E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Connecting Middle School, Oceanography, and the Real World.

ERIC Educational Resources Information Center

Brown, Susan W.; Hansen, Terri M.

2000-01-01

Introduces an activity that features 16 oceanography work stations and integrates other disciplines. Assigns students different oceanic life forms and requires students to work in stations. Explains seven of 16 stations which cover oil spills, the periodic table, ocean floor, currents, and classification of oceanic organisms. (YDS)

47 CFR 1.929 - Classification of filings as major or minor.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 1 2011-10-01 2011-10-01 false Classification of filings as major or minor. 1.929 Section 1.929 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE... Classification of filings as major or minor. Applications and amendments to applications for stations in the...

Evaluation of Barrier Cable Impact Pad Materials

DTIC Science & Technology

1988-03-01

INFORMATION CENTER CAMERON STATION ALEXANDRIA, VIRGINIA 22314 Unclassified SECURITY CLASSIFICATION OF THIS PAGE Form Approved REPORT DOCUMENTATION PAGE OMB...No. 0704-0188 _____________________________________________Exp. Date: Jun 30, 1986 la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS...Unclassified 2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/AVAILABILITY OF REPORT 2b. DECLASSIFICATION/DOWNGRADING SCHEDULE Approved for public

Validating the performance of vehicle classification stations : executive summary report.

DOT National Transportation Integrated Search

2012-05-01

Vehicle classification data are used in many transportation applications, including: pavement design, : environmental impact studies, traffic control, and traffic safety. Typical of most developed countries, every : state in the US maintains a networ...

Mining vehicle classifications from the Columbus Metropolitan Freeway Management System.

DOT National Transportation Integrated Search

2015-01-01

Vehicle classification data are used in many transportation applications, including: pavement design, : environmental impact studies, traffic control, and traffic safety. Ohio has over 200 permanent count stations, : supplemented by many more short-t...

Adaptive video-based vehicle classification technique for monitoring traffic : [executive summary].

DOT National Transportation Integrated Search

2015-08-01

Federal Highway Administration (FHWA) recommends axle-based classification standards to map : passenger vehicles, single unit trucks, and multi-unit trucks, at Automatic Traffic Recorder (ATR) stations : statewide. Many state Departments of Transport...

Determination of total Cr in wastewaters of Cr electroplating factories in the I.organize industry region (Kayseri, Turkey) by ICP-AES.

PubMed

Yilmaz, Selehattin; Türe, Melike; Sadikoglu, Murat; Duran, Ali

2010-08-01

The wastewater pollution in industrial areas is one of the most important environmental problems. Heavy metal pollution, especially chromium pollution in the wastewater sources from electroplating, dyeing, and tannery, has affected the life on earth. This pollution can affect on all ecosystems and human health directly or by food chain. Therefore, the determination of total chromium in this study is of great importance. In this study, accurate, rapid, sensitive, selective, simple, and low-cost technique for the direct determination of total Cr in wastewater samples collected from the some Cr electroplating factories in March 2008 by inductively coupled plasma-atomic emission spectrometry has been developed. The analysis of a given sample is completed in about 15 min by this technique applied. As the result of the chromium analysis, the limit of quantification for the total Cr were founded to be over the limit value (0.05 mg L(-1); WHO, EPA, TSE 266, and inland water quality classification) as 1,898.78+/-0.34 mg/L at station 1 and 3,189.02+/-0.56 mg/L at station 2. The found concentration of total Cr has been determined to be IV class quality water according to the inland water classification. In order to validate the applied method, recovery studies were performed.

Mining vehicle classifications from the Columbus Metropolitan Freeway Management System : [summary].

DOT National Transportation Integrated Search

2015-01-01

Vehicle classification data are used in many transportation applications, including: pavement design, : environmental impact studies, traffic control, and traffic safety. Ohio has over 200 permanent count : stations, supplemented by many more short-t...

Computed tomographic atlas for the new international lymph node map for lung cancer: A radiation oncologist perspective.

PubMed

Lynch, Rod; Pitson, Graham; Ball, David; Claude, Line; Sarrut, David

2013-01-01

To develop a reproducible definition for each mediastinal lymph node station based on the new TNM classification for lung cancer. This paper proposes an atlas using the new international lymph node map used in the seventh edition of the TNM classification for lung cancer. Four radiation oncologists and 1 diagnostic radiologist were involved in the project to put forward a reproducible radiologic description for the lung lymph node stations. The International Association for the Study of Lung Cancer lymph node definitions for stations 1 to 11 have been described and illustrated on axial computed tomographic scan images using a certified radiotherapy planning system. This atlas will assist both diagnostic radiologists and radiation oncologists in accurately defining the lymph node stations on computed tomographic scan in patients diagnosed with lung cancer. Copyright © 2013 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Predominant-period site classification for response spectra prediction equations in Italy

USGS Publications Warehouse

Di Alessandro, Carola; Bonilla, Luis Fabian; Boore, David M.; Rovelli, Antonio; Scotti, Oona

2012-01-01

We propose a site‐classification scheme based on the predominant period of the site, as determined from the average horizontal‐to‐vertical (H/V) spectral ratios of ground motion. Our scheme extends Zhao et al. (2006) classifications by adding two classes, the most important of which is defined by flat H/V ratios with amplitudes less than 2. The proposed classification is investigated by using 5%‐damped response spectra from Italian earthquake records. We select a dataset of 602 three‐component analog and digital recordings from 120 earthquakes recorded at 214 seismic stations within a hypocentral distance of 200 km. Selected events are in the moment‐magnitude range 4.0≤Mw≤6.8 and focal depths from a few kilometers to 46 km. We computed H/V ratios for these data and used them to classify each site into one of six classes. We then investigate the impact of this classification scheme on empirical ground‐motion prediction equations (GMPEs) by comparing its performance with that of the conventional rock/soil classification. Although the adopted approach results in only a small reduction of the overall standard deviation, the use of H/V spectral ratios in site classification does capture the signature of sites with flat frequency‐response, as well as deep and shallow‐soil profiles, characterized by long‐ and short‐period resonance, respectively; in addition, the classification scheme is relatively quick and inexpensive, which is an advantage over schemes based on measurements of shear‐wave velocity.

Optimized circulation and weather type classifications relating large-scale atmospheric conditions to local PM10 concentrations in Bavaria

NASA Astrophysics Data System (ADS)

Weitnauer, C.; Beck, C.; Jacobeit, J.

2013-12-01

In the last decades the critical increase of the emission of air pollutants like nitrogen dioxide, sulfur oxides and particulate matter especially in urban areas has become a problem for the environment as well as human health. Several studies confirm a risk of high concentration episodes of particulate matter with an aerodynamic diameter < 10 μm (PM10) for the respiratory tract or cardiovascular diseases. Furthermore it is known that local meteorological and large scale atmospheric conditions are important influencing factors on local PM10 concentrations. With climate changing rapidly, these connections need to be better understood in order to provide estimates of climate change related consequences for air quality management purposes. For quantifying the link between large-scale atmospheric conditions and local PM10 concentrations circulation- and weather type classifications are used in a number of studies by using different statistical approaches. Thus far only few systematic attempts have been made to modify consisting or to develop new weather- and circulation type classifications in order to improve their ability to resolve local PM10 concentrations. In this contribution existing weather- and circulation type classifications, performed on daily 2.5 x 2.5 gridded parameters of the NCEP/NCAR reanalysis data set, are optimized with regard to their discriminative power for local PM10 concentrations at 49 Bavarian measurement sites for the period 1980 to 2011. Most of the PM10 stations are situated in urban areas covering urban background, traffic and industry related pollution regimes. The range of regimes is extended by a few rural background stations. To characterize the correspondence between the PM10 measurements of the different stations by spatial patterns, a regionalization by an s-mode principal component analysis is realized on the high-pass filtered data. The optimization of the circulation- and weather types is implemented using two representative classification approaches, a k-means cluster analysis and an objective version of the Grosswetter types. They have been run with varying spatial and temporal settings as well as modified numbers of classes. As an evaluation metric for their performance several skill scores are used. Taking into account the outcome further attempts towards the optimization of circulation type classifications are made. These are varying meteorological input parameters (e.g. geopotential height, zonal and meridional wind, specific humidity, temperature) on several pressure levels (1000, 850 and 500 hPa) and combinations of these variables. All classification variants are again evaluated. Based on these analyses it is further intended to develop robust downscaling models for estimating possible future - climate change induced - variations of local PM10 concentrations in Bavaria from scenario runs of global CMIP5 climate models.

47 CFR 80.151 - Classification of operator licenses and endorsements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SPECIAL RADIO SERVICES STATIONS IN THE MARITIME SERVICES Operator Requirements § 80.151 Classification of... certificate). (5) MP. Marine Radio Operator Permit (radiotelephone operator's restricted certificate). (6) RP. Restricted Radiotelephone Operator Permit (radiotelephone operator's restricted certificate). (7) GOL. GMDSS...

47 CFR 80.151 - Classification of operator licenses and endorsements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... SPECIAL RADIO SERVICES STATIONS IN THE MARITIME SERVICES Operator Requirements § 80.151 Classification of.... Restricted Radiotelephone Operator Permit (radiotelephone operator's restricted certificate). (2) RL. Restricted Radiotelephone Operator Permit-Limited Use. (3) MP. Marine Radio Operator Permit (radiotelephone...

47 CFR 80.151 - Classification of operator licenses and endorsements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... SPECIAL RADIO SERVICES STATIONS IN THE MARITIME SERVICES Operator Requirements § 80.151 Classification of.... Restricted Radiotelephone Operator Permit (radiotelephone operator's restricted certificate). (2) RL. Restricted Radiotelephone Operator Permit-Limited Use. (3) MP. Marine Radio Operator Permit (radiotelephone...

47 CFR 80.151 - Classification of operator licenses and endorsements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... SPECIAL RADIO SERVICES STATIONS IN THE MARITIME SERVICES Operator Requirements § 80.151 Classification of.... Restricted Radiotelephone Operator Permit (radiotelephone operator's restricted certificate). (2) RL. Restricted Radiotelephone Operator Permit-Limited Use. (3) MP. Marine Radio Operator Permit (radiotelephone...

Indoor transformer stations and ELF magnetic field exposure: use of transformer structural characteristics to improve exposure assessment.

PubMed

Okokon, Enembe Oku; Roivainen, Päivi; Kheifets, Leeka; Mezei, Gabor; Juutilainen, Jukka

2014-01-01

Previous studies have shown that populations of multiapartment buildings with indoor transformer stations may serve as a basis for improved epidemiological studies on the relationship between childhood leukaemia and extremely-low-frequency (ELF) magnetic fields (MFs). This study investigated whether classification based on structural characteristics of the transformer stations would improve ELF MF exposure assessment. The data included MF measurements in apartments directly above transformer stations ("exposed" apartments) in 30 buildings in Finland, and reference apartments in the same buildings. Transformer structural characteristics (type and location of low-voltage conductors) were used to classify exposed apartments into high-exposure (HE) and intermediate-exposure (IE) categories. An exposure gradient was observed: both the time-average MF and time above a threshold (0.4 μT) were highest in the HE apartments and lowest in the reference apartments, showing a statistically significant trend. The differences between HE and IE apartments, however, were not statistically significant. A simulation exercise showed that the three-category classification did not perform better than a two-category classification (exposed and reference apartments) in detecting the existence of an increased risk. However, data on the structural characteristics of transformers is potentially useful for evaluating exposure-response relationship.

Development of a Lithospheric Model and Geophysical Data Base for North Africa.

DTIC Science & Technology

1996-07-19

Department of Energy Office of Non-Proliferation and National Security MONITORED BY Phillips Laboratory CONTRACT No. F 19628-C-0104 The views and...Worldwide Standardized Seismograph Netowrk stations locatdd:.&t regional distances from magnitude greater than 5.•0 earthquakes occurring within N6rth... SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACTOF REPORT OF THIS PAGE OF ABSTRACT

How can Smartphone-Based Internet Data Support Animal Ecology Fieldtrip?

NASA Astrophysics Data System (ADS)

Kurniawan, I. S.; Tapilow, F. S.; Hidayat, T.

2017-09-01

Identification and classification skills must be owned by the students. In animal ecology course, the identification and classification skills are necessary to study animals. This experimental study aims to describe the identification and classification skills of students on animal ecology field trip to studying various bird species using smartphone-based internet data. Using Involving 63 students divided into 7 groups for each observation station. Data of birds were sampled using line transect method (5000 meters/station). The results showed the identification and classification skills of students are in sufficient categories. Most students have difficulties because of the limitations of data on the internet about birds. In general, students support the use of smartphones in field trip activities. The results of this study can be used as a reference for the development of learning using smartphones in the future by developing application about birds. The outline, smartphones can be used as a method of alternative learning but needs to be developed for some special purposes.

A HIERARCHIAL STOCHASTIC MODEL OF LARGE SCALE ATMOSPHERIC CIRCULATION PATTERNS AND MULTIPLE STATION DAILY PRECIPITATION

EPA Science Inventory

A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. our algorithms are invested for classification of daily weather states; k means, fuzzy clustering, principal components, and principal components coupled with ...

77 FR 32111 - Privacy Act System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-31

... or fraud, or harm to the security or integrity of this system or other systems or programs (whether... to comment. FCC/MB-2 System Name: Broadcast Station Public Inspection Files. Security Classification: The FCC's Security Operations Center (SOC) has not assigned a security classification to this system...

IET. Coupling station (TAN620) and service room section and details. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

IET. Coupling station (TAN-620) and service room section and details. Interior electrical features inside coupling station. Cable terminal assembly for patch panel for plug. Ralph M. Parsons 902-4-ANP-620-E 401. Date: February 1954. Approved by INEEL Classification Office for public release. INEEL index code no. 035-0620-10-693-106958 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

47 CFR 1.929 - Classification of filings as major or minor.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Grants by Random Selection Wireless Radio Services Applications and Proceedings Application Requirements... applications for stations in the wireless radio services are classified as major or minor (see § 1.947... stations in all Wireless Radio Services, whether licensed geographically or on a site-specific basis, the...

47 CFR 1.929 - Classification of filings as major or minor.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Grants by Random Selection Wireless Radio Services Applications and Proceedings Application Requirements... applications for stations in the wireless radio services are classified as major or minor (see § 1.947... stations in all Wireless Radio Services, whether licensed geographically or on a site-specific basis, the...

47 CFR 1.929 - Classification of filings as major or minor.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Grants by Random Selection Wireless Radio Services Applications and Proceedings Application Requirements... applications for stations in the wireless radio services are classified as major or minor (see § 1.947... stations in all Wireless Radio Services, whether licensed geographically or on a site-specific basis, the...

Snowfall in the Northwest Iberian Peninsula: Synoptic Circulation Patterns and Their Influence on Snow Day Trends

PubMed Central

Merino, Andrés; Fernández, Sergio; Hermida, Lucía; López, Laura; Sánchez, José Luis; García-Ortega, Eduardo; Gascón, Estíbaliz

2014-01-01

In recent decades, a decrease in snowfall attributed to the effects of global warming (among other causes) has become evident. However, it is reasonable to investigate meteorological causes for such decrease, by analyzing changes in synoptic scale patterns. On the Iberian Peninsula, the Castilla y León region in the northwest consists of a central plateau surrounded by mountain ranges. This creates snowfalls that are considered both an important water resource and a transportation risk. In this work, we develop a classification of synoptic situations that produced important snowfalls at observation stations in the major cities of Castilla y León from 1960 to 2011. We used principal component analysis (PCA) and cluster techniques to define four synoptic patterns conducive to snowfall in the region. Once we confirmed homogeneity of the series and serial correlation of the snowfallday records at the stations from 1960 to 2011, we carried out a Mann-Kendall test. The results show a negative trend at most stations, so there are a decreased number of snowfall days. Finally, variations in these meteorological variables were related to changes in the frequencies of snow events belonging to each synoptic pattern favorable for snowfall production at the observatory locations. PMID:25152912

Vertically Integrated Seismological Analysis I : Modeling

NASA Astrophysics Data System (ADS)

Russell, S.; Arora, N. S.; Jordan, M. I.; Sudderth, E.

2009-12-01

As part of its CTBT verification efforts, the International Data Centre (IDC) analyzes seismic and other signals collected from hundreds of stations around the world. Current processing at the IDC proceeds in a series of pipelined stages. From station processing to network processing, each decision is made on the basis of local information. This has the advantage of efficiency, and simplifies the structure of software implementations. However, this approach may reduce accuracy in the detection and phase classification of arrivals, association of detections to hypothesized events, and localization of small-magnitude events.In our work, we approach such detection and association problems as ones of probabilistic inference. In simple terms, let X be a random variable ranging over all possible collections of events, with each event defined by time, location, magnitude, and type (natural or man-made). Let Y range over all possible waveform signal recordings at all detection stations. Then Pθ(X) describes a parameterized generative prior over events, and P[|#30#|]φ(Y | X) describes how the signal is propagated and measured (including travel time, selective absorption and scattering, noise, artifacts, sensor bias, sensor failures, etc.). Given observed recordings Y = y, we are interested in the posterior P(X | Y = y), and perhaps in the value of X that maximizes it—i.e., the most likely explanation for all the sensor readings. As detailed below, an additional focus of our work is to robustly learn appropriate model parameters θ and φ from historical data. The primary advantage we expect is that decisions about arrivals, phase classifications, and associations are made with the benefit of all available evidence, not just the local signal or predefined recipes. Important phenomena—such as the successful detection of sub-threshold signals, correction of phase classifications using arrival information at other stations, and removal of false events based on the absence of signals—should all fall out of our probabilistic framework without the need for special processing rules. In our baseline model, natural events occur according to a spatially inhomogeneous Poisson process. Complex events (swarms and aftershocks) may then be captured via temporally inhomogeneous extensions. Man-made events have a uniform probability of occurring anywhere on the earth, with a tendency to occur closer to the surface. Phases are modelled via their amplitude, frequency distribution, and origin. In the simplest case, transmission times are characterized via the one-dimensional IASPEI-91 model, accounting for model errors with Gaussian uncertainty. Such homogeneous, approximate physical models can be further refined via historical data and previously developed corrections. Signal measurements are captured by station-specific models, based on sensor types and geometries, local frequency absorption characteristics, and time-varying noise models. At the conference, we expect to be able to quantitatively demonstrate the advantages of our approach, at least for simulated data. When reporting their findings, such systems can easily flag low-confidence events, unexplained arrivals, and ambiguous classifications to focus the efforts of expert analysts.

Multistation alarm system for eruptive activity based on the automatic classification of volcanic tremor: specifications and performance

NASA Astrophysics Data System (ADS)

Langer, Horst; Falsaperla, Susanna; Messina, Alfio; Spampinato, Salvatore

2015-04-01

With over fifty eruptive episodes (Strombolian activity, lava fountains, and lava flows) between 2006 and 2013, Mt Etna, Italy, underscored its role as the most active volcano in Europe. Seven paroxysmal lava fountains at the South East Crater occurred in 2007-2008 and 46 at the New South East Crater between 2011 and 2013. Month-lasting lava emissions affected the upper eastern flank of the volcano in 2006 and 2008-2009. On this background, effective monitoring and forecast of volcanic phenomena are a first order issue for their potential socio-economic impact in a densely populated region like the town of Catania and its surroundings. For example, explosive activity has often formed thick ash clouds with widespread tephra fall able to disrupt the air traffic, as well as to cause severe problems at infrastructures, such as highways and roads. For timely information on changes in the state of the volcano and possible onset of dangerous eruptive phenomena, the analysis of the continuous background seismic signal, the so-called volcanic tremor, turned out of paramount importance. Changes in the state of the volcano as well as in its eruptive style are usually concurrent with variations of the spectral characteristics (amplitude and frequency content) of tremor. The huge amount of digital data continuously acquired by INGV's broadband seismic stations every day makes a manual analysis difficult, and techniques of automatic classification of the tremor signal are therefore applied. The application of unsupervised classification techniques to the tremor data revealed significant changes well before the onset of the eruptive episodes. This evidence led to the development of specific software packages related to real-time processing of the tremor data. The operational characteristics of these tools - fail-safe, robustness with respect to noise and data outages, as well as computational efficiency - allowed the identification of criteria for automatic alarm flagging. The system is hitherto one of the main automatic alerting tools to identify impending eruptive events at Etna. The currently operating software named KKAnalysis is applied to the data stream continuously recorded at two seismic stations. The data are merged with reference datasets of past eruptive episodes. In doing so, the results of pattern classification can be immediately compared to previous eruptive scenarios. Given the rich material collected in recent years, here we propose the application of the alert system to a wider range (up to a total of eleven) stations at different elevations (1200-3050 m) and distances (1-8 km) from the summit craters. Critical alert parameters were empirically defined to obtain an optimal tuning of the alert system for each station. To verify the robustness of this new, multistation alert system, a dataset encompassing about eight years of continuous seismic records (since 2006) was processed automatically using KKAnalysis and collateral software offline. Then, we analyzed the performance of the classifier in terms of timing and spatial distribution of the stations.

A Design Study for Quick Strike Reconnaissance/Reconnaissance Reporting Facility

DTIC Science & Technology

1976-06-01

Engineer: Ronald B. Haynes (IRRO) Copies available in DDC . ’*■ KEY WORDS (Conllnut on ranfM »id* (/ n*c»«ary and Idmnllly by block number... CLASSIFICATION OF THIS PAGE (("),.„ D.I, Bm.rvd) 40 60% mmmmm tu ’~mmmmmmmm~~-’ rfÜk UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGEfWun...include the following: Systems time and date Operators name Project/mission identification Classification Organisation. (3) Station Release

Classification of rainfall events for weather forecasting purposes in andean region of Colombia

NASA Astrophysics Data System (ADS)

Suárez Hincapié, Joan Nathalie; Romo Melo, Liliana; Vélez Upegui, Jorge Julian; Chang, Philippe

2016-04-01

This work presents a comparative analysis of the results of applying different methodologies for the identification and classification of rainfall events of different duration in meteorological records of the Colombian Andean region. In this study the work area is the urban and rural area of Manizales that counts with a monitoring hydro-meteorological network. This network is composed of forty-five (45) strategically located stations, this network is composed of forty-five (45) strategically located stations where automatic weather stations record seven climate variables: air temperature, relative humidity, wind speed and direction, rainfall, solar radiation and barometric pressure. All this information is sent wirelessly every five (5) minutes to a data warehouse located at the Institute of Environmental Studies-IDEA. With obtaining the series of rainfall recorded by the hydrometeorological station Palogrande operated by the National University of Colombia in Manizales (http://froac.manizales.unal.edu.co/bodegaIdea/); it is with this information that we proceed to perform behavior analysis of other meteorological variables, monitored at surface level and that influence the occurrence of such rainfall events. To classify rainfall events different methodologies were used: The first according to Monjo (2009) where the index n of the heavy rainfall was calculated through which various types of precipitation are defined according to the intensity variability. A second methodology that permitted to produce a classification in terms of a parameter β introduced by Rice and Holmberg (1973) and adapted by Llasat and Puigcerver, (1985, 1997) and the last one where a rainfall classification is performed according to the value of its intensity following the issues raised by Linsley (1977) where the rains can be considered light, moderate and strong fall rates to 2.5 mm / h; from 2.5 to 7.6 mm / h and above this value respectively for the previous classifications. The main contribution which is done with this research is the obtainment elements to optimize and to improve the spatial resolution of the results obtained with mesoscale models such as the Weather Research & Forecasting Model- WRF, used in Colombia for the purposes of weather forecasting and that in addition produces other tools used in current issues such as risk management.

An analysis of the synoptic and climatological applicability of circulation type classifications for Ireland

NASA Astrophysics Data System (ADS)

Broderick, Ciaran; Fealy, Rowan

2013-04-01

Circulation type classifications (CTCs) compiled as part of the COST733 Action, entitled 'Harmonisation and Application of Weather Type Classifications for European Regions', are examined for their synoptic and climatological applicability to Ireland based on their ability to characterise surface temperature and precipitation. In all 16 different objective classification schemes, representative of four different methodological approaches to circulation typing (optimization algorithms, threshold based methods, eigenvector techniques and leader algorithms) are considered. Several statistical metrics which variously quantify the ability of CTCs to discretize daily data into well-defined homogeneous groups are used to evaluate and compare different approaches to synoptic typing. The records from 14 meteorological stations located across the island of Ireland are used in the study. The results indicate that while it was not possible to identify a single optimum classification or approach to circulation typing - conditional on the location and surface variables considered - a number of general assertions regarding the performance of different schemes can be made. The findings for surface temperature indicate that that those classifications based on predefined thresholds (e.g. Litynski, GrossWetterTypes and original Lamb Weather Type) perform well, as do the Kruizinga and Lund classification schemes. Similarly for precipitation predefined type classifications return high skill scores, as do those classifications derived using some optimization procedure (e.g. SANDRA, Self Organizing Maps and K-Means clustering). For both temperature and precipitation the results generally indicate that the classifications perform best for the winter season - reflecting the closer coupling between large-scale circulation and surface conditions during this period. In contrast to the findings for temperature, spatial patterns in the performance of classifications were more evident for precipitation. In the case of this variable those more westerly synoptic stations open to zonal airflow and less influenced by regional scale forcings generally exhibited a stronger link with large-scale circulation.

Operation Tomodachi Registry: Radiation Data Compendium

DTIC Science & Technology

2013-08-01

affiliated individuals were potentially exposed to radiation as a result of the Fukushima Daiichi Nuclear Power Station radiological releases that followed...Radiation Dose, Department of Defense, Japan, Fukushima , Earthquake, Tsunami, Environmental Data, Radiation Data 16. SECURITY CLASSIFICATION OF: 17...materials from the Fukushima Daiichi Nuclear Power Station (FDNPS), the Department of Defense (DOD) responded by providing humanitarian assistance

Site Amplification Characteristics of the Several Seismic Stations at Jeju Island, in Korea, using S-wave Energy, Background Noise, and Coda waves from the East Japan earthquake (Mar. 11th, 2011) Series.

NASA Astrophysics Data System (ADS)

Seong-hwa, Y.; Wee, S.; Kim, J.

2016-12-01

Observed ground motions are composed of 3 main factors such as seismic source, seismic wave attenuation and site amplification. Among them, site amplification is also important factor and should be considered to estimate soil-structure dynamic interaction with more reliability. Though various estimation methods are suggested, this study used the method by Castro et. al.(1997) for estimating site amplification. This method has been extended to background noise, coda waves and S waves recently for estimating site amplification. This study applied the Castro et. al.(1997)'s method to 3 different seismic waves, that is, S-wave Energy, Background Noise, and Coda waves. This study analysed much more than about 200 ground motions (acceleration type) from the East Japan earthquake (March 11th, 2011) Series of seismic stations at Jeju Island (JJU, SGP, HALB, SSP and GOS; Fig. 1), in Korea. The results showed that most of the seismic stations gave similar results among three types of seismic energies. Each station showed its own characteristics of site amplification property in low, high and specific resonance frequency ranges. Comparison of this study to other studies can give us much information about dynamic amplification of domestic sites characteristics and site classification.

The ecological status of Karavasta Lagoon (Albania): Closing the stable door before the horse has bolted?

PubMed

Munari, Cristina; Tessari, Umberto; Rossi, Remigio; Mistri, Michele

2010-02-01

Karavasta is the widest and most important lagoon in Albania. This study aimed to assess the ecological quality status of the lagoon, acquire knowledge of a natural environment which might be exploited for aquaculture, and give management hints on the basis of anthropogenic impact and ecological conditions. A sampling campaign was carried out in 2008: at six stations, benthic fauna, water, and sediment parameters were considered. Statistical analyses were carried out through multivariate procedures (PCA, classification-clustering, SIMPER, RDA, DISTLM, PERMANOVA). Ecological quality was assessed through the AZTI Marine Biotic Index (AMBI), the multivariate AMBI (M-AMBI) and the Benthic Index based on Taxonomic Sufficiency (BITS). Sediment characteristics (percent organic matter, %OM; redox potential discontinuity layer depth, RPDL; particle size composition) and salinity represented contributory influences on lagoon communities. It was possible to distinguish and characterise a confined area, and benthic communities, from a marine-influenced area and its biota. The number of species was quite low when compared with other open Adriatic lagoons. The M-AMBI and BITS classifications gave quite similar results, which seemed consistent with the ecological conditions of the lagoon, that is a distinction in the ecological quality between the seaward and landward stations, with higher ecological quality (EcoQ) at the seaward stations. Given the pressures and the ecological condition of Karavasta, an intensification of aquaculture activities must be considered with caution, since the lagoon seems at significant risk of serious hypereutrophication. This situation is made worse by the limited water exchange with the marine environment due to the irregular dredging of the communication channels. 2009 Elsevier Ltd. All rights reserved.

Water quality, sediment quality, and stream-channel classification of Rock Creek, Washington, D.C., 1999-2000

USGS Publications Warehouse

Anderson, Anita L.; Miller, Cherie V.; Olsen, Lisa D.; Doheny, Edward J.; Phelan, Daniel J.

2002-01-01

Rock Creek Park is within the National Capital Region in Washington, D.C., and is maintained by the National Park Service. Part of Montgomery County, Maryland, and part of the District of Columbia drain into Rock Creek, which is a tributary of the Potomac River. Water quality in Rock Creek is important to biotic life in and near the creek, and in the Potomac River Basin and the Chesapeake Bay. The water quality of the Rock Creek Basin has been affected by continued urban and agricultural growth and development. The U.S. Geological Survey, in cooperation with the National Park Service, investigated water quality and sediment quality in Rock Creek over a 2-year period (1998?2000), and performed a stream-channel classification to determine the distribution of bottom sediment in Rock Creek. This report presents and evaluates water quality and bottom sediment in Rock Creek for water years 1999 (October 1, 1998 to September 30, 1999) and 2000 (October 1, 1999 to September 30, 2000). A synoptic surface-water assessment was conducted at five stations from June 23 to June 25, 1999, a temporal surface-water assessment was conducted at one station from February 18, 1999 to September 26, 2000, and bed-sediment samples were collected and assessed from three stations from August 17 to August 19, 1999. The synoptic surface-water assessment included pesticides (parent compounds and selected transformation products), field parameters, nutrients, and major ions. The temporal surface-water assessment included pesticides (parent compounds and selected transformation products) and field parameters. The bed-sediment assessment included trace elements and organic compounds (including low- and high-molecular weight polycyclic aromatic hydrocarbons, poly-chlorinated biphenyls, pesticides, and phthalates). Some, but not all, of the pesticides known to be used in the area were included in the synoptic water-quality assessment, the temporal water-quality assessment, and the bed-sediment assessment. In addition to the water-quality and sediment-quality assessments, a Rosgen stream-channel classification was performed on a 900-foot-long segment of Rock Creek. In the synoptic water-quality assessment, two pesticides were found to be above published criteria for the protection of aquatic life. In the temporal water-quality assessment, four pesticides were found to be above published criteria for the protection of aquatic life. In the bed-sediment assessment, 8 trace elements, 14 polycyclic aromatic hydrocarbons, 6 pesticides, and 1 phthalate compound were found to be above published criteria for the protection of aquatic life. In the Rosgen classification, a comparison to a previous classification for this segment showed an increase in sands and other fine-grained sediments in the creek bed.

Rapid classification of landsat TM imagery for phase 1 stratification using the automated NDVI threshold supervised classification (ANTSC) methodology

Treesearch

William H. Cooke; Dennis M. Jacobs

2002-01-01

FIA annual inventories require rapid updating of pixel-based Phase 1 estimates. Scientists at the Southern Research Station are developing an automated methodology that uses a Normalized Difference Vegetation Index (NDVI) for identifying and eliminating problem FIA plots from the analysis. Problem plots are those that have questionable land useiland cover information....

An Addendum to "A New Tool for Climatic Analysis Using Köppen Climate Classification"

ERIC Educational Resources Information Center

Larson, Paul R.; Lohrengel, C. Frederick, II

2014-01-01

The Köppen climatic classification system in a modified format is the most widely applied system in use today. Mapping and analysis of hundreds of arid and semiarid climate stations has made the use of the additional fourth letter in BW/BS climates essential. The addition of "s," "w," or "f" to the standard…

Impact of input data uncertainty on environmental exposure assessment models: A case study for electromagnetic field modelling from mobile phone base stations.

PubMed

Beekhuizen, Johan; Heuvelink, Gerard B M; Huss, Anke; Bürgi, Alfred; Kromhout, Hans; Vermeulen, Roel

2014-11-01

With the increased availability of spatial data and computing power, spatial prediction approaches have become a standard tool for exposure assessment in environmental epidemiology. However, such models are largely dependent on accurate input data. Uncertainties in the input data can therefore have a large effect on model predictions, but are rarely quantified. With Monte Carlo simulation we assessed the effect of input uncertainty on the prediction of radio-frequency electromagnetic fields (RF-EMF) from mobile phone base stations at 252 receptor sites in Amsterdam, The Netherlands. The impact on ranking and classification was determined by computing the Spearman correlations and weighted Cohen's Kappas (based on tertiles of the RF-EMF exposure distribution) between modelled values and RF-EMF measurements performed at the receptor sites. The uncertainty in modelled RF-EMF levels was large with a median coefficient of variation of 1.5. Uncertainty in receptor site height, building damping and building height contributed most to model output uncertainty. For exposure ranking and classification, the heights of buildings and receptor sites were the most important sources of uncertainty, followed by building damping, antenna- and site location. Uncertainty in antenna power, tilt, height and direction had a smaller impact on model performance. We quantified the effect of input data uncertainty on the prediction accuracy of an RF-EMF environmental exposure model, thereby identifying the most important sources of uncertainty and estimating the total uncertainty stemming from potential errors in the input data. This approach can be used to optimize the model and better interpret model output. Copyright © 2014 Elsevier Inc. All rights reserved.

Center for Seismic Studies Final Technical Report, October 1992 through October 1993

DTIC Science & Technology

1994-02-07

SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF THIS PAGE OF ABSTRACT...Upper limit of depth error as a function of mb for estimates based on P and S waves for three netowrks : GSETr-2, ALPHA, and ALPHA + a 50 station...U 4A 4 U 4S as 1 I I I Figure 42: Upper limit of depth error as a function of mb for estimatesbased on P and S waves for three netowrk : GSETT-2o ALPHA

Rapid Classification of Landsat TM Imagery for Phase 1 Stratification Using the Automated NDVI Threshold Supervised Classification (ANTSC) Methodology

Treesearch

William H. Cooke; Dennis M. Jacobs

2005-01-01

FIA annual inventories require rapid updating of pixel-based Phase 1 estimates. Scientists at the Southern Research Station are developing an automated methodology that uses a Normalized Difference Vegetation Index (NDVI) for identifying and eliminating problem FIA plots from the analysis. Problem plots are those that have questionable land use/land cover information....

Wall-to-wall Landsat TM classifications for Georgia in support of SAFIS using FIA plots for training and verification

Treesearch

William H. Cooke; Andrew J. Hartsell

2000-01-01

Wall-to-wall Landsat TM classification efforts in Georgia require field validation. Validation uslng FIA data was testing by developing a new crown modeling procedure. A methodology is under development at the Southern Research Station to model crown diameter using Forest Health monitoring data. These models are used to simulate the proportion of tree crowns that...

Engineering Design Handbook. Development Guide for Reliability. Part 6. Mathematical Appendix and Glossary

DTIC Science & Technology

1976-01-08

Corps, nonmilitary Government agencies, contractors, private industry, individuals, universities , and others must purchase these Handbooks from...verified by an official Department of Army representative and processed from Defense Documentation Center ( DDC ), ATTN: DDC -TSR, Cameron Station...tell, by looking at a failed item, what classification of failure is involved. Some of the classifications are for mathematical conven- ience only

IET. Coupling station (TAN620), plans and sections. Concrete shielding walls ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

IET. Coupling station (TAN-620), plans and sections. Concrete shielding walls and boron surface treatment. Elevation shows two floor levels, position of periscopes, and stairways. Ralph M. Parsons 902-4-ANP-602-A 325. Date: February 1954. Approved by INEEL Classification Office for public release. INEEL index code no. 035-0620-00-693-106910 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

Design and Analysis of a Hydrogen Compression and Storage Station

DTIC Science & Technology

2017-12-01

Holmes THIS PAGE INTENTIONALLY LEFT BLANK i REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704–0188 Public reporting burden for this collection...SECURITY CLASSIFICATION OF ABSTRACT Unclassified 20. LIMITATION OF ABSTRACT UU NSN 7540–01-280-5500 Standard Form 298 (Rev. 2–89...than fossil fuels [2]. Renewably generated hydrogen gas, such as the hydrogen station demonstrated at NPS, falls into this category of alternative

41 CFR 101-42.1101 - Federal supply classification (FSC) groups and classes which contain hazardous materials.

Code of Federal Regulations, 2011 CFR

2011-07-01

... that contain flammable chemicals. 5950 Coils and transformers Items containing polychlorinated... capacitors containing PCBs. 6120 Transformers: Distribution and power station Transformers containing PCBs...

