine "Wasserwirtschaft-Wassertechnik-WWT", which we have addressed to the sub subject field "Abwasser" (waste water). By dividing the implementation of our task in many consequent stages and sub stages we have obtained the possibilities to create the conditions which favored the manifestation of the needed linguistic synergetic activities.

Technical note: A simple approach for efficient collection of field reference data for calibrating remote sensing mapping of northern wetlands

NASA Astrophysics Data System (ADS)

Gålfalk, Magnus; Karlson, Martin; Crill, Patrick; Bousquet, Philippe; Bastviken, David

2018-03-01

The calibration and validation of remote sensing land cover products are highly dependent on accurate field reference data, which are costly and practically challenging to collect. We describe an optical method for collection of field reference data that is a fast, cost-efficient, and robust alternative to field surveys and UAV imaging. A lightweight, waterproof, remote-controlled RGB camera (GoPro HERO4 Silver, GoPro Inc.) was used to take wide-angle images from 3.1 to 4.5 m in altitude using an extendable monopod, as well as representative near-ground (< 1 m) images to identify spectral and structural features that correspond to various land covers in present lighting conditions. A semi-automatic classification was made based on six surface types (graminoids, water, shrubs, dry moss, wet moss, and rock). The method enables collection of detailed field reference data, which is critical in many remote sensing applications, such as satellite-based wetland mapping. The method uses common non-expensive equipment, does not require special skills or training, and is facilitated by a step-by-step manual that is included in the Supplement. Over time a global ground cover database can be built that can be used as reference data for studies of non-forested wetlands from satellites such as Sentinel 1 and 2 (10 m pixel size).

Automatic discovery of the communication network topology for building a supercomputer model

NASA Astrophysics Data System (ADS)

Sobolev, Sergey; Stefanov, Konstantin; Voevodin, Vadim

2016-10-01

The Research Computing Center of Lomonosov Moscow State University is developing the Octotron software suite for automatic monitoring and mitigation of emergency situations in supercomputers so as to maximize hardware reliability. The suite is based on a software model of the supercomputer. The model uses a graph to describe the computing system components and their interconnections. One of the most complex components of a supercomputer that needs to be included in the model is its communication network. This work describes the proposed approach for automatically discovering the Ethernet communication network topology in a supercomputer and its description in terms of the Octotron model. This suite automatically detects computing nodes and switches, collects information about them and identifies their interconnections. The application of this approach is demonstrated on the "Lomonosov" and "Lomonosov-2" supercomputers.

SA-SOM algorithm for detecting communities in complex networks

NASA Astrophysics Data System (ADS)

Chen, Luogeng; Wang, Yanran; Huang, Xiaoming; Hu, Mengyu; Hu, Fang

2017-10-01

Currently, community detection is a hot topic. This paper, based on the self-organizing map (SOM) algorithm, introduced the idea of self-adaptation (SA) that the number of communities can be identified automatically, a novel algorithm SA-SOM of detecting communities in complex networks is proposed. Several representative real-world networks and a set of computer-generated networks by LFR-benchmark are utilized to verify the accuracy and the efficiency of this algorithm. The experimental findings demonstrate that this algorithm can identify the communities automatically, accurately and efficiently. Furthermore, this algorithm can also acquire higher values of modularity, NMI and density than the SOM algorithm does.

Technique for finding and identifying filters that cut off OTDR lights in front of ONU from a central office

NASA Astrophysics Data System (ADS)

Takaya, Masaaki; Honda, Hiroyasu; Narita, Yoshihiro; Yamamoto, Fumihiko; Arakawa, Koji

2006-04-01

We report on a newly developed in-service measurement technique that can be used from a central office to find and identify any filter in front of an ONU on an optical fiber access network. Using this system, in-service tests can be performed because the test lights are modulated at a high frequency. Moreover, by using the equipment we developed, this confirmation operation can be performed continuously and automatically with existing automatic fiber testing systems. The developed technique is effective for constructing a fiber line testing system with an optical time domain reflectometer.

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.

Application Research of QRCode Barcode in Validation of Express Delivery

NASA Astrophysics Data System (ADS)

Liu, Zhihai; Zeng, Qingliang; Wang, Chenglong; Lu, Qing

The barcode technology has become an important way in the field of information input and identify automatically. With the outstanding features of big storage capacity, secure, rich encoding character set and fast decoding, the two-dimensional(2D) QRcode(Quick Response Barcode) has become an important choice of commerce barcode. The development of wireless communications technology and the popularization and application of mobile device has set the foundation of 2D barcode used in business. In this paper, the characteristics and the compositions of 2D QRcode are described, the secure validation workflows and contents of QRcode in goods express delivery are discussed, the encoding process of QRcode is showed, and the system framework is analyzed and established. At last, the system compositions and functions of each part are discussed.

Convolution neural-network-based detection of lung structures

NASA Astrophysics Data System (ADS)

Hasegawa, Akira; Lo, Shih-Chung B.; Freedman, Matthew T.; Mun, Seong K.

1994-05-01

Chest radiography is one of the most primary and widely used techniques in diagnostic imaging. Nowadays with the advent of digital radiology, the digital medical image processing techniques for digital chest radiographs have attracted considerable attention, and several studies on the computer-aided diagnosis (CADx) as well as on the conventional image processing techniques for chest radiographs have been reported. In the automatic diagnostic process for chest radiographs, it is important to outline the areas of the lungs, the heart, and the diaphragm. This is because the original chest radiograph is composed of important anatomic structures and, without knowing exact positions of the organs, the automatic diagnosis may result in unexpected detections. The automatic extraction of an anatomical structure from digital chest radiographs can be a useful tool for (1) the evaluation of heart size, (2) automatic detection of interstitial lung diseases, (3) automatic detection of lung nodules, and (4) data compression, etc. Based on the clearly defined boundaries of heart area, rib spaces, rib positions, and rib cage extracted, one should be able to use this information to facilitate the tasks of the CADx on chest radiographs. In this paper, we present an automatic scheme for the detection of lung field from chest radiographs by using a shift-invariant convolution neural network. A novel algorithm for smoothing boundaries of lungs is also presented.

Vaccine Hesitancy in Discussion Forums: Computer-Assisted Argument Mining with Topic Models.

PubMed

Skeppstedt, Maria; Kerren, Andreas; Stede, Manfred

2018-01-01

Arguments used when vaccination is debated on Internet discussion forums might give us valuable insights into reasons behind vaccine hesitancy. In this study, we applied automatic topic modelling on a collection of 943 discussion posts in which vaccine was debated, and six distinct discussion topics were detected by the algorithm. When manually coding the posts ranked as most typical for these six topics, a set of semantically coherent arguments were identified for each extracted topic. This indicates that topic modelling is a useful method for automatically identifying vaccine-related discussion topics and for identifying debate posts where these topics are discussed. This functionality could facilitate manual coding of salient arguments, and thereby form an important component in a system for computer-assisted coding of vaccine-related discussions.

A method for the automatic reconstruction of fetal cardiac signals from magnetocardiographic recordings

NASA Astrophysics Data System (ADS)

Mantini, D.; Alleva, G.; Comani, S.

2005-10-01

Fetal magnetocardiography (fMCG) allows monitoring the fetal heart function through algorithms able to retrieve the fetal cardiac signal, but no standardized automatic model has become available so far. In this paper, we describe an automatic method that restores the fetal cardiac trace from fMCG recordings by means of a weighted summation of fetal components separated with independent component analysis (ICA) and identified through dedicated algorithms that analyse the frequency content and temporal structure of each source signal. Multichannel fMCG datasets of 66 healthy and 4 arrhythmic fetuses were used to validate the automatic method with respect to a classical procedure requiring the manual classification of fetal components by an expert investigator. ICA was run with input clusters of different dimensions to simulate various MCG systems. Detection rates, true negative and false positive component categorization, QRS amplitude, standard deviation and signal-to-noise ratio of reconstructed fetal signals, and real and per cent QRS differences between paired fetal traces retrieved automatically and manually were calculated to quantify the performances of the automatic method. Its robustness and reliability, particularly evident with the use of large input clusters, might increase the diagnostic role of fMCG during the prenatal period.

Automated Assessment of Child Vocalization Development Using LENA.

PubMed

Richards, Jeffrey A; Xu, Dongxin; Gilkerson, Jill; Yapanel, Umit; Gray, Sharmistha; Paul, Terrance

2017-07-12

To produce a novel, efficient measure of children's expressive vocal development on the basis of automatic vocalization assessment (AVA), child vocalizations were automatically identified and extracted from audio recordings using Language Environment Analysis (LENA) System technology. Assessment was based on full-day audio recordings collected in a child's unrestricted, natural language environment. AVA estimates were derived using automatic speech recognition modeling techniques to categorize and quantify the sounds in child vocalizations (e.g., protophones and phonemes). These were expressed as phone and biphone frequencies, reduced to principal components, and inputted to age-based multiple linear regression models to predict independently collected criterion-expressive language scores. From these models, we generated vocal development AVA estimates as age-standardized scores and development age estimates. AVA estimates demonstrated strong statistical reliability and validity when compared with standard criterion expressive language assessments. Automated analysis of child vocalizations extracted from full-day recordings in natural settings offers a novel and efficient means to assess children's expressive vocal development. More research remains to identify specific mechanisms of operation.

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.

Multisource oil spill detection

NASA Astrophysics Data System (ADS)

Salberg, Arnt B.; Larsen, Siri O.; Zortea, Maciel

2013-10-01

In this paper we discuss how multisource data (wind, ocean-current, optical, bathymetric, automatic identification systems (AIS)) may be used to improve oil spill detection in SAR images, with emphasis on the use of automatic oil spill detection algorithms. We focus particularly on AIS, optical, and bathymetric data. For the AIS data we propose an algorithm for integrating AIS ship tracks into automatic oil spill detection in order to improve the confidence estimate of a potential oil spill. We demonstrate the use of ancillary data on a set of SAR images. Regarding the use of optical data, we did not observe a clear correspondence between high chlorophyll values (estimated from products derived from optical data) and observed slicks in the SAR image. Bathymetric data was shown to be a good data source for removing false detections caused by e.g. sand banks on low tide. For the AIS data we observed that a polluter could be identified for some dark slicks, however, a precise oil drift model is needed in order to identify the polluter with high certainty.

Toward image phylogeny forests: automatically recovering semantically similar image relationships.

PubMed

Dias, Zanoni; Goldenstein, Siome; Rocha, Anderson

2013-09-10

In the past few years, several near-duplicate detection methods appeared in the literature to identify the cohabiting versions of a given document online. Following this trend, there are some initial attempts to go beyond the detection task, and look into the structure of evolution within a set of related images overtime. In this paper, we aim at automatically identify the structure of relationships underlying the images, correctly reconstruct their past history and ancestry information, and group them in distinct trees of processing history. We introduce a new algorithm that automatically handles sets of images comprising different related images, and outputs the phylogeny trees (also known as a forest) associated with them. Image phylogeny algorithms have many applications such as finding the first image within a set posted online (useful for tracking copyright infringement perpetrators), hint at child pornography content creators, and narrowing down a list of suspects for online harassment using photographs. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Automatic classification of unexploded ordnance applied to Spencer Range live site for 5x5 TEMTADS sensor

NASA Astrophysics Data System (ADS)

Sigman, John B.; Barrowes, Benjamin E.; O'Neill, Kevin; Shubitidze, Fridon

2013-06-01

This paper details methods for automatic classification of Unexploded Ordnance (UXO) as applied to sensor data from the Spencer Range live site. The Spencer Range is a former military weapons range in Spencer, Tennessee. Electromagnetic Induction (EMI) sensing is carried out using the 5x5 Time-domain Electromagnetic Multi-sensor Towed Array Detection System (5x5 TEMTADS), which has 25 receivers and 25 co-located transmitters. Every transmitter is activated sequentially, each followed by measuring the magnetic field in all 25 receivers, from 100 microseconds to 25 milliseconds. From these data target extrinsic and intrinsic parameters are extracted using the Differential Evolution (DE) algorithm and the Ortho-Normalized Volume Magnetic Source (ONVMS) algorithms, respectively. Namely, the inversion provides x, y, and z locations and a time series of the total ONVMS principal eigenvalues, which are intrinsic properties of the objects. The eigenvalues are fit to a power-decay empirical model, the Pasion-Oldenburg model, providing 3 coefficients (k, b, and g) for each object. The objects are grouped geometrically into variably-sized clusters, in the k-b-g space, using clustering algorithms. Clusters matching a priori characteristics are identified as Targets of Interest (TOI), and larger clusters are automatically subclustered. Ground Truths (GT) at the center of each class are requested, and probability density functions are created for clusters that have centroid TOI using a Gaussian Mixture Model (GMM). The probability functions are applied to all remaining anomalies. All objects of UXO probability higher than a chosen threshold are placed in a ranked dig list. This prioritized list is scored and the results are demonstrated and analyzed.

Standards for the Analysis and Processing of Surface-Water Data and Information Using Electronic Methods

USGS Publications Warehouse

Sauer, Vernon B.

2002-01-01

Surface-water computation methods and procedures are described in this report to provide standards from which a completely automated electronic processing system can be developed. To the greatest extent possible, the traditional U. S. Geological Survey (USGS) methodology and standards for streamflow data collection and analysis have been incorporated into these standards. Although USGS methodology and standards are the basis for this report, the report is applicable to other organizations doing similar work. The proposed electronic processing system allows field measurement data, including data stored on automatic field recording devices and data recorded by the field hydrographer (a person who collects streamflow and other surface-water data) in electronic field notebooks, to be input easily and automatically. A user of the electronic processing system easily can monitor the incoming data and verify and edit the data, if necessary. Input of the computational procedures, rating curves, shift requirements, and other special methods are interactive processes between the user and the electronic processing system, with much of this processing being automatic. Special computation procedures are provided for complex stations such as velocity-index, slope, control structures, and unsteady-flow models, such as the Branch-Network Dynamic Flow Model (BRANCH). Navigation paths are designed to lead the user through the computational steps for each type of gaging station (stage-only, stagedischarge, velocity-index, slope, rate-of-change in stage, reservoir, tide, structure, and hydraulic model stations). The proposed electronic processing system emphasizes the use of interactive graphics to provide good visual tools for unit values editing, rating curve and shift analysis, hydrograph comparisons, data-estimation procedures, data review, and other needs. Documentation, review, finalization, and publication of records are provided for with the electronic processing system, as well as archiving, quality assurance, and quality control.

Automatic detection of diabetic retinopathy features in ultra-wide field retinal images

NASA Astrophysics Data System (ADS)

Levenkova, Anastasia; Sowmya, Arcot; Kalloniatis, Michael; Ly, Angelica; Ho, Arthur

2017-03-01

Diabetic retinopathy (DR) is a major cause of irreversible vision loss. DR screening relies on retinal clinical signs (features). Opportunities for computer-aided DR feature detection have emerged with the development of Ultra-WideField (UWF) digital scanning laser technology. UWF imaging covers 82% greater retinal area (200°), against 45° in conventional cameras3 , allowing more clinically relevant retinopathy to be detected4 . UWF images also provide a high resolution of 3078 x 2702 pixels. Currently DR screening uses 7 overlapping conventional fundus images, and the UWF images provide similar results1,4. However, in 40% of cases, more retinopathy was found outside the 7-field ETDRS) fields by UWF and in 10% of cases, retinopathy was reclassified as more severe4 . This is because UWF imaging allows examination of both the central retina and more peripheral regions, with the latter implicated in DR6 . We have developed an algorithm for automatic recognition of DR features, including bright (cotton wool spots and exudates) and dark lesions (microaneurysms and blot, dot and flame haemorrhages) in UWF images. The algorithm extracts features from grayscale (green "red-free" laser light) and colour-composite UWF images, including intensity, Histogram-of-Gradient and Local binary patterns. Pixel-based classification is performed with three different classifiers. The main contribution is the automatic detection of DR features in the peripheral retina. The method is evaluated by leave-one-out cross-validation on 25 UWF retinal images with 167 bright lesions, and 61 other images with 1089 dark lesions. The SVM classifier performs best with AUC of 94.4% / 95.31% for bright / dark lesions.

Automatic Focusing for a 675 GHz Imaging Radar with Target Standoff Distances from 14 to 34 Meters

NASA Technical Reports Server (NTRS)

Tang, Adrian; Cooper, Ken B.; Dengler, Robert J.; Llombart, Nuria; Siegel, Peter H.

2013-01-01

This paper dicusses the issue of limited focal depth for high-resolution imaging radar operating over a wide range of standoff distances. We describe a technique for automatically focusing a THz imaging radar system using translational optics combined with range estimation based on a reduced chirp bandwidth setting. The demonstarted focusing algorithm estimates the correct focal depth for desired targets in the field of view at unknown standoffs and in the presence of clutter to provide good imagery at 14 to 30 meters of standoff.

GN/C translation and rotation control parameters for AR/C (category 2)

NASA Technical Reports Server (NTRS)

Henderson, David M.

1991-01-01

Detailed analysis of the Automatic Rendezvous and Capture problem indicate a need for three different regions of mathematical description for the GN&C algorithms: (1) multi-vehicle orbital mechanics to the rendezvous interface point, i.e., within 100 n.; (2) relative motion solutions (such as Clohessy-Wiltshire type) from the far-field to the near-field interface, i.e., within 1 nm; and (3) close proximity motion, the nearfield motion where the relative differences in the gravitational and orbit inertial accelerations can be neglected from the equations of motion. This paper defines the reference coordinate frames and control parameters necessary to model the relative motion and attitude of spacecraft in the close proximity of another space system (Region 2 and 3) during the Automatic Rendezvous and Capture phase of an orbit operation.

Faraday rotation of Automatic Dependent Surveillance Broadcast (ADS-B) signals as a method of ionospheric characterization

NASA Astrophysics Data System (ADS)

Cushley, A. C.; Kabin, K.; Noel, J. M. A.

2017-12-01

Radio waves propagating through plasma in the Earth's ambient magnetic field experience Faraday rotation; the plane of the electric field of a linearly polarized wave changes as a function of the distance travelled through a plasma. Linearly polarized radio waves at 1090 MHz frequency are emitted by Automatic Dependent Surveillance Broadcast (ADS-B) devices which are installed on most commercial aircraft. These radio waves can be detected by satellites in low earth orbits, and the change of the polarization angle caused by propagation through the terrestrial ionosphere can be measured. In this work we discuss how these measurements can be used to characterize the ionospheric conditions. In the present study, we compute the amount of Faraday rotation from a prescribed total electron content value and two of the profile parameters of the NeQuick model.

Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications.

PubMed

Corneanu, Ciprian Adrian; Simon, Marc Oliu; Cohn, Jeffrey F; Guerrero, Sergio Escalera

2016-08-01

Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research.

Simulation of an automatically-controlled STOL aircraft in a microwave landing system multipath environment

NASA Technical Reports Server (NTRS)

Toda, M.; Brown, S. C.; Burrous, C. N.

1976-01-01

The simulated response is described of a STOL aircraft to Microwave Landing System (MLS) multipath errors during final approach and touchdown. The MLS azimuth, elevation, and DME multipath errors were computed for a relatively severe multipath environment at Crissy Field California, utilizing an MLS multipath simulation at MIT Lincoln Laboratory. A NASA/Ames six-degree-of-freedom simulation of an automatically-controlled deHavilland C-8A STOL aircraft was used to determine the response to these errors. The results show that the aircraft response to all of the Crissy Field MLS multipath errors was small. The small MLS azimuth and elevation multipath errors did not result in any discernible aircraft motion, and the aircraft response to the relatively large (200-ft (61-m) peak) DME multipath was noticeable but small.

A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops.

PubMed

Bengochea-Guevara, José M; Andújar, Dionisio; Sanchez-Sardana, Francisco L; Cantuña, Karla; Ribeiro, Angela

2017-12-24

Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, "on ground crop inspection" potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. "On ground monitoring" is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows.

A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops

PubMed Central

Andújar, Dionisio; Sanchez-Sardana, Francisco L.; Cantuña, Karla

2017-01-01

Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, “on ground crop inspection” potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. “On ground monitoring” is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows. PMID:29295536

Management of natural resources through automatic cartographic inventory

NASA Technical Reports Server (NTRS)

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

1974-01-01

The author has identified the following significant results. Significant correspondence codes relating ERTS imagery to ground truth from vegetation and geology maps have been established. The use of color equidensity and color composite methods for selecting zones of equal densitometric value on ERTS imagery was perfected. Primary interest of temporal color composite is stressed. A chain of transfer operations from ERTS imagery to the automatic mapping of natural resources was developed.

Arkheia: Data Management and Communication for Open Computational Neuroscience

PubMed Central

Antolík, Ján; Davison, Andrew P.

2018-01-01

Two trends have been unfolding in computational neuroscience during the last decade. First, a shift of focus to increasingly complex and heterogeneous neural network models, with a concomitant increase in the level of collaboration within the field (whether direct or in the form of building on top of existing tools and results). Second, a general trend in science toward more open communication, both internally, with other potential scientific collaborators, and externally, with the wider public. This multi-faceted development toward more integrative approaches and more intense communication within and outside of the field poses major new challenges for modelers, as currently there is a severe lack of tools to help with automatic communication and sharing of all aspects of a simulation workflow to the rest of the community. To address this important gap in the current computational modeling software infrastructure, here we introduce Arkheia. Arkheia is a web-based open science platform for computational models in systems neuroscience. It provides an automatic, interactive, graphical presentation of simulation results, experimental protocols, and interactive exploration of parameter searches, in a web browser-based application. Arkheia is focused on automatic presentation of these resources with minimal manual input from users. Arkheia is written in a modular fashion with a focus on future development of the platform. The platform is designed in an open manner, with a clearly defined and separated API for database access, so that any project can write its own backend translating its data into the Arkheia database format. Arkheia is not a centralized platform, but allows any user (or group of users) to set up their own repository, either for public access by the general population, or locally for internal use. Overall, Arkheia provides users with an automatic means to communicate information about not only their models but also individual simulation results and the entire experimental context in an approachable graphical manner, thus facilitating the user's ability to collaborate in the field and outreach to a wider audience. PMID:29556187

Automatic smoke evacuation in laparoscopic surgery: a simplified method for objective evaluation.

PubMed

Takahashi, Hidekazu; Yamasaki, Makoto; Hirota, Masashi; Miyazaki, Yasuaki; Moon, Jeong Ho; Souma, Yoshihito; Mori, Masaki; Doki, Yuichiro; Nakajima, Kiyokazu

2013-08-01

Although its theoretical usefulness has been reported, the true value of automatic smoke evacuation system in laparoscopic surgery remains unknown. This is mainly due to the lack of objective evaluation. The purpose of this study was to determine the efficacy of the automatic smoke evacuator in laparoscopic surgery, by real-time objective evaluation system using an industrial smoke-detection device. Six pigs were used in this study. Three surgical ports were placed and electrosurgical smoke was generated in a standard fashion, using either a high-frequency electrosurgical unit (HF-ESU) or laparosonic coagulating shears (LCS). The smoke was evacuated immediately in the evacuation group but not in the control nonevacuation group. The laparoscopic field-of-view was subjectively evaluated by ten independent surgeons. The composition of the surgical smoke was analyzed by mass spectrometry. The residual smoke in the abdominal cavity was aspirated manually into a smoke tester, and stains on a filter paper were image captured, digitized, and semiquantified. Subjective evaluation indicated superior field-of-view in the evacuation group, compared with the control, at 15 s after activation of the HF-ESU (P < 0.05). The smoke comprised various chemical compounds, including known carcinogens. The estimated volume of intra-abdominal residual smoke after activation of HF-ESU was significantly lower in the evacuation group (47.4 ± 16.6) than the control (76.7 ± 2.4, P = 0.0018). Only marginal amount of surgical smoke was detected in both groups after LCS when the tissue pad was free from burnt tissue deposits. However, the amount was significantly lower in the evacuation group (21.3 ± 10.7) than the control (75 ± 39.9, P = 0.044) when the tissue pad contained tissue sludge. Automatic smoke evacuation provides better field-of-view and reduces the risk of exposure to harmful compounds.

Arkheia: Data Management and Communication for Open Computational Neuroscience.

PubMed

Antolík, Ján; Davison, Andrew P

2018-01-01

Two trends have been unfolding in computational neuroscience during the last decade. First, a shift of focus to increasingly complex and heterogeneous neural network models, with a concomitant increase in the level of collaboration within the field (whether direct or in the form of building on top of existing tools and results). Second, a general trend in science toward more open communication, both internally, with other potential scientific collaborators, and externally, with the wider public. This multi-faceted development toward more integrative approaches and more intense communication within and outside of the field poses major new challenges for modelers, as currently there is a severe lack of tools to help with automatic communication and sharing of all aspects of a simulation workflow to the rest of the community. To address this important gap in the current computational modeling software infrastructure, here we introduce Arkheia. Arkheia is a web-based open science platform for computational models in systems neuroscience. It provides an automatic, interactive, graphical presentation of simulation results, experimental protocols, and interactive exploration of parameter searches, in a web browser-based application. Arkheia is focused on automatic presentation of these resources with minimal manual input from users. Arkheia is written in a modular fashion with a focus on future development of the platform. The platform is designed in an open manner, with a clearly defined and separated API for database access, so that any project can write its own backend translating its data into the Arkheia database format. Arkheia is not a centralized platform, but allows any user (or group of users) to set up their own repository, either for public access by the general population, or locally for internal use. Overall, Arkheia provides users with an automatic means to communicate information about not only their models but also individual simulation results and the entire experimental context in an approachable graphical manner, thus facilitating the user's ability to collaborate in the field and outreach to a wider audience.

Ultrasonic guided wave interpretation for structural health inspections

NASA Astrophysics Data System (ADS)

Bingham, Jill Paisley

Structural Health Management (SHM) combines the use of onboard sensors with artificial intelligence algorithms to automatically identify and monitor structural health issues. A fully integrated approach to SHM systems demands an understanding of the sensor output relative to the structure, along with sophisticated prognostic systems that automatically draw conclusions about structural integrity issues. Ultrasonic guided wave methods allow us to examine the interaction of multimode signals within key structural components. Since they propagate relatively long distances within plate- and shell-like structures, guided waves allow inspection of greater areas with fewer sensors, making this technique attractive for a variety of applications. This dissertation describes the experimental development of automatic guided wave interpretation for three real world applications. Using the guided wave theories for idealized plates we have systematically developed techniques for identifying the mass loading of underwater limpet mines on US Navy ship hulls, characterizing type and bonding of protective coatings on large diameter pipelines, and detecting the thinning effects of corrosion on aluminum aircraft structural stringers. In each of these circumstances the signals received are too complex for interpretation without knowledge of the guided wave physics. We employ a signal processing technique called the Dynamic Wavelet Fingerprint Technique (DFWT) in order to render the guided wave mode information in two-dimensional binary images. The use of wavelets allows us to keep track of both time and scale features from the original signals. With simple image processing we have developed automatic extraction algorithms for features that correspond to the arrival times of the guided wave modes of interest for each of the applications. Due to the dispersive nature of the guided wave modes, the mode arrival times give details of the structure in the propagation path. For further understanding of how the guided wave modes propagate through the real structures, we have developed parallel processing, 3D elastic wave simulations using the finite integration technique (EFIT). This full field, numeric simulation technique easily examines models too complex for analytical solutions. We have developed the algorithm to handle built up 3D structures as well as layers with different material properties and surface detail. The simulations produce informative visualizations of the guided wave modes in the structures as well as the output from sensors placed in the simulation space to mimic the placement from experiment. Using the previously developed mode extraction algorithms we were then able to compare our 3D EFIT data to their experimental counterparts with consistency.

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

Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets

PubMed Central

2012-01-01

Background While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps. Results We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features. Conclusions We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to recognize texture, it would be possible to replace this with other texture identifiers, and we plan to explore this in future work. PMID:22321695

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. Published by Elsevier Ltd. All rights reserved.

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 gold seeds are either correctly detected or a warning is raised for further manual intervention.« less

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 warning is raised for further manual intervention.

Data Flow for the TERRA-REF project

NASA Astrophysics Data System (ADS)

Kooper, R.; Burnette, M.; Maloney, J.; LeBauer, D.

2017-12-01

The Transportation Energy Resources from Renewable Agriculture Phenotyping Reference Platform (TERRA-REF) program aims to identify crop traits that are best suited to producing high-energy sustainable biofuels and match those plant characteristics to their genes to speed the plant breeding process. One tool used to achieve this goal is a high-throughput phenotyping robot outfitted with sensors and cameras to monitor the growth of 1.25 acres of sorghum. Data types range from hyperspectral imaging to 3D reconstructions and thermal profiles, all at 1mm resolution. This system produces thousands of daily measurements with high spatiotemporal resolution. The team at NCSA processes, annotates, organizes and stores the massive amounts of data produced by this system - up to 5 TB per day. Data from the sensors is streamed to a local gantry-cache server. The standardized sensor raw data stream is automatically and securely delivered to NCSA using Globus Connect service. Once files have been successfully received by the Globus endpoint, the files are removed from the gantry-cache server. As each dataset arrives or is created the Clowder system automatically triggers different software tools to analyze each file, extract information, and convert files to a common format. Other tools can be triggered to run after all required data is uploaded. For example, a stitched image of the entire field is created after all images of the field become available. Some of these tools were developed by external collaborators based on predictive models and algorithms, others were developed as part of other projects and could be leveraged by the TERRA project. Data will be stored for the lifetime of the project and is estimated to reach 10 PB over 3 years. The Clowder system, BETY and other systems will allow users to easily find data by browsing or searching the extracted information.