41 CFR 101-42.1101 - Federal supply classification (FSC) groups and classes which contain hazardous materials.

Code of Federal Regulations, 2014 CFR

2014-07-01

... that contain flammable chemicals. 5950 Coils and transformers Items containing polychlorinated... capacitors containing PCBs. 6120 Transformers: Distribution and power station Transformers containing PCBs...

41 CFR 101-42.1101 - Federal supply classification (FSC) groups and classes which contain hazardous materials.

Code of Federal Regulations, 2013 CFR

2013-07-01

... that contain flammable chemicals. 5950 Coils and transformers Items containing polychlorinated... capacitors containing PCBs. 6120 Transformers: Distribution and power station Transformers containing PCBs...

41 CFR 101-42.1101 - Federal supply classification (FSC) groups and classes which contain hazardous materials.

Code of Federal Regulations, 2010 CFR

2010-07-01

... that contain flammable chemicals. 5950 Coils and transformers Items containing polychlorinated... capacitors containing PCBs. 6120 Transformers: Distribution and power station Transformers containing PCBs...

41 CFR 101-42.1101 - Federal supply classification (FSC) groups and classes which contain hazardous materials.

Code of Federal Regulations, 2012 CFR

2012-07-01

... that contain flammable chemicals. 5950 Coils and transformers Items containing polychlorinated... capacitors containing PCBs. 6120 Transformers: Distribution and power station Transformers containing PCBs...

Lossless Compression of Classification-Map Data

NASA Technical Reports Server (NTRS)

Hua, Xie; Klimesh, Matthew

2009-01-01

A lossless image-data-compression algorithm intended specifically for application to classification-map data is based on prediction, context modeling, and entropy coding. The algorithm was formulated, in consideration of the differences between classification maps and ordinary images of natural scenes, so as to be capable of compressing classification- map data more effectively than do general-purpose image-data-compression algorithms. Classification maps are typically generated from remote-sensing images acquired by instruments aboard aircraft (see figure) and spacecraft. A classification map is a synthetic image that summarizes information derived from one or more original remote-sensing image(s) of a scene. The value assigned to each pixel in such a map is the index of a class that represents some type of content deduced from the original image data for example, a type of vegetation, a mineral, or a body of water at the corresponding location in the scene. When classification maps are generated onboard the aircraft or spacecraft, it is desirable to compress the classification-map data in order to reduce the volume of data that must be transmitted to a ground station.

Total nutrient and sediment loads, trends, yields, and nontidal water-quality indicators for selected nontidal stations, Chesapeake Bay Watershed, 1985–2011

USGS Publications Warehouse

Langland, Michael J.; Blomquist, Joel D.; Moyer, Douglas; Hyer, Kenneth; Chanat, Jeffrey G.

2013-01-01

The U.S. Geological Survey, in cooperation with Chesapeake Bay Program (CBP) partners, routinely reports long-term concentration trends and monthly and annual constituent loads for stream water-quality monitoring stations across the Chesapeake Bay watershed. This report documents flow-adjusted trends in sediment and total nitrogen and phosphorus concentrations for 31 stations in the years 1985–2011 and for 32 stations in the years 2002–2011. Sediment and total nitrogen and phosphorus yields for 65 stations are presented for the years 2006–2011. A combined nontidal water-quality indicator (based on both trends and yields) indicates there are more stations classified as “improving water-quality trend and a low yield” than “degrading water-quality trend and a high yield” for total nitrogen. The same type of 2-way classification for total phosphorus and sediment results in equal numbers of stations in each indicator class.

Repair, Evaluation, Maintenance, and Rehabilitation Research Program. Floating Debris Control; A Literature Review.

DTIC Science & Technology

1987-06-01

Debris diversion boom and debris, Appalachian Power Company Station at Winfield Lock and Dam, Kanavha River, West Virginia. Than, T 9 (sin a) - 1.94...control dam. Central gate Is blocked partly open causing .ime downstream scour. Water flows right to left. BOTTOM-Debris diversion boom and debris... Appalachian Power Company Station at Winfield Lock and Dam, Kanawha River, West Virginia. - 0 .’ Unclass ified SECURITY CLASSIFICATION OF THIS PAGE for- 40

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Use of remote sensing in agriculture

NASA Technical Reports Server (NTRS)

Pettry, D. E.; Powell, N. L.

1975-01-01

The remote sensing studies of (a) cultivated peanut areas in Southeastern Virginia; (b) studies at the Virginia Truck and Ornamentals Research Station near Painter, Virginia, the Eastern Virginia Research Station near Warsaw, Virginia, the Tidewater Research and Continuing Education Center near Suffolk, Virginia, and the Southern Piedmont Research and Continuing Education Center Blackstone, Virginia; and (c) land use classification studies at Virginia Beach, Virginia are presented. The practical feasibility of using false color infrared imagery to detect and determine the areal extent of peanut disease infestation of Cylindrocladium black rot and Sclerotinia blight is demonstrated. These diseases pose a severe hazard to this major agricultural food commodity. The value of remote sensing technology in terrain analyses and land use classification of diverse land areas is also investigated. Continued refinement of spectral signatures of major agronomic crops and documentation of pertinent environmental variables have provided a data base for the generation of an agricultural-environmental prediction model.

Analysis of Particulate and Fiber Debris Samples Returned from the International Space Station

NASA Technical Reports Server (NTRS)

Perry, Jay L.; Coston, James E.

2014-01-01

During the period of International Space Station (ISS) Increments 30 and 31, crewmember reports cited differences in the cabin environment relating to particulate matter and fiber debris compared to earlier experience as well as allergic responses to the cabin environment. It was hypothesized that a change in the cabin atmosphere's suspended particulate matter load may be responsible for the reported situation. Samples were collected and returned to ground-based laboratories for assessment. Assessments included physical classification, optical microscopy and photographic analysis, and scanning electron microscopy (SEM) evaluation using energy dispersive X-ray spectrometry (EDS) methods. Particular points of interest for assessing the samples were for the presence of allergens, carbon dioxide removal assembly (CDRA) zeolite dust, and FGB panel fibers. The results from the physical classification, optical microscopy and photographic analysis, and SEM EDS analysis are presented and discussed.

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.

Correlations between the modelled potato crop yield and the general atmospheric circulation

NASA Astrophysics Data System (ADS)

Sepp, Mait; Saue, Triin

2012-07-01

Biology-related indicators do not usually depend on just one meteorological element but on a combination of several weather indicators. One way to establish such integral indicators is to classify the general atmospheric circulation into a small number of circulation types. The aim of present study is to analyse connections between general atmospheric circulation and potato crop yield in Estonia. Meteorologically possible yield (MPY), calculated by the model POMOD, is used to characterise potato crop yield. Data of three meteorological stations and the biological parameters of two potato sorts were applied to the model, and 73 different classifications of atmospheric circulation from catalogue 1.2 of COST 733, domain 05 are used to qualify circulation conditions. Correlation analysis showed that there is at least one circulation type in each of the classifications with at least one statistically significant (99%) correlation with potato crop yield, whether in Kuressaare, Tallinn or Tartu. However, no classifications with circulation types correlating with MPY in all three stations at the same time were revealed. Circulation types inducing a decrease in the potato crop yield are more clearly represented. Clear differences occurred between the observed geographical locations as well as between the seasons: derived from the number of significant circulation types, summer and Kuressaare stand out. Of potato varieties, late 'Anti' is more influenced by circulation. Analysis of MSLP maps of circulation types revealed that the seaside stations (Tallinn, Kuressaare) suffer from negative effects of anti-cyclonic conditions (drought), while Tartu suffers from the cyclonic activity (excessive water).

Causes of the sharp increase in the time series of surface solar radiation in China between 1990 and 1993

NASA Astrophysics Data System (ADS)

Wang, Yawen; Wild, Martin

2017-02-01

During 1990-1993, a nation-wide replacement of the instruments measuring surface solar radiation (SSR) and a restructuring of SSR stations took place in China. Meanwhile, a sudden upward jump was noted in published composite time series of observed SSR records in this period. This study clarifies that about 1/3 of the magnitude of the SSR jump in China was accidentally caused by the abandonment/establishment of 51 stations (˜39% of total) during the period of 1990-1993. The remaining 2/3 of the SSR jump was only caused by 22 stations detected by the methods of the accumulated deviation curve and the Mann-Whitney U test. Out of these 22 stations, about 1/4 of the SSR jump were caused by 6 stations due to natural factors, as similar variations were recorded by sunshine duration. The other 3/4 were caused by the remaining 16 stations as a result of artificial factors such as instrument replacement, changes in the classification or location of stations, or potential operational errors.

Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology

PubMed Central

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests’ pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture. PMID:22736996

Feasibility study on a portable field pest classification system design based on DSP and 3G wireless communication technology.

PubMed

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests' pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture.

Streamflow profile classification using functional data analysis: A case study on the Kelantan River Basin

NASA Astrophysics Data System (ADS)

Jamaludin, Suhaila

2017-05-01

Extreme rainfall events such as floods and prolonged dry spells have become common phenomena in tropical countries like Malaysia. Floods are regular natural disasters in Malaysia, and happen nearly every year during the monsoon season. Recently, the magnitude of streamflow seems to have altered frequently, both spatially and temporally. Therefore, in order to have effective planning and an efficient water management system, it is advisable that streamflow data are analysed continuously over a period of time. If the data are treated as a set of functions rather than as a set of discrete values, then this ensures that they are not restricted by physical time. In addition, the derivatives of the functions may themselves be treated as functional data, which provides new information. The objective of this study is to develop a functional framework for hydrological applications using streamflow as the functional data. The daily flow series from the Kelantan River Basin were used as the main input in this study. Seven streamflow stations were employed in the analysis. Classification between the stations was done using the functional principal component, which was based on the results of the factor scores. The results indicated that two stations, namely the Kelantan River (Guillemard Bridge) and the Galas River, have a different flow pattern from the other streamflow stations. The flow curves of these two rivers are considered as the extreme curves because of their different magnitude and shape.

Adaptive neuro-fuzzy inference systems for semi-automatic discrimination between seismic events: a study in Tehran region

NASA Astrophysics Data System (ADS)

Vasheghani Farahani, Jamileh; Zare, Mehdi; Lucas, Caro

2012-04-01

Thisarticle presents an adaptive neuro-fuzzy inference system (ANFIS) for classification of low magnitude seismic events reported in Iran by the network of Tehran Disaster Mitigation and Management Organization (TDMMO). ANFIS classifiers were used to detect seismic events using six inputs that defined the seismic events. Neuro-fuzzy coding was applied using the six extracted features as ANFIS inputs. Two types of events were defined: weak earthquakes and mining blasts. The data comprised 748 events (6289 signals) ranging from magnitude 1.1 to 4.6 recorded at 13 seismic stations between 2004 and 2009. We surveyed that there are almost 223 earthquakes with M ≤ 2.2 included in this database. Data sets from the south, east, and southeast of the city of Tehran were used to evaluate the best short period seismic discriminants, and features as inputs such as origin time of event, distance (source to station), latitude of epicenter, longitude of epicenter, magnitude, and spectral analysis (fc of the Pg wave) were used, increasing the rate of correct classification and decreasing the confusion rate between weak earthquakes and quarry blasts. The performance of the ANFIS model was evaluated for training and classification accuracy. The results confirmed that the proposed ANFIS model has good potential for determining seismic events.

Probabilistic discrimination between liquid rainfall events, hailstorms, biomass burning and industrial fires from C-Band Radar Polarimetric Variables

NASA Astrophysics Data System (ADS)

Valencia, J. M.; Sepúlveda, J.; Hoyos, C.; Herrera, L.

2017-12-01

Characterization and identification of fire and hailstorm events using weather radar data in a tropical complex topography region is an important task in risk management and agriculture. Polarimetric variables from a C-Band Dual polarization weather radar have potential uses in particle classification, due to the relationship their sensitivity to shape, spatial orientation, size and fall behavior of particles. In this sense, three forest fires and two chemical fires were identified for the Áburra Valley regions. Measurements were compared between each fire event type and with typical data radar retrievals for liquid precipitation events. Results of this analysis show different probability density functions for each type of event according to the particles present in them. This is very important and useful result for early warning systems to avoid precipitation false alarms during fire events within the study region, as well as for the early detection of fires using radar retrievals in remote cases. The comparative methodology is extended to hailstorm cases. Complementary sensors like laser precipitation sensors (LPM) disdrometers and meteorological stations were used to select dates of solid precipitation occurrence. Then, in this dates weather radar data variables were taken in pixels surrounding the stations and solid precipitation polar values were statistically compared with liquid precipitation values. Spectrum precipitation measured by LPM disdrometer helps to define typical features like particles number, fall velocities and diameters for both precipitation types. In addition, to achieve a complete hailstorm characterization, other meteorological variables were analyzed: wind field from meteorological stations and radar wind profiler, profiling data from Micro Rain Radar (MRR), and thermodynamic data from a microwave radiometer.

Traffic data collection for transportation planning in the Dallas-Fort Worth area. Interim research report, January 1994-July 1995

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

Perkinson, D.G.; Dresser, G.B.

1995-07-01

The Texas Transportation Institute (TTI), under a contract with the Dallas District of the Texas Department of Transportation (TxDOT), provided traffic data for the North Central Texas Council of Governments (NCTOG) for their transportation planning in the Dallas-Fort Worth area. This effort included volume counts, vehicle classification counts, and speed data for 23 urban corridors in the area. In addition, external station volume counts were collected for 32 external stations, and journey travel time data were collected for nine activity centers.

Ichthyoplankton abundance and variance in a large river system concerns for long-term monitoring

USGS Publications Warehouse

Holland-Bartels, Leslie E.; Dewey, Michael R.; Zigler, Steven J.

1995-01-01

System-wide spatial patterns of ichthyoplankton abundance and variability were assessed in the upper Mississippi and lower Illinois rivers to address the experimental design and statistical confidence in density estimates. Ichthyoplankton was sampled from June to August 1989 in primary milieus (vegetated and non-vegated backwaters and impounded areas, main channels and main channel borders) in three navigation pools (8, 13 and 26) of the upper Mississippi River and in a downstream reach of the Illinois River. Ichthyoplankton densities varied among stations of similar aquatic landscapes (milieus) more than among subsamples within a station. An analysis of sampling effort indicated that the collection of single samples at many stations in a given milieu type is statistically and economically preferable to the collection of multiple subsamples at fewer stations. Cluster analyses also revealed that stations only generally grouped by their preassigned milieu types. Pilot studies such as this can define station groupings and sources of variation beyond an a priori habitat classification. Thus the minimum intensity of sampling required to achieve a desired statistical confidence can be identified before implementing monitoring efforts.

Identifying hub stations and important lines of bus networks: A case study in Xiamen, China

NASA Astrophysics Data System (ADS)

Zhang, Hui; Zhuge, Chengxiang; Yu, Xiaohua

2018-07-01

Hub stations and important lines play key roles in transfers between stations. In this paper, a node failure model is proposed to identify hub stations. In the model, we introduce two new indicators called neighborhood degree ratio and transfer index to evaluate the importance of stations, which consider neighborhood stations' degree of station and the initial transfer times between stations. Moreover, line accessibility is developed to measure the importance of lines in the bus network. Xiamen bus network in 2016 is utilized to test the model. The results show that the two introduced indicators are more effective to identify hub stations compared with traditional complex network indicators such as degree, clustering coefficient and betweenness.

Cluster analysis of Southeastern U.S. climate stations

NASA Astrophysics Data System (ADS)

Stooksbury, D. E.; Michaels, P. J.

1991-09-01

A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.

Support Vector Machine Model for Automatic Detection and Classification of Seismic Events

NASA Astrophysics Data System (ADS)

Barros, Vesna; Barros, Lucas

2016-04-01

The automated processing of multiple seismic signals to detect, localize and classify seismic events is a central tool in both natural hazards monitoring and nuclear treaty verification. However, false detections and missed detections caused by station noise and incorrect classification of arrivals are still an issue and the events are often unclassified or poorly classified. Thus, machine learning techniques can be used in automatic processing for classifying the huge database of seismic recordings and provide more confidence in the final output. Applied in the context of the International Monitoring System (IMS) - a global sensor network developed for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) - we propose a fully automatic method for seismic event detection and classification based on a supervised pattern recognition technique called the Support Vector Machine (SVM). According to Kortström et al., 2015, the advantages of using SVM are handleability of large number of features and effectiveness in high dimensional spaces. Our objective is to detect seismic events from one IMS seismic station located in an area of high seismicity and mining activity and classify them as earthquakes or quarry blasts. It is expected to create a flexible and easily adjustable SVM method that can be applied in different regions and datasets. Taken a step further, accurate results for seismic stations could lead to a modification of the model and its parameters to make it applicable to other waveform technologies used to monitor nuclear explosions such as infrasound and hydroacoustic waveforms. As an authorized user, we have direct access to all IMS data and bulletins through a secure signatory account. A set of significant seismic waveforms containing different types of events (e.g. earthquake, quarry blasts) and noise is being analysed to train the model and learn the typical pattern of the signal from these events. Moreover, comparing the performance of the support-vector network to various classical learning algorithms used before in seismic detection and classification is an essential final step to analyze the advantages and disadvantages of the model.

An Evaluation of Electronic Nose for Space Program Applications

NASA Technical Reports Server (NTRS)

Young, Rebecca C.; Linnell, Bruce R.; Buttner, William J.; Mersqhelte, Barry

2003-01-01

The ability to monitor air contaminants in the Shuttle and the International Space Station is important to ensure the health and safety of astronauts. Three specific space applications have been identified that would benefit from a chemical monitor: organic contaminants in crew cabins, propellant contaminants in the airlock, and pre-combustion fire detection. NASA has assessed several commercial and developing electronic noses (e-noses) for these applications. A preliminary series of tests identified those e-noses that exhibited sufficient sensitivity to the vapors of interest. These e-noses were further tested to assess their ability to identify vapors, and in-house software has been developed to enhance identification. This paper describes the tests, the classification ability of selected e-noses, and the software improvements made to meet the requirements for these space program applications.

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

Spectroscopic Classification of SN 2018bgc (=ATLAS18nvs) as a Type Ia Supernova

NASA Astrophysics Data System (ADS)

Lin, Han; Wang, Xiaofeng; Xiang, Danfeng; Rui, Liming; Hu, Lei; Hu, Maokai; Zhang, Xinhan; Li, Xue; Zhang, Tianmeng; Zhang, Jujia

2018-05-01

We obtained an optical spectrum (range 385-855 nm) of SN 2018bgc(=ATLAS18nvs), discovered by ATLAS, on UT May 08.60 2018 with the 2.16-m telescope (+BFOSC) at Xinglong Station of National Astronomical Observatories of China (NAOC).

Characterizing fuels in the 21st century.

Treesearch

David Sandberg; Roger D. Ottmar; Geoffrey H. Cushon

2001-01-01

The ongoing development of sophisticated fire behavior and effects models has demonstrated the need for a comprehensive system of fuel classification that more accurately captures the structural complexity and geographic diversity of fuelbeds. The Fire and Environmental Research Applications Team (FERA) of the USD Forest Service, Pacific Northwest Research Station, is...

48 CFR 47.303-1 - F.o.b. origin.

Code of Federal Regulations, 2011 CFR

2011-10-01

... carrier's wharf (at shipside, within reach of the ship's loading tackle, when the shipping point is within a port area having water transportation service) or the carrier's freight station; (3) To a U.S... terms of the governing freight classification or tariff (or Government rate tender) under which lowest...

48 CFR 47.303-1 - F.o.b. origin.

Code of Federal Regulations, 2013 CFR

2013-10-01

... carrier's wharf (at shipside, within reach of the ship's loading tackle, when the shipping point is within a port area having water transportation service) or the carrier's freight station; (3) To a U.S... terms of the governing freight classification or tariff (or Government rate tender) under which lowest...

48 CFR 47.303-1 - F.o.b. origin.

Code of Federal Regulations, 2014 CFR

2014-10-01

... carrier's wharf (at shipside, within reach of the ship's loading tackle, when the shipping point is within a port area having water transportation service) or the carrier's freight station; (3) To a U.S... terms of the governing freight classification or tariff (or Government rate tender) under which lowest...

48 CFR 47.303-1 - F.o.b. origin.

Code of Federal Regulations, 2012 CFR

2012-10-01

... carrier's wharf (at shipside, within reach of the ship's loading tackle, when the shipping point is within a port area having water transportation service) or the carrier's freight station; (3) To a U.S... terms of the governing freight classification or tariff (or Government rate tender) under which lowest...

39 CFR 241.3 - Discontinuance of USPS-operated retail facilities.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 39 Postal Service 1 2013-07-01 2013-07-01 false Discontinuance of USPS-operated retail facilities... ESTABLISHMENT CLASSIFICATION, AND DISCONTINUANCE § 241.3 Discontinuance of USPS-operated retail facilities. (a... of whether an existing retail Post Office, station, or branch should be discontinued. The rules cover...

39 CFR 241.3 - Discontinuance of USPS-operated retail facilities.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 39 Postal Service 1 2014-07-01 2014-07-01 false Discontinuance of USPS-operated retail facilities... ESTABLISHMENT CLASSIFICATION, AND DISCONTINUANCE § 241.3 Discontinuance of USPS-operated retail facilities. (a... of whether an existing retail Post Office, station, or branch should be discontinued. The rules cover...

39 CFR 241.3 - Discontinuance of USPS-operated retail facilities.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 39 Postal Service 1 2012-07-01 2012-07-01 false Discontinuance of USPS-operated retail facilities... ESTABLISHMENT CLASSIFICATION, AND DISCONTINUANCE § 241.3 Discontinuance of USPS-operated retail facilities. (a... of whether an existing retail Post Office, station, or branch should be discontinued. The rules cover...

50 CFR 32.37 - Louisiana.

Code of Federal Regulations, 2010 CFR

2010-10-01

... normal voice contact with) only one youth for all youth hunts except migratory birds. One adult may... the refuge at one of the self-clearing check stations indicated on the map in the refuge Hunting and...-Impaired” classification apply. 15. You may only possess approved nontoxic shot while hunting on the refuge...

Early warning, warning or alarm systems for natural hazards? A generic classification.

NASA Astrophysics Data System (ADS)

Sättele, Martina; Bründl, Michael; Straub, Daniel

2013-04-01

Early warning, warning and alarm systems have gained popularity in recent years as cost-efficient measures for dangerous natural hazard processes such as floods, storms, rock and snow avalanches, debris flows, rock and ice falls, landslides, flash floods, glacier lake outburst floods, forest fires and even earthquakes. These systems can generate information before an event causes loss of property and life. In this way, they mainly mitigate the overall risk by reducing the presence probability of endangered objects. These systems are typically prototypes tailored to specific project needs. Despite their importance there is no recognised system classification. This contribution classifies warning and alarm systems into three classes: i) threshold systems, ii) expert systems and iii) model-based expert systems. The result is a generic classification, which takes the characteristics of the natural hazard process itself and the related monitoring possibilities into account. The choice of the monitoring parameters directly determines the system's lead time. The classification of 52 active systems moreover revealed typical system characteristics for each system class. i) Threshold systems monitor dynamic process parameters of ongoing events (e.g. water level of a debris flow) and incorporate minor lead times. They have a local geographical coverage and a predefined threshold determines if an alarm is automatically activated to warn endangered objects, authorities and system operators. ii) Expert systems monitor direct changes in the variable disposition (e.g crack opening before a rock avalanche) or trigger events (e.g. heavy rain) at a local scale before the main event starts and thus offer extended lead times. The final alarm decision incorporates human, model and organisational related factors. iii) Model-based expert systems monitor indirect changes in the variable disposition (e.g. snow temperature, height or solar radiation that influence the occurrence probability of snow avalanches) or trigger events (e.g. heavy snow fall) to predict spontaneous hazard events in advance. They encompass regional or national measuring networks and satisfy additional demands such as the standardisation of the measuring stations. The developed classification and the characteristics, which were revealed for each class, yield a valuable input to quantifying the reliability of warning and alarm systems. Importantly, this will facilitate to compare them with well-established standard mitigation measures such as dams, nets and galleries within an integrated risk management approach.

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

AllamehZadeh, Mostafa, E-mail: dibaparima@yahoo.com

A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neuralmore » system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0-6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.« less

Satellite Power System (SPS). State and local regulations as applied to satellite power system microwave receiving antenna facilities

NASA Technical Reports Server (NTRS)

Kotin, A. D.

1978-01-01

State and local regulation of power plant construction and operation of solar power satellite (SPS) receiving stations is presented. Each receiving antenna station occupies a land area 100-200 km square, receives microwave transmissions from the solar power satellite, and converts them into electricity for transmission to the power grid. The long lead time associated with the SPS and the changing status of state and local regulation dictated emphasis on: generic classification of the types of regulation, and identification of regulatory vectors which affect rectenna facilities.

Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya

NASA Astrophysics Data System (ADS)

Kerandi, Noah Misati; Laux, Patrick; Arnault, Joel; Kunstmann, Harald

2017-10-01

This study investigates the ability of the regional climate model Weather Research and Forecasting (WRF) in simulating the seasonal and interannual variability of hydrometeorological variables in the Tana River basin (TRB) in Kenya, East Africa. The impact of two different land use classifications, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Geological Survey (USGS) at two horizontal resolutions (50 and 25 km) is investigated. Simulated precipitation and temperature for the period 2011-2014 are compared with Tropical Rainfall Measuring Mission (TRMM), Climate Research Unit (CRU), and station data. The ability of Tropical Rainfall Measuring Mission (TRMM) and Climate Research Unit (CRU) data in reproducing in situ observation in the TRB is analyzed. All considered WRF simulations capture well the annual as well as the interannual and spatial distribution of precipitation in the TRB according to station data and the TRMM estimates. Our results demonstrate that the increase of horizontal resolution from 50 to 25 km, together with the use of the MODIS land use classification, significantly improves the precipitation results. In the case of temperature, spatial patterns and seasonal cycle are well reproduced, although there is a systematic cold bias with respect to both station and CRU data. Our results contribute to the identification of suitable and regionally adapted regional climate models (RCMs) for East Africa.

The impact of joint responses of devices in an airport security system.

PubMed

Nie, Xiaofeng; Batta, Rajan; Drury, Colin G; Lin, Li

2009-02-01

In this article, we consider a model for an airport security system in which the declaration of a threat is based on the joint responses of inspection devices. This is in contrast to the typical system in which each check station independently declares a passenger as having a threat or not having a threat. In our framework the declaration of threat/no-threat is based upon the passenger scores at the check stations he/she goes through. To do this we use concepts from classification theory in the field of multivariate statistics analysis and focus on the main objective of minimizing the expected cost of misclassification. The corresponding correct classification and misclassification probabilities can be obtained by using a simulation-based method. After computing the overall false alarm and false clear probabilities, we compare our joint response system with two other independently operated systems. A model that groups passengers in a manner that minimizes the false alarm probability while maintaining the false clear probability within specifications set by a security authority is considered. We also analyze the staffing needs at each check station for such an inspection scheme. An illustrative example is provided along with sensitivity analysis on key model parameters. A discussion is provided on some implementation issues, on the various assumptions made in the analysis, and on potential drawbacks of the approach.

Classification and Space-Time Analysis of Precipitation Events in Manizales, Caldas, Colombia.

NASA Astrophysics Data System (ADS)

Suarez Hincapie, J. N.; Vélez, J.; Romo Melo, L.; Chang, P.

2015-12-01

Manizales is a mid-mountain Andean city located near the Nevado del Ruiz volcano in west-central Colombia, this location exposes it to earthquakes, floods, landslides and volcanic eruptions. It is located in the intertropical convergence zone (ITCZ) and presents a climate with a bimodal rainfall regime (Cortés, 2010). Its mean annual rainfall is 2000 mm, one may observe precipitation 70% of the days over a year. This rain which favors the formation of large masses of clouds and the presence of macroclimatic phenomenon as "El Niño South Oscillation", has historically caused great impacts in the region (Vélez et al, 2012). For example the geographical location coupled with rain events results in a high risk of landslides in the city. Manizales has a hydrometeorological network of 40 stations that measure and transmit data of up to eight climate variables. Some of these stations keep 10 years of historical data. However, until now this information has not been used for space-time classification of precipitation events, nor has the meteorological variables that influence them been thoroughly researched. The purpose of this study was to classify historical events of rain in an urban area of Manizales and investigate patterns of atmospheric behavior that influence or trigger such events. Classification of events was performed by calculating the "n" index of the heavy rainfall, describing the behavior of precipitation as a function of time throughout the event (Monjo, 2009). The analysis of meteorological variables was performed using statistical quantification over variable time periods before each event. The proposed classification allowed for an analysis of the evolution of rainfall events. Specially, it helped to look for the influence of different meteorological variables triggering rainfall events in hazardous areas as the city of Manizales.

33 CFR 401.80 - Reporting dangerous cargo.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 3 2010-07-01 2010-07-01 false Reporting dangerous cargo. 401.80... dangerous cargo. (a) The master of any explosive vessel or hazardous cargo vessel shall report to a Seaway station, as set out in Schedule III, the nature, quantity, and IMO classification of the dangerous cargo...

33 CFR 401.80 - Reporting dangerous cargo.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 3 2011-07-01 2011-07-01 false Reporting dangerous cargo. 401.80... dangerous cargo. (a) The master of any explosive vessel or hazardous cargo vessel shall report to a Seaway station, as set out in Schedule III, the nature, quantity, and IMO classification of the dangerous cargo...

33 CFR 401.80 - Reporting dangerous cargo.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 3 2012-07-01 2012-07-01 false Reporting dangerous cargo. 401.80... dangerous cargo. (a) The master of any explosive vessel or hazardous cargo vessel shall report to a Seaway station, as set out in Schedule III, the nature, quantity, and IMO classification of the dangerous cargo...

33 CFR 401.80 - Reporting dangerous cargo.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 3 2014-07-01 2014-07-01 false Reporting dangerous cargo. 401.80... dangerous cargo. (a) The master of any explosive vessel or hazardous cargo vessel shall report to a Seaway station, as set out in Schedule III, the nature, quantity, and IMO classification of the dangerous cargo...

33 CFR 401.80 - Reporting dangerous cargo.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 3 2013-07-01 2013-07-01 false Reporting dangerous cargo. 401.80... dangerous cargo. (a) The master of any explosive vessel or hazardous cargo vessel shall report to a Seaway station, as set out in Schedule III, the nature, quantity, and IMO classification of the dangerous cargo...

Identification and Classification of Orthogonal Frequency Division Multiple Access (OFDMA) Signals Used in Next Generation Wireless Systems

DTIC Science & Technology

2012-03-01

advanced antenna systems AMC adaptive modulation and coding AWGN additive white Gaussian noise BPSK binary phase shift keying BS base station BTC ...QAM-16, and QAM-64, and coding types include convolutional coding (CC), convolutional turbo coding (CTC), block turbo coding ( BTC ), zero-terminating

Spectroscopic Classification of SN 2018bq (=ASASSN-18ac) as a Type Ia Supernova

NASA Astrophysics Data System (ADS)

Lin, Han; Xiang, Danfeng; Rui, Liming; Wang, Xiaofeng; Xiao, Feng; Ren, Juanjuan; Zhang, Tianmeng; Zhang, Jujia

2018-01-01

We obtained an optical spectrum (range 510-860 nm) of SN 2018bq(=ASASSN-18ac), discovered by All Sky Automated Survey for Supernova(ASAS-SN), on UT 09.81 2018 with the 2.16-m telescope (+BFOSC) at Xinglong Station of National Astronomical Observatories of China (NAOC).

47 CFR 1.929 - Classification of filings as major or minor.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Wireless Radio Services Applications and Proceedings Application Requirements and Procedures § 1.929... wireless radio services are classified as major or minor ( see § 1.947). Categories of major and minor filings are listed in § 309 of the Communications Act of 1934. (a) For all stations in all Wireless Radio...

48 CFR 52.247-33 - F.o.b. Origin, With Differentials.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., and placed on, the carrier's wharf (at shipside, within reach of the ship's loading tackle, when the shipping point is within a port area having water transportation service) or the carrier's freight station... lading shall show— (i) A description of the shipment in terms of the governing freight classification or...

14 CFR 25.857 - Cargo compartment classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... detector or fire detector system to give warning at the pilot or flight engineer station. (c) Class C. A... compartment but in which— (1) There is a separate approved smoke detector or fire detector system to give... a separate approved smoke or fire detector system to give warning at the pilot or flight engineer...

14 CFR 25.857 - Cargo compartment classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... detector or fire detector system to give warning at the pilot or flight engineer station. (c) Class C. A... compartment but in which— (1) There is a separate approved smoke detector or fire detector system to give... a separate approved smoke or fire detector system to give warning at the pilot or flight engineer...

14 CFR 25.857 - Cargo compartment classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... detector or fire detector system to give warning at the pilot or flight engineer station. (c) Class C. A... compartment but in which— (1) There is a separate approved smoke detector or fire detector system to give... a separate approved smoke or fire detector system to give warning at the pilot or flight engineer...

14 CFR 25.857 - Cargo compartment classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... detector or fire detector system to give warning at the pilot or flight engineer station. (c) Class C. A... compartment but in which— (1) There is a separate approved smoke detector or fire detector system to give... a separate approved smoke or fire detector system to give warning at the pilot or flight engineer...

14 CFR 25.857 - Cargo compartment classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... detector or fire detector system to give warning at the pilot or flight engineer station. (c) Class C. A... compartment but in which— (1) There is a separate approved smoke detector or fire detector system to give... a separate approved smoke or fire detector system to give warning at the pilot or flight engineer...

31 CFR 592.502 - Annual reports by rough diamond importers and exporters.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Schedule classifications of rough diamonds during the reporting year, including: (A) Total amount of carats of each classification of rough diamonds imported and/or exported; and (B) Total of all shipments of each classification of rough diamonds imported and/or exported. (3) Information on stockpiles of rough...

Options to Improve Rain Snow Parameterization in Surface Based Models

NASA Astrophysics Data System (ADS)

Feiccabrino, J. M.

2017-12-01

Precipitation phase determination is of upmost importance in a number of surface based hydrological, ecological, and safety models. However, precipitation phase at Earth's surface is a result of cloud and atmospheric properties not measured by surface weather stations. Nonetheless, they can be inferred from the available surface datum. This study uses 681,620 weather observations with air temperatures between -3 and 5°C and identified precipitation occurring at the time of the observation to determine simple, yet accurate, thresholds for precipitation phase determination schemes (PPDS). This dataset represents 38% and 42% of precipitation observations over a 16 year period for 85 Swedish, and 84 Norwegian weather stations. The misclassified precipitation (error) from PPDS using AT, dew-point temperature (DT) and wet-bulb temperature (WB) thresholds were compared using a single threshold PPDS. The Norwegian observations between -3 and 5°C resulted in 11.64%, 11.21%, and 8.42% error for DT (-0.2°C), AT (1.2°C), and WB (0.3°C) thresholds respectively. Individual station thresholds had a range of -0.7 to 1.2°C, -1.2 to 0.9°C, and -0.1 to 2.5°C for WB, DP, and AT respectively. To address threshold variance while decreasing error, weather stations were grouped into nine landscape categories; windward (WW) ocean, WW coast, WW fjord, WW hill, WW mountain, leeward (LW) mountain, LW hill, LW rolling hills, and LW coast. Landscape classification was based on location relative to the Scandinavian Mountains, and the % water or range of elevation within 15KM. Within landscapes, stations share similar land atmosphere exchanges which differ from other landscapes. These differences change optimal thresholds for PPDS between landscapes. Also tested were threshold temperature affects based on assumed atmospheric differences for the following observation groups; 1.) occurring before and after an air mass boundary, 2.) with different water temperatures and/or NAO phases, 3.) with snow cover, 4.) coupled with higher elevation stations and 5.) with different cloud heights. For example, in Norway, as the unsaturated layer depth beneath clouds increased, AT thresholds warmed. Cloud height adjusted AT thresholds reduced error by 5% before threshold adjustments for landscapes.

The COST733 circulation type classification software: an example for surface ozone concentrations in Central Europe

NASA Astrophysics Data System (ADS)

Demuzere, Matthias; Kassomenos, P.; Philipp, A.