Heliostat kinematic system calibration using uncalibrated cameras

NASA Astrophysics Data System (ADS)

Burisch, Michael; Gomez, Luis; Olasolo, David; Villasante, Cristobal

2017-06-01

The efficiency of the solar field greatly depends on the ability of the heliostats to precisely reflect solar radiation onto a central receiver. To control the heliostats with such a precision accurate knowledge of the motion of each of them modeled as a kinematic system is required. Determining the parameters of this system for each heliostat by a calibration system is crucial for the efficient operation of the solar field. For small sized heliostats being able to make such a calibration in a fast and automatic manner is imperative as the solar field potentially contain tens or even hundreds of thousands of them. A calibration system which can rapidly recalibrate a whole solar field would also allow reducing costs. Heliostats are generally designed to provide stability over a large period of time. Being able to relax this requirement and compensate any occurring error by adapting parameters in a model, the costs of the heliostat can be reduced. The presented method describes such an automatic calibration system using uncalibrated cameras rigidly attached to each heliostat. The cameras are used to observe targets spread out through the solar field; based on this the kinematic system of the heliostat can be estimated with high precision. A comparison of this approach to similar solutions shows the viability of the proposed solution.

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.

Genital automatisms: Reappraisal of a remarkable but ignored symptom of focal seizures.

PubMed

Dede, Hava Özlem; Bebek, Nerses; Gürses, Candan; Baysal-Kıraç, Leyla; Baykan, Betül; Gökyiğit, Ayşen

2018-03-01

Genital automatisms (GAs) are uncommon clinical phenomena of focal seizures. They are defined as repeated fondling, grabbing, or scratching of the genitals. The aim of this study was to determine the lateralizing and localizing value and associated clinical characteristics of GAs. Three hundred thirteen consecutive patients with drug-resistant seizures who were referred to our tertiary center for presurgical evaluation between 2009 and 2016 were investigated. The incidence of specific kinds of behavior, clinical semiology, associated symptoms/signs with corresponding ictal electroencephalography (EEG) findings, and their potential role in seizure localization and lateralization were evaluated. Fifteen (4.8%) of 313 patients had GAs. Genital automatisms were identified in 19 (16.4%) of a total 116 seizures. Genital automatisms were observed to occur more often in men than in women (M/F: 10/5). Nine of fifteen patients (60%) had temporal lobe epilepsy (right/left: 4/5) and three (20%) had frontal lobe epilepsy (right/left: 1/2), whereas the remaining two patients could not be classified. One patient was diagnosed as having Rasmussen encephalitis. Genital automatisms were ipsilateral to epileptic focus in 12 patients and contralateral in only one patient according to ictal-interictal EEG and neuroimaging findings. Epileptic focus could not be lateralized in the last 2 patients. Genital automatisms were associated with unilateral hand automatisms such as postictal nose wiping or manual automatisms in 13 (86.7%) of 15 and contralateral dystonia was seen in 6 patients. All patients had amnesia of the performance of GAs. Genital automatisms are more frequent in seizures originating from the temporal lobe, and they can also be seen in frontal lobe seizures. Genital automatisms seem to have a high lateralizing value to the ipsilateral hemisphere and are mostly concordant with other unilateral hand automatisms. Men exhibit GAs more often than women. Copyright © 2017 Elsevier Inc. All rights reserved.

10 CFR 835.502 - High and very high radiation areas.

Code of Federal Regulations, 2010 CFR

2010-01-01

... device that functions automatically to prevent use or operation of the radiation source or field while... gain unauthorized or inadvertent access to very high radiation areas. (d) No control(s) shall be...

10 CFR 835.502 - High and very high radiation areas.

Code of Federal Regulations, 2013 CFR

2013-01-01

... device that functions automatically to prevent use or operation of the radiation source or field while... gain unauthorized or inadvertent access to very high radiation areas. (d) No control(s) shall be...

10 CFR 835.502 - High and very high radiation areas.

Code of Federal Regulations, 2011 CFR

2011-01-01

... device that functions automatically to prevent use or operation of the radiation source or field while... gain unauthorized or inadvertent access to very high radiation areas. (d) No control(s) shall be...

10 CFR 835.502 - High and very high radiation areas.

Code of Federal Regulations, 2012 CFR

2012-01-01

... device that functions automatically to prevent use or operation of the radiation source or field while... gain unauthorized or inadvertent access to very high radiation areas. (d) No control(s) shall be...

10 CFR 835.502 - High and very high radiation areas.

Code of Federal Regulations, 2014 CFR

2014-01-01

... device that functions automatically to prevent use or operation of the radiation source or field while... gain unauthorized or inadvertent access to very high radiation areas. (d) No control(s) shall be...

Automatic Summarization of MEDLINE Citations for Evidence–Based Medical Treatment: A Topic-Oriented Evaluation

PubMed Central

Fiszman, Marcelo; Demner-Fushman, Dina; Kilicoglu, Halil; Rindflesch, Thomas C.

2009-01-01

As the number of electronic biomedical textual resources increases, it becomes harder for physicians to find useful answers at the point of care. Information retrieval applications provide access to databases; however, little research has been done on using automatic summarization to help navigate the documents returned by these systems. After presenting a semantic abstraction automatic summarization system for MEDLINE citations, we concentrate on evaluating its ability to identify useful drug interventions for fifty-three diseases. The evaluation methodology uses existing sources of evidence-based medicine as surrogates for a physician-annotated reference standard. Mean average precision (MAP) and a clinical usefulness score developed for this study were computed as performance metrics. The automatic summarization system significantly outperformed the baseline in both metrics. The MAP gain was 0.17 (p < 0.01) and the increase in the overall score of clinical usefulness was 0.39 (p < 0.05). PMID:19022398

A prototype system to support evidence-based practice.

PubMed

Demner-Fushman, Dina; Seckman, Charlotte; Fisher, Cheryl; Hauser, Susan E; Clayton, Jennifer; Thoma, George R

2008-11-06

Translating evidence into clinical practice is a complex process that depends on the availability of evidence, the environment into which the research evidence is translated, and the system that facilitates the translation. This paper presents InfoBot, a system designed for automatic delivery of patient-specific information from evidence-based resources. A prototype system has been implemented to support development of individualized patient care plans. The prototype explores possibilities to automatically extract patients problems from the interdisciplinary team notes and query evidence-based resources using the extracted terms. Using 4,335 de-identified interdisciplinary team notes for 525 patients, the system automatically extracted biomedical terminology from 4,219 notes and linked resources to 260 patient records. Sixty of those records (15 each for Pediatrics, Oncology & Hematology, Medical & Surgical, and Behavioral Health units) have been selected for an ongoing evaluation of the quality of automatically proactively delivered evidence and its usefulness in development of care plans.

Automatic Analysis of Critical Incident Reports: Requirements and Use Cases.

PubMed

Denecke, Kerstin

2016-01-01

Increasingly, critical incident reports are used as a means to increase patient safety and quality of care. The entire potential of these sources of experiential knowledge remains often unconsidered since retrieval and analysis is difficult and time-consuming, and the reporting systems often do not provide support for these tasks. The objective of this paper is to identify potential use cases for automatic methods that analyse critical incident reports. In more detail, we will describe how faceted search could offer an intuitive retrieval of critical incident reports and how text mining could support in analysing relations among events. To realise an automated analysis, natural language processing needs to be applied. Therefore, we analyse the language of critical incident reports and derive requirements towards automatic processing methods. We learned that there is a huge potential for an automatic analysis of incident reports, but there are still challenges to be solved.

A new method for automatic discontinuity traces sampling on rock mass 3D model

NASA Astrophysics Data System (ADS)

Umili, G.; Ferrero, A.; Einstein, H. H.

2013-02-01

A new automatic method for discontinuity traces mapping and sampling on a rock mass digital model is described in this work. The implemented procedure allows one to automatically identify discontinuity traces on a Digital Surface Model: traces are detected directly as surface breaklines, by means of maximum and minimum principal curvature values of the vertices that constitute the model surface. Color influence and user errors, that usually characterize the trace mapping on images, are eliminated. Also trace sampling procedures based on circular windows and circular scanlines have been implemented: they are used to infer trace data and to calculate values of mean trace length, expected discontinuity diameter and intensity of rock discontinuities. The method is tested on a case study: results obtained applying the automatic procedure on the DSM of a rock face are compared to those obtained performing a manual sampling on the orthophotograph of the same rock face.

A Prototype System to Support Evidence-based Practice

PubMed Central

Demner-Fushman, Dina; Seckman, Charlotte; Fisher, Cheryl; Hauser, Susan E.; Clayton, Jennifer; Thoma, George R.

2008-01-01

Translating evidence into clinical practice is a complex process that depends on the availability of evidence, the environment into which the research evidence is translated, and the system that facilitates the translation. This paper presents InfoBot, a system designed for automatic delivery of patient-specific information from evidence-based resources. A prototype system has been implemented to support development of individualized patient care plans. The prototype explores possibilities to automatically extract patients’ problems from the interdisciplinary team notes and query evidence-based resources using the extracted terms. Using 4,335 de-identified interdisciplinary team notes for 525 patients, the system automatically extracted biomedical terminology from 4,219 notes and linked resources to 260 patient records. Sixty of those records (15 each for Pediatrics, Oncology & Hematology, Medical & Surgical, and Behavioral Health units) have been selected for an ongoing evaluation of the quality of automatically proactively delivered evidence and its usefulness in development of care plans. PMID:18998835

Automatic Control of the Concrete Mixture Homogeneity in Cycling Mixers

NASA Astrophysics Data System (ADS)

Anatoly Fedorovich, Tikhonov; Drozdov, Anatoly

2018-03-01

The article describes the factors affecting the concrete mixture quality related to the moisture content of aggregates, since the effectiveness of the concrete mixture production is largely determined by the availability of quality management tools at all stages of the technological process. It is established that the unaccounted moisture of aggregates adversely affects the concrete mixture homogeneity and, accordingly, the strength of building structures. A new control method and the automatic control system of the concrete mixture homogeneity in the technological process of mixing components have been proposed, since the tasks of providing a concrete mixture are performed by the automatic control system of processing kneading-and-mixing machinery with operational automatic control of homogeneity. Theoretical underpinnings of the control of the mixture homogeneity are presented, which are related to a change in the frequency of vibrodynamic vibrations of the mixer body. The structure of the technical means of the automatic control system for regulating the supply of water is determined depending on the change in the concrete mixture homogeneity during the continuous mixing of components. The following technical means for establishing automatic control have been chosen: vibro-acoustic sensors, remote terminal units, electropneumatic control actuators, etc. To identify the quality indicator of automatic control, the system offers a structure flowchart with transfer functions that determine the ACS operation in transient dynamic mode.

Objective assessment of the aesthetic outcomes of breast cancer treatment: toward automatic localization of fiducial points on digital photographs

NASA Astrophysics Data System (ADS)

Udpa, Nitin; Sampat, Mehul P.; Kim, Min Soon; Reece, Gregory P.; Markey, Mia K.

2007-03-01

The contemporary goals of breast cancer treatment are not limited to cure but include maximizing quality of life. All breast cancer treatment can adversely affect breast appearance. Developing objective, quantifiable methods to assess breast appearance is important to understand the impact of deformity on patient quality of life, guide selection of current treatments, and make rational treatment advances. A few measures of aesthetic properties such as symmetry have been developed. They are computed from the distances between manually identified fiducial points on digital photographs. However, this is time-consuming and subject to intra- and inter-observer variability. The purpose of this study is to investigate methods for automatic localization of fiducial points on anterior-posterior digital photographs taken to document the outcomes of breast reconstruction. Particular emphasis is placed on automatic localization of the nipple complex since the most widely used aesthetic measure, the Breast Retraction Assessment, quantifies the symmetry of nipple locations. The nipple complexes are automatically localized using normalized cross-correlation with a template bank of variants of Gaussian and Laplacian of Gaussian filters. A probability map of likely nipple locations determined from the image database is used to reduce the number of false positive detections from the matched filter operation. The accuracy of the nipple detection was evaluated relative to markings made by three human observers. The impact of using the fiducial point locations as identified by the automatic method, as opposed to the manual method, on the calculation of the Breast Retraction Assessment was also evaluated.

Initial Experience With Ultra High-Density Mapping of Human Right Atria.

PubMed

Bollmann, Andreas; Hilbert, Sebastian; John, Silke; Kosiuk, Jedrzej; Hindricks, Gerhard

2016-02-01

Recently, an automatic, high-resolution mapping system has been presented to accurately and quickly identify right atrial geometry and activation patterns in animals, but human data are lacking. This study aims to assess the clinical feasibility and accuracy of high-density electroanatomical mapping of various RA arrhythmias. Electroanatomical maps of the RA (35 partial and 24 complete) were created in 23 patients using a novel mini-basket catheter with 64 electrodes and automatic electrogram annotation. Median acquisition time was 6:43 minutes (0:39-23:05 minutes) with shorter times for partial (4.03 ± 4.13 minutes) than for complete maps (9.41 ± 4.92 minutes). During mapping 3,236 (710-16,306) data points were automatically annotated without manual correction. Maps obtained during sinus rhythm created geometry consistent with CT imaging and demonstrated activation originating at the middle to superior crista terminalis, while maps during CS pacing showed right atrial activation beginning at the infero-septal region. Activation patterns were consistent with cavotricuspid isthmus-dependent atrial flutter (n = 4), complex reentry tachycardia (n = 1), or ectopic atrial tachycardia (n = 2). His bundle and fractionated potentials in the slow pathway region were automatically detected in all patients. Ablation of the cavotricuspid isthmus (n = 9), the atrio-ventricular node (n = 2), atrial ectopy (n = 2), and the slow pathway (n = 3) was successfully and safely performed. RA mapping with this automatic high-density mapping system is fast, feasible, and safe. It is possible to reproducibly identify propagation of atrial activation during sinus rhythm, various tachycardias, and also complex reentrant arrhythmias. © 2015 Wiley Periodicals, Inc.

Automatic Mosaicking of Satellite Imagery Considering the Clouds

NASA Astrophysics Data System (ADS)

Kang, Yifei; Pan, Li; Chen, Qi; Zhang, Tong; Zhang, Shasha; Liu, Zhang

2016-06-01

With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.

High-Speed Automatic Microscopy for Real Time Tracks Reconstruction in Nuclear Emulsion

NASA Astrophysics Data System (ADS)

D'Ambrosio, N.

2006-06-01

The Oscillation Project with Emulsion-tRacking Apparatus (OPERA) experiment will use a massive nuclear emulsion detector to search for /spl nu//sub /spl mu///spl rarr//spl nu//sub /spl tau// oscillation by identifying /spl tau/ leptons through the direct detection of their decay topology. The feasibility of experiments using a large mass emulsion detector is linked to the impressive progress under way in the development of automatic emulsion analysis. A new generation of scanning systems requires the development of fast automatic microscopes for emulsion scanning and image analysis to reconstruct tracks of elementary particles. The paper presents the European Scanning System (ESS) developed in the framework of OPERA collaboration.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

University of Glasgow at TREC 2008: Experiments in Blog, Enterprise, and Relevance Feedback Tracks with Terrier

DTIC Science & Technology

2008-11-01

improves our TREC 2007 dictionary -based approach by automatically building an internal opinion dictionary from the collection itself. We measure the opin...detecting opinionated documents. The first approach improves our TREC 2007 dictionary -based approach by automat- ically building an internal opinion... dictionary from the collection itself. The second approach is based on the OpinionFinder tool, which identifies subjective sentences in text. In particular

The role of the P3 and CNV components in voluntary and automatic temporal orienting: A high spatial-resolution ERP study.