2011-08-01

In the framework of the COST733 Action "Harmonisation and Applications of Weather Types Classifications for European Regions" a new circulation type classification software (hereafter, referred to as cost733class software) is developed. The cost733class software contains a variety of (European) classification methods and is flexible towards choice of domain of interest, input variables, time step, number of circulation types, sequencing and (weighted) target variables. This work introduces the capabilities of the cost733class software in which the resulting circulation types (CTs) from various circulation type classifications (CTCs) are applied on observed summer surface ozone concentrations in Central Europe. Firstly, the main characteristics of the CTCs in terms of circulation pattern frequencies are addressed using the baseline COST733 catalogue (cat 2.0), at present the latest product of the new cost733class software. In a second step, the probabilistic Brier skill score is used to quantify the explanatory power of all classifications in terms of the maximum 8 hourly mean ozone concentrations exceeding the 120-μg/m3 threshold; this was based on ozone concentrations from 130 Central European measurement stations. Averaged evaluation results over all stations indicate generally higher performance of CTCs with a higher number of types. Within the subset of methodologies with a similar number of types, the results suggest that the use of CTCs based on optimisation algorithms are performing slightly better than those which are based on other algorithms (predefined thresholds, principal component analysis and leader algorithms). The results are further elaborated by exploring additional capabilities of the cost733class software. Sensitivity experiments are performed using different domain sizes, input variables, seasonally based classifications and multiple-day sequencing. As an illustration, CTCs which are also conditioned towards temperature with various weights are derived and tested similarly. All results exploit a physical interpretation by adapting the environment-to-circulation approach, providing more detailed information on specific synoptic conditions prevailing on days with high surface ozone concentrations. This research does not intend to bring forward a favourite classification methodology or construct a statistical ozone forecasting tool but should be seen as an introduction to the possibilities of the cost733class software. It this respect, the results presented here can provide a basic user support for the cost733class software and the development of a more user- or application-specific CTC approach.

Space Station power system autonomy demonstration

NASA Technical Reports Server (NTRS)

Kish, James A.; Dolce, James L.; Weeks, David J.

1988-01-01

The Systems Autonomy Demonstration Program (SADP) represents NASA's major effort to demonstrate, through a series of complex ground experiments, the application and benefits of applying advanced automation technologies to the Space Station project. Lewis Research Center (LeRC) and Marshall Space Flight Center (MSFC) will first jointly develop an autonomous power system using existing Space Station testbed facilities at each center. The subsequent 1990 power-thermal demonstration will then involve the cooperative operation of the LeRC/MSFC power system with the Johnson Space Center (JSC's) thermal control and DMS/OMS testbed facilities. The testbeds and expert systems at each of the NASA centers will be interconnected via communication links. The appropriate knowledge-based technology will be developed for each testbed and applied to problems requiring intersystem cooperation. Primary emphasis will be focused on failure detection and classification, system reconfiguration, planning and scheduling of electrical power resources, and integration of knowledge-based and conventional control system software into the design and operation of Space Station testbeds.

Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar.

PubMed

Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

2016-09-29

The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar

PubMed Central

Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

2016-01-01

The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications. PMID:27690051

Assessment of mesoscale convective systems using IR brightness temperature in the southwest of Iran

NASA Astrophysics Data System (ADS)

Rafati, Somayeh; Karimi, Mostafa

2017-07-01

In this research, the spatial and temporal distribution of Mesoscale Convective Systems was assessed in the southwest of Iran using Global merged satellite IR brightness temperature (acquired from Meteosat, GOES, and GMS geostationary satellites) and synoptic station data. Event days were selected using a set of storm reports and precipitation criteria. The following criteria are used to determine the days with occurrence of convective systems: (1) at least one station reported 6-h precipitation exceeding 10 mm and (2) at least three stations reported phenomena related to convection (thunderstorm, lightning, and shower). MCSs were detected based on brightness temperature, maximum areal extent, and duration thresholds (228 K, 10,000 km2, and 3 h, respectively). An MCS occurrence classification system is developed based on mean sea level, 850 and 500 hPa pressure patterns.

Seismic velocity site characterization of 10 Arizona strong-motion recording stations by spectral analysis of surface wave dispersion

USGS Publications Warehouse

Kayen, Robert E.; Carkin, Brad A.; Corbett, Skye C.

2017-10-19

Vertical one-dimensional shear wave velocity (VS) profiles are presented for strong-motion sites in Arizona for a suite of stations surrounding the Palo Verde Nuclear Generating Station. The purpose of the study is to determine the detailed site velocity profile, the average velocity in the upper 30 meters of the profile (VS30), the average velocity for the entire profile (VSZ), and the National Earthquake Hazards Reduction Program (NEHRP) site classification. The VS profiles are estimated using a non-invasive continuous-sine-wave method for gathering the dispersion characteristics of surface waves. Shear wave velocity profiles were inverted from the averaged dispersion curves using three independent methods for comparison, and the root-mean-square combined coefficient of variation (COV) of the dispersion and inversion calculations are estimated for each site.

Research on Classification of Chinese Text Data Based on SVM

NASA Astrophysics Data System (ADS)

Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

2017-09-01

Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

Classification criteria and probability risk maps: limitations and perspectives.

PubMed

Saisana, Michaela; Dubois, Gregoire; Chaloulakou, Archontoula; Spyrellis, Nikolas

2004-03-01

Delineation of polluted zones with respect to regulatory standards, accounting at the same time for the uncertainty of the estimated concentrations, relies on classification criteria that can lead to significantly different pollution risk maps, which, in turn, can depend on the regulatory standard itself. This paper reviews four popular classification criteria related to the violation of a probability threshold or a physical threshold, using annual (1996-2000) nitrogen dioxide concentrations from 40 air monitoring stations in Milan. The relative advantages and practical limitations of each criterion are discussed, and it is shown that some of the criteria are more appropriate for the problem at hand and that the choice of the criterion can be supported by the statistical distribution of the data and/or the regulatory standard. Finally, the polluted area is estimated over the different years and concentration thresholds using the appropriate risk maps as an additional source of uncertainty.

Statistical Downscaling Of Local Climate In The Alpine Region

NASA Astrophysics Data System (ADS)

Kaspar, Severin; Philipp, Andreas; Jacobeit, Jucundus

2016-04-01

The impact of climate change on the alpine region was disproportional strong in the past decades compared to the surrounding areas, which becomes manifest in a higher increase in surface air temperature. Beside the thermal changes also implications for the hydrological cycle may be expected, acting as a very important factor not only for the ecosystem but also for mankind, in the form of water security or considering economical aspects like winter tourism etc. Therefore, in climate impact studies, it is necessary to focus on variables with high influence on the hydrological cycle, for example temperature, precipitation, wind, humidity and radiation. The aim of this study is to build statistical downscaling models which are able to reproduce temperature and precipitation at the mountainous alpine weather stations Zugspitze and Sonnblick and to further project these models into the future to identify possible changes in the behavior of these climate variables and with that in the hydrological cycle. Beside facing a in general very complex terrain in this high elevated regions, we have the advantage of a more direct atmospheric influence on the meteorology of the exposed weather stations from the large scale circulation. Two nonlinear statistical methods are developed to model the station-data series on a daily basis: On the one hand a conditional classification approach was used and on the other hand a model based on artificial neural networks (ANNs) was built. The latter is in focus of this presentation. One of the important steps of developing a new model approach is to find a reliable predictor setup with e.g. informative predictor variables or adequate location and size of the spatial domain. The question is: Can we include synoptic background knowledge to identify an optimal domain for an ANN approach? The yet developed ANN setups and configurations show promising results in downscaling both, temperature (up to 80 % of explained variance) and precipitation (up to 60 % of explained variance).

Protect children from EMF.

PubMed

Markov, M; Grigoriev, Y

2015-09-01

The twenty-first century is marked with aggressive development of the wireless communications (satellite, mobile phones, Internet, Wi-Fi). In addition to thousand of satellites that deliver radio and TV signals, large satellite and base station networks secure intensive instant delivery of audio and video information. It is fair to say that that the entire civilization, both biosphere and mankind are exposed to continuous exposure of multitude of radiofrequency (RF) signals. It should be taken into account that the entire world population is exposed to exponentially increasing RF radiation from base stations and satellite antennas. While several years ago the potential hazard was connected with placement of mobile phones close to human head, today "smart phones" represent small, but powerful computers continuously receiving audio and video data. The largest group of users is the children and teenagers who "need" to communicate nearly 24 h a day. This is even more important because cell phones and tablets may be seen in the hands of children as little as two years in age. There is no way to assess and predict the potential damages of children brain, vision and hearing under exposure to RF radiation. The WHO precautionary principle and IARC classification must be applied in discussing the potential hazard of the use of today's and tomorrow's communication devices.

Extraction and visualization of the central chest lymph-node stations

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Merritt, Scott A.; Higgins, William E.

2008-03-01

Lung cancer remains the leading cause of cancer death in the United States and is expected to account for nearly 30% of all cancer deaths in 2007. Central to the lung-cancer diagnosis and staging process is the assessment of the central chest lymph nodes. This assessment typically requires two major stages: (1) location of the lymph nodes in a three-dimensional (3D) high-resolution volumetric multi-detector computed-tomography (MDCT) image of the chest; (2) subsequent nodal sampling using transbronchial needle aspiration (TBNA). We describe a computer-based system for automatically locating the central chest lymph-node stations in a 3D MDCT image. Automated analysis methods are first run that extract the airway tree, airway-tree centerlines, aorta, pulmonary artery, lungs, key skeletal structures, and major-airway labels. This information provides geometrical and anatomical cues for localizing the major nodal stations. Our system demarcates these stations, conforming to criteria outlined for the Mountain and Wang standard classification systems. Visualization tools within the system then enable the user to interact with these stations to locate visible lymph nodes. Results derived from a set of human 3D MDCT chest images illustrate the usage and efficacy of the system.

Station Set Residual: Event Classification Using Historical Distribution of Observing Stations

NASA Astrophysics Data System (ADS)

Procopio, Mike; Lewis, Jennifer; Young, Chris

2010-05-01

Analysts working at the International Data Centre in support of treaty monitoring through the Comprehensive Nuclear-Test-Ban Treaty Organization spend a significant amount of time reviewing hypothesized seismic events produced by an automatic processing system. When reviewing these events to determine their legitimacy, analysts take a variety of approaches that rely heavily on training and past experience. One method used by analysts to gauge the validity of an event involves examining the set of stations involved in the detection of an event. In particular, leveraging past experience, an analyst can say that an event located in a certain part of the world is expected to be detected by Stations A, B, and C. Implicit in this statement is that such an event would usually not be detected by Stations X, Y, or Z. For some well understood parts of the world, the absence of one or more "expected" stations—or the presence of one or more "unexpected" stations—is correlated with a hypothesized event's legitimacy and to its survival to the event bulletin. The primary objective of this research is to formalize and quantify the difference between the observed set of stations detecting some hypothesized event, versus the expected set of stations historically associated with detecting similar nearby events close in magnitude. This Station Set Residual can be quantified in many ways, some of which are correlated with the analysts' determination of whether or not the event is valid. We propose that this Station Set Residual score can be used to screen out certain classes of "false" events produced by automatic processing with a high degree of confidence, reducing the analyst burden. Moreover, we propose that the visualization of the historically expected distribution of detecting stations can be immediately useful as an analyst aid during their review process.

A Classification Methodology and Retrieval Model to Support Software Reuse

DTIC Science & Technology

1988-01-01

Dewey Decimal Classification ( DDC 18), an enumerative scheme, occupies 40 pages [Buchanan 19791. Langridge [19731 states that the facets listed in the...sense of historical importance or wide spread use. The schemes are: Dewey Decimal Classification ( DDC ), Universal Decimal Classification (UDC...Classification Systems ..... ..... 2.3.3 Library Classification__- .52 23.3.1 Dewey Decimal Classification -53 2.33.2 Universal Decimal Classification 55 2333

IET. Fuel transfer pumping building (TAN625). Elevations, foundation. Detail of ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

IET. Fuel transfer pumping building (TAN-625). Elevations, foundation. Detail of access stairway to coupling station. Ralph M. Parsons 902-a-ANY-620-625-A&S 414. Date: February 1954. Approved by INEEL Classification Office for public release. INEEL index code no. 035-0625-00-693-106971 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

Combating Tobacco Use in the United States Army

DTIC Science & Technology

2010-04-01

videogame , tobacco use, military. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE... videogame is theory-guided and uses animations, videos and interactive activities to provide facts about smoking and tobacco use, as well as provides...prevention and cessation interactive multimedia tool ( videogame ) among active Army personnel stationed at Fort Hood, Texas. Body Throughout the

Autonomous power management and distribution

NASA Technical Reports Server (NTRS)

Dolce, Jim; Kish, Jim

1990-01-01

The goal of the Autonomous Power System program is to develop and apply intelligent problem solving and control to the Space Station Freedom's electric power testbed being developed at NASA's Lewis Research Center. Objectives are to establish artificial intelligence technology paths, craft knowledge-based tools and products for power systems, and integrate knowledge-based and conventional controllers. This program represents a joint effort between the Space Station and Office of Aeronautics and Space Technology to develop and demonstrate space electric power automation technology capable of: (1) detection and classification of system operating status, (2) diagnosis of failure causes, and (3) cooperative problem solving for power scheduling and failure recovery. Program details, status, and plans will be presented.

A Features Selection for Crops Classification

NASA Astrophysics Data System (ADS)

Liu, Yifan; Shao, Luyi; Yin, Qiang; Hong, Wen

2016-08-01

The components of the polarimetric target decomposition reflect the differences of target since they linked with the scattering properties of the target and can be imported into SVM as the classification features. The result of decomposition usually concentrate on part of the components. Selecting a combination of components can reduce the features that importing into the SVM. The features reduction can lead to less calculation and targeted classification of one target when we classify a multi-class area. In this research, we import different combinations of features into the SVM and find a better combination for classification with a data of AGRISAR.

Classifying Life, Reconstructing History and Teaching Diversity: Philosophical Issues in the Teaching of Biological Systematics and Biodiversity

NASA Astrophysics Data System (ADS)

Reydon, Thomas A. C.

2013-02-01

Classification is a central endeavor in every scientific field of work. Classification in biology, however, is distinct from classification in other fields of science in a number of ways. Thus, understanding how biological classification works is an important element in understanding the nature of biological science. In the present paper, I discuss a number of philosophical issues that are characteristic for classification in biological science, paying special attention to questions related to science education. My aims are (1) to provide science educators and others concerned with the teaching of biology with an accessible overview of the philosophy of biological classification and (2) to show how knowledge of the philosophy of classification can play an important role in science teaching.

Temporal water quality response in an urban river: a case study in peninsular Malaysia

NASA Astrophysics Data System (ADS)

VishnuRadhan, Renjith; Zainudin, Zaki; Sreekanth, G. B.; Dhiman, Ravinder; Salleh, Mohd. Noor; Vethamony, P.

2017-05-01

Ambient water quality is a prerequisite for the health and self-purification capacity of riverine ecosystems. To understand the general water quality situation, the time series data of selected water quality parameters were analyzed in an urban river in Peninsular Malaysia. In this regard, the stations were selected from the main stem of the river as well as from the side channel. The stations located at the main stem of the river are less polluted than that in the side channel. Water Quality Index scores indicated that the side channel station is the most polluted, breaching the Class IV water quality criteria threshold during the monitoring period, followed by stations at the river mouth and the main channel. The effect of immediate anthropogenic waste input is also evident at the side channel station. The Organic Pollution Index of side channel station is (14.99) 3 times higher than at stations at river mouth (4.11) and 6 times higher than at the main channel (2.57). The two-way ANOVA showed significant difference among different stations. Further, the factor analysis on water quality parameters yielded two significant factors. They discriminated the stations into two groups. The land-use land cover classification of the study area shows that the region near the sampling sites is dominated by urban settlements (33.23 %) and this can contribute significantly to the deterioration of ambient river water quality. The present study estimated the water quality condition and response in the river and the study can be an immediate yardstick for base lining river water quality, and a basis for future water quality modeling studies in the region.

High Dimensional Classification Using Features Annealed Independence Rules.

PubMed

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

16 CFR 1402.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Practices CONSUMER PRODUCT SAFETY COMMISSION CONSUMER PRODUCT SAFETY ACT REGULATIONS CB BASE STATION... (including importers) of Citizens Band (CB) base station antennas, outdoor television (TV) antennas, and... importer, after September 26, 1978. (1) Antennas designed or intended to be used as outdoor CB base station...

Teaching Classification To Fit a Modern and Sustainable LIS Curriculum: The Case of Croatia.

ERIC Educational Resources Information Center

Slavic, Aida

Library classification at the Croatian library school of the Department of Information Sciences, University of Zagreb (Croatia) has an important place in the department's curriculum. This is due to the fact that classification is the most important indexing language in Croatian libraries and documentation centers and services, and its role has not…

Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

NASA Technical Reports Server (NTRS)

Goncalves, Fabio G.; Yatskov, Mikhail; dos Santos, Joao Roberto; Treuhaft, Robert N.; Law, Beverly E.

2010-01-01

In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

The classification of PM10 concentrations in Johor Based on Seasonal Monsoons

NASA Astrophysics Data System (ADS)

Hamid, Hazrul Abdul; Hanafi Rahmat, Muhamad; Aisyah Sapani, Siti

2018-04-01

Air is the most important living resource in life. Contaminated air could adversely affect human health and the environment, especially during the monsoon season. Contamination occurs as a result of human action and haze. There are several pollutants present in the air where one of them is PM10. Secondary data was obtained from the Department of Environment from 2010 until 2014 and was analyzed using the hourly average of PM10 concentrations. This paper examined the relation between PM10 concentrations and the monsoon seasons (Northeast Monsoon and Southwest Monsoon) in Larkin and Pasir Gudang. It was expected that the concentration of PM10 would be higher during the Southwest Monsoon as it is a dry season. The data revealed that the highest PM10 concentrations were recorded between 2010 to 2014 during this particular monsoon season. The characteristics of PM10 concentration were compared using descriptive statistics based on the monsoon seasons and classified using the hierarchical cluster analysis (Ward Methods). The annual average of PM10 concentration during the Southwest Monsoon had exceeded the standard set by the Malaysia Ambient Air Quality Guidelines (50 μg/m3) while the PM10 concentration during the Northeast Monsoon was below the acceptable level for both stations. The dendrogram displayed showed two clusters for each monsoon season for both stations excepted for the PM10 concentration during the Northeast Monsoon in Larkin which was classified into three clusters due to the haze in 2010. Overall, the concentration of PM10 in 2013 was higher based on the clustering shown for every monsoon season at both stations according to the characteristics in the descriptive statistics.

Spatio-temporal atmospheric circulation variability around the Antarctic Peninsula based on hemispheric circulation modes and weather types

NASA Astrophysics Data System (ADS)

Wachter, Paul; Beck, Christoph; Philipp, Andreas; Jacobeit, Jucundus; Höppner, Kathrin

2017-04-01

Large parts of the Polar Regions are affected by a warming trend associated with substantial changes in the cryosphere. In Antarctica this positive trend pattern is most dominant in the western part of the continent and on the Antarctic Peninsula (AP). An important driving mechanism of temperature variability and trends in this region is the atmospheric circulation. Changes in atmospheric circulation modes and frequencies of circulation types have major impacts on temperature characteristics at a certain station or region. We present results of a statistical downscaling study focused on AP temperature variability showing both results of large-scale atmospheric circulation modes and regional weather type classifications derived from monthly and daily gridded reanalysis data sets. In order to investigate spatial trends and variabilities of the Southern Annular Mode (SAM), we analyze spatio-temporally resolved SAM-pattern maps from 1979 to 2015. First results show dominant multi-annual to decadal pattern variabilities which can be directly linked to temperature variabilities at the Antarctic Peninsula. A sub-continental to regional view on the influence of atmospheric circulation on AP temperature variability is given by the analysis of weather type classifications (WTC). With this analysis we identify significant changes in the frequency of occurrence of highly temperature-relevant circulation patterns. The investigated characteristics of weather type frequencies can also be related to the identified changes of the SAM.

A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin.

PubMed

Wu, Bingfang; Liu, Shufu; Zhu, Weiwei; Yu, Mingzhao; Yan, Nana; Xing, Qiang

2016-11-04

Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index-FY-2D cloud type sunshine factor-is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration.

A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin

PubMed Central

Wu, Bingfang; Liu, Shufu; Zhu, Weiwei; Yu, Mingzhao; Yan, Nana; Xing, Qiang

2016-01-01

Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index—FY-2D cloud type sunshine factor—is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration. PMID:27827935

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D.; Kiem, A. S.

2008-10-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

A fast topographic characterization of seismic station locations in Iran through integrated use of digital elevation models and GIS

NASA Astrophysics Data System (ADS)

Karimzadeh, Sadra; Miyajima, Masakatsu; Kamel, Batoul; Pessina, Vera

2015-10-01

We present topographic slope positions of seismic stations within four independent networks (IGUT, IIEES, GSI, and BHRC) in Iran through integrated use of digital elevation models and GIS. Since topographic amplification factor (TAF) due to ground surface irregularity could be one of the reasons of earthquake wave amplification and unexpected damage of structures located on the top of ridges in many previous studies, the ridge stations in the study area are recognized using topographic position index (TPI) as a spatial-based scale-dependent approach that helps in classification of topographic positions. We also present the correlation between local topographic positions and V {/s 30} along with Voronoi tiles of two networks (IGUT and IIEES). The obtained results can be profitably used in seismology to establish homogeneous subnetworks based on Voronoi tiles with precise feedback and in the formulation of new ground motion prediction equations with respect to topographic position and topographic amplification factor.

Seismogenic structures activated during the pre-eruptive and intrusive swarms of Piton de la Fournaise volcano (La Réunion island) between 2008 and 2011

NASA Astrophysics Data System (ADS)

Battaglia, J.; Brenguier, F.

2011-12-01

Piton de la Fournaise is a frequently active basaltic volcano with more than 30 fissure eruptions since 1998. These eruptions are always preceded by pre-eruptive swarms of volcano-tectonic earthquakes which accompany dike propagation. Occasionally, intrusion swarms occur without leading to any eruption. From October 2008 to May 2011, as part of the research project Undervolc, a temporary network of 15 broadband stations has been installed on the volcano to complement the local monitoring network. We examined in detail the 6 intrusive and 5 pre-eruptive swarms which occurred during the temporary experiment. All the crises lasted for a few hours and only included shallow events clustered below the summit craters, around and above sea level, showing no signs of deeper magma transfers. These characteristics are common to most swarms observed at Piton de la Fournaise arising questions about the origin of the seismicity which seems to be poorly linked with dike propagation. With the aim to identify the main seismogenic structures active during the swarms, we applied precise earthquake detection and classification techniques based on waveform cross-correlation. For each swarm, the onsets of all transients, including small amplitude ones, have been precisely detected at a single station by scanning the continuous data with reference waveforms. The classification of the detected transients indicates the presence of several families of similar earthquakes. The two main families (F01 and F02) include several hundred events. They are systematically activated at the beginning of each pre-eruptive swarm but are inactive during the intrusive ones. They group more than 50 percent of the detected events for the corresponding crises. The other clusters are mostly associated with single swarms. To determine the spatial characteristics of the structures corresponding to the main families, we applied precise relocation techniques. Based on the one-station classification, the events have first been picked at all available stations by cross-correlating waveforms with those of master events whose arrival times have been manually determined. All events have been located using a 3D velocity model to determine accurate hypocentral azimuths and take-off angles. Precise relative locations have been computed for each multiplet using cross-correlation delays calculated for all available stations between all pairs of events. The results indicate the presence at sea level of a major structure grouping families F01 and F02 and describing an East-West elongated pattern with sub-vertical extension. Small scale earthquake migrations, mostly horizontal, occur during the pre-eruptive swarms along that structure. The smaller multiplets define vertically elongated patterns extending around and above the main F01-F02 multiplet. Our results show that different processes are involved in pre-eruptive and intrusive crises and that a structure located around 2.5 km below the summit controls the occurrence of recent eruptions of Piton de la Fournaise volcano.

Automated Terrestrial EMI Emitter Detection, Classification, and Localization

NASA Astrophysics Data System (ADS)

Stottler, R.; Ong, J.; Gioia, C.; Bowman, C.; Bhopale, A.

Clear operating spectrum at ground station antenna locations is critically important for communicating with, commanding, controlling, and maintaining the health of satellites. Electro Magnetic Interference (EMI) can interfere with these communications, so it is extremely important to track down and eliminate sources of EMI. The Terrestrial RFI-locating Automation with CasE based Reasoning (TRACER) system is being implemented to automate terrestrial EMI emitter localization and identification to improve space situational awareness, reduce manpower requirements, dramatically shorten EMI response time, enable the system to evolve without programmer involvement, and support adversarial scenarios such as jamming. The operational version of TRACER is being implemented and applied with real data (power versus frequency over time) for both satellite communication antennas and sweeping Direction Finding (DF) antennas located near them. This paper presents the design and initial implementation of TRACER’s investigation data management, automation, and data visualization capabilities. TRACER monitors DF antenna signals and detects and classifies EMI using neural network technology, trained on past cases of both normal communications and EMI events. When EMI events are detected, an Investigation Object is created automatically. The user interface facilitates the management of multiple investigations simultaneously. Using a variant of the Friis transmission equation, emissions data is used to estimate and plot the emitter’s locations over time for comparison with current flights. The data is also displayed on a set of five linked graphs to aid in the perception of patterns spanning power, time, frequency, and bearing. Based on details of the signal (its classification, direction, and strength, etc.), TRACER retrieves one or more cases of EMI investigation methodologies which are represented as graphical behavior transition networks (BTNs). These BTNs can be edited easily, and they naturally represent the flow-chart-like process often followed by experts in time pressured situations.

12 CFR 403.4 - Derivative classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 5 2014-01-01 2014-01-01 false Derivative classification. 403.4 Section 403.4 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative...

12 CFR 403.4 - Derivative classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 12 Banks and Banking 5 2013-01-01 2013-01-01 false Derivative classification. 403.4 Section 403.4 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative...

Estimating Classification Consistency and Accuracy for Cognitive Diagnostic Assessment

ERIC Educational Resources Information Center

Cui, Ying; Gierl, Mark J.; Chang, Hua-Hua

2012-01-01

This article introduces procedures for the computation and asymptotic statistical inference for classification consistency and accuracy indices specifically designed for cognitive diagnostic assessments. The new classification indices can be used as important indicators of the reliability and validity of classification results produced by…

12 CFR 403.4 - Derivative classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 5 2012-01-01 2012-01-01 false Derivative classification. 403.4 Section 403.4 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative...

12 CFR 403.4 - Derivative classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 4 2011-01-01 2011-01-01 false Derivative classification. 403.4 Section 403.4 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative...

LPT. Shield test facility (TAN645 and 646). Sections show relationships ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

LPT. Shield test facility (TAN-645 and -646). Sections show relationships among control rooms, coupling station, counting rooms, pools, equipment rooms, data room and other areas. Ralph M. Parsons 1229-17 ANP/GE-6-645-A-4. April 1957. Approved by INEEL Classification Office for public release. INEEL index code no. 037-0645/0646-00-693-107350 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

VS30, site amplifications and some comparisons: The Adapazari (Turkey) case

NASA Astrophysics Data System (ADS)

Ozcep, Tazegul; Ozcep, Ferhat; Ozel, Oguz

The aim of this study was to investigate the role of VS30 in site amplifications in the Adapazari region, Turkey. To fulfil this aim, amplifications from VS30 measurements were compared with earthquake data for different soil types in the seismic design codes. The Adapazari area was selected as the study area, and shear-wave velocity distribution was obtained by the multichannel analysis of surface waves (MASWs) method at 100 sites for the top 50 m of soil. Aftershock data following the Mw 7.4 Izmit earthquake of 17 August 1999 gave magnitudes between 4.0 and 5.6 at six stations installed in and around the Adapazari Basin, at Babalı, Şeker, Genç, Hastane, Toyota and Imar. This data was used to estimate site amplifications by the reference-station method. In addition, the fundamental periods of the station sites were estimated by the single station method. Site classifications based on VS30 in the seismic design codes were compared with the fundamental periods and amplification values. It was found that site amplifications (from earthquake data) and relevant spectra (from VS30) are not in good agreement for soils in Adapazari (Turkey).

A novel hazard assessment method for biomass gasification stations based on extended set pair analysis

PubMed Central

Yan, Fang; Xu, Kaili; Li, Deshun; Cui, Zhikai

2017-01-01

Biomass gasification stations are facing many hazard factors, therefore, it is necessary to make hazard assessment for them. In this study, a novel hazard assessment method called extended set pair analysis (ESPA) is proposed based on set pair analysis (SPA). However, the calculation of the connection degree (CD) requires the classification of hazard grades and their corresponding thresholds using SPA for the hazard assessment. In regard to the hazard assessment using ESPA, a novel calculation algorithm of the CD is worked out when hazard grades and their corresponding thresholds are unknown. Then the CD can be converted into Euclidean distance (ED) by a simple and concise calculation, and the hazard of each sample will be ranked based on the value of ED. In this paper, six biomass gasification stations are introduced to make hazard assessment using ESPA and general set pair analysis (GSPA), respectively. By the comparison of hazard assessment results obtained from ESPA and GSPA, the availability and validity of ESPA can be proved in the hazard assessment for biomass gasification stations. Meanwhile, the reasonability of ESPA is also justified by the sensitivity analysis of hazard assessment results obtained by ESPA and GSPA. PMID:28938011

Credit Risk Evaluation Using a C-Variable Least Squares Support Vector Classification Model

NASA Astrophysics Data System (ADS)

Yu, Lean; Wang, Shouyang; Lai, K. K.

Credit risk evaluation is one of the most important issues in financial risk management. In this paper, a C-variable least squares support vector classification (C-VLSSVC) model is proposed for credit risk analysis. The main idea of this model is based on the prior knowledge that different classes may have different importance for modeling and more weights should be given to those classes with more importance. The C-VLSSVC model can be constructed by a simple modification of the regularization parameter in LSSVC, whereby more weights are given to the lease squares classification errors with important classes than the lease squares classification errors with unimportant classes while keeping the regularized terms in its original form. For illustration purpose, a real-world credit dataset is used to test the effectiveness of the C-VLSSVC model.

Polarimetric SAR image classification based on discriminative dictionary learning model

NASA Astrophysics Data System (ADS)

Sang, Cheng Wei; Sun, Hong

2018-03-01

Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

12 CFR 403.3 - Classification principles and authority.

Code of Federal Regulations, 2014 CFR

2014-01-01

... to any document is limited as follows and is nondelegable: Classification Classifier CONFIDENTIAL... 12 Banks and Banking 5 2014-01-01 2014-01-01 false Classification principles and authority. 403.3 Section 403.3 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION...

12 CFR 403.3 - Classification principles and authority.

Code of Federal Regulations, 2013 CFR

2013-01-01

... to any document is limited as follows and is nondelegable: Classification Classifier CONFIDENTIAL... 12 Banks and Banking 5 2013-01-01 2013-01-01 false Classification principles and authority. 403.3 Section 403.3 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION...

12 CFR 403.3 - Classification principles and authority.

Code of Federal Regulations, 2012 CFR

2012-01-01

... to any document is limited as follows and is nondelegable: Classification Classifier CONFIDENTIAL... 12 Banks and Banking 5 2012-01-01 2012-01-01 false Classification principles and authority. 403.3 Section 403.3 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION...

Marking Importance in Lectures: Interactive and Textual Orientation

ERIC Educational Resources Information Center

Deroey, Katrien L. B.

2015-01-01

This paper provides a comprehensive overview of lexicogrammatical markers of important lecture points and proposes a classification in terms of their interactive and textual orientation. The importance markers were extracted from the British Academic Spoken English corpus using corpus-driven and corpus-based methods. The classification is based on…

A Comparison of Two-Group Classification Methods

ERIC Educational Resources Information Center

Holden, Jocelyn E.; Finch, W. Holmes; Kelley, Ken

2011-01-01

The statistical classification of "N" individuals into "G" mutually exclusive groups when the actual group membership is unknown is common in the social and behavioral sciences. The results of such classification methods often have important consequences. Among the most common methods of statistical classification are linear discriminant analysis,…

Improving the mapping of crop types in the Midwestern U.S. by fusing Landsat and MODIS satellite data

NASA Astrophysics Data System (ADS)

Zhu, Likai; Radeloff, Volker C.; Ives, Anthony R.

2017-06-01

Mapping crop types is of great importance for assessing agricultural production, land-use patterns, and the environmental effects of agriculture. Indeed, both radiometric and spatial resolution of Landsat's sensors images are optimized for cropland monitoring. However, accurate mapping of crop types requires frequent cloud-free images during the growing season, which are often not available, and this raises the question of whether Landsat data can be combined with data from other satellites. Here, our goal is to evaluate to what degree fusing Landsat with MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data can improve crop-type classification. Choosing either one or two images from all cloud-free Landsat observations available for the Arlington Agricultural Research Station area in Wisconsin from 2010 to 2014, we generated 87 combinations of images, and used each combination as input into the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to predict Landsat-like images at the nominal dates of each 8-day MODIS NBAR product. Both the original Landsat and STARFM-predicted images were then classified with a support vector machine (SVM), and we compared the classification errors of three scenarios: 1) classifying the one or two original Landsat images of each combination only, 2) classifying the one or two original Landsat images plus all STARFM-predicted images, and 3) classifying the one or two original Landsat images together with STARFM-predicted images for key dates. Our results indicated that using two Landsat images as the input of STARFM did not significantly improve the STARFM predictions compared to using only one, and predictions using Landsat images between July and August as input were most accurate. Including all STARFM-predicted images together with the Landsat images significantly increased average classification error by 4% points (from 21% to 25%) compared to using only Landsat images. However, incorporating only STARFM-predicted images for key dates decreased average classification error by 2% points (from 21% to 19%) compared to using only Landsat images. In particular, if only a single Landsat image was available, adding STARFM predictions for key dates significantly decreased the average classification error by 4 percentage points from 30% to 26% (p < 0.05). We conclude that adding STARFM-predicted images can be effective for improving crop-type classification when only limited Landsat observations are available, but carefully selecting images from a full set of STARFM predictions is crucial. We developed an approach to identify the optimal subsets of all STARFM predictions, which gives an alternative method of feature selection for future research.

Behavior of a Large-Scale Pile Group Subjected to Cyclic Lateral Loading.

DTIC Science & Technology

1988-02-01

Unlimited DTIC " APR 1 3 1988 H Prepared for US Army Engineer Waterways Experiment Station PO Box 631, Vicksburg, Mississippi 39180-0631 LABORATO Under...not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval...of the use of such commercial products. ~5.ww~ .. - V ~ ~ *% *w %~ , , sr ’. .. - lr - Unrla Wipd SECURITY CLASSIFICATION OF THIS PAGE Form

A Matched Field Processing Framework for Coherent Detection Over Local and Regional Networks

DTIC Science & Technology

2011-06-01

Northern Finland Seismological Network, FN) and to the University of Helsinki for data from the VRF and HEF stations (part of the Finnish seismograph ...shows the results of classification with the FK measurement . Most of the events are incorrectly assigned to one particular mine (K2 – Rasvumchorr...generalization of the single-phase matched field processing method that encodes the full structure of the entire wavefield? What would this

Public Use Land Requirements, Tennessee Colony Lake.

DTIC Science & Technology

1972-03-30

source of pollution by oil and oil field brines. If these and existing gas fields continue to operate, oil -pumping and storage stations and oil and gas ...the lake and large numbers can be expected to visit this area. The land is in the middle of the Cayuga oil field and there are many oil and gas ...Project Area Geographic boundary and physiographic classification The Trinity River meanders south- southeast through Freestone, Anderson, Navarro and

Attribute-Level and Pattern-Level Classification Consistency and Accuracy Indices for Cognitive Diagnostic Assessment

ERIC Educational Resources Information Center

Wang, Wenyi; Song, Lihong; Chen, Ping; Meng, Yaru; Ding, Shuliang

2015-01-01

Classification consistency and accuracy are viewed as important indicators for evaluating the reliability and validity of classification results in cognitive diagnostic assessment (CDA). Pattern-level classification consistency and accuracy indices were introduced by Cui, Gierl, and Chang. However, the indices at the attribute level have not yet…

Per-field crop classification in irrigated agricultural regions in middle Asia using random forest and support vector machine ensemble

NASA Astrophysics Data System (ADS)

Löw, Fabian; Schorcht, Gunther; Michel, Ulrich; Dech, Stefan; Conrad, Christopher

2012-10-01

Accurate crop identification and crop area estimation are important for studies on irrigated agricultural systems, yield and water demand modeling, and agrarian policy development. In this study a novel combination of Random Forest (RF) and Support Vector Machine (SVM) classifiers is presented that (i) enhances crop classification accuracy and (ii) provides spatial information on map uncertainty. The methodology was implemented over four distinct irrigated sites in Middle Asia using RapidEye time series data. The RF feature importance statistics was used as feature-selection strategy for the SVM to assess possible negative effects on classification accuracy caused by an oversized feature space. The results of the individual RF and SVM classifications were combined with rules based on posterior classification probability and estimates of classification probability entropy. SVM classification performance was increased by feature selection through RF. Further experimental results indicate that the hybrid classifier improves overall classification accuracy in comparison to the single classifiers as well as useŕs and produceŕs accuracy.

Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery

NASA Astrophysics Data System (ADS)

Mahdianpari, Masoud; Salehi, Bahram; Mohammadimanesh, Fariba; Motagh, Mahdi

2017-08-01

Wetlands are important ecosystems around the world, although they are degraded due both to anthropogenic and natural process. Newfoundland is among the richest Canadian province in terms of different wetland classes. Herbaceous wetlands cover extensive areas of the Avalon Peninsula, which are the habitat of a number of animal and plant species. In this study, a novel hierarchical object-based Random Forest (RF) classification approach is proposed for discriminating between different wetland classes in a sub-region located in the north eastern portion of the Avalon Peninsula. Particularly, multi-polarization and multi-frequency SAR data, including X-band TerraSAR-X single polarized (HH), L-band ALOS-2 dual polarized (HH/HV), and C-band RADARSAT-2 fully polarized images, were applied in different classification levels. First, a SAR backscatter analysis of different land cover types was performed by training data and used in Level-I classification to separate water from non-water classes. This was followed by Level-II classification, wherein the water class was further divided into shallow- and deep-water classes, and the non-water class was partitioned into herbaceous and non-herbaceous classes. In Level-III classification, the herbaceous class was further divided into bog, fen, and marsh classes, while the non-herbaceous class was subsequently partitioned into urban, upland, and swamp classes. In Level-II and -III classifications, different polarimetric decomposition approaches, including Cloude-Pottier, Freeman-Durden, Yamaguchi decompositions, and Kennaugh matrix elements were extracted to aid the RF classifier. The overall accuracy and kappa coefficient were determined in each classification level for evaluating the classification results. The importance of input features was also determined using the variable importance obtained by RF. It was found that the Kennaugh matrix elements, Yamaguchi, and Freeman-Durden decompositions were the most important parameters for wetland classification in this study. Using this new hierarchical RF classification approach, an overall accuracy of up to 94% was obtained for classifying different land cover types in the study area.

Criteria for mitral regurgitation classification were inadequate for dilated cardiomyopathy.

PubMed

Mancuso, Frederico José Neves; Moisés, Valdir Ambrosio; Almeida, Dirceu Rodrigues; Oliveira, Wercules Antonio; Poyares, Dalva; Brito, Flavio Souza; Paola, Angelo Amato Vincenzo de; Carvalho, Antonio Carlos Camargo; Campos, Orlando

2013-11-01

Mitral regurgitation (MR) is common in patients with dilated cardiomyopathy (DCM). It is unknown whether the criteria for MR classification are inadequate for patients with DCM. We aimed to evaluate the agreement among the four most common echocardiographic methods for MR classification. Ninety patients with DCM were included. Functional MR was classified using four echocardiographic methods: color flow jet area (JA), vena contracta (VC), effective regurgitant orifice area (ERO) and regurgitant volume (RV). MR was classified as mild, moderate or important according to the American Society of Echocardiography criteria and by dividing the values into terciles. The Kappa test was used to evaluate whether the methods agreed, and the Pearson correlation coefficient was used to evaluate the correlation between the absolute values of each method. MR classification according to each method was as follows: JA: 26 mild, 44 moderate, 20 important; VC: 12 mild, 72 moderate, 6 important; ERO: 70 mild, 15 moderate, 5 important; RV: 70 mild, 16 moderate, 4 important. The agreement was poor among methods (kappa=0.11; p<0.001). It was observed a strong correlation between the absolute values of each method, ranging from 0.70 to 0.95 (p<0.01) and the agreement was higher when values were divided into terciles (kappa = 0.44; p < 0.01) CONCLUSION: The use of conventional echocardiographic criteria for MR classification seems inadequate in patients with DCM. It is necessary to establish new cutoff values for MR classification in these patients.

Criteria for Mitral Regurgitation Classification were inadequate for Dilated Cardiomyopathy

PubMed Central

Mancuso, Frederico José Neves; Moisés, Valdir Ambrosio; Almeida, Dirceu Rodrigues; Oliveira, Wercules Antonio; Poyares, Dalva; Brito, Flavio Souza; de Paola, Angelo Amato Vincenzo; Carvalho, Antonio Carlos Camargo; Campos, Orlando

2013-01-01

Background Mitral regurgitation (MR) is common in patients with dilated cardiomyopathy (DCM). It is unknown whether the criteria for MR classification are inadequate for patients with DCM. Objective We aimed to evaluate the agreement among the four most common echocardiographic methods for MR classification. Methods Ninety patients with DCM were included. Functional MR was classified using four echocardiographic methods: color flow jet area (JA), vena contracta (VC), effective regurgitant orifice area (ERO) and regurgitant volume (RV). MR was classified as mild, moderate or important according to the American Society of Echocardiography criteria and by dividing the values into terciles. The Kappa test was used to evaluate whether the methods agreed, and the Pearson correlation coefficient was used to evaluate the correlation between the absolute values of each method. Results MR classification according to each method was as follows: JA: 26 mild, 44 moderate, 20 important; VC: 12 mild, 72 moderate, 6 important; ERO: 70 mild, 15 moderate, 5 important; RV: 70 mild, 16 moderate, 4 important. The agreement was poor among methods (kappa = 0.11; p < 0.001). It was observed a strong correlation between the absolute values of each method, ranging from 0.70 to 0.95 (p < 0.01) and the agreement was higher when values were divided into terciles (kappa = 0.44; p < 0.01) Conclusion The use of conventional echocardiographic criteria for MR classification seems inadequate in patients with DCM. It is necessary to establish new cutoff values for MR classification in these patients. PMID:24100692

Comparison of benthic indices for the evaluation of ecological status of three Slovenian transitional water bodies (northern Adriatic).

PubMed

Pitacco, Valentina; Lipej, Lovrenc; Mavrič, Borut; Mistri, Michele; Munari, Cristina

2018-04-01

Benthic indicators are important tools for the classification of coastal and transitional water bodies. The aim of the work was to assess for the first time the Environmental Status (ES) of Slovenian transitional waters, comparing the following biotic indices: richness, Shannon-Weaver diversity, AMBI, M-AMBI, BENTIX and BITS indices. A total of 13 stations were sampled with a Van Veen grab, in three ecosystems in the northern Adriatic. Samples were sieved and sorted, invertebrates identified and counted. The anthropogenic impact was estimated with professional judgement. Richness and diversity showed a good response to anthropogenic pressure. Conversely, indices based on sensitivity/tolerance groups did not showed a clear distinction between more and less impacted ecosystems. In particular BENTIX underestimated the ES, while with BITS there was a overestimation. The best evaluation was obtained with M-AMBI, because even if based on a sensitivity/tolerance approach, it considered also the structural aspect of the community. Copyright © 2017 Elsevier Ltd. All rights reserved.

Remote sensing of surface currents with single shipborne high-frequency surface wave radar

NASA Astrophysics Data System (ADS)

Wang, Zhongbao; Xie, Junhao; Ji, Zhenyuan; Quan, Taifan

2016-01-01

High-frequency surface wave radar (HFSWR) is a useful technology for remote sensing of surface currents. It usually requires two (or more) stations spaced apart to create a two-dimensional (2D) current vector field. However, this method can only obtain the measurements within the overlapping coverage, which wastes most of the data from only one radar observation. Furthermore, it increases observation's costs significantly. To reduce the number of required radars and increase the ocean area that can be measured, this paper proposes an economical methodology for remote sensing of the 2D surface current vector field using single shipborne HFSWR. The methodology contains two parts: (1) a real space-time multiple signal classification (MUSIC) based on sparse representation and unitary transformation techniques is developed for measuring the radial currents from the spreading first-order spectra, and (2) the stream function method is introduced to obtain the 2D surface current vector field. Some important conclusions are drawn, and simulations are included to validate the correctness of them.

Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest

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

Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn

2016-07-15

Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifiermore » for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.« less

Review on Selection and Suitability of Rail Transit Station Design Pertaining to Public Safety

NASA Astrophysics Data System (ADS)

Akabal, Farah Mohd; Masirin, Mohd Idrus Haji Mohd; Abidin Akasah, Zainal; Rohani, Munzilah Md

2017-08-01

Railway has emerged as a fast, convenient, safe, clean, and low-cost alternative to air and road transportation. Many countries have invested in rail transportation. In America, Europe and Asia, large investments are planned for rail transportation. This is because congestion problems can be reduced with the introduction of rail transportation. Rail transportation involves several components which are important to ensure the smooth and safe delivery of services such as locomotives, rail stations and railway tracks. Rail transit stations are places where trains stop to pick-up and drop-off passengers. Stations are vital for many to enable them to engage in work and social commitments. This paper focuses only on the rail transit station as it is one of the important components in rail transportation. It is also considered as a key public meeting place and space for interactions in a community. The role of rail transit station and the requirements of a good rail transit station are also described in this paper. Steps in selecting the location of rail transit station include the function and facilities in rail transit station are discussed with reference to best practices and handbooks. Selection of the appropriate rail transit station locations may help users indirectly. In addition, this paper will also elucidate on the design considerations for an efficient and effective rail transit station. Design selections for the rail transit station must be balanced between aesthetic value and functional efficiency. The right design selection may help conserve energy, assure and facilitate consumers even thought a rail transit station plays a smaller role in attracting consumers compared to a shopping complex or a residential building. This will contribute towards better and greener building for a green transportation facility. Thus, with this paper it is expected to assist the relevant authority to identify important elements in the selection and determination of suitable rail transit station design for the future. It is also important to ensure the design is appropriate from the selection and suitability perspective as design and operation will assist to facilitate the success of the national rail network and encourage the public to use rail transit system. A conducive and neatly design railway station will not only add to the passenger experience but also, as a supporting facility to the economic, social and environmental benefits of the rail industry.

Assessing Wetland Hydroperiod and Soil Moisture With Remote Sensing: A Demonstration for the NASA Plum Brook Station Year 2

NASA Technical Reports Server (NTRS)

Brooks, Colin; Bourgeau-Chavez, Laura; Endres, Sarah; Battaglia, Michael; Shuchman, Robert

2015-01-01

Primary Goal: Assist with the evaluation and measuring of wetlands hydroperiod at the PlumBrook Station using multi-source remote sensing data as part of a larger effort on projecting climate change-related impacts on the station's wetland ecosystems. MTRI expanded on the multi-source remote sensing capabilities to help estimate and measure hydroperiod and the relative soil moisture of wetlands at NASA's Plum Brook Station. Multi-source remote sensing capabilities are useful in estimating and measuring hydroperiod and relative soil moisture of wetlands. This is important as a changing regional climate has several potential risks for wetland ecosystem function. The year two analysis built on the first year of the project by acquiring and analyzing remote sensing data for additional dates and types of imagery, combined with focused field work. Five deliverables were planned and completed: 1) Show the relative length of hydroperiod using available remote sensing datasets 2) Date linked table of wetlands extent over time for all feasible non-forested wetlands 3) Utilize LIDAR data to measure topographic height above sea level of all wetlands, wetland to catchment area radio, slope of wetlands, and other useful variables 4) A demonstration of how analyzed results from multiple remote sensing data sources can help with wetlands vulnerability assessment 5) A MTRI style report summarizing year 2 results. This report serves as a descriptive summary of our completion of these our deliverables. Additionally, two formal meetings were held with Larry Liou and Amanda Sprinzl to provide project updates and receive direction on outputs. These were held on 2/26/15 and 9/17/15 at the Plum Brook Station. Principal Component Analysis (PCA) is a multivariate statistical technique used to identify dominant spatial and temporal backscatter signatures. PCA reduces the information contained in the temporal dataset to the first few new Principal Component (PC) images. Some advantages of PCA include the ability to filter out temporal autocorrelation and reduce speckle to the higher order PC images. A PCA was performed using ERDAS Imagine on a time series of PALSAR dates. Hydroperiod maps were created by separating the PALSAR dates into two date ranges, 2006-2008 and 2010, and performing an unsupervised classification on the PCAs.

Seismic monitoring at Deception Island volcano (Antarctica): Recent advances

NASA Astrophysics Data System (ADS)

Carmona, E.; Almendros, J.; Martín, R.; Cortés, G.; Alguacil, G.; Moreno, J.; Martín, B.; Martos, A.; Serrano, I.; Stich, D.; Ibáñez, J. M.

2012-04-01

Deception Island (South Shetland Island, Antarctica) is an active volcano with recent eruptions (e.g. 1967, 1969 and 1970). It is also among the Antarctic sites most visited by tourists. Besides, there are currently two scientific bases operating during the austral summers, usually from late November to early March. For these reasons it is necessary to deploy a volcano monitoring system as complete as possible, designed specifically to endure the extreme conditions of the volcanic environment and the Antarctic climate. The Instituto Andaluz de Geofísica of University of Granada, Spain (IAG-UGR) performs seismic monitoring on Deception Island since 1994 during austral summer surveys. The seismicity basically includes volcano-tectonic earthquakes, long-period events and volcanic tremor, among other signals. The level of seismicity is moderate, except for a seismo-volcanic crisis in 1999. The seismic monitoring system has evolved during these years, following the trends of the technological developments and software improvements. Recent advances have been mainly focused on: (1) the improvement of the seismic network introducing broadband stations and 24-bit data acquisition systems; (2) the development of a short-period seismic array, with a 12-channel, 24-bit data acquisition system; (3) the implementation of wireless data transmission from the network stations and also from the seismic array to a recording center, allowing for real-time monitoring; (4) the efficiency of the power supply systems and the monitoring of the battery levels and power consumption; (5) the optimization of data analysis procedures, including database management, automated event recognition tools for the identification and classification of seismo-volcanic signals, and apparent slowness vector estimates using seismic array data; (6) the deployment of permanent seismic stations and the transmission of data during the winter using a satellite connection. A single permanent station is operating at Deception Island since 2008. In the current survey we collaborate with the Spanish Army to add another permanent station that will be able to send to the IAG-UGR seismic information about the activity of the volcano during the winter, using a communications satellite (SPAINSAT). These advances simplify the field work and the data acquisition procedures, and allow us to obtain high-quality seismic data in real-time. These improvements have a very important significance for a better and faster interpretation of the seismo-volcanic activity and assessment of the volcanic hazards at Deception Island volcano.

Effects of human activities and climate variability on water resources in the Saveh plain, Iran.

PubMed

Mohammadi Ghaleni, M; Ebrahimi, K

2015-02-01

Quantity and quality distribution of surface water and groundwater are changing under the impacts of both climate variability and human activities. The main goal of this paper is to evaluate the abovementioned impacts on the water resources in the Saveh plain, central Iran. To achieve this aim, spatial and temporal changes of the surface and groundwater quality and quantity have been analyzed, using hydrometric and meteorological data. The nonparametric Mann-Kendall test was used to identify trends and change points in the annual rainfall and runoff for the period of 1946 to 2011. In order to analyze the impacts of the Saveh Dam on runoff, the dam operation year, 1994, was considered as a change point. Mann-Kendall test results show that rainfall time series was divided into two parts, namely, 1966-1989 and 1990-2007, and averages of annual rainfall in five stations increase from 10 to 21 %. Also, runoff time series was divided into two parts, namely, 1946-1995 and 1996-2007 and averages of annual runoff in four stations decrease from 8 to 83 %. Results show that rainfall changes in Shahabasi, Razin, Jalayer, Emamabad, and Ahmadabad stations increased from 9 to 33 % before and after 1994. Nevertheless, runoff decreased from 24 to 81 %. The results indicate that the greatest lack of runoff between stations is at Shahabasi station and one important reason for the severe lack is operation of the Saveh Dam in 1994. Highest groundwater level decline, about 168.67 cm, occurred in 1994 that is the operation year of the Saveh Dam. Trend analysis of surface water quality show that electrical conductivity increased 957.34 μmho/cm before and after 1994. Also, the Wilcox water quality classification method has been reduced from C3-S1 to C4-S2. Average groundwater electrical conductivity (EC) during 1999-2003 and 2004-2009 increased to 89.6 μmho/cm. Also, the groundwater quality indices for agricultural usages are classified in four classes including, C4-S2 16, C4-S1 46, C3-S1 30, and C2-S1 8 % of the total aquifer area. In conclusion, in order to have a sustainable development, the effects of water projects on environment and water resources need to be predicted very carefully.

Land use/cover classification in the Brazilian Amazon using satellite images.

PubMed

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant'anna, Sidnei João Siqueira

2012-09-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Land use/cover classification in the Brazilian Amazon using satellite images

PubMed Central

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant’Anna, Sidnei João Siqueira

2013-01-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data. PMID:24353353

Land cover/use classification of Cairns, Queensland, Australia: A remote sensing study involving the conjunctive use of the airborne imaging spectrometer, the large format camera and the thematic mapper simulator

NASA Technical Reports Server (NTRS)

Heric, Matthew; Cox, William; Gordon, Daniel K.

1987-01-01

In an attempt to improve the land cover/use classification accuracy obtainable from remotely sensed multispectral imagery, Airborne Imaging Spectrometer-1 (AIS-1) images were analyzed in conjunction with Thematic Mapper Simulator (NS001) Large Format Camera color infrared photography and black and white aerial photography. Specific portions of the combined data set were registered and used for classification. Following this procedure, the resulting derived data was tested using an overall accuracy assessment method. Precise photogrammetric 2D-3D-2D geometric modeling techniques is not the basis for this study. Instead, the discussion exposes resultant spectral findings from the image-to-image registrations. Problems associated with the AIS-1 TMS integration are considered, and useful applications of the imagery combination are presented. More advanced methodologies for imagery integration are needed if multisystem data sets are to be utilized fully. Nevertheless, research, described herein, provides a formulation for future Earth Observation Station related multisensor studies.

Classifications for Cesarean Section: A Systematic Review

PubMed Central

Torloni, Maria Regina; Betran, Ana Pilar; Souza, Joao Paulo; Widmer, Mariana; Allen, Tomas; Gulmezoglu, Metin; Merialdi, Mario

2011-01-01

Background Rising cesarean section (CS) rates are a major public health concern and cause worldwide debates. To propose and implement effective measures to reduce or increase CS rates where necessary requires an appropriate classification. Despite several existing CS classifications, there has not yet been a systematic review of these. This study aimed to 1) identify the main CS classifications used worldwide, 2) analyze advantages and deficiencies of each system. Methods and Findings Three electronic databases were searched for classifications published 1968–2008. Two reviewers independently assessed classifications using a form created based on items rated as important by international experts. Seven domains (ease, clarity, mutually exclusive categories, totally inclusive classification, prospective identification of categories, reproducibility, implementability) were assessed and graded. Classifications were tested in 12 hypothetical clinical case-scenarios. From a total of 2948 citations, 60 were selected for full-text evaluation and 27 classifications identified. Indications classifications present important limitations and their overall score ranged from 2–9 (maximum grade = 14). Degree of urgency classifications also had several drawbacks (overall scores 6–9). Woman-based classifications performed best (scores 5–14). Other types of classifications require data not routinely collected and may not be relevant in all settings (scores 3–8). Conclusions This review and critical appraisal of CS classifications is a methodologically sound contribution to establish the basis for the appropriate monitoring and rational use of CS. Results suggest that women-based classifications in general, and Robson's classification, in particular, would be in the best position to fulfill current international and local needs and that efforts to develop an internationally applicable CS classification would be most appropriately placed in building upon this classification. The use of a single CS classification will facilitate auditing, analyzing and comparing CS rates across different settings and help to create and implement effective strategies specifically targeted to optimize CS rates where necessary. PMID:21283801

Increasing accuracy of vehicle detection from conventional vehicle detectors - counts, speeds, classification, and travel time.

DOT National Transportation Integrated Search

2014-09-01

Vehicle classification is an important traffic parameter for transportation planning and infrastructure : management. Length-based vehicle classification from dual loop detectors is among the lowest cost : technologies commonly used for collecting th...

19 CFR 141.90 - Notation of tariff classification and value on invoice.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Notation of tariff classification and value on... classification and value on invoice. (a) [Reserved] (b) Classification and rate of duty. The importer or customs... invoice value which have been made to arrive at the aggregate entered value. In addition, the entered unit...

It is time to bring borderline intellectual functioning back into the main fold of classification systems

PubMed Central

Wieland, Jannelien; Zitman, Frans G.

2016-01-01

Borderline intellectual functioning is an important and frequently unrecognised comorbid condition relevant to the diagnosis and treatment of any and all psychiatric disorders. In the DSM-IV-TR, it is defined by IQ in the 71–84 range. In DSM-5, IQ boundaries are no longer part of the classification, leaving the concept without a clear definition. This modification is one of the least highlighted changes in DSM-5. In this article we describe the history of the classification of borderline intellectual functioning. We provide information about it and on the importance of placing it in the right context and in the right place in future DSM editions and other classification systems such as the International Classification of Diseases. PMID:27512590

12 CFR 403.1 - General policies and definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 403.1 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND... the Export-Import Bank (the Bank) implements executive orders which govern the classification... the United States. (5) Confidential source means any individual or organization that has provided, or...

12 CFR 403.1 - General policies and definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 403.1 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND... the Export-Import Bank (the Bank) implements executive orders which govern the classification... the United States. (5) Confidential source means any individual or organization that has provided, or...

12 CFR 403.1 - General policies and definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 403.1 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND... the Export-Import Bank (the Bank) implements executive orders which govern the classification... the United States. (5) Confidential source means any individual or organization that has provided, or...

12 CFR 403.1 - General policies and definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 403.1 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND... the Export-Import Bank (the Bank) implements executive orders which govern the classification... the United States. (5) Confidential source means any individual or organization that has provided, or...

The Reliability of Galaxy Classifications by Citizen Scientists

NASA Astrophysics Data System (ADS)

Francis, Lennox; Kautsch, Stefan J.; Bizyaev, Dmitry

2017-01-01

Citizen scientists are becoming more and more important in helping professionals working through big data. An example in astronomy is crowdsourced galaxy classification. But how reliable are these classifications for studies of galaxy evolution? We present a tool in order to investigate those morphological classifications and test it on a diverse population on our campus. We observe a slight offset towards earlier Hubble types in the crowdsourced morphologies, when compared to professional classifications.

SAMPIE Measurements of the Space Station Plasma Current Analyzed

NASA Technical Reports Server (NTRS)

1996-01-01

In March of 1994, STS-62 carried the NASA Lewis Research Center's Solar Array Module Plasma Interactions Experiment (SAMPIE) into orbit, where it investigated the plasma current collected and the arcs from solar arrays and other space power materials immersed in the low-Earth-orbit space plasma. One of the important experiments conducted was the plasma current collected by a four-cell coupon sample of solar array cells for the international space station. The importance of this experiment dates back to the 1990 and 1991 meetings of the Space Station Electrical Grounding Tiger Team. The Tiger Team determined that unless the electrical potentials on the space station structure were actively controlled via a plasma contactor, the space station structure would arc into the plasma at a rate that would destroy the thermal properties of its surface coatings in only a few years of operation. The space station plasma contactor will control its potentials by emitting electrons into the surrounding low-Earth-orbit plasma at the same rate that they are collected by the solar arrays. Thus, the level at which the space station solar arrays can collect current is very important in verifying that the plasma contactor design can do its job.

Imaging and Forecasting of Ionospheric Structures and Their System Impacts

DTIC Science & Technology

2005-01-27

Radiation Belt Remediation (RBR) studies were done and many of them remain active. The results of two HAARP heating experiments with the digisonde at...LORERS, Plasmasphere, HAARP , Cal/Val, Drift Software, ARTIST 4.5 16. SECURITY CLASSIFICATION OF: 17. UMITATION OF 1. NUMBER 19a. NAME OF RESPONSIBLE...STATION OBSERVATIONS 1 1.3 VLF INDUCED ELECTRON PITCH ANGLE SCATTERING (IEPAS) 2 1.4 HAARP CAMPAIGN 2 1.5 DRIFT SOFTWARE DEVELOPMENT 2 1.6 DISS SUPPORT

List of Research Publications 1940-1980

DTIC Science & Technology

1981-10-01

comparison of the amount of tolerance for misplaced answers found in the GPO and the IBM machine-scored answer sheets. January 1942. (X6304) 1-18 A& .1...machine scoring of answer sheets. March 1942. The effect of the use of No. I pencils on the accuracy of scoring IBM answer sheets by machine. July 1942...X6427) 482 Hobbies - IBM code. 483 Relationship of Classification Test, R-I and WAC Classi- 4023 fication Test-2 for a recruiting station population

Bracing the Infantry’s Backbone for 21st Century Operations

DTIC Science & Technology

2010-04-27

TERMS Strategic Corporal, NCO Training and Education, Enlisted Retention. 16 . SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18. NUMBER ABSTRACT OF...Demographics and Why We Must Change .......... 9 Building the Backbone One Vertebrae at a Time: Fixing NCO Training and Education .. 16 Don’t Let a Good Thing...scorn of nearly everything on earth. .... They were the Leathernecks, the Old Timers: collected from ship’s guards and shore stations all over the

BRAC, What Will it Cost

DTIC Science & Technology

1992-04-10

Devens - Fort Huachuca FY 91 FY 95 Fort McClellan FY 92 FY 96 Fort Chaffee FY 92 FY 97 Cameron Station FY 91 FY 95 53 Stand Alone Housing Sites FY 90 FY...Army, Headquarters Forces Command, &as Realianment and Closure Implementation Plan - Fort Devens Closure Package, Implementation Plan, Fort McPherson, GA...Classification) RAC , What Will It Cost? 12. PERSONAL AUTHOR(S) TLIN, Robert B. LTC, USA 13. TYPE OF REPORT 13b. TIME COVERED 14. DATE OF REPORT (Year

A Climatic Classification for Citrus Winter Survival in China.

NASA Astrophysics Data System (ADS)

Shou, Bo Huang

1991-05-01

The citrus tree is susceptible to frost damage. Winter injury to citrus from freezing weather is the major meteorological problem in the northern pail of citrus growing regions in China. Based on meteorological data collected at 120 stations in southern China and on the extent of citrus freezing injury, five climatic regions for citrus winter survival in China were developed. They were: 1) no citrus tree injury. 2) light injury to mandarins (citrus reticulate) or moderate injury to oranges (citrus sinensis), 3) moderate injury to mandarins or heavy injury to oranges, 4) heavy injury to mandarins, and 5) impossible citrus tree growth. This citrus climatic classification was an attempt to provide guidelines for regulation of citrus production, to effectively utilize land and climatic resources, to chose suitable citrus varieties, and to develop methods to prevent injury by freezing.

EFFECT OF SITE ON BACTERIAL POPULATIONS IN THE SAPWOOD OF COARSE WOODY DEBRIS.

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

Porter, Emma, G.,; Waldrop, Thomas, A.; McElreath, Susan, D.

1998-01-01

Porter, Emma G., T.A. Waldrop, Susan D. McElreath, and Frank H. Tainter. 1998. Effect of site on bacterial populations in the sapwood of coarse woody debris. Pp. 480-484. In: Proc. 9th Bienn. South. Silv. Res. Conf. T.A. Waldrop (ed). USDA Forest Service, Southern Research Station. Gen. Tech. Rep. SRS-20. Abstract: Coarse woody debris (CWD) is an important structural component of southeastern forest ecosystems, yet little is known about its dynamics in these systems. This project identified bacterial populations associated with CWD and their dynamics across landscape ecosystem classification (LEC) units. Bolts of red oak and loblolly pine were placed onmore » plots at each of three hydric, mesic, and xeric sites at the Savannah River Station. After the controls were processed, samples were taken at four intervals over a 16-week period. Samples were ground within an anaerobe chamber using nonselective media. Aerobic and facultative anaerobic bacteria were identified using the Biolog system and the anaerobes were identified using the API 20A system. Major genera isolated were: Bacillus, Buttiauxella, Cedecea, Enterobacter, Erwinia, Escherichia, Klebsiella, Pantoea, Pseudomonas, Serratia, and Xanthomonas. The mean total isolates were determined by LEC units and sample intervals. Differences occurred between the sample intervals with total isolates of 6.67, 13.33, 10.17, and 9.50 at 3, 6, 10, and 16 weeks, respectively. No significant differences in the numbers of bacteria isolated were found between LEC units.« less

The sonographic features of malignant mediastinal lymph nodes and a proposal for an algorithmic approach for sampling during endobronchial ultrasound.

PubMed

Alici, Ibrahim Onur; Yılmaz Demirci, Nilgün; Yılmaz, Aydın; Karakaya, Jale; Özaydın, Esra

2016-09-01

There are several papers on the sonographic features of mediastinal lymph nodes affected by several diseases, but none gives the importance and clinical utility of the features. In order to find out which lymph node should be sampled in a particular nodal station during endobronchial ultrasound, we investigated the diagnostic performances of certain sonographic features and proposed an algorithmic approach. We retrospectively analyzed 1051 lymph nodes and randomly assigned them into a preliminary experimental and a secondary study group. The diagnostic performances of the sonographic features (gray scale, echogeneity, shape, size, margin, presence of necrosis, presence of calcification and absence of central hilar structure) were calculated, and an algorithm for lymph node sampling was obtained with decision tree analysis in the experimental group. Later, a modified algorithm was applied to the patients in the study group to give the accuracy. The demographic characteristics of the patients were not statistically significant between the primary and the secondary groups. All of the features were discriminative between malignant and benign diseases. The modified algorithm sensitivity, specificity, and positive and negative predictive values and diagnostic accuracy for detecting metastatic lymph nodes were 100%, 51.2%, 50.6%, 100% and 67.5%, respectively. In this retrospective analysis, the standardized sonographic classification system and the proposed algorithm performed well in choosing the node that should be sampled in a particular station during endobronchial ultrasound. © 2015 John Wiley & Sons Ltd.

Meteorological factors affecting the sudden decline in Lake Urmia's water level

NASA Astrophysics Data System (ADS)

Arkian, Foroozan; Nicholson, Sharon E.; Ziaie, Bahareh

2018-01-01

Lake Urmia, in northwest Iran, is the second most saline lake in the world. During the past two decades, the level of water has markedly decreased. In this paper, climate of the lake region is investigated by using data from four meteorological stations near the lake. The data include climatic parameters such as temperature, precipitation, humidity, wind speed, sunshine hours, number of rain days, and evaporation. Climate around the lake is examined by way of climate classification in the periods before and after the reduction in water level. Rainfall in the lake catchment is also evaluated using both gauge and satellite data. The results show a significant decreasing trend in mean annual precipitation and wind speed and an increasing trend in annual average temperature and sunshine hours at the four stations. Precipitation and wind speed have decreased by 37 mm and 2.7 m/s, respectively, and the mean annual temperature and sunshine hours have increased by 1.4 °C and 41.6 days, respectively, over these six decades. Only the climate of the Tabriz region is seen to have significantly changed, going from semiarid to arid. Gauge records and satellite data show a large-scale decreasing trend in rainfall since 1995. The correlation between rainfall and year-to-year changes in lake level is 0.69 over the period 1965 to 2010. The relationship is particularly strong from the early 1990s to 2005. This suggests that precipitation has played an important role in the documented decline of the lake.

Characteristics of a global classification system for perinatal deaths: a Delphi consensus study.

PubMed

Wojcieszek, Aleena M; Reinebrant, Hanna E; Leisher, Susannah Hopkins; Allanson, Emma; Coory, Michael; Erwich, Jan Jaap; Frøen, J Frederik; Gardosi, Jason; Gordijn, Sanne; Gulmezoglu, Metin; Heazell, Alexander E P; Korteweg, Fleurisca J; McClure, Elizabeth; Pattinson, Robert; Silver, Robert M; Smith, Gordon; Teoh, Zheyi; Tunçalp, Özge; Flenady, Vicki

2016-08-15

Despite the global burden of perinatal deaths, there is currently no single, globally-acceptable classification system for perinatal deaths. Instead, multiple, disparate systems are in use world-wide. This inconsistency hinders accurate estimates of causes of death and impedes effective prevention strategies. The World Health Organisation (WHO) is developing a globally-acceptable classification approach for perinatal deaths. To inform this work, we sought to establish a consensus on the important characteristics of such a system. A group of international experts in the classification of perinatal deaths were identified and invited to join an expert panel to develop a list of important characteristics of a quality global classification system for perinatal death. A Delphi consensus methodology was used to reach agreement. Three rounds of consultation were undertaken using a purpose built on-line survey. Round one sought suggested characteristics for subsequent scoring and selection in rounds two and three. The panel of experts agreed on a total of 17 important characteristics for a globally-acceptable perinatal death classification system. Of these, 10 relate to the structural design of the system and 7 relate to the functional aspects and use of the system. This study serves as formative work towards the development of a globally-acceptable approach for the classification of the causes of perinatal deaths. The list of functional and structural characteristics identified should be taken into consideration when designing and developing such a system.

Classifying Life, Reconstructing History and Teaching Diversity: Philosophical Issues in the Teaching of Biological Systematics and Biodiversity

ERIC Educational Resources Information Center

Reydon, Thomas A. C.

2013-01-01

Classification is a central endeavor in every scientific field of work. Classification in biology, however, is distinct from classification in other fields of science in a number of ways. Thus, understanding how biological classification works is an important element in understanding the nature of biological science. In the present paper, I…

Design of monitoring system for mail-sorting based on the Profibus S7 series PLC

NASA Astrophysics Data System (ADS)

Zhang, W.; Jia, S. H.; Wang, Y. H.; Liu, H.; Tang, G. C.

2017-01-01

With the rapid development of the postal express, the workload of mail sorting is increasing, but the automatic technology of mail sorting is not mature enough. In view of this, the system uses Siemens S7-300 PLC as the main station controller, PLC of Siemens S7-200/400 is from the station controller, through the man-machine interface configuration software MCGS, PROFIBUS-DP communication, RFID technology and mechanical sorting hand achieve mail classification sorting monitoring. Among them, distinguish mail-sorting by scanning RFID posted in the mail electronic bar code (fixed code), the system uses the corresponding controller on the acquisition of information processing, the processed information transmit to the sorting manipulator by PROFIBUS-DP. The system can realize accurate and efficient mail sorting, which will promote the development of mail sorting technology.

Space Station

NASA Image and Video Library

1952-01-01

This is a von Braun 1952 space station concept. In a 1952 series of articles written in Collier's, Dr. Wernher von Braun, then Technical Director of the Army Ordnance Guided Missiles Development Group at Redstone Arsenal, wrote of a large wheel-like space station in a 1,075-mile orbit. This station, made of flexible nylon, would be carried into space by a fully reusable three-stage launch vehicle. Once in space, the station's collapsible nylon body would be inflated much like an automobile tire. The 250-foot-wide wheel would rotate to provide artificial gravity, an important consideration at the time because little was known about the effects of prolonged zero-gravity on humans. Von Braun's wheel was slated for a number of important missions: a way station for space exploration, a meteorological observatory and a navigation aid. This concept was illustrated by artist Chesley Bonestell.

Guide to the measurement of tree characteristics important to the quality classification for young hardwood trees

Treesearch

David L. Sonderman

1979-01-01

A procedure is shown for measuring external tree characteristics that are important in determining the current and future quality of young hardwood trees. This guide supplements a precious study which describes the quality classification system for young hardwood trees

Metro passenger behaviors and their relations to metro incident involvement.