PubMed

Mento, Giovanni

2017-12-01

A main distinction has been proposed between voluntary and automatic mechanisms underlying temporal orienting (TO) of selective attention. Voluntary TO implies the endogenous directing of attention induced by symbolic cues. Conversely, automatic TO is exogenously instantiated by the physical properties of stimuli. A well-known example of automatic TO is sequential effects (SEs), which refer to the adjustments in participants' behavioral performance as a function of the trial-by-trial sequential distribution of the foreperiod between two stimuli. In this study a group of healthy adults underwent a cued reaction time task purposely designed to assess both voluntary and automatic TO. During the task, both post-cue and post-target event-related potentials (ERPs) were recorded by means of a high spatial resolution EEG system. In the results of the post-cue analysis, the P3a and P3b were identified as two distinct ERP markers showing distinguishable spatiotemporal features and reflecting automatic and voluntary a priori expectancy generation, respectively. The brain source reconstruction further revealed that distinct cortical circuits supported these two temporally dissociable components. Namely, the voluntary P3b was supported by a left sensorimotor network, while the automatic P3a was generated by a more distributed frontoparietal circuit. Additionally, post-cue contingent negative variation (CNV) and post-target P3 modulations were observed as common markers of voluntary and automatic expectancy implementation and response selection, although partially dissociable neural networks subserved these two mechanisms. Overall, these results provide new electrophysiological evidence suggesting that distinct neural substrates can be recruited depending on the voluntary or automatic cognitive nature of the cognitive mechanisms subserving TO. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classification of independent components of EEG into multiple artifact classes.

PubMed

Frølich, Laura; Andersen, Tobias S; Mørup, Morten

2015-01-01

In this study, we aim to automatically identify multiple artifact types in EEG. We used multinomial regression to classify independent components of EEG data, selecting from 65 spatial, spectral, and temporal features of independent components using forward selection. The classifier identified neural and five nonneural types of components. Between subjects within studies, high classification performances were obtained. Between studies, however, classification was more difficult. For neural versus nonneural classifications, performance was on par with previous results obtained by others. We found that automatic separation of multiple artifact classes is possible with a small feature set. Our method can reduce manual workload and allow for the selective removal of artifact classes. Identifying artifacts during EEG recording may be used to instruct subjects to refrain from activity causing them. Copyright © 2014 Society for Psychophysiological Research.

Automatic cloud tracking applied to GOES and Meteosat observations

NASA Technical Reports Server (NTRS)

Endlich, R. M.; Wolf, D. E.

1981-01-01

An improved automatic processing method for the tracking of cloud motions as revealed by satellite imagery is presented and applications of the method to GOES observations of Hurricane Eloise and Meteosat water vapor and infrared data are presented. The method is shown to involve steps of picture smoothing, target selection and the calculation of cloud motion vectors by the matching of a group at a given time with its best likeness at a later time, or by a cross-correlation computation. Cloud motion computations can be made in as many as four separate layers simultaneously. For data of 4 and 8 km resolution in the eye of Hurricane Eloise, the automatic system is found to provide results comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System, with results obtained by the pattern recognition and cross correlation computations differing by only fractions of a pixel. For Meteosat water vapor data from the tropics and midlatitudes, the automatic motion computations are found to be reliable only in areas where the water vapor fields contained small-scale structure, although excellent results are obtained using Meteosat IR data in the same regions. The automatic method thus appears to be competitive in accuracy and coverage with motion determination by human analysts.

A Batch Feeder for Inhomogeneous Bulk Materials

NASA Astrophysics Data System (ADS)

Vislov, I. S.; Kladiev, S. N.; Slobodyan, S. M.; Bogdan, A. M.

2016-04-01

The work includes the mechanical analysis of mechanical feeders and batchers that find application in various technological processes and industrial fields. Feeders are usually classified according to their design features into two groups: conveyor-type feeders and non-conveyor feeders. Batchers are used to batch solid bulk materials. Less frequently, they are used for liquids. In terms of a batching method, they are divided into volumetric and weighting batchers. Weighting batchers do not provide for sufficient batching accuracy. Automatic weighting batchers include a mass controlling sensor and systems for automatic material feed and automatic mass discharge control. In terms of operating principle, batchers are divided into gravitational batchers and batchers with forced feed of material using conveyors and pumps. Improved consumption of raw materials, decreased loss of materials, ease of use in automatic control systems of industrial facilities allows increasing the quality of technological processes and improve labor conditions. The batch feeder suggested by the authors is a volumetric batcher that has no comparable counterparts among conveyor-type feeders and allows solving the problem of targeted feeding of bulk material batches increasing reliability and hermeticity of the device.

Automatic indexing in a drug information portal.

PubMed

Sakji, Saoussen; Letord, Catherine; Dahamna, Badisse; Kergourlay, Ivan; Pereira, Suzanne; Joubert, Michel; Darmoni, Stéfan

2009-01-01

The objective of this work is to create a bilingual (French/English) Drug Information Portal (DIP), in a multi-terminological context and to emphasize its exploitation by an ATC automatic indexing allowing having more pertinent information about substances, organs or systems on which drugs act and their therapeutic and chemical characteristics. The development of the DIP was based on the CISMeF portal, which catalogues and indexes the most important and quality-controlled sources of institutional health information in French. DIP has created specific functionalities and uses specific drugs terminologies such as the ATC classification which used to automatic index the DIP resources. DIP is the result of collaboration between the CISMeF team and the VIDAL Company, specialized in drug information. DIP is conceived to facilitate the user information retrieval. The ATC automatic indexing provided relevant results in 76% of cases. Using multi-terminological context and in the framework of the drug field, indexing drugs with the appropriate codes or/and terms revealed to be very important to have the appropriate information storage and retrieval. The main challenge in the coming year is to increase the accuracy of the approach.

Temperature controlled retinal photocoagulation

NASA Astrophysics Data System (ADS)

Schlott, Kerstin; Koinzer, Stefan; Baade, Alexander; Birngruber, Reginald; Roider, Johann; Brinkmann, Ralf

2013-06-01

Retinal photocoagulation lacks objective dosage in clinical use, thus the commonly applied lesions are too deep and strong, associated with pain reception and the risk of visual field defects and induction of choroidal neovascularisations. Optoacoustics allows real-time non-invasive temperature measurement in the fundus during photocoagulation by applying short probe laser pulses additionally to the treatment radiation, which excite the emission of ultrasonic waves. Due to the temperature dependence of the Grüneisen parameter, the amplitudes of the ultrasonic waves can be used to derive the temperature of the absorbing tissue. By measuring the temperatures in real-time and automatically controlling the irradiation by feedback to the treatment laser, the strength of the lesions can be defined. Different characteristic functions for the time and temperature dependent lesion sizes were used as rating curves for the treatment laser, stopping the irradiation automatically after a desired lesion size is achieved. The automatically produced lesion sizes are widely independent of the adjusted treatment laser power and individual absorption. This study was performed on anaesthetized rabbits and is a step towards a clinical trial with automatically controlled photocoagulation.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

Patterns of glaucomatous visual field loss in sita fields automatically identified using independent component analysis.

PubMed

Goldbaum, Michael H; Jang, Gil-Jin; Bowd, Chris; Hao, Jiucang; Zangwill, Linda M; Liebmann, Jeffrey; Girkin, Christopher; Jung, Tzyy-Ping; Weinreb, Robert N; Sample, Pamela A

2009-12-01

To determine if the patterns uncovered with variational Bayesian-independent component analysis-mixture model (VIM) applied to a large set of normal and glaucomatous fields obtained with the Swedish Interactive Thresholding Algorithm (SITA) are distinct, recognizable, and useful for modeling the severity of the field loss. SITA fields were obtained with the Humphrey Visual Field Analyzer (Carl Zeiss Meditec, Inc, Dublin, California) on 1,146 normal eyes and 939 glaucoma eyes from subjects followed by the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. VIM modifies independent component analysis (ICA) to develop separate sets of ICA axes in the cluster of normal fields and the 2 clusters of abnormal fields. Of 360 models, the model with the best separation of normal and glaucomatous fields was chosen for creating the maximally independent axes. Grayscale displays of fields generated by VIM on each axis were compared. SITA fields most closely associated with each axis and displayed in grayscale were evaluated for consistency of pattern at all severities. The best VIM model had 3 clusters. Cluster 1 (1,193) was mostly normal (1,089, 95% specificity) and had 2 axes. Cluster 2 (596) contained mildly abnormal fields (513) and 2 axes; cluster 3 (323) held mostly moderately to severely abnormal fields (322) and 5 axes. Sensitivity for clusters 2 and 3 combined was 88.9%. The VIM-generated field patterns differed from each other and resembled glaucomatous defects (eg, nasal step, arcuate, temporal wedge). SITA fields assigned to an axis resembled each other and the VIM-generated patterns for that axis. Pattern severity increased in the positive direction of each axis by expansion or deepening of the axis pattern. VIM worked well on SITA fields, separating them into distinctly different yet recognizable patterns of glaucomatous field defects. The axis and pattern properties make VIM a good candidate as a preliminary process for detecting progression.

MISR Toolkit

Atmospheric Science Data Center

2018-03-14

... which makes it very easy to extract and use MISR data sets. Reading a parameter requires the user to simply specify a file, grid, field, ... Automatically stitch, unpack and unscale MISR data while reading Performing coordinate conversions between lat/lon, SOM x/y, ...

Fail-safe fire detection system

NASA Technical Reports Server (NTRS)

Bloam, E. T.

1974-01-01

Fire detection control system continually monitors its own integrity, automatically signals any malfunction, and separately signals fire in any zone being monitored. Should be of interest in fields of chemical and petroleum processing, power generation, equipment testing, and building protection.

Origins of inert Higgs doublets

DOE PAGES

Kephart, Thomas W.; Yuan, Tzu -Chiang

2016-03-24

Here, we consider beyond the standard model embedding of inert Higgs doublet fields. We argue that inert Higgs doublets can arise naturally in grand unified theories where the necessary associated Z 2 symmetry can occur automatically. Several examples are discussed.

Faraday Rotation of Automatic Dependent Surveillance-Broadcast (ADS-B) Signals as a Method of Ionospheric Characterization

NASA Astrophysics Data System (ADS)

Cushley, A. C.; Kabin, K.; Noël, J.-M.

2017-10-01

Radio waves propagating through plasma in the Earth's ambient magnetic field experience Faraday rotation; the plane of the electric field of a linearly polarized wave changes as a function of the distance travelled through a plasma. Linearly polarized radio waves at 1090 MHz frequency are emitted by Automatic Dependent Surveillance Broadcast (ADS-B) devices that are installed on most commercial aircraft. These radio waves can be detected by satellites in low Earth orbits, and the change of the polarization angle caused by propagation through the terrestrial ionosphere can be measured. In this manuscript we discuss how these measurements can be used to characterize the ionospheric conditions. In the present study, we compute the amount of Faraday rotation from a prescribed total electron content value and two of the profile parameters of the NeQuick ionospheric model.

Automatic differentiation for Fourier series and the radii polynomial approach

NASA Astrophysics Data System (ADS)

Lessard, Jean-Philippe; Mireles James, J. D.; Ransford, Julian

2016-11-01

In this work we develop a computer-assisted technique for proving existence of periodic solutions of nonlinear differential equations with non-polynomial nonlinearities. We exploit ideas from the theory of automatic differentiation in order to formulate an augmented polynomial system. We compute a numerical Fourier expansion of the periodic orbit for the augmented system, and prove the existence of a true solution nearby using an a-posteriori validation scheme (the radii polynomial approach). The problems considered here are given in terms of locally analytic vector fields (i.e. the field is analytic in a neighborhood of the periodic orbit) hence the computer-assisted proofs are formulated in a Banach space of sequences satisfying a geometric decay condition. In order to illustrate the use and utility of these ideas we implement a number of computer-assisted existence proofs for periodic orbits of the Planar Circular Restricted Three-Body Problem (PCRTBP).

Beyond associations: Do implicit beliefs play a role in smoking addiction?

PubMed

Tibboel, Helen; De Houwer, Jan; Dirix, Nicolas; Spruyt, Adriaan

2017-01-01

Influential dual-system models of addiction suggest that an automatic system that is associative and habitual promotes drug use, whereas a controlled system that is propositional and rational inhibits drug use. It is assumed that effects on the Implicit Association Test (IAT) reflect the automatic processes that guide drug seeking. However, results have been inconsistent, challenging: (1) the validity of addiction IATs; and (2) the assumption that the automatic system contains only simple associative information. We aimed to further test the validity of IATs that are used within this field of research using an experimental design. Second, we introduced a new procedure aimed at examining the automatic activation of complex propositional knowledge, the Relational Responding Task (RRT) and examine the validity of RRT effects in the context of smoking. In two experiments, smokers performed two different tasks: an approach/avoid IAT and a liking IAT in Experiment 1, and a smoking urges RRT and a valence IAT in Experiment 2. Smokers were tested once immediately after smoking and once after 10 hours of nicotine-deprivation. None of the IAT scores were affected by the deprivation manipulation. RRT scores revealed a stronger implicit desire for smoking in the deprivation condition compared to the satiation condition. IATs that are currently used to assess automatic processes in addiction have serious drawbacks. Furthermore, the automatic system may contain not only associations but complex drug-related beliefs as well. The RRT may be a useful and valid tool to examine these beliefs.

Identification of malaria infected red blood samples by digital holographic quantitative phase microscope

NASA Astrophysics Data System (ADS)

Patel, Nimit R.; Chhaniwal, Vani K.; Javidi, Bahram; Anand, Arun

2015-07-01

Development of devices for automatic identification of diseases is desired especially in developing countries. In the case of malaria, even today the gold standard is the inspection of chemically treated blood smears through a microscope. This requires a trained technician/microscopist to identify the cells in the field of view, with which the labeling chemicals gets attached. Bright field microscopes provide only low contrast 2D images of red blood cells and cell thickness distribution cannot be obtained. Quantitative phase contrast microscopes can provide both intensity and phase profiles of the cells under study. The phase information can be used to determine thickness profile of the cell. Since cell morphology is available, many parameters pertaining to the 3D shape of the cell can be computed. These parameters in turn could be used to decide about the state of health of the cell leading to disease diagnosis. Here the investigations done on digital holographic microscope, which provides quantitative phase images, for comparison of parameters obtained from the 3D shape profile of objects leading to identification of diseased samples is described.

Language impairment is reflected in auditory evoked fields.

PubMed

Pihko, Elina; Kujala, Teija; Mickos, Annika; Alku, Paavo; Byring, Roger; Korkman, Marit

2008-05-01

Specific language impairment (SLI) is diagnosed when a child has problems in producing or understanding language despite having a normal IQ and there being no other obvious explanation. There can be several associated problems, and no single underlying cause has yet been identified. Some theories propose problems in auditory processing, specifically in the discrimination of sound frequency or rapid temporal frequency changes. We compared automatic cortical speech-sound processing and discrimination between a group of children with SLI and control children with normal language development (mean age: 6.6 years; range: 5-7 years). We measured auditory evoked magnetic fields using two sets of CV syllables, one with a changing consonant /da/ba/ga/ and another one with a changing vowel /su/so/sy/ in an oddball paradigm. The P1m responses for onsets of repetitive stimuli were weaker in the SLI group whereas no significant group differences were found in the mismatch responses. The results indicate that the SLI group, having weaker responses to the onsets of sounds, might have slightly depressed sensory encoding.

Drilling Automation Demonstrations in Subsurface Exploration for Astrobiology

NASA Technical Reports Server (NTRS)

Glass, Brian; Cannon, H.; Lee, P.; Hanagud, S.; Davis, K.

2006-01-01

This project proposes to study subsurface permafrost microbial habitats at a relevant Arctic Mars-analog site (Haughton Crater, Devon Island, Canada) while developing and maturing the subsurface drilling and drilling automation technologies that will be required by post-2010 missions. It builds on earlier drilling technology projects to add permafrost and ice-drilling capabilities to 5m with a lightweight drill that will be automatically monitored and controlled in-situ. Frozen cores obtained with this drill under sterilized protocols will be used in testing three hypotheses pertaining to near-surface physical geology and ground H2O ice distribution, viewed as a habitat for microbial life in subsurface ice and ice-consolidated sediments. Automation technologies employed will demonstrate hands-off diagnostics and drill control, using novel vibrational dynamical analysis methods and model-based reasoning to monitor and identify drilling fault states before and during faults. Three field deployments, to a Mars-analog site with frozen impact crater fallback breccia, will support science goals, provide a rigorous test of drilling automation and lightweight permafrost drilling, and leverage past experience with the field site s particular logistics.

SHARPs - A Near-Real-Time Space Weather Data Product from HMI

NASA Astrophysics Data System (ADS)

Bobra, M.; Turmon, M.; Baldner, C.; Sun, X.; Hoeksema, J. T.

2012-12-01

A data product from the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO), called Space-weather HMI Active Region Patches (SHARPs), is now available through the SDO Joint Science Operations Center (JSOC) and the Virtual Solar Observatory. SHARPs are magnetically active regions identified on the solar disk and tracked automatically in time. SHARP data are processed within a few hours of the observation time. The SHARP data series contains active region-sized disambiguated vector magnetic field data in both Lambert Cylindrical Equal-Area and CCD coordinates on a 12 minute cadence. The series also provides simultaneous HMI maps of the line-of-sight magnetic field, continuum intensity, and velocity on the same ~0.5 arc-second pixel grid. In addition, the SHARP data series provides space weather quantities computed on the inverted, disambiguated, and remapped data. The values for each tracked region are computed and updated in near real time. We present space weather results for several X-class flares; furthermore, we compare said space weather quantities with helioseismic quantities calculated using ring-diagram analysis.

Autonomously Generating Operations Sequences for a Mars Rover Using Artificial Intelligence-Based Planning

NASA Astrophysics Data System (ADS)

Sherwood, R.; Mutz, D.; Estlin, T.; Chien, S.; Backes, P.; Norris, J.; Tran, D.; Cooper, B.; Rabideau, G.; Mishkin, A.; Maxwell, S.

2001-07-01

This article discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This artificial intelligence (AI)-based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules. An automated planning and scheduling system encodes rover design knowledge and uses search and reasoning techniques to automatically generate low-level command sequences while respecting rover operability constraints, science and engineering preferences, environmental predictions, and also adhering to hard temporal constraints. This prototype planning system has been field-tested using the Rocky 7 rover at JPL and will be field-tested on more complex rovers to prove its effectiveness before transferring the technology to flight operations for an upcoming NASA mission. Enabling goal-driven commanding of planetary rovers greatly reduces the requirements for highly skilled rover engineering personnel. This in turn greatly reduces mission operations costs. In addition, goal-driven commanding permits a faster response to changes in rover state (e.g., faults) or science discoveries by removing the time-consuming manual sequence validation process, allowing rapid "what-if" analyses, and thus reducing overall cycle times.

Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

PubMed

Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

2014-01-01

The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Automatic optimization of well locations in a North Sea fractured chalk reservoir using a front tracking reservoir simulator

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

Rian, D.T.; Hage, A.

1994-12-31

A numerical simulator is often used as a reservoir management tool. One of its main purposes is to aid in the evaluation of number of wells, well locations and start time for wells. Traditionally, the optimization of a field development is done by a manual trial and error process. In this paper, an example of an automated technique is given. The core in the automization process is the reservoir simulator Frontline. Frontline is based on front tracking techniques, which makes it fast and accurate compared to traditional finite difference simulators. Due to its CPU-efficiency the simulator has been coupled withmore » an optimization module, which enables automatic optimization of location of wells, number of wells and start-up times. The simulator was used as an alternative method in the evaluation of waterflooding in a North Sea fractured chalk reservoir. Since Frontline, in principle, is 2D, Buckley-Leverett pseudo functions were used to represent the 3rd dimension. The area full field simulation model was run with up to 25 wells for 20 years in less than one minute of Vax 9000 CPU-time. The automatic Frontline evaluation indicated that a peripheral waterflood could double incremental recovery compared to a central pattern drive.« less

Identifying large scale structures at 1 AU using fluctuations and wavelets

NASA Astrophysics Data System (ADS)

Niembro, T.; Lara, A.

2016-12-01

The solar wind (SW) is inhomogeneous and it is dominated for two types of flows: one quasi-stationary and one related to large scale transients (such as coronal mass ejections and co-rotating interaction regions). The SW inhomogeneities can be study as fluctuations characterized by a wide range of length and time scales. We are interested in the study of the characteristic fluctuations caused by large scale transient events. To do so, we define the vector space F with the normalized moving monthly/annual deviations as the orthogonal basis. Then, we compute the norm in this space of the solar wind parameters (velocity, magnetic field, density and temperature) fluctuations using WIND data from August 1992 to August 2015. This norm gives important information about the presence of a large structure disturbance in the solar wind and by applying a wavelet transform to this norm, we are able to determine, without subjectivity, the duration of the compression regions of these large transient structures and, even more, to identify if the structure corresponds to a single or complex (or merged) event. With this method we have automatically detected most of the events identified and published by other authors.

Screening the working environment in outdoor pig systems.

PubMed

Geng, Q; Torén, A; Salomon, E

2009-07-01

This study investigated how well organic growing-fattening pig systems provided a safe and healthy working environment and identified areas where improvements are needed. The study formed part of a larger project aimed at identifying strategies for creating a good animal and working environment and resource-efficient nutrient management in outdoor pig systems. Field studies were carried out at six Swedish farms in two types of outdoor pig systems (mobile and stationary). A method known as WEST (Work Environment Screening Tool) and a modified version of WEST, called WEST-agriculture (WEST-AG), were utilized for screening. Together, the two methods covered six factors of the working environment. The results were expressed in WEST-AG points and WEST points, an economic measure of the risk of impacts on health and productivity expressed as Swedish Krona (SEK) per thousand working hours. The results demonstrated that the risk of injury and ergonomic load during manual feeding and watering was much higher than during semi-automatic feeding and watering at farms with the mobile system. The study also identified other health-risk areas and provided valuable information for further improvement of the working environment in different outdoor pig systems.

Does flexibility in perceptual organization compete with automatic grouping?

PubMed

van Assche, Mitsouko; Gos, Pierre; Giersch, Anne

2012-02-06

Segregated objects can be sought simultaneously, i.e., mentally "re-grouped." Although the mechanisms underlying such "re-grouping" clearly differ from automatic grouping, it is unclear whether or not the end products of "re-grouping" and automatic grouping are the same. If they are, they would have similar impact on visual organization but would be in conflict. We compared the consequences of grouping and re-grouping on the performance cost induced by stimuli presented across hemifields. Two identical and contiguous target figures had to be identified within a display of circles and squares alternating around a fixation point. Eye tracking was used to check central fixation. The target pair could be located in the same or separate hemifields. A large cost of presenting targets across hemifields was observed. Grouping by connectedness yielded two types of target pair, connected and unconnected. Subjects prioritized unconnected pairs efficiently when prompted to do so, suggesting "re-grouping." However, unlike automatic grouping, this did not affect the cost of across-hemifield presentation. The suggestion is that re-grouping yields different outputs to automatic grouping, such that a fresh representation resulting from re-grouping complements the one resulting from automatic grouping but does not replace it. This is one step toward understanding how our mental exploration of the world ties in and coexists with ongoing perception.

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.

Comparison of red-cockaded woodpecker (Picoides borealis) nestling diet in old-growth and old-field longleaf pine (Pinus palustris) habitats

Treesearch

James L. Hanula; R. Todd Engstrom

2000-01-01

Automatic cameras were used to record adult red-cockaded woodpecker (Picoides borealis) nest visits with food for nestlings. Diet of nestlings on or near an old-growth longleaf pine (Pinus palustris) remnant in southern Georgia was compared to that in longleaf pine stands established on old farm fields in western South Carolina....

40 CFR 60.541 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... operation means the operation identified as Michelin-A in the Emission Standards and Engineering Division... identified as Michelin-B in the Emission Standards and Engineering Division confidential file as referenced... Michelin-C-automatic in the Emission Standards and Engineering Division confidential file as referenced in...

40 CFR 60.541 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... operation means the operation identified as Michelin-A in the Emission Standards and Engineering Division... identified as Michelin-B in the Emission Standards and Engineering Division confidential file as referenced... Michelin-C-automatic in the Emission Standards and Engineering Division confidential file as referenced in...

40 CFR 60.541 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... operation means the operation identified as Michelin-A in the Emission Standards and Engineering Division... identified as Michelin-B in the Emission Standards and Engineering Division confidential file as referenced... Michelin-C-automatic in the Emission Standards and Engineering Division confidential file as referenced in...

40 CFR 60.541 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... operation means the operation identified as Michelin-A in the Emission Standards and Engineering Division... identified as Michelin-B in the Emission Standards and Engineering Division confidential file as referenced... Michelin-C-automatic in the Emission Standards and Engineering Division confidential file as referenced in...

Does semi-automatic bone-fragment segmentation improve the reproducibility of the Letournel acetabular fracture classification?

PubMed

Boudissa, M; Orfeuvre, B; Chabanas, M; Tonetti, J

2017-09-01

The Letournel classification of acetabular fracture shows poor reproducibility in inexperienced observers, despite the introduction of 3D imaging. We therefore developed a method of semi-automatic segmentation based on CT data. The present prospective study aimed to assess: (1) whether semi-automatic bone-fragment segmentation increased the rate of correct classification; (2) if so, in which fracture types; and (3) feasibility using the open-source itksnap 3.0 software package without incurring extra cost for users. Semi-automatic segmentation of acetabular fractures significantly increases the rate of correct classification by orthopedic surgery residents. Twelve orthopedic surgery residents classified 23 acetabular fractures. Six used conventional 3D reconstructions provided by the center's radiology department (conventional group) and 6 others used reconstructions obtained by semi-automatic segmentation using the open-source itksnap 3.0 software package (segmentation group). Bone fragments were identified by specific colors. Correct classification rates were compared between groups on Chi 2 test. Assessment was repeated 2 weeks later, to determine intra-observer reproducibility. Correct classification rates were significantly higher in the "segmentation" group: 114/138 (83%) versus 71/138 (52%); P<0.0001. The difference was greater for simple (36/36 (100%) versus 17/36 (47%); P<0.0001) than complex fractures (79/102 (77%) versus 54/102 (53%); P=0.0004). Mean segmentation time per fracture was 27±3min [range, 21-35min]. The segmentation group showed excellent intra-observer correlation coefficients, overall (ICC=0.88), and for simple (ICC=0.92) and complex fractures (ICC=0.84). Semi-automatic segmentation, identifying the various bone fragments, was effective in increasing the rate of correct acetabular fracture classification on the Letournel system by orthopedic surgery residents. It may be considered for routine use in education and training. III: prospective case-control study of a diagnostic procedure. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

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 from Varian Medical System.« less

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.

Identifying the arterial input function from dynamic contrast-enhanced magnetic resonance images using an apex-seeking technique

NASA Astrophysics Data System (ADS)

Martel, Anne L.

2004-04-01

In order to extract quantitative information from dynamic contrast-enhanced MR images (DCE-MRI) it is usually necessary to identify an arterial input function. This is not a trivial problem if there are no major vessels present in the field of view. Most existing techniques rely on operator intervention or use various curve parameters to identify suitable pixels but these are often specific to the anatomical region or the acquisition method used. They also require the signal from several pixels to be averaged in order to improve the signal to noise ratio, however this introduces errors due to partial volume effects. We have described previously how factor analysis can be used to automatically separate arterial and venous components from DCE-MRI studies of the brain but although that method works well for single slice images through the brain when the blood brain barrier technique is intact, it runs into problems for multi-slice images with more complex dynamics. This paper will describe a factor analysis method that is more robust in such situations and is relatively insensitive to the number of physiological components present in the data set. The technique is very similar to that used to identify spectral end-members from multispectral remote sensing images.

An improved approach for the segmentation of starch granules in microscopic images

PubMed Central

2010-01-01

Background Starches are the main storage polysaccharides in plants and are distributed widely throughout plants including seeds, roots, tubers, leaves, stems and so on. Currently, microscopic observation is one of the most important ways to investigate and analyze the structure of starches. The position, shape, and size of the starch granules are the main measurements for quantitative analysis. In order to obtain these measurements, segmentation of starch granules from the background is very important. However, automatic segmentation of starch granules is still a challenging task because of the limitation of imaging condition and the complex scenarios of overlapping granules. Results We propose a novel method to segment starch granules in microscopic images. In the proposed method, we first separate starch granules from background using automatic thresholding and then roughly segment the image using watershed algorithm. In order to reduce the oversegmentation in watershed algorithm, we use the roundness of each segment, and analyze the gradient vector field to find the critical points so as to identify oversegments. After oversegments are found, we extract the features, such as the position and intensity of the oversegments, and use fuzzy c-means clustering to merge the oversegments to the objects with similar features. Experimental results demonstrate that the proposed method can alleviate oversegmentation of watershed segmentation algorithm successfully. Conclusions We present a new scheme for starch granules segmentation. The proposed scheme aims to alleviate the oversegmentation in watershed algorithm. We use the shape information and critical points of gradient vector flow (GVF) of starch granules to identify oversegments, and use fuzzy c-mean clustering based on prior knowledge to merge these oversegments to the objects. Experimental results on twenty microscopic starch images demonstrate the effectiveness of the proposed scheme. PMID:21047380

[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.

Automatic detection and decoding of honey bee waggle dances.

PubMed

Wario, Fernando; Wild, Benjamin; Rojas, Raúl; Landgraf, Tim

2017-01-01

The waggle dance is one of the most popular examples of animal communication. Forager bees direct their nestmates to profitable resources via a complex motor display. Essentially, the dance encodes the polar coordinates to the resource in the field. Unemployed foragers follow the dancer's movements and then search for the advertised spots in the field. Throughout the last decades, biologists have employed different techniques to measure key characteristics of the waggle dance and decode the information it conveys. Early techniques involved the use of protractors and stopwatches to measure the dance orientation and duration directly from the observation hive. Recent approaches employ digital video recordings and manual measurements on screen. However, manual approaches are very time-consuming. Most studies, therefore, regard only small numbers of animals in short periods of time. We have developed a system capable of automatically detecting, decoding and mapping communication dances in real-time. In this paper, we describe our recording setup, the image processing steps performed for dance detection and decoding and an algorithm to map dances to the field. The proposed system performs with a detection accuracy of 90.07%. The decoded waggle orientation has an average error of -2.92° (± 7.37°), well within the range of human error. To evaluate and exemplify the system's performance, a group of bees was trained to an artificial feeder, and all dances in the colony were automatically detected, decoded and mapped. The system presented here is the first of this kind made publicly available, including source code and hardware specifications. We hope this will foster quantitative analyses of the honey bee waggle dance.