PubMed

Wan, Xin; Li, Qiming; Yuan, Jingfeng; Schonfeld, Paul M

2015-09-01

The frequent incidents caused by metro passengers in China suggest that it is necessary to explore the classification and effects of passenger behaviors and their relations to incident involvement. A metro passenger behavior questionnaire (MPBQ) and a metro station staff questionnaire (MSSQ), both comprising 32 behavior items, were developed and surveyed on a sample of metro passengers (N=579) and metro staff (N=99). Using the MPBQ, the self-reported frequency of each aberrant behavior was measured and subjected to explanatory factor analysis, which revealed a three-factor solution on the 28 retained behavior items: transgressions, self-willed inattentions and abrupt violations. ANOVA was used to examine the effects of demographic and riding profile variables on different types of behaviors. The MSSQ was used to collect metro staff opinions on behavior frequency, severity and entities that might be affected, given that a specific behavior occurred. An importance hierarchy was established over the 32 identified behaviors to determine the most important riding behaviors. Finally, logistic regression showed that riding time, number of stops experienced by a passenger and, more importantly, transgressions and abrupt violations, were significant predictors of incident involvement. The possible explanations and implications of the findings might help in understanding passenger behaviors and targeting metro safety interventions in ways that promote safer operations. Copyright © 2015 Elsevier Ltd. All rights reserved.

MLP based models to predict PM10, O3 concentrations, in Sines industrial area

NASA Astrophysics Data System (ADS)

Durao, R.; Pereira, M. J.

2012-04-01

Sines is an important Portuguese industrial area located southwest cost of Portugal with important nearby protected natural areas. The main economical activities are related with this industrial area, the deep-water port, petrochemical and thermo-electric industry. Nevertheless, tourism is also an important economic activity especially in summer time with potential to grow. The aim of this study is to develop prediction models of pollutant concentration categories (e.g. low concentration and high concentration) in order to provide early warnings to the competent authorities who are responsible for the air quality management. The knowledge in advanced of pollutant high concentrations occurrence will allow the implementation of mitigation actions and the release of precautionary alerts to population. The regional air quality monitoring network consists in three monitoring stations where a set of pollutants' concentrations are registered on a continuous basis. From this set stands out the tropospheric ozone (O3) and particulate matter (PM10) due to the high concentrations occurring in the region and their adverse effects on human health. Moreover, the major industrial plants of the region monitor SO2, NO2 and particles emitted flows at the principal chimneys (point sources), also on a continuous basis,. Therefore Artificial neuronal networks (ANN) were the applied methodology to predict next day pollutant concentrations; due to the ANNs structure they have the ability to capture the non-linear relationships between predictor variables. Hence the first step of this study was to apply multivariate exploratory techniques to select the best predictor variables. The classification trees methodology (CART) was revealed to be the most appropriate in this case.. Results shown that pollutants atmospheric concentrations are mainly dependent on industrial emissions and a complex combination of meteorological factors and the time of the year. In the second step, the Multi-layer perceptron (MLP) have shown to be able to learn the existent complex relationships using different combination of meteorological and emissions variables. Furthermore, MLP models identified what are the meteorological conditions that most affect O3 and PM10 concentrations in the region, namely wind speed and direction, boundary layer height, temperature, sunshine duration, relative humidity and the weather type. The developed MLP models showed good predictive success with model performances between 0.66 and 0.87, indicating a reasonable accuracy for models development and generalization capability. These performance values are obtained using cross entropy error functions. This error functions are only available for classification problems and ensure that the network outputs are true class membership probabilities, which is known to enhance the performance of classification neural networks.

Integrating Multibeam Backscatter Angular Response, Mosaic and Bathymetry Data for Benthic Habitat Mapping

PubMed Central

Che Hasan, Rozaimi; Ierodiaconou, Daniel; Laurenson, Laurie; Schimel, Alexandre

2014-01-01

Multibeam echosounders (MBES) are increasingly becoming the tool of choice for marine habitat mapping applications. In turn, the rapid expansion of habitat mapping studies has resulted in a need for automated classification techniques to efficiently map benthic habitats, assess confidence in model outputs, and evaluate the importance of variables driving the patterns observed. The benthic habitat characterisation process often involves the analysis of MBES bathymetry, backscatter mosaic or angular response with observation data providing ground truth. However, studies that make use of the full range of MBES outputs within a single classification process are limited. We present an approach that integrates backscatter angular response with MBES bathymetry, backscatter mosaic and their derivatives in a classification process using a Random Forests (RF) machine-learning algorithm to predict the distribution of benthic biological habitats. This approach includes a method of deriving statistical features from backscatter angular response curves created from MBES data collated within homogeneous regions of a backscatter mosaic. Using the RF algorithm we assess the relative importance of each variable in order to optimise the classification process and simplify models applied. The results showed that the inclusion of the angular response features in the classification process improved the accuracy of the final habitat maps from 88.5% to 93.6%. The RF algorithm identified bathymetry and the angular response mean as the two most important predictors. However, the highest classification rates were only obtained after incorporating additional features derived from bathymetry and the backscatter mosaic. The angular response features were found to be more important to the classification process compared to the backscatter mosaic features. This analysis indicates that integrating angular response information with bathymetry and the backscatter mosaic, along with their derivatives, constitutes an important improvement for studying the distribution of benthic habitats, which is necessary for effective marine spatial planning and resource management. PMID:24824155

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026

Similarity-dissimilarity plot for visualization of high dimensional data in biomedical pattern classification.

PubMed

Arif, Muhammad

2012-06-01

In pattern classification problems, feature extraction is an important step. Quality of features in discriminating different classes plays an important role in pattern classification problems. In real life, pattern classification may require high dimensional feature space and it is impossible to visualize the feature space if the dimension of feature space is greater than four. In this paper, we have proposed a Similarity-Dissimilarity plot which can project high dimensional space to a two dimensional space while retaining important characteristics required to assess the discrimination quality of the features. Similarity-dissimilarity plot can reveal information about the amount of overlap of features of different classes. Separable data points of different classes will also be visible on the plot which can be classified correctly using appropriate classifier. Hence, approximate classification accuracy can be predicted. Moreover, it is possible to know about whom class the misclassified data points will be confused by the classifier. Outlier data points can also be located on the similarity-dissimilarity plot. Various examples of synthetic data are used to highlight important characteristics of the proposed plot. Some real life examples from biomedical data are also used for the analysis. The proposed plot is independent of number of dimensions of the feature space.

Environmental Assessment: Tree Removal to Improve FAA Radar Coverage, Youngstown Air Reserve Station

DTIC Science & Technology

2009-12-01

Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a ...collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE DEC 2009 2. REPORT TYPE 3. DATES COVERED 00-00...CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18. NUMBER OF PAGES 73 19a. NAME OF RESPONSIBLE PERSON a . REPORT unclassified b

Investigation of the Fisheries of Africa, Buck, and Judd Lakes, Louisiana.

DTIC Science & Technology

1987-10-01

D-A188 978 INVESTIGATION OF THE FISHERIES VVW NJ 7 LAKES LOUISIA A(U) ARMY ENGINEER UATERWiAYS EXPERIMENT STATION VICKSBURG MS ENVIR L G SANDERS ET...MISCELLANEOUS PAPER EL-87-10 INVESTIGATION OF THE FISHERIES OF AFRICA, S BUCK, AND JUDD LAKES, LOUISIANA by AD-A188 978 Larry G. Sanders, John A...0060 ELEMENT NO. NO NO. rCCESSION NO 11 TITLE (Include Security Classification) Investigation of the Fisheries of Africa, Buck, and Judd Lakes

IET. Movable test cell building (TAN624). Plans, sections, and elevations ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

IET. Movable test cell building (TAN-624). Plans, sections, and elevations show trapezoidal shape of front/rear elevations, vertical sliding door panels, wheels, periscope and camera locations, fixed concrete wall, and relationship to coupling station (TAN-620) and rail track. Ralph M. Parson 902-4-ANP-624-A 329. Date: February 1954. Approved by INEEL Classification Office for public release. INEEL Index code no. 035-0624-00-693-106911 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

SNS Proton Beam Window Disposal

NASA Astrophysics Data System (ADS)

Popova, Irina; Gallmeier, Franz X.; Trotter, Steven

2017-09-01

In order to support the disposal of the proton beam window assembly of the Spallation Neutron Source beamline to the target station, waste classification analyses are performed. The window has a limited life-time due to radiation-induced material damage. Analyses include calculation of the radionuclide inventory and shielding analyses for the transport package/container to ensure that the container is compliant with the transportation and waste management regulations. In order to automate this procedure and minimize manual work a script in Perl language was written.

User Centered System Design: Papers for the CHI � Conference on Human Factors in Computer Systems.

DTIC Science & Technology

1983-11-01

purpose of the United States Government. ONR REPORT830383 2e0 104 Unclagsified ’tCCU*ITY CLASSIFICATION OF THIS PAGE (Whom, Des enteredE) REPORT... con - mand languages versus menu-based systems, choices of names, and handheld computers versus work stations are examined briefly. UN.ATkrr SErXjftTyv...lsted above in alphabetical order their intentions during the session. An extract from one of We wish to thank Don Norman. Bob Glushko, and Jnathan

Tool for Analyzing Station Characteristics (TASC) : evaluating the performance of intermodal connectivity.

DOT National Transportation Integrated Search

2012-08-01

In previous phases of this research, we developed a methodology for surveying transit riders about their levels of satisfaction and how : important they find various attributes at transit stops and stations. We applied an Importance-Satisfaction Anal...

Classification, disease, and diagnosis.

PubMed

Jutel, Annemarie

2011-01-01

Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

Location of Road Emergency Stations in Fars Province, Using Spatial Multi-Criteria Decision Making.

PubMed

Goli, Ali; Ansarizade, Najmeh; Barati, Omid; Kavosi, Zahra

2015-01-01

To locate the road emergency stations in Fars province based on using spatial multi-criteria decision making (Delphi method). In this study, the criteria affecting the location of road emergency stations have been identified through Delphi method and their importance was determined using Analytical Hierarchical Process (AHP). With regard to the importance of the criteria and by using Geographical Information System (GIS), the appropriateness of the existing stations with the criteria and the way of their distribution has been explored, and the appropriate arenas for creating new emergency stations were determined. In order to investigate the spatial distribution pattern of the stations, Moran's Index was used. The accidents (0.318), placement position (0.235), time (0.198), roads (0.160), and population (0.079) were introduced as the main criteria in location road emergency stations. The findings showed that the distribution of the existing stations was clustering (Moran's I=0.3). Three priorities were introduced for establishing new stations. Some arenas including Abade, north of Eghlid and Khoram bid, and small parts of Shiraz, Farashband, Bavanat, and Kazeroon were suggested as the first priority. GIS is a useful and applicable tool in investigating spatial distribution and geographical accessibility to the setting that provide health care, including emergency stations.

Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.

PubMed

Peker, Musa; Şen, Baha; Gürüler, Hüseyin

2015-02-01

The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.

Habitat typing versus advanced vegetation classification in western forests

Treesearch

Tony Kusbach; John Shaw; James Long; Helga Van Miegroet

2012-01-01

Major habitat and community types in northern Utah were compared with plant alliances and associations that were derived from fidelity- and diagnostic-species classification concepts. Each of these classification approaches was associated with important environmental factors. Within a 20,000-ha watershed, 103 forest ecosystems were described by physiographic features,...

Degree Classification and Recent Graduates' Ability: Is There Any Signalling Effect?

ERIC Educational Resources Information Center

Di Pietro, Giorgio

2017-01-01

Research across several countries has shown that degree classification (i.e. the final grade awarded to students successfully completing university) is an important determinant of graduates' first destination outcome. Graduates leaving university with higher degree classifications have better employment opportunities and a higher likelihood of…

Psychology Problem Classification for Children and Youth.

ERIC Educational Resources Information Center

Minnesota Systems Research, Inc., Washington, DC.

The development of Psychology Problem Classification is an early step in the direction of providing a uniform nomenclature for classifying the needs and problems of children and youth. There are many potential uses for a diagnostic classification and coding system. The two most important uses for the practitioner are problem identification and…

Classification of forest land attributes using multi-source remotely sensed data

NASA Astrophysics Data System (ADS)

Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri

2016-02-01

The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.

USCS and the USDA Soil Classification System: Development of a Mapping Scheme

DTIC Science & Technology

2015-03-01

important to human daily living. A variety of disciplines (geology, agriculture, engineering, etc.) require a sys- tematic categorization of soil, detailing...it is often important to also con- sider parameters that indicate soil strength. Two important properties used for engineering-related problems are...that many textural clas- sification systems were developed to meet specifics needs. In agriculture, textural classification is used to determine crop

Applying a Hidden Markov Model-Based Event Detection and Classification Algorithm to Apollo Lunar Seismic Data

NASA Astrophysics Data System (ADS)

Knapmeyer-Endrun, B.; Hammer, C.

2014-12-01

The seismometers that the Apollo astronauts deployed on the Moon provide the only recordings of seismic events from any extra-terrestrial body so far. These lunar events are significantly different from ones recorded on Earth, in terms of both signal shape and source processes. Thus they are a valuable test case for any experiment in planetary seismology. In this study, we analyze Apollo 16 data with a single-station event detection and classification algorithm in view of NASA's upcoming InSight mission to Mars. InSight, scheduled for launch in early 2016, has the goal to investigate Mars' internal structure by deploying a seismometer on its surface. As the mission does not feature any orbiter, continuous data will be relayed to Earth at a reduced rate. Full range data will only be available by requesting specific time-windows within a few days after the receipt of the original transmission. We apply a recently introduced algorithm based on hidden Markov models that requires only a single example waveform of each event class for training appropriate models. After constructing the prototypes we detect and classify impacts and deep and shallow moonquakes. Initial results for 1972 (year of station installation with 8 months of data) indicate a high detection rate of over 95% for impacts, of which more than 80% are classified correctly. Deep moonquakes, which occur in large amounts, but often show only very weak signals, are detected with less certainty (~70%). As there is only one weak shallow moonquake covered, results for this event class are not statistically significant. Daily adjustments of the background noise model help to reduce false alarms, which are mainly erroneous deep moonquake detections, by about 25%. The algorithm enables us to classify events that were previously listed in the catalog without classification, and, through the combined use of long period and short period data, identify some unlisted local impacts as well as at least two yet unreported deep moonquakes.

Effects of two classification strategies on a Benthic Community Index for streams in the Northern Lakes and Forests Ecoregion

USGS Publications Warehouse

Butcher, Jason T.; Stewart, Paul M.; Simon, Thomas P.

2003-01-01

Ninety-four sites were used to analyze the effects of two different classification strategies on the Benthic Community Index (BCI). The first, a priori classification, reflected the wetland status of the streams; the second, a posteriori classification, used a bio-environmental analysis to select classification variables. Both classifications were examined by measuring classification strength and testing differences in metric values with respect to group membership. The a priori (wetland) classification strength (83.3%) was greater than the a posteriori (bio-environmental) classification strength (76.8%). Both classifications found one metric that had significant differences between groups. The original index was modified to reflect the wetland classification by re-calibrating the scoring criteria for percent Crustacea and Mollusca. A proposed refinement to the original Benthic Community Index is suggested. This study shows the importance of using hypothesis-driven classifications, as well as exploratory statistical analysis, to evaluate alternative ways to reveal environmental variability in biological assessment tools.

A multi-temporal fusion-based approach for land cover mapping in support of nuclear incident response

NASA Astrophysics Data System (ADS)

Sah, Shagan

An increasingly important application of remote sensing is to provide decision support during emergency response and disaster management efforts. Land cover maps constitute one such useful application product during disaster events; if generated rapidly after any disaster, such map products can contribute to the efficacy of the response effort. In light of recent nuclear incidents, e.g., after the earthquake/tsunami in Japan (2011), our research focuses on constructing rapid and accurate land cover maps of the impacted area in case of an accidental nuclear release. The methodology involves integration of results from two different approaches, namely coarse spatial resolution multi-temporal and fine spatial resolution imagery, to increase classification accuracy. Although advanced methods have been developed for classification using high spatial or temporal resolution imagery, only a limited amount of work has been done on fusion of these two remote sensing approaches. The presented methodology thus involves integration of classification results from two different remote sensing modalities in order to improve classification accuracy. The data used included RapidEye and MODIS scenes over the Nine Mile Point Nuclear Power Station in Oswego (New York, USA). The first step in the process was the construction of land cover maps from freely available, high temporal resolution, low spatial resolution MODIS imagery using a time-series approach. We used the variability in the temporal signatures among different land cover classes for classification. The time series-specific features were defined by various physical properties of a pixel, such as variation in vegetation cover and water content over time. The pixels were classified into four land cover classes - forest, urban, water, and vegetation - using Euclidean and Mahalanobis distance metrics. On the other hand, a high spatial resolution commercial satellite, such as RapidEye, can be tasked to capture images over the affected area in the case of a nuclear event. This imagery served as a second source of data to augment results from the time series approach. The classifications from the two approaches were integrated using an a posteriori probability-based fusion approach. This was done by establishing a relationship between the classes, obtained after classification of the two data sources. Despite the coarse spatial resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion-based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. This fusion thus contributed to classification accuracy refinement, with a few additional advantages, such as correction for cloud cover and providing for an approach that is robust against point-in-time seasonal anomalies, due to the inclusion of multi-temporal data. We concluded that this approach is capable of generating land cover maps of acceptable accuracy and rapid turnaround, which in turn can yield reliable estimates of crop acreage of a region. The final algorithm is part of an automated software tool, which can be used by emergency response personnel to generate a nuclear ingestion pathway information product within a few hours of data collection.

Training sample selection based on self-training for liver cirrhosis classification using ultrasound images

NASA Astrophysics Data System (ADS)

Fujita, Yusuke; Mitani, Yoshihiro; Hamamoto, Yoshihiko; Segawa, Makoto; Terai, Shuji; Sakaida, Isao

2017-03-01

Ultrasound imaging is a popular and non-invasive tool used in the diagnoses of liver disease. Cirrhosis is a chronic liver disease and it can advance to liver cancer. Early detection and appropriate treatment are crucial to prevent liver cancer. However, ultrasound image analysis is very challenging, because of the low signal-to-noise ratio of ultrasound images. To achieve the higher classification performance, selection of training regions of interest (ROIs) is very important that effect to classification accuracy. The purpose of our study is cirrhosis detection with high accuracy using liver ultrasound images. In our previous works, training ROI selection by MILBoost and multiple-ROI classification based on the product rule had been proposed, to achieve high classification performance. In this article, we propose self-training method to select training ROIs effectively. Evaluation experiments were performed to evaluate effect of self-training, using manually selected ROIs and also automatically selected ROIs. Experimental results show that self-training for manually selected ROIs achieved higher classification performance than other approaches, including our conventional methods. The manually ROI definition and sample selection are important to improve classification accuracy in cirrhosis detection using ultrasound images.

Weather types and strokes in the Augsburg region (Southern Germany)

NASA Astrophysics Data System (ADS)

Beck, Christoph; Ertl, Michael; Giemsa, Esther; Jacobeit, Jucundus; Naumann, Markus; Seubert, Stefanie

2017-04-01

Strokes are one of the leading causes of morbidity and mortality worldwide and the main reason for longterm care dependency in Germany. Concerning the economical impact on patients and healthcare systems it is of particular importance to prevent this disease as well as to improve the outcome of the affected persons. Beside the primary well-known risk factors like hypertension, cigarette smoking, physical inactivity and others, also weather seems to have pronounced influence on the occurrence and frequency of strokes. Previous studies most often focused on effects of singular meteorological variables like ambient air temperature, air pressure or humidity. An advanced approach is to link the entire suite of daily weather elements classified to air mass- or weather types to cerebrovascular morbidity or mortality. In a joint pilot study bringing together climatologists, environmental scientists and physicians from the University of Augsburg and the clinical centre Augsburg, we analysed relationships between singular meteorological parameters as well as combined weather effects (e.g. weather types) and strokes in the urban area of Augsburg and the surrounding rural region. A total of 17.501 stroke admissions to Neurological Clinic and Clinical Neurophysiology at Klinikum Augsburg between 2006 and 2015 are classified to either "ischaemic" (16.354) or "haemorrhagic" (1.147) subtype according to etiology (based on the International Classification of Diseases - 10th Revision). Spearman correlations between daily frequencies of ischaemic and haemorrhagic strokes and singular atmospheric parameters (T, Tmin, Tmax, air pressure, humidity etc.) measured at the DWD (German weather service) meteorological station at Augsburg Muehlhausen are rather low. However, higher correlations are achieved when considering sub-samples of "homogenous weather conditions" derived from synoptic circulation classifications: e.g. within almost all of 10 types arising from a classification of central European mean sea level pressure fields into "Großwettertypes" (Beck 2000) the relationships between meteorological variables and stroke frequencies are increasing. Mainly temperature variables (Tmin, Tmax, Tmean) appear to be important particularly in winter and summer. Moreover distinct correlations of similar magnitude are obtained with other variables like wind speed or precipitation for specific weather types (e.g. westerly type). In how far these initial findings do really point to additional health impacts beyond temperature effects is subject of ongoing work.

Classification and its scale analysis of Severe Haze recently observed in Korea

NASA Astrophysics Data System (ADS)

Lee, K. M.; Eun, S. H.; Kim, B. G.; Kim, S. W.; Park, J. S.

2015-12-01

Cloud-aerosol-precipitation interactions mechanism is heavily dependent upon scale problems, and thus the first thing to understand its mechanism is to quantify the time (or spatial) scale of forcing driver, aerosols. This study is focused on recently occurring dense haze episodes accompanied with severe visibility impairment from 2011 to 2013 at two adjacent monitoring stations (Baengnyeongdo and Seoul) in Korea. Baengnyeongdo is an island being located 200 km west from Seoul. First of all, we have tested various flow charts to classify the various categories of heavy haze events by making use of aerosol scattering coefficient, PM2.5, and time lag difference of PM2.5 increase time at both stations, backward trajectories, and the ratio of PM2.5 to PM10 specifically in the quantitative perspective. One of them is selected for this study. Long range transported haze (LH) and Yellow Sand (YS) show very distinctive time lags of both PM2.5 and PM10 between both stations, but much higher ratio of PM2.5 to PM10 for LH in comparison with YS. Meanwhile urban haze (UH) has a significant increase in PM2.5 only at Seoul as easily expected. Time scales (e-folding time) of aerosol light scattering coefficients for LH and UH are 6-12 hrs and 7-16 hrs, respectively calculated for several episodes according to the criteria developed, which eventually corresponds to spatial scale of 120 - 240 km, 140 - 320 km, respectively by assuming average boundary wind speed, 5.6 m/s (Anderson et al., 2003). In general, long-range transported hazes have larger temporal and spatial dimension (about meso-a scale) than domestic hazes, after carefully designed classification of haze episodes. These results can be an useful basis for the estimation of regional aerosol radiative forcings in East Asia.

Streamflow variability and classification using false nearest neighbor method

NASA Astrophysics Data System (ADS)

Vignesh, R.; Jothiprakash, V.; Sivakumar, B.

2015-12-01

Understanding regional streamflow dynamics and patterns continues to be a challenging problem. The present study introduces the false nearest neighbor (FNN) algorithm, a nonlinear dynamic-based method, to examine the spatial variability of streamflow over a region. The FNN method is a dimensionality-based approach, where the dimension of the time series represents its variability. The method uses phase space reconstruction and nearest neighbor concepts, and identifies false neighbors in the reconstructed phase space. The FNN method is applied to monthly streamflow data monitored over a period of 53 years (1950-2002) in an extensive network of 639 stations in the contiguous United States (US). Since selection of delay time in phase space reconstruction may influence the FNN outcomes, analysis is carried out for five different delay time values: monthly, seasonal, and annual separation of data as well as delay time values obtained using autocorrelation function (ACF) and average mutual information (AMI) methods. The FNN dimensions for the 639 streamflow series are generally identified to range from 4 to 12 (with very few exceptional cases), indicating a wide range of variability in the dynamics of streamflow across the contiguous US. However, the FNN dimensions for a majority of the streamflow series are found to be low (less than or equal to 6), suggesting low level of complexity in streamflow dynamics in most of the individual stations and over many sub-regions. The FNN dimension estimates also reveal that streamflow dynamics in the western parts of the US (including far west, northwestern, and southwestern parts) generally exhibit much greater variability compared to that in the eastern parts of the US (including far east, northeastern, and southeastern parts), although there are also differences among 'pockets' within these regions. These results are useful for identification of appropriate model complexity at individual stations, patterns across regions and sub-regions, interpolation and extrapolation of data, and catchment classification. An attempt is also made to relate the FNN dimensions with catchment characteristics and streamflow statistical properties.

Comparison Of Semi-Automatic And Automatic Slick Detection Algorithms For Jiyeh Power Station Oil Spill, Lebanon

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ozkan, C.; Sunar, F.

2013-10-01

After air strikes on July 14 and 15, 2006 the Jiyeh Power Station started leaking oil into the eastern Mediterranean Sea. The power station is located about 30 km south of Beirut and the slick covered about 170 km of coastline threatening the neighboring countries Turkey and Cyprus. Due to the ongoing conflict between Israel and Lebanon, cleaning efforts could not start immediately resulting in 12 000 to 15 000 tons of fuel oil leaking into the sea. In this paper we compare results from automatic and semi-automatic slick detection algorithms. The automatic detection method combines the probabilities calculated for each pixel from each image to obtain a joint probability, minimizing the adverse effects of atmosphere on oil spill detection. The method can readily utilize X-, C- and L-band data where available. Furthermore wind and wave speed observations can be used for a more accurate analysis. For this study, we utilize Envisat ASAR ScanSAR data. A probability map is generated based on the radar backscatter, effect of wind and dampening value. The semi-automatic algorithm is based on supervised classification. As a classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) classifier is used since it is more flexible and efficient than conventional maximum likelihood classifier for multisource and multi-temporal data. The learning algorithm for ANN MLP is chosen as the Levenberg-Marquardt (LM). Training and test data for supervised classification are composed from the textural information created from SAR images. This approach is semiautomatic because tuning the parameters of classifier and composing training data need a human interaction. We point out the similarities and differences between the two methods and their results as well as underlining their advantages and disadvantages. Due to the lack of ground truth data, we compare obtained results to each other, as well as other published oil slick area assessments.

Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey

USGS Publications Warehouse

Rydlund, Jr., Paul H.; Densmore, Brenda K.

2012-01-01

Geodetic surveys have evolved through the years to the use of survey-grade (centimeter level) global positioning to perpetuate and post-process vertical datum. The U.S. Geological Survey (USGS) uses Global Navigation Satellite Systems (GNSS) technology to monitor natural hazards, ensure geospatial control for climate and land use change, and gather data necessary for investigative studies related to water, the environment, energy, and ecosystems. Vertical datum is fundamental to a variety of these integrated earth sciences. Essentially GNSS surveys provide a three-dimensional position x, y, and z as a function of the North American Datum of 1983 ellipsoid and the most current hybrid geoid model. A GNSS survey may be approached with post-processed positioning for static observations related to a single point or network, or involve real-time corrections to provide positioning "on-the-fly." Field equipment required to facilitate GNSS surveys range from a single receiver, with a power source for static positioning, to an additional receiver or network communicated by radio or cellular for real-time positioning. A real-time approach in its most common form may be described as a roving receiver augmented by a single-base station receiver, known as a single-base real-time (RT) survey. More efficient real-time methods involving a Real-Time Network (RTN) permit the use of only one roving receiver that is augmented to a network of fixed receivers commonly known as Continually Operating Reference Stations (CORS). A post-processed approach in its most common form involves static data collection at a single point. Data are most commonly post-processed through a universally accepted utility maintained by the National Geodetic Survey (NGS), known as the Online Position User Service (OPUS). More complex post-processed methods involve static observations among a network of additional receivers collecting static data at known benchmarks. Both classifications provide users flexibility regarding efficiency and quality of data collection. Quality assurance of survey-grade global positioning is often overlooked or not understood and perceived uncertainties can be misleading. GNSS users can benefit from a blueprint of data collection standards used to ensure consistency among USGS mission areas. A classification of GNSS survey qualities provide the user with the ability to choose from the highest quality survey used to establish objective points with low uncertainties, identified as a Level I, to a GNSS survey for general topographic control without quality assurance, identified as a Level IV. A Level I survey is strictly limited to post-processed methods, whereas Level II, Level III, and Level IV surveys integrate variations of a RT approach. Among these classifications, techniques involving blunder checks and redundancy are important, and planning that involves the assessment of the overall satellite configuration, as well as terrestrial and space weather, are necessary to ensure an efficient and quality campaign. Although quality indicators and uncertainties are identified in post-processed methods using CORS, the accuracy of a GNSS survey is most effectively expressed as a comparison to a local benchmark that has a high degree of confidence. Real-time and post-processed methods should incorporate these "trusted" benchmarks as a check during any campaign. Global positioning surveys are expected to change rapidly in the future. The expansion of continuously operating reference stations, combined with newly available satellite signals, and enhancements to the conterminous geoid, are all sufficient indicators for substantial growth in real-time positioning and quality thereof.

Dedication of emergency diesel generators` control air subsystem

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

Harrington, M.; Myers, G.; Palumbo, M.

1994-12-31

In the spring of 1993, the need to upgrade Seabrook Station`s emergency diesel generators` (EDGs`) control air system from nonsafety related to safety related was identified. This need was identified as a result of questions raised by the US Nuclear Regulatory Commission, which was conducting an Electrical Distribution Safety Functional Inspection at Seabrook at that time. The specific reason for the reassignment of safety classification was recognition that failure of the control air supply to the EDGs` jacket cooling water temperature control valves could cause overcooling of the EDGs, which potentially could result in EDG failure during long-term operation. Thismore » paper addresses how the installed control air system was upgraded to safety related using Seabrook`s Commercial Grade Dedication (CGD) Program and how, by using the dedication skills obtained over the past few years, it was done at minimal cost.« less

An investigation of the key parameters for predicting PV soiling losses

DOE PAGES

Micheli, Leonardo; Muller, Matthew

2017-01-25

One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination ( R 2) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of drymore » periods had the best correlation with the soiling ratio. Lastly, a preliminary investigation of two-variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM 2.5 and a binary classification for the average length of the dry period was introduced.« less

Atmospheric CO2 Concentrations--The Canadian Background Air Pollution Monitoring Network (1993) (NDP-034)

DOE Data Explorer

Trivett, N. B. A. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Hudec, V. C. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Wong, C. S. [Marine Carbon Research Centre, Institute of Ocean Sciences, Sidney, British Columbia, Canada

1993-01-01

Flask air samples collected at roughly weekly intervals at three Canadian sites [Alert, Northwest Territories (July 1975 through July 1992); Sable Island, Nova Scotia (March 1975 through July 1992); and Cape St. James, British Columbia (May 1979 through July 1992)] were analyzed for CO2 concentration with the measurements directly traceable to the WMO primary CO2 standards. Each record includes the date, atmospheric CO2 concentration, and flask classification code. They provide an accurate record of CO2 concentration levels in Canada during the past two decades. Because these data are directly traceable to WMO standards, this record may be compared with records from other Background Air Pollution Monitoring Network (BAPMoN) stations. The data are in three files (one for each of the monitoring stations) ranging in size from 9.4 to 20.1 kB.

Principles of soil mapping of a megalopolis with St. Petersburg as an example

NASA Astrophysics Data System (ADS)

Aparin, B. F.; Sukhacheva, E. Yu.

2014-07-01

For the first time, a soil map of St. Petersburg has been developed on a scale of 1 : 50000 using MicroStation V8i software. The legend to this map contains more than 60 mapping units. The classification of urban soils and information on the soil cover patterns are principally new elements of this legend. New concepts of the urbanized soil space and urbopedocombinations have been suggested for soil mapping of urban territories. The typification of urbopedocombinations in St. Petersburg has been performed on the basis of data on the geometry and composition of the polygons of soils and nonsoil formations. The ratio between the areas of soils and nonsoil formations and their spatial distribution patterns have been used to distinguish between six types of the urbanized soil space. The principles of classification of the soils of urban territories have been specified, and a separate order of pedo-allochthonous soils has been suggested for inclusion into the Classification and Diagnostic System of Russian Soils (2004). Six types of pedo-allochthonous soils have been distinguished on the basis of data on their humus and organic horizons and the character of the underlying mineral substrate.

Objective local weather types with applications on urban air pollution and on mortality with chronicle illnesses

NASA Astrophysics Data System (ADS)

Mika, Janos; Ivady, Anett; Fulop, Andrea; Makra, László

2010-05-01

Synoptic climatology i.e. classification of the endless variability of the everyday weather states according to the pressure configuration and frontal systems relative to the point, or region of interest has long history in meteorology. Its logical alternative, i.e. classification of weather according to the observed local weather elements was less popular until the recent times when the numerical weather forecasts became able to outline not only the synoptic situation, but the near-surface meteorological variables, as well. Nowadays the computer-based statistical facilities are able to operate with matrices of multivariate diurnal samples, as well. The paper presents an attempt to define a set of local weather types using point-wise series at five rural stations, Szombathely, Pécs, Budapest, Szeged és Debrecen in the 1961-1990 reference period. Ten local variables are used, i.e. the diurnal mean temperature, the diurnal temperature range; the cloudiness, the sunshine duration, the water vapour pressure, the precipitation in a logarithmic scale, also differing trace (below 0.1 mm) and no precipitation, the relative humidity and wind speed, including the more extremity indicators of the two latter parameters, i.e. number of hours with over 80 % relative humidity and over 15 m/s wind gusts. Factor analysis of these ten variables was performed leading to 5 fairly independent variables retained for cluster analysis to obtain the local weather types. Hierarchical cluster analysis was performed to classify the 840-930 days within each month of the 30 years period. Furthers neighbour approach was preferred based on Euclidean metrics to establish optimum number of types. The 12 months and the 5 stations exhibited slightly different results but the optimum number of the types was always between 4 and 12 which is a quite reasonable number from practical considerations. According to a further reasonable compromise, the common number of the types not too bad in either stations or months defines that the common optimum number of local weather types is nine. This set of weather types, specified for each station, was used to "explain" the possible portion of local inter-diurnal variance of seven daily urban air quality measurements, i.e. CO, NO, NO2, NOx, O3, SO2 and PM10. Another set of data for testing the types are the mortalities with chronicle illnesses, i.e. cardio-vascular and respiratory illnesses. This set of 35 years data (1971-2005) is layered for capital city (Budapest, 2 million inhabitants) and rest of the countries (max. 200 000 inhab.). The use of complex weather types is likely better than the common use of individual weather elements, e.g. diurnal mean temperature or a kind of bioclimatic index. The ability of the types to decrease the variability is also compared for both sets of target variables to the analogous ability of macrosynoptic classification by Peczely. The results are also discussed by grouping the investigated contaminants according to their origin.

Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art

ERIC Educational Resources Information Center

Rupp, Andre A.; Templin, Jonathan L.

2008-01-01

"Diagnostic classification models" (DCM) are frequently promoted by psychometricians as important modelling alternatives for analyzing response data in situations where multivariate classifications of respondents are made on the basis of multiple postulated latent skills. In this review paper, a definitional boundary of the space of DCM…

Quantitative classification of a historic northern Wisconsin (U.S.A.) landscape: mapping forests at regional scales

Treesearch

Lisa A. Schulte; David J. Mladenoff; Erik V. Nordheim

2002-01-01

We developed a quantitative and replicable classification system to improve understanding of historical composition and structure within northern Wisconsin's forests. The classification system was based on statistical cluster analysis and two forest metrics, relative dominance (% basal area) and relative importance (mean of relative dominance and relative density...

Social Work Problem Classification for Children and Youth.

ERIC Educational Resources Information Center

Minnesota Systems Research, Inc., Washington, DC.

The development of the Social Work Problem Classification is an early step in the provision of a uniform nomenclature for classifying the needs and problems of children and youth. There are many potential uses for a diagnostic classification and coding system. The two most important for the practitioner are: (1) problem identification and…

Feasibility of Multispectral Airborne Laser Scanning for Land Cover Classification, Road Mapping and Map Updating

NASA Astrophysics Data System (ADS)

Matikainen, L.; Karila, K.; Hyyppä, J.; Puttonen, E.; Litkey, P.; Ahokas, E.

2017-10-01

This article summarises our first results and experiences on the use of multispectral airborne laser scanner (ALS) data. Optech Titan multispectral ALS data over a large suburban area in Finland were acquired on three different dates in 2015-2016. We investigated the feasibility of the data from the first date for land cover classification and road mapping. Object-based analyses with segmentation and random forests classification were used. The potential of the data for change detection of buildings and roads was also demonstrated. The overall accuracy of land cover classification results with six classes was 96 % compared with validation points. The data also showed high potential for road detection, road surface classification and change detection. The multispectral intensity information appeared to be very important for automated classifications. Compared to passive aerial images, the intensity images have interesting advantages, such as the lack of shadows. Currently, we focus on analyses and applications with the multitemporal multispectral data. Important questions include, for example, the potential and challenges of the multitemporal data for change detection.

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

Spectra and physical properties of Taurid meteoroids

NASA Astrophysics Data System (ADS)

Matlovič, Pavol; Tóth, Juraj; Rudawska, Regina; Kornoš, Leonard

2017-09-01

Taurids are an extensive stream of particles produced by comet 2P/Encke, which can be observed mainly in October and November as a series of meteor showers rich in bright fireballs. Several near-Earth asteroids have also been linked with the meteoroid complex, and recently the orbits of two carbonaceous meteorites were proposed to be related to the stream, raising interesting questions about the origin of the complex and the composition of 2P/Encke. Our aim is to investigate the nature and diversity of Taurid meteoroids by studying their spectral, orbital, and physical properties determined from video meteor observations. Here we analyze 33 Taurid meteor spectra captured during the predicted outburst in November 2015 by stations in Slovakia and Chile, including 14 multi-station observations for which the orbital elements, material strength parameters, dynamic pressures, and mineralogical densities were determined. It was found that while orbits of the 2015 Taurids show similarities with several associated asteroids, the obtained spectral and physical characteristics point towards cometary origin with highly heterogeneous content. Observed spectra exhibited large dispersion of iron content and significant Na intensity in all cases. The determined material strengths are typically cometary in the KB classification, while PE criterion is on average close to values characteristic for carbonaceous bodies. The studied meteoroids were found to break up under low dynamic pressures of 0.02-0.10 MPa, and were characterized by low mineralogical densities of 1.3-2.5 g cm-3. The widest spectral classification of Taurid meteors to date is presented.

Supervised machine learning on a network scale: application to seismic event classification and detection

NASA Astrophysics Data System (ADS)

Reynen, Andrew; Audet, Pascal

2017-09-01

A new method using a machine learning technique is applied to event classification and detection at seismic networks. This method is applicable to a variety of network sizes and settings. The algorithm makes use of a small catalogue of known observations across the entire network. Two attributes, the polarization and frequency content, are used as input to regression. These attributes are extracted at predicted arrival times for P and S waves using only an approximate velocity model, as attributes are calculated over large time spans. This method of waveform characterization is shown to be able to distinguish between blasts and earthquakes with 99 per cent accuracy using a network of 13 stations located in Southern California. The combination of machine learning with generalized waveform features is further applied to event detection in Oklahoma, United States. The event detection algorithm makes use of a pair of unique seismic phases to locate events, with a precision directly related to the sampling rate of the generalized waveform features. Over a week of data from 30 stations in Oklahoma, United States are used to automatically detect 25 times more events than the catalogue of the local geological survey, with a false detection rate of less than 2 per cent. This method provides a highly confident way of detecting and locating events. Furthermore, a large number of seismic events can be automatically detected with low false alarm, allowing for a larger automatic event catalogue with a high degree of trust.

Data Processing of LAPAN-A3 Thermal Imager

NASA Astrophysics Data System (ADS)

Hartono, R.; Hakim, P. R.; Syafrudin, AH

2018-04-01

As an experimental microsatellite, LAPAN-A3/IPB satellite has an experimental thermal imager, which is called as micro-bolometer, to observe earth surface temperature for horizon observation. The imager data is transmitted from satellite to ground station by S-band video analog signal transmission, and then processed by ground station to become sequence of 8-bit enhanced and contrasted images. Data processing of LAPAN-A3/IPB thermal imager is more difficult than visual digital camera, especially for mosaic and classification purpose. This research aims to describe simple mosaic and classification process of LAPAN-A3/IPB thermal imager based on several videos data produced by the imager. The results show that stitching using Adobe Photoshop produces excellent result but can only process small area, while manual approach using ImageJ software can produce a good result but need a lot of works and time consuming. The mosaic process using image cross-correlation by Matlab offers alternative solution, which can process significantly bigger area in significantly shorter time processing. However, the quality produced is not as good as mosaic images of the other two methods. The simple classifying process that has been done shows that the thermal image can classify three distinct objects, i.e.: clouds, sea, and land surface. However, the algorithm fail to classify any other object which might be caused by distortions in the images. All of these results can be used as reference for development of thermal imager in LAPAN-A4 satellite.

How to estimate exposure when studying the temperature-mortality relationship? A case study of the Paris area.

PubMed

Schaeffer, Laura; de Crouy-Chanel, Perrine; Wagner, Vérène; Desplat, Julien; Pascal, Mathilde

2016-01-01

Time series studies assessing the effect of temperature on mortality generally use temperatures measured by a single weather station. In the Paris region, there is a substantial measurement network, and a variety of exposure indicators created from multiple stations can be tested. The aim of this study is to test the influence of exposure indicators on the temperature-mortality relationship in the Paris region. The relationship between temperature and non-accidental mortality was assessed based on a time series analysis using Poisson regression and a generalised additive model. Twenty-five stations in Paris and its three neighbouring departments were used to create four exposure indicators. These indicators were (1) the temperature recorded by one reference station, (2) a simple average of the temperatures of all stations, (3) an average weighted on the departmental population and (4) a classification of the stations based on land use and an average weighted on the population in each class. The relative risks and the Akaike criteria were similar for all the exposure indicators. The estimated temperature-mortality relationship therefore did not appear to be significantly affected by the indicator used, regardless of study zone (departments or region) or age group. The increase in temperatures from the 90(th) to the 99(th) percentile of the temperature distribution led to a significant increase in mortality over 75 years (RR = 1.10 [95% CI, 1.07; 1.14]). Conversely, the decrease in temperature between the 10(th) and 1(st) percentile had a significant effect on the mortality under 75 years (RR = 1.04 [95% CI, 1.01; 1.06]). In the Paris area, there is no added value in taking multiple climatic stations into account when estimating exposure in time series studies. Methods to better represent the subtle temperature variations in densely populated areas in epidemiological studies are needed.

A Classification of Remote Sensing Image Based on Improved Compound Kernels of Svm

NASA Astrophysics Data System (ADS)

Zhao, Jianing; Gao, Wanlin; Liu, Zili; Mou, Guifen; Lu, Lin; Yu, Lina

The accuracy of RS classification based on SVM which is developed from statistical learning theory is high under small number of train samples, which results in satisfaction of classification on RS using SVM methods. The traditional RS classification method combines visual interpretation with computer classification. The accuracy of the RS classification, however, is improved a lot based on SVM method, because it saves much labor and time which is used to interpret images and collect training samples. Kernel functions play an important part in the SVM algorithm. It uses improved compound kernel function and therefore has a higher accuracy of classification on RS images. Moreover, compound kernel improves the generalization and learning ability of the kernel.

Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2012-01-01

A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

River restoration and biocoenoses improvement in two streams renaturated using bioengeneering.

NASA Astrophysics Data System (ADS)

Leoni, B.; Forasacco, E.; Dobner, R.; Cotta Ramusino, M.

2003-04-01

The Bioengineering is a constructive discipline having its own technical, ecological and environmental friendly scopes, by using living materials. The aim of this study is to assess the river restoration efficiency of Bioengineering. The basic goals of many management-concepts are the integrity of the river habitat, self-regulation and self-regeneration, the preservation of intact resources, to recreate the uniqueness, diversity and beauty of natural river landscape. From an ecological point of view the richness, diversity and age composition of the populations developing after restoration as a result of habitat improvement reveal the degree to which comprehensive concepts were applied (Jungwirth et al., 1995). The following results summarised an investigation on streams Boesio and Rancina in Valcuvia, (Varese, Northern Italy). These streams are characterised by human impacts like water pollution, river engineering and river bioengineering (palificata doppia viva). The samples of macrobenthic fauna were collected between August 2000 and July 2001 in 4 stations for each stream, where the 3rd station of Boesio and Rancina streams is characterised by bioengeneering measure, using a Surber sampler (0.125 m2, mesh size 0.45 mm). The zoobenthic communities of these pre-alpine streams are characterised by low richness and diversity and few families and genera were predominant. In Rancina stream, Ephemeroptera (genus Baetis), Trichoptera (families Hydropsychidae, Limnephilidae and Rhyacophilidae) and Diptera (families Chironomidae and Simuliidae) are present throughout the year with significant densities. The faunal composition of Boesio stream is similar. It differs, only, from stream Rancina to costant presence of Plecoptera with genus Leuctra. To evaluate the restoration of environmental quality two indices were applied: Indice Biotico Esteso (I.B.E.- Ghetti, 1995); Indice di Funzionalità Fluviale (I.F.F.- Siligardi, 2000). The E.B.I. scores of Boesio stream indicate that stations 1 and 2 are in good condition (Ecological status classification: II): therefore the level of diversity and abundance of macrobenthic taxa is slightly outside the range associated with the normal conditions and the most of the sensitive taxa of the type specific communities are present. The stations 3 and 4 are in moderate condition (Ecological status classification: III): the level of diversity and abundance of invertebrate taxa is moderately outside the normal condition range, the taxa indicative of pollution are present and many of the sensitive taxa of the type specific communities are absent. In the Rancina stream in all of the 4 stations the ecological status is indicated like moderate (Ecological status classification: III): there is a predominance of taxa more resistant at pollution and at changes in other biological components of the stream. The I.F.F. show that in Boesio stream the right shore score is moderate-good and the left shore score is moderate-poor. Differently, the Rancina stream presents the right shore with a value poor and the left shore with a wide gradient between good and poor-bad. In conclusion, we can affirm the low efficiency of Bioengineering to restore the Boesio and Rancina streams, because we cannot observe the habitat and aquatic biocoenoses improvement. An explication could be that the conversions are restricted to morphological measures, which are carried out on a small way of banks. Whereas, the restoration using the Bioengineering requires taking the entire catchment area into consideration.

Important Questions Remain to Be Addressed before Adopting a Dimensional Classification of Mental Disorders

ERIC Educational Resources Information Center

Ruscio, Ayelet Meron

2008-01-01

Comments on the original article "Plate tectonics in the classification of personality disorder: Shifting to a dimensional model," by T. A. Widiger and T. J. Trull (2007). Widiger and Trull raised important nosological issues that warrant serious consideration not only for the personality disorders but for all mental disorders as the Diagnostic…

Automated Terrestrial EMI Emitter Detection, Classification, and Localization

NASA Astrophysics Data System (ADS)

Stottler, R.; Bowman, C.; Bhopale, A.

2016-09-01

Clear operating spectrum at ground station antenna locations is critically important for communicating with, commanding, controlling, and maintaining the health of satellites. Electro Magnetic Interference (EMI) can interfere with these communications so tracking down the source of EMI is extremely important to prevent it from occurring in the future. The Terrestrial RFI-locating Automation with CasE based Reasoning (TRACER) system is designed to automate terrestrial EMI emitter localization and identification, providing improved space situational awareness, realizing significant manpower savings, dramatically shortening EMI response time, providing capabilities for the system to evolve without programmer involvement, and offering increased support for adversarial scenarios (e.g. jamming). TRACER has been prototyped and tested with real data (amplitudes versus frequency over time) for both satellite communication antennas and sweeping Direction Finding (DF) antennas located near them. TRACER monitors the satellite communication and DF antenna signals to detect and classify EMI using neural network technology trained on past cases of both normal communications and EMI events. Based on details of the signal (its classification, its direction and strength, etc.) one or more cases of EMI investigation methodologies are retrieved, represented as graphical behavior transition networks (BTNs), which very naturally represent the flowchart-like process often followed by experts in time pressured situations, are intuitive to SMEs, and easily edited by them. The appropriate actions, as determined by the BTN are executed and the resulting data processed by Bayesian Networks to update the probabilities of the various possible platforms and source types of the EMI. Bearing sweep of the EMI is used to determine if the EMI's platform is aerial, a ground vehicle or ship, or stationary. If moving, the Friis transmission equation is used to plot the emitter's location and compare it to current flights or moving vehicles. This paper describes the TRACER technologies and results of prototype testing.

Analysis of A Drug Target-based Classification System using Molecular Descriptors.

PubMed

Lu, Jing; Zhang, Pin; Bi, Yi; Luo, Xiaomin

2016-01-01

Drug-target interaction is an important topic in drug discovery and drug repositioning. KEGG database offers a drug annotation and classification using a target-based classification system. In this study, we gave an investigation on five target-based classes: (I) G protein-coupled receptors; (II) Nuclear receptors; (III) Ion channels; (IV) Enzymes; (V) Pathogens, using molecular descriptors to represent each drug compound. Two popular feature selection methods, maximum relevance minimum redundancy and incremental feature selection, were adopted to extract the important descriptors. Meanwhile, an optimal prediction model based on nearest neighbor algorithm was constructed, which got the best result in identifying drug target-based classes. Finally, some key descriptors were discussed to uncover their important roles in the identification of drug-target classes.

Regional Variability in Ozone in the Tropical and Subtropical Free Troposphere and Tropopause Transition Layer based on Aura-Era SHADOZ Data (2005-2009)

NASA Astrophysics Data System (ADS)

Miller, S. K.; Thompson, A. M.; Witte, J. C.; Balashov, N. V.; Kollonige, D. E.

2012-12-01

The more than 5000 sets of ozone and P-T-U profiles provided for the tropics and subtropics by the Southern Hemisphere Additional Ozonesondes (SHADOZ) since 1998 have provided a wealth of insights into convective and mixing processes, especially in the upper troposphere through lower stratosphere. The observations have been used in evaluations of satellite ozone and chemical-transport and climate-chemistry models. Recently, we analyzed a climatology of ozone profiles based on the 2005-2009 SHADOZ data when 4 new stations joined the network (15 stations total), giving latitudinal coverage from 25S to 21N. We answer the following questions: How do ozone distributions at two new subtropical stations, Hanoi and Hilo in the northern hemisphere, compare to those at the southern subtropical stations, Irene and La Réunion? Are there better-defined regional classifications of tropospheric and tropopause transition layer (TTL) SHADOZ ozone profiles in the tropics, defined as within + 18 degrees latitude, than the Atlantic-Pacific differentiation identified in published studies with 1998-2004 SHADOZ data? Three distinct regions of the tropics are identified based on the criteria: ozone structure in the TTL; convective influence inferred from laminar identification (LID) of ozone and potential temperature; degree of pollution in the free troposphere (FT). These are: (1) western Pacific/eastern Indian Ocean; (2) equatorial Americas (San Cristóbal, Alajuela, Paramaribo); (3) Atlantic Ocean and Africa. In addition, we have re-examined potential trends in FT and TTL ozone at several SHADOZ stations for which data extend back to the early 1990s.

Accurate crop classification using hierarchical genetic fuzzy rule-based systems

NASA Astrophysics Data System (ADS)

Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

2014-10-01

This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

NASA Astrophysics Data System (ADS)

Jürgens, Björn; Herrero-Solana, Victor

2017-04-01

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

An improved arteriovenous classification method for the early diagnostics of various diseases in retinal image.

PubMed

Xu, Xiayu; Ding, Wenxiang; Abràmoff, Michael D; Cao, Ruofan

2017-04-01

Retinal artery and vein classification is an important task for the automatic computer-aided diagnosis of various eye diseases and systemic diseases. This paper presents an improved supervised artery and vein classification method in retinal image. Intra-image regularization and inter-subject normalization is applied to reduce the differences in feature space. Novel features, including first-order and second-order texture features, are utilized to capture the discriminating characteristics of arteries and veins. The proposed method was tested on the DRIVE dataset and achieved an overall accuracy of 0.923. This retinal artery and vein classification algorithm serves as a potentially important tool for the early diagnosis of various diseases, including diabetic retinopathy and cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

A preliminary examination of patient loyalty: an application of the customer loyalty classification framework in the health care industry.

PubMed

Heiens, R A; Pleshko, L P

1997-01-01

The present article applies the customer loyalty classification framework developed by Dick and Basu (1994) to the health care industry. Based on a two factor classification, consisting of repeat patronage and relative attitude, four categories of patient loyalty are proposed and examined, including true loyalty, latent loyalty, spurious loyalty, and no loyalty. Data is collected and the four patient loyalty categories are profiled and compared on the basis of perceived risk, product class importance, provider decision importance, provider awareness, provider consideration, number of providers visited, and self-reported loyalty.

Photovoltaic central station step and touch potential considerations in grounding system design

NASA Technical Reports Server (NTRS)

Engmann, G.

1983-01-01

The probability of hazardous step and touch potentials is an important consideration in central station grounding system design. Steam turbine generating station grounding system design is based on accepted industry practices and there is extensive in-service experience with these grounding systems. A photovoltaic (PV) central station is a relatively new concept and there is limited experience with PV station grounding systems. The operation and physical configuration of a PV central station is very different from a steam electric station. A PV station bears some similarity to a substation and the PV station step and touch potentials might be addressed as they are in substation design. However, the PV central station is a generating station and it is appropriate to examine the effect that the differences and similarities of the two types of generating stations have on step and touch potential considerations.

Pet fur color and texture classification

NASA Astrophysics Data System (ADS)

Yen, Jonathan; Mukherjee, Debarghar; Lim, SukHwan; Tretter, Daniel

2007-01-01

Object segmentation is important in image analysis for imaging tasks such as image rendering and image retrieval. Pet owners have been known to be quite vocal about how important it is to render their pets perfectly. We present here an algorithm for pet (mammal) fur color classification and an algorithm for pet (animal) fur texture classification. Per fur color classification can be applied as a necessary condition for identifying the regions in an image that may contain pets much like the skin tone classification for human flesh detection. As a result of the evolution, fur coloration of all mammals is caused by a natural organic pigment called Melanin and Melanin has only very limited color ranges. We have conducted a statistical analysis and concluded that mammal fur colors can be only in levels of gray or in two colors after the proper color quantization. This pet fur color classification algorithm has been applied for peteye detection. We also present here an algorithm for animal fur texture classification using the recently developed multi-resolution directional sub-band Contourlet transform. The experimental results are very promising as these transforms can identify regions of an image that may contain fur of mammals, scale of reptiles and feather of birds, etc. Combining the color and texture classification, one can have a set of strong classifiers for identifying possible animals in an image.

Toward optimal feature and time segment selection by divergence method for EEG signals classification.

PubMed

Wang, Jie; Feng, Zuren; Lu, Na; Luo, Jing

2018-06-01

Feature selection plays an important role in the field of EEG signals based motor imagery pattern classification. It is a process that aims to select an optimal feature subset from the original set. Two significant advantages involved are: lowering the computational burden so as to speed up the learning procedure and removing redundant and irrelevant features so as to improve the classification performance. Therefore, feature selection is widely employed in the classification of EEG signals in practical brain-computer interface systems. In this paper, we present a novel statistical model to select the optimal feature subset based on the Kullback-Leibler divergence measure, and automatically select the optimal subject-specific time segment. The proposed method comprises four successive stages: a broad frequency band filtering and common spatial pattern enhancement as preprocessing, features extraction by autoregressive model and log-variance, the Kullback-Leibler divergence based optimal feature and time segment selection and linear discriminate analysis classification. More importantly, this paper provides a potential framework for combining other feature extraction models and classification algorithms with the proposed method for EEG signals classification. Experiments on single-trial EEG signals from two public competition datasets not only demonstrate that the proposed method is effective in selecting discriminative features and time segment, but also show that the proposed method yields relatively better classification results in comparison with other competitive methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Estimates of Median Flows for Streams on the 1999 Kansas Surface Water Register

USGS Publications Warehouse

Perry, Charles A.; Wolock, David M.; Artman, Joshua C.

2004-01-01

The Kansas State Legislature, by enacting Kansas Statute KSA 82a?2001 et. seq., mandated the criteria for determining which Kansas stream segments would be subject to classification by the State. One criterion for the selection as a classified stream segment is based on the statistic of median flow being equal to or greater than 1 cubic foot per second. As specified by KSA 82a?2001 et. seq., median flows were determined from U.S. Geological Survey streamflow-gaging-station data by using the most-recent 10 years of gaged data (KSA) for each streamflow-gaging station. Median flows also were determined by using gaged data from the entire period of record (all-available hydrology, AAH). Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating median flows for uncontrolled stream segments. The drainage area of the gaging stations on uncontrolled stream segments used in the regression analyses ranged from 2.06 to 12,004 square miles. A logarithmic transformation of the data was needed to develop the best linear relation for computing median flows. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. Tobit analyses of KSA data yielded a model standard error of prediction of 0.285 logarithmic units, and the best equations using Tobit analyses of AAH data had a model standard error of prediction of 0.250 logarithmic units. These regression equations and an interpolation procedure were used to compute median flows for the uncontrolled stream segments on the 1999 Kansas Surface Water Register. Measured median flows from gaging stations were incorporated into the regression-estimated median flows along the stream segments where available. The segments that were uncontrolled were interpolated using gaged data weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled segments of Kansas streams, the median flow information was interpolated between gaging stations using only gaged data weighted by drainage area. Of the 2,232 total stream segments on the Kansas Surface Water Register, 34.5 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second when the KSA analysis was used. When the AAH analysis was used, 36.2 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second. This report supercedes U.S. Geological Survey Water-Resources Investigations Report 02?4292.

The Application of Speaker Recognition Techniques in the Detection of Tsunamigenic Earthquakes

NASA Astrophysics Data System (ADS)

Gorbatov, A.; O'Connell, J.; Paliwal, K.

2015-12-01

Tsunami warning procedures adopted by national tsunami warning centres largely rely on the classical approach of earthquake location, magnitude determination, and the consequent modelling of tsunami waves. Although this approach is based on known physics theories of earthquake and tsunami generation processes, this may be the main shortcoming due to the need to satisfy minimum seismic data requirement to estimate those physical parameters. At least four seismic stations are necessary to locate the earthquake and a minimum of approximately 10 minutes of seismic waveform observation to reliably estimate the magnitude of a large earthquake similar to the 2004 Indian Ocean Tsunami Earthquake of M9.2. Consequently the total time to tsunami warning could be more than half an hour. In attempt to reduce the time of tsunami alert a new approach is proposed based on the classification of tsunamigenic and non tsunamigenic earthquakes using speaker recognition techniques. A Tsunamigenic Dataset (TGDS) was compiled to promote the development of machine learning techniques for application to seismic trace analysis and, in particular, tsunamigenic event detection, and compare them to existing seismological methods. The TGDS contains 227 off shore events (87 tsunamigenic and 140 non-tsunamigenic earthquakes with M≥6) from Jan 2000 to Dec 2011, inclusive. A Support Vector Machine classifier using a radial-basis function kernel was applied to spectral features derived from 400 sec frames of 3-comp. 1-Hz broadband seismometer data. Ten-fold cross-validation was used during training to choose classifier parameters. Voting was applied to the classifier predictions provided from each station to form an overall prediction for an event. The F1 score (harmonic mean of precision and recall) was chosen to rate each classifier as it provides a compromise between type-I and type-II errors, and due to the imbalance between the representative number of events in the tsunamigenic and non-tsunamigenic classes. The described classifier achieved an F1 score of 0.923, with tsunamigenic classification precision and recall/sensitivity of 0.928 and 0.919 respectively. The system requires a minimum of 3 stations with ~400 seconds of data each to make a prediction. The accuracy improves as further stations and data become available.

Analysis of chosen urban bioclimatic conditions in Upper Silesian Industrial Region, Poland

NASA Astrophysics Data System (ADS)

Zimnol, Jan

2013-04-01

Due to the increasing urbanization, people spend more and more time in cities. Because of that fact during the last century the human bioclimatological approach had an important influence on the applied urban bioclimatology. The aim of the study was to analyze chosen thermal bioclimatic conditions in urban area of Upper Silesian Industrial Region in connection with the atmospheric circulation and air masses. The study was focused on the thermal conditions that are important for the bioclimatological research on human thermal comfort. They were the basis for making study on how to show the influence of the air masses and circulations types on frequency and variability of the chosen bioclimate indexes. That research was based on data (2004 - 2008) acquired by the Silesian University (Faculty of Earth Sciences) meteorological station located in the city of Sosnowiec (50°17'N, 19°08'E, h=263 m a.s.l.). The temperature measurements were made automatically every 10 minutes on the 2 meters above the ground level. Previous research showed that the station is a good representation of the local urban climate conditions in Upper Silesian Industrial Region. In the study the following air temperatures were taken into consideration: average day temperature, maximum day temperature, minimum day temperature and the average air temperature at 12 UTC. They were associated with atmospheric circulation types and masses typical for the region. Using the data mentioned above I conducted a classification to divide days into following objective categories: cool, cold, comfortable, hot, warm and very hot in the seasonal depiction. The final stage of the work was to find the answer to the following question: "When and how do the strong air masses and air circulations types modify bioclimatic conditions in the study area?" Answer to that question together with further results of the research will be presented on my poster.

Temporal trends of Persistent Organic Pollutants (POPs) in arctic air: 20 years of monitoring under the Arctic Monitoring and Assessment Programme (AMAP).

PubMed

Hung, Hayley; Katsoyiannis, Athanasios A; Brorström-Lundén, Eva; Olafsdottir, Kristin; Aas, Wenche; Breivik, Knut; Bohlin-Nizzetto, Pernilla; Sigurdsson, Arni; Hakola, Hannele; Bossi, Rossana; Skov, Henrik; Sverko, Ed; Barresi, Enzo; Fellin, Phil; Wilson, Simon

2016-10-01

Temporal trends of Persistent Organic Pollutants (POPs) measured in Arctic air are essential in understanding long-range transport to remote regions and to evaluate the effectiveness of national and international chemical control initiatives, such as the Stockholm Convention (SC) on POPs. Long-term air monitoring of POPs is conducted under the Arctic Monitoring and Assessment Programme (AMAP) at four Arctic stations: Alert, Canada; Stórhöfði, Iceland; Zeppelin, Svalbard; and Pallas, Finland, since the 1990s using high volume air samplers. Temporal trends observed for POPs in Arctic air are summarized in this study. Most POPs listed for control under the SC, e.g. polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs) and chlordanes, are declining slowly in Arctic air, reflecting the reduction of primary emissions during the last two decades and increasing importance of secondary emissions. Slow declining trends also signifies their persistence and slow degradation under the Arctic environment, such that they are still detectable after being banned for decades in many countries. Some POPs, e.g. hexachlorobenzene (HCB) and lighter PCBs, showed increasing trends at specific locations, which may be attributable to warming in the region and continued primary emissions at source. Polybrominated diphenyl ethers (PBDEs) do not decline in air at Canada's Alert station but are declining in European Arctic air, which may be due to influence of local sources at Alert and the much higher historical usage of PBDEs in North America. Arctic air samples are screened for chemicals of emerging concern to provide information regarding their environmental persistence (P) and long-range transport potential (LRTP), which are important criteria for classification as a POP under SC. The AMAP network provides consistent and comparable air monitoring data of POPs for trend development and acts as a bridge between national monitoring programs and SC's Global Monitoring Plan (GMP). Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Nemani, Ramakrishna

2005-01-01

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

Leak detection in gas pipeline by acoustic and signal processing - A review

NASA Astrophysics Data System (ADS)

Adnan, N. F.; Ghazali, M. F.; Amin, M. M.; Hamat, A. M. A.

2015-12-01

The pipeline system is the most important part in media transport in order to deliver fluid to another station. The weak maintenance and poor safety will contribute to financial losses in term of fluid waste and environmental impacts. There are many classifications of techniques to make it easier to show their specific method and application. This paper's discussion about gas leak detection in pipeline system using acoustic method will be presented in this paper. The wave propagation in the pipeline is a key parameter in acoustic method when the leak occurs and the pressure balance of the pipe will generated by the friction between wall in the pipe. The signal processing is used to decompose the raw signal and show in time- frequency. Findings based on the acoustic method can be used for comparative study in the future. Acoustic signal and HHT is the best method to detect leak in gas pipelines. More experiments and simulation need to be carried out to get the fast result of leaking and estimation of their location.

Forest site classification in the interior uplands

Treesearch

Glendon W. Smalley

1989-01-01

Classification and evaluation of forest sites is an essential step in managing central hardwood forests. In Note 4.01, The Importance of Site Quality, the usefulness of land classification systems was discussed. The present Note describes one of those systems in more detail. It is an easy-to-use system developed for the Cumberland Plateau and Highland Rim-Pennyroyal...

ASTM and other specifications and classifications for petroleum products and lubricants. Fifth edition

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

Not Available

1989-01-01

This book includes specifications and classifications from ASTM committees on paint and related coatings and materials; road and paving materials; wood; roofing, waterproofing and bituminous materials; rubber; soaps and other detergents; aromatic hydrocarbons and related chemicals; and electrical insulating liquids and gases. Also included are several related, important specifications and classifications from other organizations.

The Importance of Motor Functional Levels from the Activity Limitation Perspective of ICF in Children with Cerebral Palsy

ERIC Educational Resources Information Center

Mutlu, Akmer

2010-01-01

Our purpose in this study was to evaluate performance and capacity as defined by Gross Motor Function Classification System (GMFCS) and Manual Ability Classification System (MACS) from the "activity limitation" perspective of International Classification of Functioning, Disability, and Health (ICF) and to investigate the relationship between the…

Variations in Precipitation Parameters between Drought and Nondrought Periods in Texas and Some Implications for Cloud Seeding.

NASA Astrophysics Data System (ADS)

Flynn, Michael S.; Griffiths, John F.

1980-12-01

An analysis of the possible differences among various rainfall parameters during drought and nondrought periods was undertaken for 12 Texas stations. The division of monthly rainfall amounts into quintiles served as the rainfall classification. Rainfall amounts, number of rains and rainfall intensities were calculated for each quintile for four thresholds of rainfall 0.0254, 0.2540, 0.5080 and 1.2700 cm. The thresholds were applied on a daily and hourly basis. At low rainfall thresholds in nearly every case, numbers of rains in very dry periods proved to be <100% of normal.The possible differences in persistence of rainfall during Very Dry and Very Wet periods were examined by calculating runs of rains of 0.0254 cm or more per hour. Medians of runs of rain hours in Very Dry periods were found to be less than those in Very Wet periods except at Corpus Christi in April and at Waco in February. Probabilities that a run of rain hours would extend to a given length were determined. During Very Dry periods a probability >0.5 that a rain will extend into a second hour during a month of key importance to agriculture (June, July and August) occurs only at Amarillo, Lovelady, Port Arthur and Waco. The probability that a rain will extend into a third hour is never above 0.5 during the key months in Very Dry periods for any of the stations studied.The implications of these findings are discussed in relation to feasibility of cloud seeding and to irrigation management during severe drought.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Brentwood Lessons Learned Project Report

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

Rivkin, Carl H.; Caton, Melanie C.; Ainscough, Christopher D.

The purpose of this report is to document lessons learned in the installation of the hydrogen fueling station at the National Park Service Brentwood site in Washington, D.C., to help further the deployment of hydrogen infrastructure required to support hydrogen and other fuel cell technologies. Hydrogen fueling is the most difficult infrastructure component to build and permit. Hydrogen fueling can include augmenting hydrogen fueling capability to existing conventional fuel fueling stations as well as building brand new hydrogen fueling stations. This report was produced as part of the Brentwood Lessons Learned project. The project consisted of transplanting an existing modularmore » hydrogen fueling station from Connecticut to the National Park Service Brentwood site. This relocation required design and construction at the Brentwood site to accommodate the existing station design as well as installation and validation of the updated station. One of the most important lessons learned was that simply moving an existing modular station to an operating site was not necessarily straight-forward - performing the relocation required significant effort and cost. The station has to function at the selected operating site and this functionality requires a power supply, building supports connecting to an existing alarm system, electrical grounding and lighting, providing nitrogen for purging, and providing deionized water if an electrolyzer is part of the station package. Most importantly, the station has to fit into the existing site both spatially and operationally and not disrupt existing operations at the site. All of this coordination and integration requires logistical planning and project management. The idea that a hydrogen fueling station can be simply dropped onto a site and made immediately operational is generally not realistic. Other important lessons learned include that delineating the boundaries of the multiple jurisdictions that have authority over a project for all parties involved in the project are key to an efficient approval process; and site investigation is necessary when integrating a new station design onto an existing site, particularly an older existing site that may have limited documentation on the site history and operations. The lessons learned for permitting and subcontracting construction work can be applied to other similar sites and to commercial sites.« less

The Advantages and Limitations of International Classification of Diseases, Injuries and Causes of Death from Aspect of Existing Health Care System of Bosnia and Herzegovina

PubMed Central

Kurbasic, Izeta; Pandza, Haris; Masic, Izet; Huseinagic, Senad; Tandir, Salih; Alicajic, Fredi; Toromanovic, Selim

2008-01-01

CONFLICT OF INTEREST: NONE DECLARED Introduction The International classification of diseases (ICD) is the most important classification in medicine. It is used by all medical professionals. Concept The basic concept of ICD is founded on the standardization of the nomenclature for the names of diseases and their basic systematization in the hierarchically structured category. Advantages and disadvantages The health care provider institutions such as hospitals are subjects that should facilitate implementation of medical applications that follows the patient medical condition and facts connected with him. The definitive diagnosis that can be coded using ICD can be achieved after several visits of patient and rarely during the first visit. Conclusion The ICD classification is one of the oldest and most important classifications in medicine. In the scope of ICD are all fields of medicine. It is used in statistical purpose and as a coding system in medical databases. PMID:24109155

Computational approaches for the classification of seed storage proteins.

PubMed

Radhika, V; Rao, V Sree Hari

2015-07-01

Seed storage proteins comprise a major part of the protein content of the seed and have an important role on the quality of the seed. These storage proteins are important because they determine the total protein content and have an effect on the nutritional quality and functional properties for food processing. Transgenic plants are being used to develop improved lines for incorporation into plant breeding programs and the nutrient composition of seeds is a major target of molecular breeding programs. Hence, classification of these proteins is crucial for the development of superior varieties with improved nutritional quality. In this study we have applied machine learning algorithms for classification of seed storage proteins. We have presented an algorithm based on nearest neighbor approach for classification of seed storage proteins and compared its performance with decision tree J48, multilayer perceptron neural (MLP) network and support vector machine (SVM) libSVM. The model based on our algorithm has been able to give higher classification accuracy in comparison to the other methods.

Combining various types of classifiers and features extracted from magnetic resonance imaging data in schizophrenia recognition.

PubMed

Janousova, Eva; Schwarz, Daniel; Kasparek, Tomas

2015-06-30

We investigated a combination of three classification algorithms, namely the modified maximum uncertainty linear discriminant analysis (mMLDA), the centroid method, and the average linkage, with three types of features extracted from three-dimensional T1-weighted magnetic resonance (MR) brain images, specifically MR intensities, grey matter densities, and local deformations for distinguishing 49 first episode schizophrenia male patients from 49 healthy male subjects. The feature sets were reduced using intersubject principal component analysis before classification. By combining the classifiers, we were able to obtain slightly improved results when compared with single classifiers. The best classification performance (81.6% accuracy, 75.5% sensitivity, and 87.8% specificity) was significantly better than classification by chance. We also showed that classifiers based on features calculated using more computation-intensive image preprocessing perform better; mMLDA with classification boundary calculated as weighted mean discriminative scores of the groups had improved sensitivity but similar accuracy compared to the original MLDA; reducing a number of eigenvectors during data reduction did not always lead to higher classification accuracy, since noise as well as the signal important for classification were removed. Our findings provide important information for schizophrenia research and may improve accuracy of computer-aided diagnostics of neuropsychiatric diseases. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A feature illustration and application of azimuthal P receiver function patterns

NASA Astrophysics Data System (ADS)

Eckhardt, C.; Rabbel, W.

2009-12-01

Based on a synthetic catalog of thirty azimuthal patterns of P receiver functions for crustal structures down to thirty km depth we have summarized and illustrated the most important azimuthal features. We have constructed five model classes encompassing (an-)isotropic horizontal and dipping layers. The model classes were initialized by in situ observations of three deep reflection seismic profiles (DEKORP) of varying high reflective zones and a spiral shaped foliation scheme of an upper crustal bore hole out of the German Continental Deep Drilling Program (KTB). Up to fourteen azimuthal features were extracted out of the synthetic patterns and could be grouped into an already known fundamental part, a multiple part and into an extension part. Each feature was rated by a specific grade A, B, C to inform about the type of its initialization ((an-) isotropy and/or layer dipping). We have evaluated the fourteen features on the synthetic patterns to apply a hierarchical classification. From the classification of the model objects we found that nearly eighty percent of the models are well explained by the fundamental part. The hierarchical order of the model objects can be used as a template to screen real observed azimuthal patterns to find a starting model for a forward modeling or an inversion procedure. For one station of the German Regional Seismic Network (GRSN) we have evaluated the features and screened them through the template. A forward simulation of the azimuthal pattern, using the modified first found model explanation out of the hierarchical order for station MOX, leads to a good coincidence between the real and the simulated pattern. The final 1D model could be divided into an upper crustal part (8 km deep) with an axis of symmetry tilt of 55° and 20°NW trend (direction of axis tilt) and a lower crustal part (24 km thickness) with an axis of symmetry of increasing tilt from 55° to 85° and a trend orientation of 20°SE. For the simulation we have assumed 8 and 7 percent of negative P+S anisotropy for hexagonal symmetry of the upper and lower crust, respectively. From the synthetic and the real observations it is evident that additional boundaries beside the Moho discontinuity are merely detectable for certain circumstances in an azimuthal resolution and will be blinded out in the traditional radial stack.