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

Reflected ray retrieval from radio occultation data using radio holographic filtering of wave fields in ray space

NASA Astrophysics Data System (ADS)

Gorbunov, Michael E.; Cardellach, Estel; Lauritsen, Kent B.

2018-03-01

Linear and non-linear representations of wave fields constitute the basis of modern algorithms for analysis of radio occultation (RO) data. Linear representations are implemented by Fourier Integral Operators, which allow for high-resolution retrieval of bending angles. Non-linear representations include Wigner Distribution Function (WDF), which equals the pseudo-density of energy in the ray space. Representations allow for filtering wave fields by suppressing some areas of the ray space and mapping the field back from the transformed space to the initial one. We apply this technique to the retrieval of reflected rays from RO observations. The use of reflected rays may increase the accuracy of the retrieval of the atmospheric refractivity. Reflected rays can be identified by the visual inspection of WDF or spectrogram plots. Numerous examples from COSMIC data indicate that reflections are mostly observed over oceans or snow, in particular over Antarctica. We introduce the reflection index that characterizes the relative intensity of the reflected ray with respect to the direct ray. The index allows for the automatic identification of events with reflections. We use the radio holographic estimate of the errors of the retrieved bending angle profiles of reflected rays. A comparison of indices evaluated for a large base of events including the visual identification of reflections indicated a good agreement with our definition of reflection index.

Automated detection of optical counterparts to GRBs with RAPTOR

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

Wozniak, P. R.; Vestrand, W. T.; Evans, S.

2006-05-19

The RAPTOR system (RAPid Telescopes for Optical Response) is an array of several distributed robotic telescopes that automatically respond to GCN localization alerts. Raptor-S is a 0.4-m telescope with 24 arc min. field of view employing a 1k x 1k Marconi CCD detector, and has already detected prompt optical emission from several GRBs within the first minute of the explosion. We present a real-time data analysis and alert system for automated identification of optical transients in Raptor-S GRB response data down to the sensitivity limit of {approx} 19 mag. Our custom data processing pipeline is designed to minimize the timemore » required to reliably identify transients and extract actionable information. The system utilizes a networked PostgreSQL database server for catalog access and distributes email alerts with successful detections.« less

Automatic 3d Building Model Generations with Airborne LiDAR Data

NASA Astrophysics Data System (ADS)

Yastikli, N.; Cetin, Z.

2017-11-01

LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D building models can be generated successfully using raw LiDAR point cloud data.

Semi-automatic tracking, smoothing and segmentation of hyoid bone motion from videofluoroscopic swallowing study.

PubMed

Kim, Won-Seok; Zeng, Pengcheng; Shi, Jian Qing; Lee, Youngjo; Paik, Nam-Jong

2017-01-01

Motion analysis of the hyoid bone via videofluoroscopic study has been used in clinical research, but the classical manual tracking method is generally labor intensive and time consuming. Although some automatic tracking methods have been developed, masked points could not be tracked and smoothing and segmentation, which are necessary for functional motion analysis prior to registration, were not provided by the previous software. We developed software to track the hyoid bone motion semi-automatically. It works even in the situation where the hyoid bone is masked by the mandible and has been validated in dysphagia patients with stroke. In addition, we added the function of semi-automatic smoothing and segmentation. A total of 30 patients' data were used to develop the software, and data collected from 17 patients were used for validation, of which the trajectories of 8 patients were partly masked. Pearson correlation coefficients between the manual and automatic tracking are high and statistically significant (0.942 to 0.991, P-value<0.0001). Relative errors between automatic tracking and manual tracking in terms of the x-axis, y-axis and 2D range of hyoid bone excursion range from 3.3% to 9.2%. We also developed an automatic method to segment each hyoid bone trajectory into four phases (elevation phase, anterior movement phase, descending phase and returning phase). The semi-automatic hyoid bone tracking from VFSS data by our software is valid compared to the conventional manual tracking method. In addition, the ability of automatic indication to switch the automatic mode to manual mode in extreme cases and calibration without attaching the radiopaque object is convenient and useful for users. Semi-automatic smoothing and segmentation provide further information for functional motion analysis which is beneficial to further statistical analysis such as functional classification and prognostication for dysphagia. Therefore, this software could provide the researchers in the field of dysphagia with a convenient, useful, and all-in-one platform for analyzing the hyoid bone motion. Further development of our method to track the other swallowing related structures or objects such as epiglottis and bolus and to carry out the 2D curve registration may be needed for a more comprehensive functional data analysis for dysphagia with big data.

Towards Automatic Treatment of Natural Language.

ERIC Educational Resources Information Center

Lonsdale, Deryle

1984-01-01

Because automated natural language processing relies heavily on the still developing fields of linguistics, knowledge representation, and computational linguistics, no system is capable of mimicking human linguistic capabilities. For the present, interactive systems may be used to augment today's technology. (MSE)

Image-Based High-Throughput Field Phenotyping of Crop Roots1[W][OPEN

PubMed Central

Bucksch, Alexander; Burridge, James; York, Larry M.; Das, Abhiram; Nord, Eric; Weitz, Joshua S.; Lynch, Jonathan P.

2014-01-01

Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions. PMID:25187526

Automatic Hidden-Web Table Interpretation by Sibling Page Comparison

NASA Astrophysics Data System (ADS)

Tao, Cui; Embley, David W.

The longstanding problem of automatic table interpretation still illudes us. Its solution would not only be an aid to table processing applications such as large volume table conversion, but would also be an aid in solving related problems such as information extraction and semi-structured data management. In this paper, we offer a conceptual modeling solution for the common special case in which so-called sibling pages are available. The sibling pages we consider are pages on the hidden web, commonly generated from underlying databases. We compare them to identify and connect nonvarying components (category labels) and varying components (data values). We tested our solution using more than 2,000 tables in source pages from three different domains—car advertisements, molecular biology, and geopolitical information. Experimental results show that the system can successfully identify sibling tables, generate structure patterns, interpret tables using the generated patterns, and automatically adjust the structure patterns, if necessary, as it processes a sequence of hidden-web pages. For these activities, the system was able to achieve an overall F-measure of 94.5%.

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

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...

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.

ALOHA: Automatic libraries of helicity amplitudes for Feynman diagram computations

NASA Astrophysics Data System (ADS)

de Aquino, Priscila; Link, William; Maltoni, Fabio; Mattelaer, Olivier; Stelzer, Tim

2012-10-01

We present an application that automatically writes the HELAS (HELicity Amplitude Subroutines) library corresponding to the Feynman rules of any quantum field theory Lagrangian. The code is written in Python and takes the Universal FeynRules Output (UFO) as an input. From this input it produces the complete set of routines, wave-functions and amplitudes, that are needed for the computation of Feynman diagrams at leading as well as at higher orders. The representation is language independent and currently it can output routines in Fortran, C++, and Python. A few sample applications implemented in the MADGRAPH 5 framework are presented. Program summary Program title: ALOHA Catalogue identifier: AEMS_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEMS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: http://www.opensource.org/licenses/UoI-NCSA.php No. of lines in distributed program, including test data, etc.: 6094320 No. of bytes in distributed program, including test data, etc.: 7479819 Distribution format: tar.gz Programming language: Python2.6 Computer: 32/64 bit Operating system: Linux/Mac/Windows RAM: 512 Mbytes Classification: 4.4, 11.6 Nature of problem: An effcient numerical evaluation of a squared matrix element can be done with the help of the helicity routines implemented in the HELAS library [1]. This static library contains a limited number of helicity functions and is therefore not always able to provide the needed routine in the presence of an arbitrary interaction. This program provides a way to automatically create the corresponding routines for any given model. Solution method: ALOHA takes the Feynman rules associated to the vertex obtained from the model information (in the UFO format [2]), and multiplies it by the different wavefunctions or propagators. As a result the analytical expression of the helicity routines is obtained. Subsequently, this expression is automatically written in the requested language (Python, Fortran or C++) Restrictions: The allowed fields are currently spin 0, 1/2, 1 and 2, and the propagators of these particles are canonical. Running time: A few seconds for the SM and the MSSM, and up to a few minutes for models with spin 2 particles. References: [1] Murayama, H. and Watanabe, I. and Hagiwara, K., HELAS: HELicity Amplitude Subroutines for Feynman diagram evaluations, KEK-91-11, (1992) http://www-lib.kek.jp/cgi-bin/img_index?199124011 [2] C. Degrande, C. Duhr, B. Fuks, D. Grellscheid, O. Mattelaer, et al., UFO— The Universal FeynRules Output, Comput. Phys. Commun. 183 (2012) 1201-1214. arXiv:1108.2040, doi:10.1016/j.cpc.2012.01.022.

Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud

NASA Astrophysics Data System (ADS)

Chen, Jianqin; Zhu, Hehua; Li, Xiaojun

2016-10-01

This paper presents a new method for extracting discontinuity orientation automatically from rock mass surface 3D point cloud. The proposed method consists of four steps: (1) automatic grouping of discontinuity sets using an improved K-means clustering method, (2) discontinuity segmentation and optimization, (3) discontinuity plane fitting using Random Sample Consensus (RANSAC) method, and (4) coordinate transformation of discontinuity plane. The method is first validated by the point cloud of a small piece of a rock slope acquired by photogrammetry. The extracted discontinuity orientations are compared with measured ones in the field. Then it is applied to a publicly available LiDAR data of a road cut rock slope at Rockbench repository. The extracted discontinuity orientations are compared with the method proposed by Riquelme et al. (2014). The results show that the presented method is reliable and of high accuracy, and can meet the engineering needs.

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

[Construction of automatic elucidation platform for mechanism of traditional Chinese medicine].

PubMed

Zhang, Bai-xia; Luo, Si-jun; Yan, Jing; Gu, Hao; Luo, Ji; Zhang, Yan-ling; Tao, Ou; Wang, Yun

2015-10-01

Aim at the two problems in the field of traditional Chinese medicine (TCM) mechanism elucidation, one is the lack of detailed biological processes information, next is the low efficient in constructing network models, we constructed an auxiliary elucidation system for the TCM mechanism and realize the automatic establishment of biological network model. This study used the Entity Grammar Systems (EGS) as the theoretical framework, integrated the data of formulae, herbs, chemical components, targets of component, biological reactions, signaling pathways and disease related proteins, established the formal models, wrote the reasoning engine, constructed the auxiliary elucidation system for the TCM mechanism elucidation. The platform provides an automatic modeling method for biological network model of TCM mechanism. It would be benefit to perform the in-depth research on TCM theory of natures and combination and provides the scientific references for R&D of TCM.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction.

PubMed

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatic process control in anaerobic digestion technology: A critical review.

PubMed

Nguyen, Duc; Gadhamshetty, Venkataramana; Nitayavardhana, Saoharit; Khanal, Samir Kumar

2015-10-01

Anaerobic digestion (AD) is a mature technology that relies upon a synergistic effort of a diverse group of microbial communities for metabolizing diverse organic substrates. However, AD is highly sensitive to process disturbances, and thus it is advantageous to use online monitoring and process control techniques to efficiently operate AD process. A range of electrochemical, chromatographic and spectroscopic devices can be deployed for on-line monitoring and control of the AD process. While complexity of the control strategy ranges from a feedback control to advanced control systems, there are some debates on implementation of advanced instrumentations or advanced control strategies. Centralized AD plants could be the answer for the applications of progressive automatic control field. This article provides a critical overview of the available automatic control technologies that can be implemented in AD processes at different scales. Copyright © 2015 Elsevier Ltd. All rights reserved.

Language and vertical space: on the automaticity of language action interconnections.

PubMed

Dudschig, Carolin; de la Vega, Irmgard; De Filippis, Monica; Kaup, Barbara

2014-09-01

Grounded models of language processing propose a strong connection between language and sensorimotor processes (Barsalou, 1999, 2008; Glenberg & Kaschak, 2002). However, it remains unclear how functional and automatic these connections are for understanding diverse sets of words (Ansorge, Kiefer, Khalid, Grassl, & König, 2010). Here, we investigate whether words referring to entities with a typical location in the upper or lower visual field (e.g., sun, ground) automatically influence subsequent motor responses even when language-processing levels are kept minimal. The results show that even subliminally presented words influence subsequent actions, as can be seen in a reversed compatibility effect. These finding have several implications for grounded language processing models. Specifically, these results suggest that language-action interconnections are not only the result of strategic language processes, but already play an important role during pre-attentional language processing stages. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sleep violence--forensic science implications: polygraphic and video documentation.

PubMed

Mahowald, M W; Bundlie, S R; Hurwitz, T D; Schenck, C H

1990-03-01

During the past century, infrequent, anecdotal reports of sleep-related violence with forensic science implications have appeared. Recent rapid developments in the field of sleep-disorders medicine have resulted in greater understanding of a variety of sleep-related behaviors, and formal sleep-behavior monitoring techniques have permitted their documentation and classification. Sleep-related violence can be associated with a number of diagnosable and treatable sleep disorders, including (1) night terrors/sleepwalking, (2) nocturnal seizures, (3) rapid eye movement (REM) sleep-behavior disorder, (4) sleep drunkenness, and (5) psychogenic dissociative states occurring during the sleep period. Potentially violent automatized behavior, without consciousness, can and does occur during sleep. The violence resulting from these disorders may be misinterpreted as purposeful suicide, assault, or even homicide. Sleep-related violence must be added to the list of automatisms. A classification system of both waking and sleep-related automatic behavior is proposed, with recommendations for assessment of such behavior.

Towards Automatic Processing of Virtual City Models for Simulations

NASA Astrophysics Data System (ADS)

Piepereit, R.; Schilling, A.; Alam, N.; Wewetzer, M.; Pries, M.; Coors, V.

2016-10-01

Especially in the field of numerical simulations, such as flow and acoustic simulations, the interest in using virtual 3D models to optimize urban systems is increasing. The few instances in which simulations were already carried out in practice have been associated with an extremely high manual and therefore uneconomical effort for the processing of models. Using different ways of capturing models in Geographic Information System (GIS) and Computer Aided Engineering (CAE), increases the already very high complexity of the processing. To obtain virtual 3D models suitable for simulation, we developed a tool for automatic processing with the goal to establish ties between the world of GIS and CAE. In this paper we introduce a way to use Coons surfaces for the automatic processing of building models in LoD2, and investigate ways to simplify LoD3 models in order to reduce unnecessary information for a numerical simulation.

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.

Automatización de la adquisición de campos planos de cielo durante el atardecer

NASA Astrophysics Data System (ADS)

Areal, M. B.; Acosta, J. A.; Buccino, A. P.; Perna, P.; Areso, O.; Mauas, P.