[Some problems of space medicine].

PubMed

Gurovskiĭ, N N; Egorov, A D

1976-01-01

The paper discusses the problems to be resolved by space medicine and the main stages in the development of this branch of science, beginning with the vertical launches of rockets and ending with the flights of orbital stations. On the basis of ground-based simulation experiments and real space flights it presents a classification of the major symptomocomplexes that may occur inflight. The paper describes the main stages of adaptation to weightlessness and physiological changes in the weightless state. The paper also outlines further pathways in the development of space medicine.

Advanced Electron Optics for Vibrational Spectroscopy.

DTIC Science & Technology

1987-10-02

observations of vibrational losses measured 0 2z b n t l o a i r u e h s i by inelastic elctron scattering from surfaces. The basic dif- ference...AFOSR-86-6291 UNCLASSIFIED F/Ci 26/14 U EhEilEEEEEBI / E /EEiEEElh E /EEEE~h R-~ ~ 3 -00 0 0 S *...S :04 *.: UNA A ASSIFIED 469 RT CLASSIFICATION OF THIS...Surfaces", J.L. Erskine, American Vacuum Society Lecture, Texas A&M Unversity, College Station, Texas, April 24,1984. e "Electron Energy Loss Studies of

9 CFR 93.410 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2012 CFR

2012-01-01

... quarantine station. 93.410 Section 93.410 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported ruminants shall be cleaned... transferred from the conveyance to the quarantine grounds in boats, cars, or vehicles approved by the...

9 CFR 93.410 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2011 CFR

2011-01-01

... quarantine station. 93.410 Section 93.410 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported ruminants shall be cleaned... transferred from the conveyance to the quarantine grounds in boats, cars, or vehicles approved by the...

9 CFR 93.410 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2014 CFR

2014-01-01

... quarantine station. 93.410 Section 93.410 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported ruminants shall be cleaned... transferred from the conveyance to the quarantine grounds in boats, cars, or vehicles approved by the...

9 CFR 93.410 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2013 CFR

2013-01-01

... quarantine station. 93.410 Section 93.410 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported ruminants shall be cleaned... transferred from the conveyance to the quarantine grounds in boats, cars, or vehicles approved by the...

A comparative analysis of high-speed rail station development into destination and multi-use facilities : the case of San Jose Diridon.

DOT National Transportation Integrated Search

2017-02-01

As a burgeoning literature on high-speed rail development indicates, good station-area planning is a very important prerequisite for the eventual successful operation of a high-speed rail station; it can also trigger opportunities for economic develo...

78 FR 24666 - Updates to the List of Plant Inspection Stations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-26

... plant material imported for plant breeding and research programs. The Plant Germplasm Inspection Station... DEPARTMENT OF AGRICULTURE Animal and Plant Health Inspection Service 7 CFR Part 319 [Docket No. APHIS-2012-0099] Updates to the List of Plant Inspection Stations AGENCY: Animal and Plant Health...

The Miners' Radio Stations in Bolivia: A Culture of Resistance.

ERIC Educational Resources Information Center

O'Connor, Alan

1990-01-01

Examines local community radio stations in rural regions of Bolivia. Finds that active miners' radio has flourished as an entertainment and political medium and that, through their radio stations, miners' organizations have played an important role in shaping the political position of the Bolivian union movement. (KEH)

Space station control moment gyro control

NASA Technical Reports Server (NTRS)

Bordano, Aldo

1987-01-01

The potential large center-of-pressure to center-of-gravity offset of the space station makes the short term, within an orbit, variations in density of primary importance. The large range of uncertainty in the prediction of solar activity will penalize the design, developments, and operation of the space station.

The Importance of Radio News to Listeners.

ERIC Educational Resources Information Center

Martin, Ernie

While the news is considered a vitally important aspect of most radio stations' formats, broadcasters need to determine what a listener wants from the news-listening experience and how a station can program news in the form most desirable for the listener. This study, based on a Lawrence, Kansas, telephone survey of radio listeners, found that…

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Classification, Seriation, and Counting in Grades 1, 2, and 3 as Two-Year Longitudinal Predictors for Low Achieving in Numerical Facility and Arithmetical Achievement?

ERIC Educational Resources Information Center

Desoete, Annemie; Stock, Pieter; Schepens, Annemie; Baeyens, Dieter; Roeyers, Herbert

2009-01-01

Previous research stresses the importance of seriation, classification, and counting abilities that should be assessed in kindergarten, when looking for crucial predictors of mathematical learning disabilities in Grade 1. This study examines (n = 158) two-year-long predictive relationships between children's seriation, classification, procedural…

Forested land cover classification on the Cumberland Plateau, Jackson County, Alabama: a comparison of Landsat ETM+ and SPOT5 images

Treesearch

Yong Wang; Shanta Parajuli; Callie Schweitzer; Glendon Smalley; Dawn Lemke; Wubishet Tadesse; Xiongwen Chen

2010-01-01

Forest cover classifications focus on the overall growth form (physiognomy) of the community, dominant vegetation, and species composition of the existing forest. Accurately classifying the forest cover type is important for forest inventory and silviculture. We compared classification accuracy based on Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) and Satellite...

Random forests for classification in ecology

USGS Publications Warehouse

Cutler, D.R.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J.

2007-01-01

Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature. ?? 2007 by the Ecological Society of America.

Aggressive B-cell lymphomas in the update of the 4th edition of the World Health Organization classification of haematopoietic and lymphatic tissues: refinements of the classification, new entities and genetic findings.

PubMed

Ott, German

2017-09-01

The update of the 4th edition of the World Health Organization Classification of Haematopoietic and Lymphatic Tissues portends important new findings and concepts in the diagnosis, classification and biology of lymphomas. This review summarizes the basic concepts and cornerstones of the classification of aggressive B-cell lymphomas and details the major changes. Of importance, there is a new concept of High-grade B-cell lymphomas (HGBL), partly replacing the provisional entity of B-cell lymphoma, unclassifiable, with features intermediate between diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma, the so-called grey zone lymphomas. They either harbour MYC translocations together with a BCL2 and/or a BCL6 rearrangement (HGBL-Double Hit) or HGBL, not otherwise specified (NOS), lacking a double or triple hit constellation. In addition, the requirement for providing the cell-of-origin classification in the diagnostic work-up of DLBCLs, the role of MYC alterations in DLBCL subtypes, and newer findings in the specific variants/subtypes are highlighted. © 2017 John Wiley & Sons Ltd.

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Non-linear molecular pattern classification using molecular beacons with multiple targets.

PubMed

Lee, In-Hee; Lee, Seung Hwan; Park, Tai Hyun; Zhang, Byoung-Tak

2013-12-01

In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The US space station: Potential base for a spaceborne microwave facility

NASA Technical Reports Server (NTRS)

Mcconnell, D.

1983-01-01

Concepts for a U.S. space station were studied to achieve the full potential of the Space Shuttle and to provide a more permanent presence in space. The space station study is summarized in the following questions: Given a space station in orbit in the 1990's, how should it best be used to achieve science and applications objectives important at that time? To achieve those objectives, of what elements should the station be comprised and how should the elements be configured and equipped. These questions are addressed.

47 CFR 74.633 - Temporary authorizations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... name and address, facility identification number of the associated broadcast station(s) (if any), call... wide-spread interest and importance which cannot be transmitted successfully on these frequencies...

New Myositis Classification Criteria-What We Have Learned Since Bohan and Peter.

PubMed

Leclair, Valérie; Lundberg, Ingrid E

2018-03-17

Idiopathic inflammatory myopathy (IIM) classification criteria have been a subject of debate for many decades. Despite several limitations, the Bohan and Peter criteria are still widely used. The aim of this review is to discuss the evolution of IIM classification criteria. New IIM classification criteria are periodically proposed. The discovery of myositis-specific and myositis-associated autoantibodies led to the development of clinico-serological criteria, while in-depth description of IIM morphological features improved histopathology-based criteria. The long-awaited European League Against Rheumatism and American College of Rheumatology (EULAR/ACR) IIM classification criteria were recently published. The Bohan and Peter criteria are outdated and validated classification criteria are necessary to improve research in IIM. The new EULAR/ACR IIM classification criteria are thus a definite improvement and an important step forward in the field.

Atmospheric circulation classification comparison based on wildfires in Portugal

NASA Astrophysics Data System (ADS)

Pereira, M. G.; Trigo, R. M.

2009-04-01

Atmospheric circulation classifications are not a simple description of atmospheric states but a tool to understand and interpret the atmospheric processes and to model the relation between atmospheric circulation and surface climate and other related variables (Radan Huth et al., 2008). Classifications were initially developed with weather forecasting purposes, however with the progress in computer processing capability, new and more robust objective methods were developed and applied to large datasets prompting atmospheric circulation classification methods to one of the most important fields in synoptic and statistical climatology. Classification studies have been extensively used in climate change studies (e.g. reconstructed past climates, recent observed changes and future climates), in bioclimatological research (e.g. relating human mortality to climatic factors) and in a wide variety of synoptic climatological applications (e.g. comparison between datasets, air pollution, snow avalanches, wine quality, fish captures and forest fires). Likewise, atmospheric circulation classifications are important for the study of the role of weather in wildfire occurrence in Portugal because the daily synoptic variability is the most important driver of local weather conditions (Pereira et al., 2005). In particular, the objective classification scheme developed by Trigo and DaCamara (2000) to classify the atmospheric circulation affecting Portugal have proved to be quite useful in discriminating the occurrence and development of wildfires as well as the distribution over Portugal of surface climatic variables with impact in wildfire activity such as maximum and minimum temperature and precipitation. This work aims to present: (i) an overview the existing circulation classification for the Iberian Peninsula, and (ii) the results of a comparison study between these atmospheric circulation classifications based on its relation with wildfires and relevant meteorological variables. To achieve these objectives we consider the main classifications for Iberia developed within the framework of COST action 733 (Radan Huth et al., 2008). This European project aims to provide a wide range of atmospheric circulation classifications for Europe and sub-regions (http://www.cost733.org/) with an ambitious objective of assessing, comparing and classifying all relevant weather situations in Europe. Pereira et al. (2005) "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology,129, 11-25. Radan Huth et al. (2008) "Classifications of Atmospheric circulation patterns. Recent advances and applications". Trends and Directions in Climate Research: Ann. N.Y. Acad. Sci. 1146: 105-152. doi: 10.1196/annals.1446.019. Trigo R.M., DaCamara C. (2000) "Circulation Weather Types and their impact on the precipitation regime in Portugal". Int J of Climatology, 20, 1559-1581.

9 CFR 93.509 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2014 CFR

2014-01-01

... quarantine station. 93.509 Section 93.509 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported swine shall be cleaned and... conveyance to the quarantine grounds in boats, cars, or vehicles approved by the inspector in charge at the...

9 CFR 93.509 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2012 CFR

2012-01-01

... quarantine station. 93.509 Section 93.509 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported swine shall be cleaned and... conveyance to the quarantine grounds in boats, cars, or vehicles approved by the inspector in charge at the...

9 CFR 93.509 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2011 CFR

2011-01-01

... quarantine station. 93.509 Section 93.509 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported swine shall be cleaned and... conveyance to the quarantine grounds in boats, cars, or vehicles approved by the inspector in charge at the...

9 CFR 93.509 - Movement from conveyances to quarantine station.

Code of Federal Regulations, 2013 CFR

2013-01-01

... quarantine station. 93.509 Section 93.509 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... conveyances to quarantine station. Platforms and chutes used for handling imported swine shall be cleaned and... conveyance to the quarantine grounds in boats, cars, or vehicles approved by the inspector in charge at the...

A comparative analysis of high speed rail station development into destination and/or multi-use facilities : the case of San Jose Diridon.

DOT National Transportation Integrated Search

2017-02-01

As a burgeoning literature on high-speed rail development indicates, good station-area planning is a very important prerequisite for the : eventual successful operation of a high-speed rail station; it can also trigger opportunities for economic deve...

Space stations: Living in zero gravity, developmental task for psychologists and space environmental experts

NASA Technical Reports Server (NTRS)

Ludwig, E.

1984-01-01

The recent advances in the psychological aspects of space station design are discussed, including the impact of the increase in awareness of both the public in general as well as space environmental experts of the importance of psychological factors when designing space stations and training astronauts.

The effect of Kingston Harbour outflow on the zooplankton populations of Hellshire, south-east coast, Jamaica

NASA Astrophysics Data System (ADS)

Lindo, Mona K.

1991-06-01

Zooplankton sampling was conducted at 16 stations located at the mouth of Kingston Harbour and throughout the Hellshire area from November 1985 to March 1987. Parameters examined included total biomass, total numbers and numbers of numerically important zooplankton species. Maximum values were recorded west of the Harbour mouth (station 1) and these gradually decreased with distance from the Harbour especially at the 'offshore' stations, producing a gradient effect in this area. Mean biomass and abundance for the period sampled ranged from 14 g m -3 and 16 313 individuals m -3 at the western side of the Harbour mouth to 0·4 g m -3 and 172 individuals m -3 at Wreck Reef. Stations within the bays of Hellshire occasionally had values similar to those recorded at the mouth of Kingston Harbour and here there was less evidence of a gradual decline. Considerable monthly fluctuation occurred in these parameters but there was no discernible seasonal pattern. Copepods dominated the population at most stations and the sergestid Lucifer faxoni also proved an important member at the western Harbour mouth station.

Research on station management in subway operation safety

NASA Astrophysics Data System (ADS)

Li, Yiman

2017-10-01

The management of subway station is an important part of the safe operation of urban subway. In order to ensure the safety of subway operation, it is necessary to study the relevant factors that affect station management. In the protection of subway safety operations on the basis of improving the quality of service, to promote the sustained and healthy development of subway stations. This paper discusses the influencing factors of subway operation accident and station management, and analyzes the specific contents of station management security for subway operation, and develops effective suppression measures. It is desirable to improve the operational quality and safety factor for subway operations.

Measurement and analysis of electromagnetic pollution generated by GSM-900 mobile phone networks in Erciyes University, Turkey.

PubMed

Sorgucu, Ugur; Develi, Ibrahim

2012-12-01

Mobile phones are becoming increasingly important in our everyday lives. The rising number of mobile phones reflects a similar increase in the number of base stations. Because of this rapid evolution, the establishment and planning of new base stations has become mandatory. However, the rise in the number of base stations, in terms of human health, is potentially very harmful. It is important to analyze the radiation levels of base stations until we can confirm that they are definitely not harmful in the long term. Mapping of electromagnetic field (EMF) is also important from a medical point of view because it provides useful information, for example, on the detection of diseases caused by EMF. With the help of this information the distribution of diseases over different regions can be obtained. In this article, the electromagnetic radiation levels of base stations were measured at 80 different points in Erciyes University (ERU), Turkey and detailed information about the measurement tools and measurement method were given. It was observed that no area in ERU exceeded the national and international limits. It is also observed that the effects of base stations vary according to duration and degree of exposure. Therefore, if people are exposed to a very low-intensity electromagnetic field for a very long time, serious health problems can occur.

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

PubMed

Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

2013-09-01

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

Enhancing the Value and Sustainability of Field Stations and Marine Laboratories in the 21st Century

ERIC Educational Resources Information Center

National Academies Press, 2014

2014-01-01

For over a century, field stations have been important entryways for scientists to study and make important discoveries about the natural world. They are centers of research, conservation, education, and public outreach, often embedded in natural environments that range from remote to densely populated urban locations. Because they lack…

Agricultural Land Cover from Multitemporal C-Band SAR Data

NASA Astrophysics Data System (ADS)

Skriver, H.

2013-12-01

Henning Skriver DTU Space, Technical University of Denmark Ørsteds Plads, Building 348, DK-2800 Lyngby e-mail: hs@space.dtu.dk Problem description This paper focuses on land cover type from SAR data using high revisit acquisitions, including single and dual polarisation and fully polarimetric data, at C-band. The data set were acquired during an ESA-supported campaign, AgriSAR09, with the Radarsat-2 system. Ground surveys to obtain detailed land cover maps were performed during the campaign. Classification methods using single- and dual-polarisation data, and fully polarimetric data are used with multitemporal data with short revisit time. Results for airborne campaigns have previously been reported in Skriver et al. (2011) and Skriver (2012). In this paper, the short revisit satellite SAR data will be used to assess the trade-off between polarimetric SAR data and data as single or dual polarisation SAR data. This is particularly important in relation to the future GMES Sentinel-1 SAR satellites, where two satellites with a relatively wide swath will ensure a short revisit time globally. Questions dealt with are: which accuracy can we expect from a mission like the Sentinel-1, what is the improvement of using polarimetric SAR compared to single or dual polarisation SAR, and what is the optimum number of acquisitions needed. Methodology The data have sufficient number of looks for the Gaussian assumption to be valid for the backscatter coefficients for the individual polarizations. The classification method used for these data is therefore the standard Bayesian classification method for multivariate Gaussian statistics. For the full-polarimetric cases two classification methods have been applied, the standard ML Wishart classifier, and a method based on a reversible transform of the covariance matrix into backscatter intensities. The following pre-processing steps were performed on both data sets: The scattering matrix data in the form of SLC products were coregistered, converted to covariance matrix format and multilooked to a specific equivalent number of looks. Results The multitemporal data improve significantly the classification results, and single acquisition data cannot provide the necessary classification performance. The multitemporal data are especially important for the single and dual polarization data, but less important for the fully polarimetric data. The satellite data set produces realistic classification results based on about 2000 fields. The best classification results for the single-polarized mode provide classification errors in the mid-twenties. Using the dual-polarized mode reduces the classification error with about 5 percentage points, whereas the polarimetric mode reduces it with about 10 percentage points. These results show, that it will be possible to obtain reasonable results with relatively simple systems with short revisit time. This very important result shows that systems like the Sentinel-1 mission will be able to produce fairly good results for global land cover classification. References Skriver, H. et al., 2011, 'Crop Classification using Short-Revisit Multitemporal SAR Data', IEEE J. Sel. Topics in Appl. Earth Obs. Rem. Sens., vol. 4, pp. 423-431. Skriver, H., 2012, 'Crop classification by multitemporal C- and L-band single- and dual-polarization and fully polarimetric SAR', IEEE Trans. Geosc. Rem. Sens., vol. 50, pp. 2138-2149.

A classification of large amplitude oscillations of a spring-pendulum system

NASA Technical Reports Server (NTRS)

Broucke, R.

1977-01-01

We present a detailed classification of large amplitude oscillations of a non-integrable autonomous system with two degrees of freedom: the spring pendulum system. The classification is made with the method of invariant curves. The results show the importance of three types of motion: periodic, quasi-periodic and semi-ergodic. The numerical results are given for nine different values of the energy constant.

Naval Recruit Classification Tests As Predictors of Performance in 87 Class "A" Enlisted Schools (1964-1966). Final Report.

ERIC Educational Resources Information Center

Thomas, Edmund D.

Scores earned on the Navy's enlisted classification tests determine, in large part, the type of job specialty training a recruit will receive. About 50% of recruits qualify for academic training in Basic Class "A" level schools. How well the classification tests predict performance in these schools is important from both a cost and a…

An unbalanced spectra classification method based on entropy

NASA Astrophysics Data System (ADS)

Liu, Zhong-bao; Zhao, Wen-juan

2017-05-01

How to solve the problem of distinguishing the minority spectra from the majority of the spectra is quite important in astronomy. In view of this, an unbalanced spectra classification method based on entropy (USCM) is proposed in this paper to deal with the unbalanced spectra classification problem. USCM greatly improves the performances of the traditional classifiers on distinguishing the minority spectra as it takes the data distribution into consideration in the process of classification. However, its time complexity is exponential with the training size, and therefore, it can only deal with the problem of small- and medium-scale classification. How to solve the large-scale classification problem is quite important to USCM. It can be easily obtained by mathematical computation that the dual form of USCM is equivalent to the minimum enclosing ball (MEB), and core vector machine (CVM) is introduced, USCM based on CVM is proposed to deal with the large-scale classification problem. Several comparative experiments on the 4 subclasses of K-type spectra, 3 subclasses of F-type spectra and 3 subclasses of G-type spectra from Sloan Digital Sky Survey (SDSS) verify USCM and USCM based on CVM perform better than kNN (k nearest neighbor) and SVM (support vector machine) in dealing with the problem of rare spectra mining respectively on the small- and medium-scale datasets and the large-scale datasets.

A comparison of autonomous techniques for multispectral image analysis and classification

NASA Astrophysics Data System (ADS)

Valdiviezo-N., Juan C.; Urcid, Gonzalo; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso

2012-10-01

Multispectral imaging has given place to important applications related to classification and identification of objects from a scene. Because of multispectral instruments can be used to estimate the reflectance of materials in the scene, these techniques constitute fundamental tools for materials analysis and quality control. During the last years, a variety of algorithms has been developed to work with multispectral data, whose main purpose has been to perform the correct classification of the objects in the scene. The present study introduces a brief review of some classical as well as a novel technique that have been used for such purposes. The use of principal component analysis and K-means clustering techniques as important classification algorithms is here discussed. Moreover, a recent method based on the min-W and max-M lattice auto-associative memories, that was proposed for endmember determination in hyperspectral imagery, is introduced as a classification method. Besides a discussion of their mathematical foundation, we emphasize their main characteristics and the results achieved for two exemplar images conformed by objects similar in appearance, but spectrally different. The classification results state that the first components computed from principal component analysis can be used to highlight areas with different spectral characteristics. In addition, the use of lattice auto-associative memories provides good results for materials classification even in the cases where some spectral similarities appears in their spectral responses.

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Snyder v. Phelps: Public Servant or Private Citizen?

DTIC Science & Technology

2011-05-05

important to the military. 15. SUBJECT TERMS First Amendment, Military Funerals, Freedom of Speech 16. SECURITY CLASSIFICATION OF...26 KEY TERMS: First Amendment, Military Funerals, Freedom of Speech CLASSIFICATION: Unclassified In October 2010, the Supreme Court was

[Child abuse: a world problem].

PubMed

Santana-Tavira, R; Sánchez-Ahedo, R; Herrera-Basto, E

1998-01-01

Several problems are encountered in the study of child abuse: ignorance of its real proportions, deep cultural and historical roots, diversity of opinion as to its definition and classification and, finally, very diverse considerations on its repercussions and therapeutic management. The present study approaches child abuse from its historical precedents, its classifications, definitions and epidemiology. In addition, repercussions are reviewed, and treatment alternatives considered which are held as fundamental to confront this alarmingly increasing phenomenon. It is important to unify criteria as to the definition and classification of scientific information surrounding demographic data which, in the end, will situate the problem, the progress related to its causes, diagnosis, preventive measures and treatment. It is extremely important to prevent child abuse by all possible means, since this harm is reflected in the adult life of the child. Various classifications are considered, as well as characteristics of the abuser and of the abused.

In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning.

PubMed

Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito José; Ribeiro, Richardson; Bertotti, Fábio Luiz; Assmann, Tangriani Simioni

2015-11-11

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning

PubMed Central

Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito José; Ribeiro, Richardson; Bertotti, Fábio Luiz; Assmann, Tangriani Simioni

2015-01-01

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%. PMID:26569250

Contributions for classification of platelet rich plasma - proposal of a new classification: MARSPILL.

PubMed

Lana, Jose Fabio Santos Duarte; Purita, Joseph; Paulus, Christian; Huber, Stephany Cares; Rodrigues, Bruno Lima; Rodrigues, Ana Amélia; Santana, Maria Helena; Madureira, João Lopo; Malheiros Luzo, Ângela Cristina; Belangero, William Dias; Annichino-Bizzacchi, Joyce Maria

2017-07-01

Platelet-rich plasma (PRP) has emerged as a significant therapy used in medical conditions with heterogeneous results. There are some important classifications to try to standardize the PRP procedure. The aim of this report is to describe PRP contents studying celular and molecular components, and also propose a new classification for PRP. The main focus is on mononuclear cells, which comprise progenitor cells and monocytes. In addition, there are important variables related to PRP application incorporated in this study, which are the harvest method, activation, red blood cells, number of spins, image guidance, leukocytes number and light activation. The other focus is the discussion about progenitor cells presence on peripherial blood which are interesting due to neovasculogenesis and proliferation. The function of monocytes (in tissue-macrophages) are discussed here and also its plasticity, a potential property for regenerative medicine treatments.

Classification of air quality using fuzzy synthetic multiplication.

PubMed

Abdullah, Lazim; Khalid, Noor Dalina

2012-11-01

Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.

47 CFR 80.1133 - Transmission of safety communications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... SERVICES STATIONS IN THE MARITIME SERVICES Global Maritime Distress and Safety System (GMDSS) Operating... calling station has an important navigational or meteorological warning to transmit. (e) In radiotelephony...

47 CFR 80.1133 - Transmission of safety communications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES STATIONS IN THE MARITIME SERVICES Global Maritime Distress and Safety System (GMDSS) Operating... calling station has an important navigational or meteorological warning to transmit. (e) In radiotelephony...

47 CFR 80.1133 - Transmission of safety communications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... SERVICES STATIONS IN THE MARITIME SERVICES Global Maritime Distress and Safety System (GMDSS) Operating... calling station has an important navigational or meteorological warning to transmit. (e) In radiotelephony...

47 CFR 80.1133 - Transmission of safety communications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... SERVICES STATIONS IN THE MARITIME SERVICES Global Maritime Distress and Safety System (GMDSS) Operating... calling station has an important navigational or meteorological warning to transmit. (e) In radiotelephony...

[From new genetic and histological classifications to direct treatment].

PubMed

Compérat, Eva; Furudoï, Adeline; Varinot, Justine; Rioux-Leclerq, Nathalie

2016-08-01

The most important criterion for optimal cancer treatment is a correct classification of the tumour. During the last three years, several very important progresses have been made with a better definition of urothelial carcinoma (UC), especially from a molecular point of view. We start having a global understanding of UC, although many details are still not completely understood. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Unsupervised Wishart Classfication of Wetlands in Newfoundland, Canada Using Polsar Data Based on Fisher Linear Discriminant Analysis

NASA Astrophysics Data System (ADS)

Mohammadimanesh, F.; Salehi, B.; Mahdianpari, M.; Homayouni, S.

2016-06-01

Polarimetric Synthetic Aperture Radar (PolSAR) imagery is a complex multi-dimensional dataset, which is an important source of information for various natural resources and environmental classification and monitoring applications. PolSAR imagery produces valuable information by observing scattering mechanisms from different natural and man-made objects. Land cover mapping using PolSAR data classification is one of the most important applications of SAR remote sensing earth observations, which have gained increasing attention in the recent years. However, one of the most challenging aspects of classification is selecting features with maximum discrimination capability. To address this challenge, a statistical approach based on the Fisher Linear Discriminant Analysis (FLDA) and the incorporation of physical interpretation of PolSAR data into classification is proposed in this paper. After pre-processing of PolSAR data, including the speckle reduction, the H/α classification is used in order to classify the basic scattering mechanisms. Then, a new method for feature weighting, based on the fusion of FLDA and physical interpretation, is implemented. This method proves to increase the classification accuracy as well as increasing between-class discrimination in the final Wishart classification. The proposed method was applied to a full polarimetric C-band RADARSAT-2 data set from Avalon area, Newfoundland and Labrador, Canada. This imagery has been acquired in June 2015, and covers various types of wetlands including bogs, fens, marshes and shallow water. The results were compared with the standard Wishart classification, and an improvement of about 20% was achieved in the overall accuracy. This method provides an opportunity for operational wetland classification in northern latitude with high accuracy using only SAR polarimetric data.

Determination of quality television programmes based on sentiment analysis on Twitter

NASA Astrophysics Data System (ADS)

Amalia, A.; Oktinas, W.; Aulia, I.; Rahmat, R. F.

2018-03-01

Public sentiment from social media like Twitter can be used as one of the indicators to determine the quality of TV Programmes. In this study, we implemented information extraction on Twitter by using sentiment analysis method to assess the quality of TV Programmes. The first stage of this study is pre-processing which consists of cleansing, case folding, tokenizing, stop-word removal, stemming, and redundancy filtering. The next stage is weighting process for every single word by using TF-IDF method. The last step of this study is the sentiment classification process which is divided into three sentiment category which is positive, negative and neutral. We classify the TV programmes into several categories such as news, children, or films/soap operas. We implemented an improved k-nearest neighbor method in classification 4000 twitter status, for four biggest TV stations in Indonesia, with ratio 70% data for training and 30% of data for the testing process. The result obtained from this research generated the highest accuracy with k=10 as big as 90%.

Combining biological and geomorphological data to introduce biotopes of Bushehr Province, the Persian Gulf.

PubMed

Aghajanpour, Fatemeh; Savari, Ahmad; Danehkar, Afshin; Chegini, Vahid

2015-12-01

Identification and classification of intertidal areas provides the basic knowledge needed for studies of biogeography, macro-ecology, and faunal populations, as well as for conservation planning and managing human activities in coastal areas. In this research, the eastern coast of Bushehr Province was classified using the Coastal and Marine Ecological Classification Standard (CMECS). Seven substrate subgroups, five geoform types in unconsolidated mineral substrate, five micro-habitats in rock substrate, and nine biotic groups were identified in study stations. The non-metric multidimensional scaling (nMDS) ordinations and one-way analysis of similarity (ANOSIM) showed that macroinvertebrate species composition differed significantly among different geoform types (habitat types). Eight biotopes are introduced for the eastern coast of Bushehr Province based on observational and statistical methods. The results presented here show that identifying intertidal biotopes using CMECS is an appropriate method both for classifying the southern coastal areas of Iran and for integrating biotic and abiotic components.

Infrared monitoring of the Space Station environment

NASA Technical Reports Server (NTRS)

Kostiuk, Theodor; Jennings, Donald E.; Mumma, Michael J.

1988-01-01

The measurement and monitoring of infrared emission in the environment of the Space Station has a twofold importance - for the study of the phenomena itself and as an aid in planning and interpreting Station based infrared experiments. Spectral measurements of the infrared component of the spacecraft glow will, along with measurements in other spectral regions, provide data necessary to fully understand and model the physical and chemical processes producing these emissions. The monitoring of the intensity of these emissions will provide background limits for Space Station based infrared experiments and permit the determination of optimum instrument placement and pointing direction. Continuous monitoring of temporal changes in the background radiation (glow) will also permit better interpretation of Station-based infrared earth sensing and astronomical observations. The primary processes producing infrared emissions in the Space Station environment are: (1) Gas phase excitations of Station generated molecules ( e.g., CO2, H2O, organics...) by collisions with the ambient flux of mainly O and N2. Molecular excitations and generation of new species by collisions of ambient molecules with Station surfaces. They provide a list of resulting species, transition energies, excitation cross sections and relevant time constants. The modeled spectrum of the excited species occurs primarily at wavelengths shorter than 8 micrometer. Emissions at longer wavelengths may become important during rocket firing or in the presence of dust.

Retrospective analysis of the Draize test for serious eye damage/eye irritation: importance of understanding the in vivo endpoints under UN GHS/EU CLP for the development and evaluation of in vitro test methods.

PubMed

Adriaens, Els; Barroso, João; Eskes, Chantra; Hoffmann, Sebastian; McNamee, Pauline; Alépée, Nathalie; Bessou-Touya, Sandrine; De Smedt, Ann; De Wever, Bart; Pfannenbecker, Uwe; Tailhardat, Magalie; Zuang, Valérie

2014-03-01

For more than two decades, scientists have been trying to replace the regulatory in vivo Draize eye test by in vitro methods, but so far only partial replacement has been achieved. In order to better understand the reasons for this, historical in vivo rabbit data were analysed in detail and resampled with the purpose of (1) revealing which of the in vivo endpoints are most important in driving United Nations Globally Harmonized System/European Union Regulation on Classification, Labelling and Packaging (UN GHS/EU CLP) classification for serious eye damage/eye irritation and (2) evaluating the method's within-test variability for proposing acceptable and justifiable target values of sensitivity and specificity for alternative methods and their combinations in testing strategies. Among the Cat 1 chemicals evaluated, 36-65 % (depending on the database) were classified based only on persistence of effects, with the remaining being classified mostly based on severe corneal effects. Iritis was found to rarely drive the classification (<4 % of both Cat 1 and Cat 2 chemicals). The two most important endpoints driving Cat 2 classification are conjunctiva redness (75-81 %) and corneal opacity (54-75 %). The resampling analyses demonstrated an overall probability of at least 11 % that chemicals classified as Cat 1 by the Draize eye test could be equally identified as Cat 2 and of about 12 % for Cat 2 chemicals to be equally identified as No Cat. On the other hand, the over-classification error for No Cat and Cat 2 was negligible (<1 %), which strongly suggests a high over-predictive power of the Draize eye test. Moreover, our analyses of the classification drivers suggest a critical revision of the UN GHS/EU CLP decision criteria for the classification of chemicals based on Draize eye test data, in particular Cat 1 based only on persistence of conjunctiva effects or corneal opacity scores of 4. In order to successfully replace the regulatory in vivo Draize eye test, it will be important to recognise these uncertainties and to have in vitro tools to address the most important in vivo endpoints identified in this paper.

Effects of granularity on the natural classification of loose cover layer rock

NASA Astrophysics Data System (ADS)

Zhang, Shuhui; Wang, Peng; Zhang, Zhiqiang

2018-03-01

In the sublevel caving method, with developing depth of underground mines increasing, the ore loss and dilution is become more and more remarkable that is due to the natural classification of loose cover layer rock. Therefore, this paper researches that granularity are one of the main factors affecting the natural classification, and carries out a physical simulation experiment of loose cover layer rock granularity effects of natural classification. Through the experiment we found that granularity has important effect on natural classification. Under the condition of the same weight, we found the closer of granularities that consist of cover layer rock, the less prone to natural classification. Otherwise, it will be prone to natural classification. This study has a guiding significance for a mine, forming a scientific and reasonable cover layer rock, and reducing the ore loss and dilution in the mining process.

Intelligent man/machine interfaces on the space station

NASA Technical Reports Server (NTRS)

Daughtrey, Rodney S.

1987-01-01

Some important topics in the development of good, intelligent, usable man/machine interfaces for the Space Station are discussed. These computer interfaces should adhere strictly to three concepts or doctrines: generality, simplicity, and elegance. The motivation for natural language interfaces and their use and value on the Space Station, both now and in the future, are discussed.

Classification with spatio-temporal interpixel class dependency contexts

NASA Technical Reports Server (NTRS)

Jeon, Byeungwoo; Landgrebe, David A.

1992-01-01

A contextual classifier which can utilize both spatial and temporal interpixel dependency contexts is investigated. After spatial and temporal neighbors are defined, a general form of maximum a posterior spatiotemporal contextual classifier is derived. This contextual classifier is simplified under several assumptions. Joint prior probabilities of the classes of each pixel and its spatial neighbors are modeled by the Gibbs random field. The classification is performed in a recursive manner to allow a computationally efficient contextual classification. Experimental results with bitemporal TM data show significant improvement of classification accuracy over noncontextual pixelwise classifiers. This spatiotemporal contextual classifier should find use in many applications of remote sensing, especially when the classification accuracy is important.

Use of machine learning methods to classify Universities based on the income structure

NASA Astrophysics Data System (ADS)

Terlyga, Alexandra; Balk, Igor

2017-10-01

In this paper we discuss use of machine learning methods such as self organizing maps, k-means and Ward’s clustering to perform classification of universities based on their income. This classification will allow us to quantitate classification of universities as teaching, research, entrepreneur, etc. which is important tool for government, corporations and general public alike in setting expectation and selecting universities to achieve different goals.

Refining the classification of left ventricular hypertrophy to provide new insights into the progression from hypertension to heart failure.