2016-08-01

Since 2009, the Instituto de Astronomia y Fisica del Espacio keeps in development an optical observatory mainly aimed to the detection of extrasolar planets and the monitoring of stellar activity. In this framework, the telescopes Meade LX200 16 Horacio Ghielmetti in the Complejo Astronomico El Leoncito, and MATE (Magnetic Activity and Transiting Exoplanets) in the Estación de Altura at the Observatorio Astronomico Felix Aguilar were assembled. Both telescopes can operate automatically through all night, which generates a massive volume of data. Because of this, it becomes essential the automatization of the acquisition and analysis of the regular observations as well as the calibration images; in particular the flat fields. In this work a method to simplify and automatize the acquisition of these images was developed. This method uses the luminosity values of the sky, registered by a weather station located next to the observation site.

2D automatic body-fitted structured mesh generation using advancing extraction method

NASA Astrophysics Data System (ADS)

Zhang, Yaoxin; Jia, Yafei

2018-01-01

This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like topography with extrusion-like structures (i.e., branches or tributaries) and intrusion-like structures (i.e., peninsula or dikes). With the AEM, the hierarchical levels of sub-domains can be identified, and the block boundary of each sub-domain in convex polygon shape in each level can be extracted in an advancing scheme. In this paper, several examples were used to illustrate the effectiveness and applicability of the proposed algorithm for automatic structured mesh generation, and the implementation of the method.

Computerized multiple image analysis on mammograms: performance improvement of nipple identification for registration of multiple views using texture convergence analyses

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Sahiner, Berkman; Hadjiiski, Lubomir M.; Paramagul, Chintana

2004-05-01

Automated registration of multiple mammograms for CAD depends on accurate nipple identification. We developed two new image analysis techniques based on geometric and texture convergence analyses to improve the performance of our previously developed nipple identification method. A gradient-based algorithm is used to automatically track the breast boundary. The nipple search region along the boundary is then defined by geometric convergence analysis of the breast shape. Three nipple candidates are identified by detecting the changes along the gray level profiles inside and outside the boundary and the changes in the boundary direction. A texture orientation-field analysis method is developed to estimate the fourth nipple candidate based on the convergence of the tissue texture pattern towards the nipple. The final nipple location is determined from the four nipple candidates by a confidence analysis. Our training and test data sets consisted of 419 and 368 randomly selected mammograms, respectively. The nipple location identified on each image by an experienced radiologist was used as the ground truth. For 118 of the training and 70 of the test images, the radiologist could not positively identify the nipple, but provided an estimate of its location. These were referred to as invisible nipple images. In the training data set, 89.37% (269/301) of the visible nipples and 81.36% (96/118) of the invisible nipples could be detected within 1 cm of the truth. In the test data set, 92.28% (275/298) of the visible nipples and 67.14% (47/70) of the invisible nipples were identified within 1 cm of the truth. In comparison, our previous nipple identification method without using the two convergence analysis techniques detected 82.39% (248/301), 77.12% (91/118), 89.93% (268/298) and 54.29% (38/70) of the nipples within 1 cm of the truth for the visible and invisible nipples in the training and test sets, respectively. The results indicate that the nipple on mammograms can be detected accurately. This will be an important step towards automatic multiple image analysis for CAD techniques.

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.

Learning from examples - Generation and evaluation of decision trees for software resource analysis

NASA Technical Reports Server (NTRS)

Selby, Richard W.; Porter, Adam A.

1988-01-01

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

Digital ocular fundus imaging: a review.

PubMed

Bernardes, Rui; Serranho, Pedro; Lobo, Conceição

2011-01-01

Ocular fundus imaging plays a key role in monitoring the health status of the human eye. Currently, a large number of imaging modalities allow the assessment and/or quantification of ocular changes from a healthy status. This review focuses on the main digital fundus imaging modality, color fundus photography, with a brief overview of complementary techniques, such as fluorescein angiography. While focusing on two-dimensional color fundus photography, the authors address the evolution from nondigital to digital imaging and its impact on diagnosis. They also compare several studies performed along the transitional path of this technology. Retinal image processing and analysis, automated disease detection and identification of the stage of diabetic retinopathy (DR) are addressed as well. The authors emphasize the problems of image segmentation, focusing on the major landmark structures of the ocular fundus: the vascular network, optic disk and the fovea. Several proposed approaches for the automatic detection of signs of disease onset and progression, such as microaneurysms, are surveyed. A thorough comparison is conducted among different studies with regard to the number of eyes/subjects, imaging modality, fundus camera used, field of view and image resolution to identify the large variation in characteristics from one study to another. Similarly, the main features of the proposed classifications and algorithms for the automatic detection of DR are compared, thereby addressing computer-aided diagnosis and computer-aided detection for use in screening programs. Copyright © 2011 S. Karger AG, Basel.

Application of ESPI techniques for the study of dynamic vibrations

NASA Astrophysics Data System (ADS)

Krupka, Rene

2004-06-01

Full field optical measurement techniques have already entered into various fields of industrial applications covering static as well as dynamic phenomena. The electronic speckle pattern interferometry (ESPI) allows the non contact, sensitive and three dimensional measurement of displacements in the sub micron range of objects with dimensions from mm2 to m2. For dynamic and transient phenomena, the use of pulsed laser have already been reported for various applications and successfully proven for the determination of the structural response of different components. In this paper we would like to present recent developments in the field of pulsed ESPI applications where emphasis is put onto the full field measurement result. The use of a completely computer controlled system allows easy access to mode shape characterization, deformation measurements and the characterization of transient events like shock wave propagation. Recent developments of the 3D-PulseESPI technique led to a very compact and complete system with improved characteristics regarding robustness and operation. The integrated design of the illumination laser and sensors for image acquisition allows easy aiming and adjustments with respect to the object of inspection. The laser is completely computer controlled which is advantageously used in a completely automatic brake squeal inspection system, which captures the squealing signal, automatically fires the laser and provides the complete deformation map of the component under test. Examples of recent applications in the field of dynamic structure response, with an emphasis in the field of automotive applications are given.

Scattering of classical and quantum particles by impulsive fields

NASA Astrophysics Data System (ADS)

Balasin, Herbert; Aichelburg, Peter C.

2018-05-01

We investigate the scattering of classical and quantum particles in impulsive backgrounds fields. These fields model short outbursts of radiation propagating with the speed of light. The singular nature of the problem will be accounted for by the use of Colombeau’s generalized function which however give rise to ambiguities. It is the aim of the paper to show that these ambiguities can be overcome by implementing additional physical conditions, which in the non-singular case would be satisfied automatically. As example we discuss the scattering of classical, Klein–Gordon and Dirac particles in impulsive electromagnetic fields.

Species distribution modeling based on the automated identification of citizen observations.

PubMed

Botella, Christophe; Joly, Alexis; Bonnet, Pierre; Monestiez, Pascal; Munoz, François

2018-02-01

A species distribution model computed with automatically identified plant observations was developed and evaluated to contribute to future ecological studies. We used deep learning techniques to automatically identify opportunistic plant observations made by citizens through a popular mobile application. We compared species distribution modeling of invasive alien plants based on these data to inventories made by experts. The trained models have a reasonable predictive effectiveness for some species, but they are biased by the massive presence of cultivated specimens. The method proposed here allows for fine-grained and regular monitoring of some species of interest based on opportunistic observations. More in-depth investigation of the typology of the observations and the sampling bias should help improve the approach in the future.

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 could be achieved from either accelerometer position. Conclusions Machine learning techniques can be used for automatic activity recognition, as they provide very accurate activity recognition, significantly more accurate than when keeping a diary. Identification of jogging periods in adolescents can be performed using only one accelerometer. Performance-wise there is no significant benefit from using accelerometers on both locations. PMID:28880923

In-Flight Field-of-View with ANVIS

DTIC Science & Technology

1992-12-01

AD-A259 905 USMRL Report No. 93-8 In-flight Field-of-View with ANVIS By John C. Kotulak D I FEO51993 Sensory Research Division ... ~ December 1992...Organizations receiving reports from the U.S. Army Aeromedical Research Laboratory on automatic mailing lists should confirm correct address when...corresponding about laboratory reports . Disposition Destroy this report when it is no longer needed. Do not return to the originator. Disclaimer The views

Automatic Digital Hardware Synthesis

DTIC Science & Technology

1990-09-01

VHDL to PALASM, a hardware synthesis language. The PALASM description is then directly implemented into a field programmable gate array (FPGAI using...process of translating VHDL to PALASM, a hardware synthesis language. The PALASM description is then directly implemented into a field programmable gate...allows the engineer to use VHDL to create and validate a design, and then to implement it in a gate array. The development of software o translate VHDL

Space Particle Hazard Specification, Forecasting, and Mitigation

DTIC Science & Technology

2007-11-30

Automated FTP scripts permitted users to automatically update their global input parameter data set directly from the National Oceanic and...of CEASE capabilities. The angular field-of-view for CEASE is relatively large and will not allow for pitch angle resolved measurements. However... angular zones spanning 120° in the plane containing the magnetic field with an approximate 4° width in the direction perpendicular to the look-plane

Controllers for Flow-Field Survey Apparatus

NASA Technical Reports Server (NTRS)

Ashby George C., JR.; Vaccarelli, M. D.

1986-01-01

Control systems of flow-field survey apparatuses of 22-inch (56centimeter) Hypersonic Helium Facility (two-dimensional) and 20-inch (51centimeter) Mach 6 Tunnel (three-dimensional) at Langley Research Center equipped with single-chip microcomputer and single-board microcomputer, respectively, to drive probes at selected speeds and perform other functions automatically. Various modes of operation programed as need arises. Both of these control systems fabricated relatively inexpensively from commercially available stock components.

Evaluation of an automatic-timed insecticide application system for backyard mosquito control.

PubMed

Cilek, J E; Hallmon, C F; Johnson, R

2008-12-01

Several manufacturers and pest management companies have begun to market and install outdoor automatically timed insecticide application systems that claim to provide an envelope of protection against host-seeking mosquitoes within a defined area, e.g., residential backyards. A typical system consists of a multi-gallon reservoir attached to a continuous loop of plastic tubing with multiple single spray head nozzles. Nozzles are usually placed along the perimeter of a backyard in landscaping or other areas suitable for mosquito harborage. This array is then connected to a programmable electric pump set to automatically apply an insecticide at predetermined intervals. An operational field study was conducted to evaluate this technology using previously installed MistAway systems at.3 residences in northwestern Florida. This system applied a mist-like application of 0.05% AI synergized pyrethrins for 45 sec at dawn and again at dusk in each backyard. Twice-weekly collections from ABC suction light traps, baited with carbon dioxide, were used as the evaluation tool. Female mosquitoes from treatment backyards were compared with trap collections from 3 backyards without automatic misting systems used as controls. We found that weekly mosquito reduction was highly variable and ranged from 98% to 14% during the 35-wk study. Because the primary method of reduction by these application systems was not well understood, a MistAway system was installed in an outdoor simulated residential backyard to determine exposure pathway under controlled conditions with field cage and excised-leaf bioassays. Using laboratory-reared females of Aedes albopictus and Culex quinquefasciatus in those assays, we found that reduction by the MistAway system was primarily achieved by direct exposure of the mosquitoes to the insecticide application and not from residual deposits on treated vegetation.

Development of Software for Automatic Analysis of Intervention in the Field of Homeopathy.

PubMed

Jain, Rajesh Kumar; Goyal, Shagun; Bhat, Sushma N; Rao, Srinath; Sakthidharan, Vivek; Kumar, Prasanna; Sajan, Kannanaikal Rappayi; Jindal, Sameer Kumar; Jindal, Ghanshyam D

2018-05-01

To study the effect of homeopathic medicines (in higher potencies) in normal subjects, Peripheral Pulse Analyzer (PPA) has been used to record physiologic variability parameters before and after administration of the medicine/placebo in 210 normal subjects. Data have been acquired in seven rounds; placebo was administered in rounds 1 and 2 and medicine in potencies 6, 30, 200, 1 M, and 10 M was administered in rounds 3 to 7, respectively. Five different medicines in the said potencies were given to a group of around 40 subjects each. Although processing of data required human intervention, a software application has been developed to analyze the processed data and detect the response to eliminate the undue delay as well as human bias in subjective analysis. This utility named Automatic Analysis of Intervention in the Field of Homeopathy is run on the processed PPA data and the outcome has been compared with the manual analysis. The application software uses adaptive threshold based on statistics for detecting responses in contrast to fixed threshold used in manual analysis. The automatic analysis has detected 12.96% higher responses than subjective analysis. Higher response rates have been manually verified to be true positive. This indicates robustness of the application software. The automatic analysis software was run on another set of pulse harmonic parameters derived from the same data set to study cardiovascular susceptibility and 385 responses were detected in contrast to 272 of variability parameters. It was observed that 65% of the subjects, eliciting response, were common. This not only validates the software utility for giving consistent yield but also reveals the certainty of the response. This development may lead to electronic proving of homeopathic medicines (e-proving).

Automatic control of positioning along the joint during EBW in conditions of action of magnetic fields

NASA Astrophysics Data System (ADS)

Druzhinina, A. A.; Laptenok, V. D.; Murygin, A. V.; Laptenok, P. V.

2016-11-01

Positioning along the joint during the electron beam welding is a difficult scientific and technical problem to achieve the high quality of welds. The final solution of this problem is not found. This is caused by weak interference protection of sensors of the joint position directly in the welding process. Frequently during the electron beam welding magnetic fields deflect the electron beam from the optical axis of the electron beam gun. The collimated X-ray sensor is used to monitor the beam deflection caused by the action of magnetic fields. Signal of X-ray sensor is processed by the method of synchronous detection. Analysis of spectral characteristics of the X-ray sensor showed that the displacement of the joint from the optical axis of the gun affects on the output signal of sensor. The authors propose dual-circuit system for automatic positioning of the electron beam on the joint during the electron beam welding in conditions of action of magnetic interference. This system includes a contour of joint tracking and contour of compensation of magnetic fields. The proposed system is stable. Calculation of dynamic error of system showed that error of positioning does not exceed permissible deviation of the electron beam from the joint plane.

Modis, SeaWIFS, and Pathfinder funded activities

NASA Technical Reports Server (NTRS)

Evans, Robert H.

1995-01-01

MODIS (Moderate Resolution Imaging Spectrometer), SeaWIFS (Sea-viewing Wide Field Sensor), Pathfinder, and DSP (Digital Signal Processor) objectives are summarized. An overview of current progress is given for the automatic processing database, client/server status, matchup database, and DSP support.

Classification of cloud fields based on textural characteristics

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1987-01-01

The present study reexamines the applicability of texture-based features for automatic cloud classification using very high spatial resolution (57 m) Landsat multispectral scanner digital data. It is concluded that cloud classification can be accomplished using only a single visible channel.

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.

Intended actions and unexpected outcomes: automatic and controlled processing in a rapid motor task

PubMed Central

Cheyne, Douglas O.; Ferrari, Paul; Cheyne, James A.

2012-01-01

Human action involves a combination of controlled and automatic behavior. These processes may interact in tasks requiring rapid response selection or inhibition, where temporal constraints preclude timely intervention by conscious, controlled processes over automatized prepotent responses. Such contexts tend to produce frequent errors, but also rapidly executed correct responses, both of which may sometimes be perceived as surprising, unintended, or “automatic”. In order to identify neural processes underlying these two aspects of cognitive control, we measured neuromagnetic brain activity in 12 right-handed subjects during manual responses to rapidly presented digits, with an infrequent target digit that required switching response hand (bimanual task) or response finger (unimanual task). Automaticity of responding was evidenced by response speeding (shorter response times) prior to both failed and fast correct switches. Consistent with this automaticity interpretation of fast correct switches, we observed bilateral motor preparation, as indexed by suppression of beta band (15–30 Hz) oscillations in motor cortex, prior to processing of the switch cue in the bimanual task. In contrast, right frontal theta activity (4–8 Hz) accompanying correct switch responses began after cue onset, suggesting that it reflected controlled inhibition of the default response. Further, this activity was reduced on fast correct switch trials suggesting a more automatic mode of inhibitory control. We also observed post-movement (event-related negativity) ERN-like responses and theta band increases in medial and anterior frontal regions that were significantly larger on error trials, and may reflect a combination of error and delayed inhibitory signals. We conclude that both automatic and controlled processes are engaged in parallel during rapid motor tasks, and that the relative strength and timing of these processes may underlie both optimal task performance and subjective experiences of automaticity or control. PMID:22912612

Automatic thermographic image defect detection of composites

NASA Astrophysics Data System (ADS)

Luo, Bin; Liebenberg, Bjorn; Raymont, Jeff; Santospirito, SP

2011-05-01

Detecting defects, and especially reliably measuring defect sizes, are critical objectives in automatic NDT defect detection applications. In this work, the Sentence software is proposed for the analysis of pulsed thermography and near IR images of composite materials. Furthermore, the Sentence software delivers an end-to-end, user friendly platform for engineers to perform complete manual inspections, as well as tools that allow senior engineers to develop inspection templates and profiles, reducing the requisite thermographic skill level of the operating engineer. Finally, the Sentence software can also offer complete independence of operator decisions by the fully automated "Beep on Defect" detection functionality. The end-to-end automatic inspection system includes sub-systems for defining a panel profile, generating an inspection plan, controlling a robot-arm and capturing thermographic images to detect defects. A statistical model has been built to analyze the entire image, evaluate grey-scale ranges, import sentencing criteria and automatically detect impact damage defects. A full width half maximum algorithm has been used to quantify the flaw sizes. The identified defects are imported into the sentencing engine which then sentences (automatically compares analysis results against acceptance criteria) the inspection by comparing the most significant defect or group of defects against the inspection standards.

IADE: a system for intelligent automatic design of bioisosteric analogs

NASA Astrophysics Data System (ADS)

Ertl, Peter; Lewis, Richard

2012-11-01

IADE, a software system supporting molecular modellers through the automatic design of non-classical bioisosteric analogs, scaffold hopping and fragment growing, is presented. The program combines sophisticated cheminformatics functionalities for constructing novel analogs and filtering them based on their drug-likeness and synthetic accessibility using automatic structure-based design capabilities: the best candidates are selected according to their similarity to the template ligand and to their interactions with the protein binding site. IADE works in an iterative manner, improving the fitness of designed molecules in every generation until structures with optimal properties are identified. The program frees molecular modellers from routine, repetitive tasks, allowing them to focus on analysis and evaluation of the automatically designed analogs, considerably enhancing their work efficiency as well as the area of chemical space that can be covered. The performance of IADE is illustrated through a case study of the design of a nonclassical bioisosteric analog of a farnesyltransferase inhibitor—an analog that has won a recent "Design a Molecule" competition.

Pre-Session Satiation as a Treatment for Stereotypy During Group Activities.

PubMed

Rispoli, Mandy; Camargo, Síglia Hoher; Neely, Leslie; Gerow, Stephanie; Lang, Russell; Goodwyn, Fara; Ninci, Jennifer

2014-05-01

Individuals with developmental disabilities may engage in automatically reinforced behaviors that may interfere with learning opportunities. Manipulation of motivating operations has been shown to reduce automatically maintained behavior in some individuals. Considering behavioral indicators of satiation may assist in identifying the point at which an abolishing operation has begun to effect behavior. The purpose of this study was to evaluate the effects of pre-session satiation of automatic reinforcement on subsequent levels of stereotypy and activity engagement during group activities for three males ages 5 to 13 years with developmental disabilities. Following functional analyses with analogue conditions, an alternating treatment design compared a pre-session access to stereotypy condition with a no-pre-session access condition prior to group activity sessions. Results indicated that pre-session satiation of the putative reinforcer produced by stereotypy was effective in decreasing stereotypy and increasing activity engagement during subsequent group activities for all participants. These findings add to the literature supporting the effectiveness of abolishing operations to decrease automatically maintained stereotypy. © The Author(s) 2013.

IADE: a system for intelligent automatic design of bioisosteric analogs.

PubMed

Ertl, Peter; Lewis, Richard

2012-11-01

IADE, a software system supporting molecular modellers through the automatic design of non-classical bioisosteric analogs, scaffold hopping and fragment growing, is presented. The program combines sophisticated cheminformatics functionalities for constructing novel analogs and filtering them based on their drug-likeness and synthetic accessibility using automatic structure-based design capabilities: the best candidates are selected according to their similarity to the template ligand and to their interactions with the protein binding site. IADE works in an iterative manner, improving the fitness of designed molecules in every generation until structures with optimal properties are identified. The program frees molecular modellers from routine, repetitive tasks, allowing them to focus on analysis and evaluation of the automatically designed analogs, considerably enhancing their work efficiency as well as the area of chemical space that can be covered. The performance of IADE is illustrated through a case study of the design of a nonclassical bioisosteric analog of a farnesyltransferase inhibitor--an analog that has won a recent "Design a Molecule" competition.

Examples of testing global identifiability of biological and biomedical models with the DAISY software.

PubMed

Saccomani, Maria Pia; Audoly, Stefania; Bellu, Giuseppina; D'Angiò, Leontina

2010-04-01

DAISY (Differential Algebra for Identifiability of SYstems) is a recently developed computer algebra software tool which can be used to automatically check global identifiability of (linear and) nonlinear dynamic models described by differential equations involving polynomial or rational functions. Global identifiability is a fundamental prerequisite for model identification which is important not only for biological or medical systems but also for many physical and engineering systems derived from first principles. Lack of identifiability implies that the parameter estimation techniques may not fail but any obtained numerical estimates will be meaningless. The software does not require understanding of the underlying mathematical principles and can be used by researchers in applied fields with a minimum of mathematical background. We illustrate the DAISY software by checking the a priori global identifiability of two benchmark nonlinear models taken from the literature. The analysis of these two examples includes comparison with other methods and demonstrates how identifiability analysis is simplified by this tool. Thus we illustrate the identifiability analysis of other two examples, by including discussion of some specific aspects related to the role of observability and knowledge of initial conditions in testing identifiability and to the computational complexity of the software. The main focus of this paper is not on the description of the mathematical background of the algorithm, which has been presented elsewhere, but on illustrating its use and on some of its more interesting features. DAISY is available on the web site http://www.dei.unipd.it/ approximately pia/. 2010 Elsevier Ltd. All rights reserved.

SigVox - A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo

2017-06-01

Urban road environments contain a variety of objects including different types of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point clouds. This work proposes a methodology for urban road object recognition from MLS point clouds. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point clouds. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically identifies different types of lamp poles and traffic signs. The workflow starts by tiling the raw point clouds along the scanning trajectory and by identifying non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically identified. The feasibility and quality of the proposed method is verified on two point clouds obtained in opposite direction of a stretch of road of 4 km. 6 types of lamp pole and 4 types of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate that the proposed method is able to recognize street furniture in a practical scenario. Remaining difficult cases are touching objects, like a lamp pole close to a tree.

Terminologies for text-mining; an experiment in the lipoprotein metabolism domain

PubMed Central

Alexopoulou, Dimitra; Wächter, Thomas; Pickersgill, Laura; Eyre, Cecilia; Schroeder, Michael

2008-01-01

Background The engineering of ontologies, especially with a view to a text-mining use, is still a new research field. There does not yet exist a well-defined theory and technology for ontology construction. Many of the ontology design steps remain manual and are based on personal experience and intuition. However, there exist a few efforts on automatic construction of ontologies in the form of extracted lists of terms and relations between them. Results We share experience acquired during the manual development of a lipoprotein metabolism ontology (LMO) to be used for text-mining. We compare the manually created ontology terms with the automatically derived terminology from four different automatic term recognition (ATR) methods. The top 50 predicted terms contain up to 89% relevant terms. For the top 1000 terms the best method still generates 51% relevant terms. In a corpus of 3066 documents 53% of LMO terms are contained and 38% can be generated with one of the methods. Conclusions Given high precision, automatic methods can help decrease development time and provide significant support for the identification of domain-specific vocabulary. The coverage of the domain vocabulary depends strongly on the underlying documents. Ontology development for text mining should be performed in a semi-automatic way; taking ATR results as input and following the guidelines we described. Availability The TFIDF term recognition is available as Web Service, described at PMID:18460175

A Unified Overset Grid Generation Graphical Interface and New Concepts on Automatic Gridding Around Surface Discontinuities

NASA Technical Reports Server (NTRS)

Chan, William M.; Akien, Edwin (Technical Monitor)

2002-01-01

For many years, generation of overset grids for complex configurations has required the use of a number of different independently developed software utilities. Results created by each step were then visualized using a separate visualization tool before moving on to the next. A new software tool called OVERGRID was developed which allows the user to perform all the grid generation steps and visualization under one environment. OVERGRID provides grid diagnostic functions such as surface tangent and normal checks as well as grid manipulation functions such as extraction, extrapolation, concatenation, redistribution, smoothing, and projection. Moreover, it also contains hyperbolic surface and volume grid generation modules that are specifically suited for overset grid generation. It is the first time that such a unified interface existed for the creation of overset grids for complex geometries. New concepts on automatic overset surface grid generation around surface discontinuities will also be briefly presented. Special control curves on the surface such as intersection curves, sharp edges, open boundaries, are called seam curves. The seam curves are first automatically extracted from a multiple panel network description of the surface. Points where three or more seam curves meet are automatically identified and are called seam corners. Seam corner surface grids are automatically generated using a singular axis topology. Hyperbolic surface grids are then grown from the seam curves that are automatically trimmed away from the seam corners.

Automatically-computed prehospital severity scores are equivalent to scores based on medic documentation.

PubMed

Reisner, Andrew T; Chen, Liangyou; McKenna, Thomas M; Reifman, Jaques

2008-10-01

Prehospital severity scores can be used in routine prehospital care, mass casualty care, and military triage. If computers could reliably calculate clinical scores, new clinical and research methodologies would be possible. One obstacle is that vital signs measured automatically can be unreliable. We hypothesized that Signal Quality Indices (SQI's), computer algorithms that differentiate between reliable and unreliable monitored physiologic data, could improve the predictive power of computer-calculated scores. In a retrospective analysis of trauma casualties transported by air ambulance, we computed the Triage Revised Trauma Score (RTS) from archived travel monitor data. We compared the areas-under-the-curve (AUC's) of receiver operating characteristic curves for prediction of mortality and red blood cell transfusion for 187 subjects with comparable quantities of good-quality and poor-quality data. Vital signs deemed reliable by SQI's led to significantly more discriminatory severity scores than vital signs deemed unreliable. We also compared automatically-computed RTS (using the SQI's) versus RTS computed from vital signs documented by medics. For the subjects in whom the SQI algorithms identified 15 consecutive seconds of reliable vital signs data (n = 350), the automatically-computed scores' AUC's were the same as the medic-based scores' AUC's. Using the Prehospital Index in place of RTS led to very similar results, corroborating our findings. SQI algorithms improve automatically-computed severity scores, and automatically-computed scores using SQI's are equivalent to medic-based scores.

Manual vs. automatic capture management in implantable cardioverter defibrillators and cardiac resynchronization therapy defibrillators.

PubMed

Murgatroyd, Francis D; Helmling, Erhard; Lemke, Bernd; Eber, Bernd; Mewis, Christian; van der Meer-Hensgens, Judith; Chang, Yanping; Khalameizer, Vladimir; Katz, Amos

2010-06-01

The Secura ICD and Consulta CRT-D are the first defibrillators to have automatic right atrial (RA), right ventricular (RV), and left ventricular (LV) capture management (CM). Complete CM was evaluated in an implantable cardioverter defibrillator (ICD) population. Two prospective clinical studies were conducted in 28 centres in Europe and Israel. Automatic CM data were compared with manual threshold measurements, the CM applicability was determined, and adjustments to pacing outputs were analysed. In total, 160 patients [age 64.6 +/- 10.4 years, 77% male, 80 ICD and 80 cardiac resynchronization therapy defibrillator (CRT-D)] were included. The differences between automatic and manual measurements were 2.5 V) due to raised RA threshold in seven (4.4%), high RV threshold in nine (5.6%), and high LV threshold in three patients (3.8%). All high threshold detections and all automatic modulations of pacing output were adjudicated appropriate. Complete CM adjusts pacing output appropriately, permitting a reduction in office visits while it may maximize device longevity. The study was registered at ClinicalTrials.gov identifiers: NCT00526227 and NCT00526162.

46 CFR 111.103-7 - Ventilation stop stations.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Case of Fire Break Glass and Operate Switch to Stop Ventilation;” (c) Have the “stop” position of the switch clearly identified; (d) Have a nameplate that identifies the system controlled; and (e) Be arranged so that damage to the switch or cable automatically stops the equipment controlled. ...

46 CFR 111.103-7 - Ventilation stop stations.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Case of Fire Break Glass and Operate Switch to Stop Ventilation;” (c) Have the “stop” position of the switch clearly identified; (d) Have a nameplate that identifies the system controlled; and (e) Be arranged so that damage to the switch or cable automatically stops the equipment controlled. ...

46 CFR 111.103-7 - Ventilation stop stations.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Case of Fire Break Glass and Operate Switch to Stop Ventilation;” (c) Have the “stop” position of the switch clearly identified; (d) Have a nameplate that identifies the system controlled; and (e) Be arranged so that damage to the switch or cable automatically stops the equipment controlled. ...

46 CFR 111.103-7 - Ventilation stop stations.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Case of Fire Break Glass and Operate Switch to Stop Ventilation;” (c) Have the “stop” position of the switch clearly identified; (d) Have a nameplate that identifies the system controlled; and (e) Be arranged so that damage to the switch or cable automatically stops the equipment controlled. ...

A software framework for pipelined arithmetic algorithms in field programmable gate arrays

NASA Astrophysics Data System (ADS)

Kim, J. B.; Won, E.

2018-03-01

Pipelined algorithms implemented in field programmable gate arrays are extensively used for hardware triggers in the modern experimental high energy physics field and the complexity of such algorithms increases rapidly. For development of such hardware triggers, algorithms are developed in C++, ported to hardware description language for synthesizing firmware, and then ported back to C++ for simulating the firmware response down to the single bit level. We present a C++ software framework which automatically simulates and generates hardware description language code for pipelined arithmetic algorithms.