PubMed

Garg, Sonia; Drazner, Mark H

2016-07-01

Left ventricular hypertrophy (LVH), an important consequence of hypertension, is traditionally classified as either concentric or eccentric based on the presence or absence of increased relative wall thickness. In 2010, we proposed a novel four-tiered classification that accounted for LV dilatation in addition to LV wall thickness. The purpose of this review is to discuss the rationale for this revised classification and highlight subsequent studies that have assessed its utility. A series of recent observational studies have tested whether the four-tiered classification identifies subphenotypes of LVH with differential risk of adverse outcomes, including incident heart failure. The majority have confirmed that eccentric hypertrophy can be subdivided into a high-risk and a low-risk group based on whether LV dilatation is present. Additional studies have shown that LV dilatation is an independent risk factor for the development of heart failure. Incorporation of LV dilatation into the assessment of LVH identifies important subphenotypes within the standard two-tiered classification that have differential risk. Such refinements in the classification of LVH may yield new insights into how LVH progresses to heart failure, help identify risk factors for this transition, and improve therapeutic efforts to prevent its occurrence.

SOARCA Peach Bottom Atomic Power Station Long-Term Station Blackout Uncertainty Analysis: Knowledge Advancement.

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

Gauntt, Randall O.; Mattie, Patrick D.; Bixler, Nathan E.

2014-02-01

This paper describes the knowledge advancements from the uncertainty analysis for the State-of- the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout accident scenario at the Peach Bottom Atomic Power Station. This work assessed key MELCOR and MELCOR Accident Consequence Code System, Version 2 (MACCS2) modeling uncertainties in an integrated fashion to quantify the relative importance of each uncertain input on potential accident progression, radiological releases, and off-site consequences. This quantitative uncertainty analysis provides measures of the effects on consequences, of each of the selected uncertain parameters both individually and in interaction with other parameters. The results measure the modelmore » response (e.g., variance in the output) to uncertainty in the selected input. Investigation into the important uncertain parameters in turn yields insights into important phenomena for accident progression and off-site consequences. This uncertainty analysis confirmed the known importance of some parameters, such as failure rate of the Safety Relief Valve in accident progression modeling and the dry deposition velocity in off-site consequence modeling. The analysis also revealed some new insights, such as dependent effect of cesium chemical form for different accident progressions. (auth)« less

Nursing Classification Systems

PubMed Central

Henry, Suzanne Bakken; Mead, Charles N.

1997-01-01

Abstract Our premise is that from the perspective of maximum flexibility of data usage by computer-based record (CPR) systems, existing nursing classification systems are necessary, but not sufficient, for representing important aspects of “what nurses do.” In particular, we have focused our attention on those classification systems that represent nurses' clinical activities through the abstraction of activities into categories of nursing interventions. In this theoretical paper, we argue that taxonomic, combinatorial vocabularies capable of coding atomic-level nursing activities are required to effectively capture in a reproducible and reversible manner the clinical decisions and actions of nurses, and that, without such vocabularies and associated grammars, potentially important clinical process data is lost during the encoding process. Existing nursing intervention classification systems do not fulfill these criteria. As background to our argument, we first present an overview of the content, methods, and evaluation criteria used in previous studies whose focus has been to evaluate the effectiveness of existing coding and classification systems. Next, using the Ingenerf typology of taxonomic vocabularies, we categorize the formal type and structure of three existing nursing intervention classification systems—Nursing Interventions Classification, Omaha System, and Home Health Care Classification. Third, we use records from home care patients to show examples of lossy data transformation, the loss of potentially significant atomic data, resulting from encoding using each of the three systems. Last, we provide an example of the application of a formal representation methodology (conceptual graphs) which we believe could be used as a model to build the required combinatorial, taxonomic vocabulary for representing nursing interventions. PMID:9147341

Evaluation of local site effect in the western side of the Suez Canal area by applying H/V and MASW techniques

NASA Astrophysics Data System (ADS)

Mohamed, Emad K.; Shokry, M. M. F.; Hassoup, Awad; Helal, A. M. A.

2016-11-01

The soft sediments are one of the most important factors responsible for the amplification of the seismic ground motion in an area of study. Three components, single-station microtremor measurements were performed at 61 sites along the Suez Canal to estimate the fundamental frequencies of the soil and corresponding H/V amplitude ratios by using the horizontal-to-vertical spectral ratio (HVSR) method. We have applied the investigations of the shear wave velocity for supplementing the existing seismic microzonation of the Suez Canal. The multichannel analysis of surface wave (MASW) tests were done along the Suez Canal in the three cities, Suez, Ismailia, and Port Said using 24 channels digital engineering seismograph with 4.5 Hz geophones from September 2014 to January 2015 to get the shear wave velocity VS30. The SeisImager/SW software was used for analyzing the data, and 1D-shear wave velocity model have achieved for each site. The HVSR curves show that the fundamental frequency values are ranging from 0.57 to 1.08 Hz, and H/V amplitude ratios are ranging from 4.05 to 6.46. The average values of VS30 are (548, 301), (241, 319), (194, 110, 238) for Suez, Ismailia, and Port Said respectively. The average of shear wave velocity up to 30 m depth is estimated and used for site classification based on the National Earthquake Hazard Reduction Program (NEHRP) classification. The majority of the sites was classified as Class D (stiff soil) except one site at Port Said city is classified as Class E (soft soils), and another site in the Suez city is classified as Class C (hard rock).

Evaluation for the ecological quality status of coastal waters in East China Sea using fuzzy integrated assessment method.

PubMed

Wu, H Y; Chen, K L; Chen, Z H; Chen, Q H; Qiu, Y P; Wu, J C; Zhang, J F

2012-03-01

This research presented an evaluation for the ecological quality status (EcoQS) of three semi-enclosed coastal areas using fuzzy integrated assessment method (FIAM). With this method, the hierarchy structure was clarified by an index system of 11 indicators selected from biotic elements and physicochemical elements, and the weight vector of index system was calculated with Delphi-Analytic Hierarchy Process (AHP) procedure. Then, the FIAM was used to achieve an EcoQS assessment. As a result of assessment, most of the sampling stations demonstrated a clear gradient in EcoQS, ranging from high to poor status. Among the four statuses, high and good, owning a ratio of 55.9% and 26.5%, respectively, were two dominant statuses for three bays, especially for Sansha Bay and Luoyuan Bay. The assessment results were found consistent with the pressure information and parameters obtained at most stations. In addition, the sources of uncertainty in classification of EcoQS were also discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Foehn at the lowest place on earth

NASA Astrophysics Data System (ADS)

Mayr, Georg; Metzger, Jutta; Mayr, Raphael

2017-04-01

Foehn occurs at the Dead Sea. Measurements from weather stations at the valley floor and on the slope show that the prime season for foehn is summer and the prime time late afternoon and evening (using the objective classification algorithm of Plavcan et al (2014)[1]). During summer synoptic scale forcing with cross-barrier winds is rare and thus the gravity-wave-driven concept cannot be used to explain the occurrence of foehn. The density-driven foehn concept [2], on the other hand, with denser air at crest level upstream than in the valley can explain the occurrence of foehn. It also explains the differences in foehn frequency between the slope and valley bottom station. References: [1] Plavcan, D., Mayr, G. J., & Zeileis, A. (2014). Automatic and probabilistic foehn diagnosis with a statistical mixture model. Journal of Applied Meteorology and Climatology, 53(3), 652-659. [2] Mayr, G. J., & Armi, L. (2010). The influence of downstream diurnal heating on the descent of flow across the Sierras. Journal of Applied Meteorology and Climatology, 49(9), 1906-1912.

Heavy metal pollution monitoring with foraminifera in the estuaries of Nellore coast, East coast of India.

PubMed

Sundara Raja Reddy, B C; Jayaraju, N; Sreenivasulu, G; Suresh, U; Reddy, A N

2016-12-15

A total of 112 bottom water and sediment samples collected at fixed stations in pre-monsoon and post-monsoon from four estuaries (Pennar, Uppateru, Swarnamukhi, and Kalangi) showed foraminiferal test abnormalities in heavy metal concentrations (Co, Cr, Cu, Fe, Mn, Ni, and Pb). Low diversity of fauna was due to the predominance of a limited number of opportunistic species capable of achieving high densities in adverse environmental conditions and the reduction in the number of species intolerant of such conditions. In this study, classification of 54 common species according to their distribution is presented. Approximately 15 species showed quite low diversities at stations 23-27 and 44-51. Because of the effect of heavy metal pollution in these estuaries, drastic changes in the number of species and diversity of foraminifera were observed. These changes in foraminiferal species and the increase in test abnormalities are proxies of environmental stress on the estuarine ecosystem. Copyright © 2016 Elsevier Ltd. All rights reserved.

Characterization of spatial and temporal variability in hydrochemistry of Johor Straits, Malaysia.

PubMed

Abdullah, Pauzi; Abdullah, Sharifah Mastura Syed; Jaafar, Othman; Mahmud, Mastura; Khalik, Wan Mohd Afiq Wan Mohd

2015-12-15

Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Investigation of environmental indices from the Earth Resources Technology Satellite

NASA Technical Reports Server (NTRS)

Greeley, R. S. (Principal Investigator); Riley, E. L.; Stryker, S.; Ward, E. A.

1973-01-01

The author has identified the following significant results. Land use, quality, and air quality trends are being deduced from both ERTS-1 MSS and computer compatible tapes. The data analysis plan and the preliminary data analysis phase were conducted in January 1973. Results from these two phases are: (1) Method of analysis has been selected and checked out. (2) Land use for two dates have been generated for one test site. (3) Water quality for one date has been produced partially. (4) Air quality for three has been produced and compared with ground truth. (5) One of the two DCP stations is in operation; the second station will be installed in March 1973. Land use classification exceeds pre-launch expectations. Water quality (turbidity) is not progressing as expected. Finally, mesoscale air quality results have shown correlation with NOAA/EPA turbidity network. If air quality correlations continue to show favorable results, a rapid means of global turbidity may be available from ERTS-1 MSS observations.

The Future of New Discoveries on the International Space Station

NASA Technical Reports Server (NTRS)

Schlagheck, Ronald; Trach, Brian

2000-01-01

The Materials Science program is one of the five Microgravity research disciplines in NASA's Human Exploration and Development of Space (HEDS). This research uses the low gravity environment to obtain the fundamental understanding of various phenomena effects and it's relationship to structure, processing, and properties of materials. The International Space Station (ISS) will complete the first major assembly phase within the next year thus providing the opportunity for on-orbit research and scientific utilization in early 2001. Research will become routine as the final Space Station configuration is completed. Accommodations will support a variety of Materials Science payload hardware both in the US and international partner modules. This paper addresses the current scope of the flight investigator program that will utilize the various capabilities on ISS. The type of research and classification of materials that are addressed using multiple types of flight apparatus will be explained. The various flight and ground facilities that are used to support the NASA program are described. The early utilization schedule for the materials science payloads with associated hardware will be covered. The Materials Science Research Facility and related international experiment modules serves as the foundation for this capability. The potential applications and technologies obtained from the Materials Science program are described.

Digital watermarking for secure and adaptive teleconferencing

NASA Astrophysics Data System (ADS)

Vorbrueggen, Jan C.; Thorwirth, Niels

2002-04-01

The EC-sponsored project ANDROID aims to develop a management system for secure active networks. Active network means allowing the network's customers to execute code (Java-based so-called proxylets) on parts of the network infrastructure. Secure means that the network operator nonetheless retains full control over the network and its resources, and that proxylets use ANDROID-developed facilities to provide secure applications. Management is based on policies and allows autonomous, distributed decisions and actions to be taken. Proxylets interface with the system via policies; among actions they can take is controlling execution of other proxylets or redirection of network traffic. Secure teleconferencing is used as the application to demonstrate the approach's advantages. A way to control a teleconference's data streams is to use digital watermarking of the video, audio and/or shared-whiteboard streams, providing an imperceptible and inseparable side channel that delivers information from originating or intermediate stations to downstream stations. Depending on the information carried by the watermark, these stations can take many different actions. Examples are forwarding decisions based on security classifications (possibly time-varying) at security boundaries, set-up and tear-down of virtual private networks, intelligent and adaptive transcoding, recorder or playback control (e.g., speaking off the record), copyright protection, and sender authentication.

Water quality of the Lexington Reservoir, Santa Clara County, California, 1978-80

USGS Publications Warehouse

Iwatsubo, R.T.; Sylvester, M.A.; Gloege, I.S.

1988-01-01

Analysis of water samples from Lexington Reservoir and Los Gatos Creek upstream from the reservoir from June 1978 through September 1980 showed that water generally met water-quality objectives identified by California Regional Water Quality Control Board, San Francisco Bay Region. Water-temperature profiles show that Lexington Reservoir is a warm monomictic lake. During summer, dissolved-oxygen concentrations generally were not reduced below 5.0 mg/L in the hyplimnion; only once during the study did bottom waters become anoxic. Water transparency decreased with depth. The euphotic zone ranged from 1.0 to 5.4 m, depending on suspended solids and algae, and was greater in summer than in spring. Calcium and bicarbonate were dominant ions at all stations except during spring, following the rainy season, when waters were a mixed cation bicarbonate type. Nitrogen concentrations were greater in samples from reservoir stations than in those from Los Gatos Creek, with most of the nitrogen in ammonia and organic forms. The amount of dissolved nitrate appeared to be related to phytoplankton abundance. Phosphorus and trace-element concentrations were low at all stations. Estimates of net primary productivity and Carlson 's trophic-state index, based on chlorophyll-a concentrations, indicated that reservoir classification ranges from oligotrophic to mesotrophic. Blue-green algae generally were predominant in reservoir samples. (USGS)

Improving highway advisory radio predictability and performance

DOT National Transportation Integrated Search

2011-01-01

Highway Advisory Radio (HAR) stations, sometimes referred to as Travelers Information Stations (TIS), : allow highway agencies to broadcast important messages about traffic, weather and roadway conditions to : motorists. Caltrans has deployed HAR ...

Aerobrake assembly with minimum Space Station accommodation

NASA Technical Reports Server (NTRS)

Katzberg, Steven J.; Butler, David H.; Doggett, William R.; Russell, James W.; Hurban, Theresa

1991-01-01

The minimum Space Station Freedom accommodations required for initial assembly, repair, and refurbishment of the Lunar aerobrake were investigated. Baseline Space Station Freedom support services were assumed, as well as reasonable earth-to-orbit possibilities. A set of three aerobrake configurations representative of the major themes in aerobraking were developed. Structural assembly concepts, along with on-orbit assembly and refurbishment scenarios were created. The scenarios were exercised to identify required Space Station Freedom accommodations. Finally, important areas for follow-on study were also identified.

Advanced fire observation by the Intelligent Infrared Sensor prototype FOCUS on the International Space Station

NASA Astrophysics Data System (ADS)

Oertel, D.; Haschberger, P.; Tank, V.; Lanzl, F.; Zhukov, B.; Jahn, H.; Briess, K.; Lorenz, E.; Roeser, H.-P.; Ginati, A.; Tobehn, C.; Schulte in den Bäumen, J.; Christmann, U.

1999-01-01

Current and planned operational space-borne Earth observation systems provide spatially, radiometrically or temporally crude data for the detection and monitoring of high temperature phenomena on the surface of our planet. High Temperature Events (HTE) very often cause environmental disasters. Such HTE are forest and savannah fires, fires of open coal mines, volcanic activities and others (e.g. fires of oil wells, pipelines etc.). A simultaneous co-registration of a combination of infrared (IR) and visible (VIS) channels is the key for a reliable autonomous on-board detection of High Temperature Events (HTE) on Earth surface, such as vegetation fires and volcano eruptions. This is the main feature of the FOCUS experiment. Furthermore there are ecology-oriented objectives of the FOCUS experiment mainly related to spectrometric/imaging remote inspection and parameter extraction of selected HTEs, and to the assessment of some ecological consequences of HTEs, such as aerosol and gas emission. Based on own experimental work and supported by Co-Investigators from Italy, Greece, France, Spain, Russia and Germany, DLR proposed in 1997 to use the International Space Station (ISS) in its early utilization phase as a platform and test-bed for an Intelligent Infrared Sensor prototype FOCUS of a future Environmental Disaster Recognition Satellite System. FOCUS is considered by ESA as an important mission combining a number of proven technologies and observation techniques to provide the scientific and operational user community with key data for the classification and monitoring of forest fires. FOCUS was selected as one of five European ``Groupings'' to be flown as an externally mounted payload during the early utilisation phase of the ISS. The FOCUS Phase A Study will be performed by OHB-System, DLR and Zeiss from September 1998 until May 1999.

Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?

NASA Astrophysics Data System (ADS)

Švab Lenarčič, Andreja; Đurić, Nataša; Čotar, Klemen; Ritlop, Klemen; Oštir, Krištof

2016-10-01

It is a broadly established belief that the segmentation result significantly affects subsequent image classification accuracy. However, the actual correlation between the two has never been evaluated. Such an evaluation would be of considerable importance for any attempts to automate the object-based classification process, as it would reduce the amount of user intervention required to fine-tune the segmentation parameters. We conducted an assessment of segmentation and classification by analyzing 100 different segmentation parameter combinations, 3 classifiers, 5 land cover classes, 20 segmentation evaluation metrics, and 7 classification accuracy measures. The reliability definition of segmentation evaluation metrics as indicators of land cover classification accuracy was based on the linear correlation between the two. All unsupervised metrics that are not based on number of segments have a very strong correlation with all classification measures and are therefore reliable as indicators of land cover classification accuracy. On the other hand, correlation at supervised metrics is dependent on so many factors that it cannot be trusted as a reliable classification quality indicator. Algorithms for land cover classification studied in this paper are widely used; therefore, presented results are applicable to a wider area.

The process and utility of classification and regression tree methodology in nursing research

PubMed Central

Kuhn, Lisa; Page, Karen; Ward, John; Worrall-Carter, Linda

2014-01-01

Aim This paper presents a discussion of classification and regression tree analysis and its utility in nursing research. Background Classification and regression tree analysis is an exploratory research method used to illustrate associations between variables not suited to traditional regression analysis. Complex interactions are demonstrated between covariates and variables of interest in inverted tree diagrams. Design Discussion paper. Data sources English language literature was sourced from eBooks, Medline Complete and CINAHL Plus databases, Google and Google Scholar, hard copy research texts and retrieved reference lists for terms including classification and regression tree* and derivatives and recursive partitioning from 1984–2013. Discussion Classification and regression tree analysis is an important method used to identify previously unknown patterns amongst data. Whilst there are several reasons to embrace this method as a means of exploratory quantitative research, issues regarding quality of data as well as the usefulness and validity of the findings should be considered. Implications for Nursing Research Classification and regression tree analysis is a valuable tool to guide nurses to reduce gaps in the application of evidence to practice. With the ever-expanding availability of data, it is important that nurses understand the utility and limitations of the research method. Conclusion Classification and regression tree analysis is an easily interpreted method for modelling interactions between health-related variables that would otherwise remain obscured. Knowledge is presented graphically, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. PMID:24237048

The process and utility of classification and regression tree methodology in nursing research.

PubMed

Kuhn, Lisa; Page, Karen; Ward, John; Worrall-Carter, Linda

2014-06-01

This paper presents a discussion of classification and regression tree analysis and its utility in nursing research. Classification and regression tree analysis is an exploratory research method used to illustrate associations between variables not suited to traditional regression analysis. Complex interactions are demonstrated between covariates and variables of interest in inverted tree diagrams. Discussion paper. English language literature was sourced from eBooks, Medline Complete and CINAHL Plus databases, Google and Google Scholar, hard copy research texts and retrieved reference lists for terms including classification and regression tree* and derivatives and recursive partitioning from 1984-2013. Classification and regression tree analysis is an important method used to identify previously unknown patterns amongst data. Whilst there are several reasons to embrace this method as a means of exploratory quantitative research, issues regarding quality of data as well as the usefulness and validity of the findings should be considered. Classification and regression tree analysis is a valuable tool to guide nurses to reduce gaps in the application of evidence to practice. With the ever-expanding availability of data, it is important that nurses understand the utility and limitations of the research method. Classification and regression tree analysis is an easily interpreted method for modelling interactions between health-related variables that would otherwise remain obscured. Knowledge is presented graphically, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. © 2013 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

Groundwater dynamics converted to a groundwater classification as a tool for nature development programs in the dunes

NASA Astrophysics Data System (ADS)

Martens, Kristine; Van Camp, Marc; Van Damme, Dirk; Walraevens, Kristine

2013-08-01

Within the European Union, Habitat Directives are developed with the aim of restoration and preservation of endangered species. The level of biodiversity in coastal dune systems is generally very high compared to other natural ecosystems, but suffers from deterioration. Groundwater extraction and urbanisation are the main reasons for the decrease in biodiversity. Many restoration actions are being carried out and are focusing on the restoration of groundwater level with the aim of re-establishing rare species. These actions have different degrees of success. The evaluation of the actions is mainly based on the appearance of red list species. The groundwater classes, developed in the Netherlands, are used for the evaluation of opportunities for vegetation, while the natural variability of the groundwater level and quality are under-estimated. Vegetation is used as a seepage indicator. The existing classification is not valid in the Belgian dunes, as the vegetation observed in the study area is not in correspondence with this classification. Therefore, a new classification is needed. The new classification is based on the variability of the groundwater level on a long term with integration of ecological factors. Based on the new classification, the importance of seasonal and inter-yearly fluctuations of the water table can be deduced. Inter-yearly fluctuations are more important in recharge areas while seasonal fluctuations are dominant in discharge areas. The new classification opens opportunities for relating vegetation and groundwater dynamics.

The plankton food web of the Bizerte Lagoon (South-western Mediterranean): II. Carbon steady-state modelling using inverse analysis

NASA Astrophysics Data System (ADS)

Grami, Boutheïna; Niquil, Nathalie; Sakka Hlaili, Asma; Gosselin, Michel; Hamel, Dominique; Hadj Mabrouk, Hassine

2008-08-01

A steady-state model of the planktonic food web of the Bizerte Lagoon (Tunisia, South-western Mediterranean) was developed to characterize its structure and functioning through four stations: MA under urban discharge, MB impacted by industrial input, MJ located at proximity of shellfish farming and R in the central area of the lagoon. Carbon stocks of eight chosen compartments were determined and flows were assigned for each one from field data. Missing flow values were calculated by inverse analysis for each station. Network analysis was applied to the resulting food web models to characterize their properties. These analyses mainly showed similarity among stations concerning (1) a high primary production of phytoplankton which was dominated by >10 μm cells (i.e. diatoms); (2) important herbivory against detritivory in stations MA and MJ; (3) major role of detritivory in stations MB and R; (4) efficiency of microbial link in transferring carbon for higher trophic level; (5) efficiency of microzooplankton as a trophic link between detritus, dissolved organic carbon, autotrophs and mesozooplankton; (6) important recycling of carbon leading to conclude about an immature state of the ecosystem. Differences between the functioning of microbial food webs in the lagoon are mainly due to the location of stations. The proximity of station MB to inland and industrial discharges affected its productivity and made it the least productive station. Water circulation into the lagoon made pollutant concentrate into the south and the western sections which seemed to affect the planktonic food web, since the values of productivity reported for stations MB and R were lower than those calculated for the others stations.

A novel approach to malignant-benign classification of pulmonary nodules by using ensemble learning classifiers.

PubMed

Tartar, A; Akan, A; Kilic, N

2014-01-01

Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this paper, a novel Computer-Aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. The proposed CAD system using ensemble learning classifiers, provides an important support to radiologists at the diagnosis process of the disease, achieves high classification performance. The proposed approach with bagging classifier results in 94.7 %, 90.0 % and 77.8 % classification sensitivities for benign, malignant and undetermined classes (89.5 % accuracy), respectively.

Design of neural networks for classification of remotely sensed imagery

NASA Technical Reports Server (NTRS)

Chettri, Samir R.; Cromp, Robert F.; Birmingham, Mark

1992-01-01

Classification accuracies of a backpropagation neural network are discussed and compared with a maximum likelihood classifier (MLC) with multivariate normal class models. We have found that, because of its nonparametric nature, the neural network outperforms the MLC in this area. In addition, we discuss techniques for constructing optimal neural nets on parallel hardware like the MasPar MP-1 currently at GSFC. Other important discussions are centered around training and classification times of the two methods, and sensitivity to the training data. Finally, we discuss future work in the area of classification and neural nets.

The Molecular Pathology of Myelodysplastic Syndrome.

PubMed

Haferlach, Torsten

2018-05-23

The diagnosis and classification of myelodysplastic syndromes (MDS) are based on cytomorphology and cytogenetics (WHO classification). Prognosis is best defined by the Revised International Prognostic Scoring System (IPSS-R). In recent years, an increasing number of molecular aberrations have been discovered. They are already included in the classification (e.g., SF3B1) and, more importantly, have emerged as valuable markers for better classification, particularly for defining risk groups. Mutations in genes such as SF3B1 and IDH1/2 have already had an impact on targeted treatment approaches in MDS. © 2018 S. Karger AG, Basel.

Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture

NASA Technical Reports Server (NTRS)

Hilland, Jeffrey E.; Bicknell, Thomas; Miller, Carol L.

1991-01-01

The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Assessment of the Activation State of RAS and Map Kinase in Human Breast Cancer Specimens (96Breast)

DTIC Science & Technology

1999-09-01

Cancer 16. PRICE CODE 17. SECURITY CLASSIFICATION 18 . SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF...THIS PAGE OF ABSTRACT Unclassified Unclassified Unclassified Unlimited NSN 7640-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39- 18 ...transformation and regulate cell morphology, adhesion and motility through cytoskeletal dynamics and play an important role in carcinogenesis ( 18 ). Rho

Functional Interactions Between c-Src and HER1 Potentiate Neoplastic Transformation: Implications for the Etiology of Human Breast Cancer

DTIC Science & Technology

2000-07-01

receptor 120 16. PRICE CODE 17. SECURITY CLASSIFICATION 18 . SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF...THIS PAGE OF ABSTRACT Unclassified Unclassified Unclassified Unlimited NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39- 18 ... 18 -26 Appended Manuscripts 3 INTRODUCTION Recent work in our laboratory has established the importance of a

Regression-Based Approach For Feature Selection In Classification Issues. Application To Breast Cancer Detection And Recurrence

NASA Astrophysics Data System (ADS)

Belciug, Smaranda; Serbanescu, Mircea-Sebastian

2015-09-01

Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.

Data Rescue for precipitation station network in Slovak Republic

NASA Astrophysics Data System (ADS)

Fasko, Pavel; Bochníček, Oliver; Švec, Marek; Paľušová, Zuzana; Markovič, Ladislav

2016-04-01

Transparency of archive catalogues presents very important task for the data saving. It helps to the further activities e.g. digitalization and homogenization. For the time being visualization of time series continuation in precipitation stations (approximately 1250 stations) is under way in Slovak Republic since the beginning of observation (meteorological stations gradually began to operate during the second half of the 19th century in Slovakia). Visualization is joined with the activities like verification and accessibility of the data mentioned in the archive catalogue, station localization according to the historical annual books, conversion of coordinates into x-JTSK, y-JTSK and hydrological catchment assignment. Clustering of precipitation stations at the specific hydrological catchment in the map and visualization of the data duration (line graph) will lead to the effective assignment of corresponding precipitation stations for the prolongation of time series. This process should be followed by the process of turn or trend detection and homogenization. The risks and problems at verification of records from archive catalogues, their digitalization, repairs and the way of visualization will be seen in poster. During the searching process of the historical and often short time series, we realized the importance of mainly those stations, located in the middle and higher altitudes. They might be used as replacement for up to now quoted fictive points used at the construction of precipitation maps. Supplementing and enhancing the time series of individual stations will enable to follow changes in precipitation totals during the certain period as well as area totals for individual catchments in various time periods appreciated mainly by hydrologists and agro-climatologists.

A CLASSIFICATION OF U.S. ESTUARIES BASED ON PHYSICAL, HYDROLOGIC ATTRIBUTES

EPA Science Inventory

A classification of U.S. estuaries is presented based on estuarine characteristics that have been identified as important for quantifying stressor-response

relationships in coastal systems. Estuaries within a class have similar physical/hydrologic and land use characteris...

System Complexity Reduction via Feature Selection

ERIC Educational Resources Information Center

Deng, Houtao

2011-01-01

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

Considering the dynamic refueling behavior in locating electric vehicle charging stations

NASA Astrophysics Data System (ADS)

Liu, K.; Sun, X. H.

2014-11-01

Electric vehicles (EVs) will certainly play an important role in addressing the energy and environmental challenges at current situation. However, location problem of EV charging stations was realized as one of the key issues of EVs launching strategy. While for the case of locating EV charging stations, more influence factors and constraints need to be considered since the EVs have some special attributes. The minimum requested charging time for EVs is usually more than 30minutes, therefore the possible delay time due to waiting or looking for an available station is one of the most important influence factors. In addition, the intention to purchase and use of EVs that also affects the location of EV charging stations is distributed unevenly among regions and should be considered when modelling. Unfortunately, these kinds of time-spatial constraints were always ignored in previous models. Based on the related research of refuelling behaviours and refuelling demands, this paper developed a new concept with dual objectives of minimum waiting time and maximum service accessibility for locating EV charging stations - named as Time-Spatial Location Model (TSLM). The proposed model and the traditional flow-capturing location model are applied on an example network respectively and the results are compared. Results demonstrate that time constraint has great effects on the location of EV charging stations. The proposed model has some obvious advantages and will help energy providers to make a viable plan for the network of EV charging stations.

Influence Analysis for the Area Under the Receiver Operating Characteristic Curve.

PubMed

Ke, Bo-Shiang; Chiang, An Jen; Chang, Yuan-Chin Ivan

2018-01-01

Classification measures play essential roles in the assessment and construction of classifiers. Hence, determining how to prevent these measures from being affected by individual observations has become an important problem. In this paper, we propose several indexes based on the influence function and the concept of local influence to identify influential observations that affect the estimate of the area under the receiver operating characteristic curve (AUC), an important and commonly used measure. Cumulative lift charts are also used to equipoise the disagreements among the proposed indexes. Both the AUC indexes and the graphical tools only rely on the classification scores, and both are applicable to classifiers that can produce real-valued classification scores. A real data set is used for illustration.

The research on medical image classification algorithm based on PLSA-BOW model.

PubMed

Cao, C H; Cao, H L

2016-04-29

With the rapid development of modern medical imaging technology, medical image classification has become more important for medical diagnosis and treatment. To solve the existence of polysemous words and synonyms problem, this study combines the word bag model with PLSA (Probabilistic Latent Semantic Analysis) and proposes the PLSA-BOW (Probabilistic Latent Semantic Analysis-Bag of Words) model. In this paper we introduce the bag of words model in text field to image field, and build the model of visual bag of words model. The method enables the word bag model-based classification method to be further improved in accuracy. The experimental results show that the PLSA-BOW model for medical image classification can lead to a more accurate classification.

EMG finger movement classification based on ANFIS

NASA Astrophysics Data System (ADS)

Caesarendra, W.; Tjahjowidodo, T.; Nico, Y.; Wahyudati, S.; Nurhasanah, L.

2018-04-01

An increase number of people suffering from stroke has impact to the rapid development of finger hand exoskeleton to enable an automatic physical therapy. Prior to the development of finger exoskeleton, a research topic yet important i.e. machine learning of finger gestures classification is conducted. This paper presents a study on EMG signal classification of 5 finger gestures as a preliminary study toward the finger exoskeleton design and development in Indonesia. The EMG signals of 5 finger gestures were acquired using Myo EMG sensor. The EMG signal features were extracted and reduced using PCA. The ANFIS based learning is used to classify reduced features of 5 finger gestures. The result shows that the classification of finger gestures is less than the classification of 7 hand gestures.

Space station needs, attributes and architectural options. Volume 4, task 2 and 3: Mission implementation and cost

NASA Technical Reports Server (NTRS)

1983-01-01

An overview of the basic space station infrastructure is presented. A strong case is made for the evolution of the station using the basic Space Transportation System (STS) to achieve a smooth transition and cost effective implementation. The integrated logistics support (ILS) element of the overall station infrastructure is investigated. The need for an orbital transport system capability that is the key to servicing and spacecraft positioning scenarios and associated mission needs is examined. Communication is also an extremely important element and the basic issue of station autonomy versus ground support effects the system and subsystem architecture.

Perspectives on Machine Learning for Classification of Schizotypy Using fMRI Data.

PubMed

Madsen, Kristoffer H; Krohne, Laerke G; Cai, Xin-Lu; Wang, Yi; Chan, Raymond C K

2018-03-15

Functional magnetic resonance imaging is capable of estimating functional activation and connectivity in the human brain, and lately there has been increased interest in the use of these functional modalities combined with machine learning for identification of psychiatric traits. While these methods bear great potential for early diagnosis and better understanding of disease processes, there are wide ranges of processing choices and pitfalls that may severely hamper interpretation and generalization performance unless carefully considered. In this perspective article, we aim to motivate the use of machine learning schizotypy research. To this end, we describe common data processing steps while commenting on best practices and procedures. First, we introduce the important role of schizotypy to motivate the importance of reliable classification, and summarize existing machine learning literature on schizotypy. Then, we describe procedures for extraction of features based on fMRI data, including statistical parametric mapping, parcellation, complex network analysis, and decomposition methods, as well as classification with a special focus on support vector classification and deep learning. We provide more detailed descriptions and software as supplementary material. Finally, we present current challenges in machine learning for classification of schizotypy and comment on future trends and perspectives.

Cosmetics Europe compilation of historical serious eye damage/eye irritation in vivo data analysed by drivers of classification to support the selection of chemicals for development and evaluation of alternative methods/strategies: the Draize eye test Reference Database (DRD).

PubMed

Barroso, João; Pfannenbecker, Uwe; Adriaens, Els; Alépée, Nathalie; Cluzel, Magalie; De Smedt, Ann; Hibatallah, Jalila; Klaric, Martina; Mewes, Karsten R; Millet, Marion; Templier, Marie; McNamee, Pauline

2017-02-01

A thorough understanding of which of the effects assessed in the in vivo Draize eye test are responsible for driving UN GHS/EU CLP classification is critical for an adequate selection of chemicals to be used in the development and/or evaluation of alternative methods/strategies and for properly assessing their predictive capacity and limitations. For this reason, Cosmetics Europe has compiled a database of Draize data (Draize eye test Reference Database, DRD) from external lists that were created to support past validation activities. This database contains 681 independent in vivo studies on 634 individual chemicals representing a wide range of chemical classes. A description of all the ocular effects observed in vivo, i.e. degree of severity and persistence of corneal opacity (CO), iritis, and/or conjunctiva effects, was added for each individual study in the database, and the studies were categorised according to their UN GHS/EU CLP classification and the main effect driving the classification. An evaluation of the various in vivo drivers of classification compiled in the database was performed to establish which of these are most important from a regulatory point of view. These analyses established that the most important drivers for Cat 1 Classification are (1) CO mean ≥ 3 (days 1-3) (severity) and (2) CO persistence on day 21 in the absence of severity, and those for Cat 2 classification are (3) CO mean ≥ 1 and (4) conjunctival redness mean ≥ 2. Moreover, it is shown that all classifiable effects (including persistence and CO = 4) should be present in ≥60 % of the animals to drive a classification. As a consequence, our analyses suggest the need for a critical revision of the UN GHS/EU CLP decision criteria for the Cat 1 classification of chemicals. Finally, a number of key criteria are identified that should be taken into consideration when selecting reference chemicals for the development, evaluation and/or validation of alternative methods and/or strategies for serious eye damage/eye irritation testing. Most important, the DRD is an invaluable tool for any future activity involving the selection of reference chemicals.

Sensitivity study of Space Station Freedom operations cost and selected user resources

NASA Technical Reports Server (NTRS)

Accola, Anne; Fincannon, H. J.; Williams, Gregory J.; Meier, R. Timothy

1990-01-01

The results of sensitivity studies performed to estimate probable ranges for four key Space Station parameters using the Space Station Freedom's Model for Estimating Space Station Operations Cost (MESSOC) are discussed. The variables examined are grouped into five main categories: logistics, crew, design, space transportation system, and training. The modification of these variables implies programmatic decisions in areas such as orbital replacement unit (ORU) design, investment in repair capabilities, and crew operations policies. The model utilizes a wide range of algorithms and an extensive trial logistics data base to represent Space Station operations. The trial logistics data base consists largely of a collection of the ORUs that comprise the mature station, and their characteristics based on current engineering understanding of the Space Station. A nondimensional approach is used to examine the relative importance of variables on parameters.

Channel morphology [Chapter 5

Treesearch

Jonathan W. Long; Alvin L. Medina; Daniel G. Neary

2012-01-01

Channel morphology has become an increasingly important subject for analyzing the health of rivers and associated fish populations, particularly since the popularization of channel classification and assessment methods. Morphological data can help to evaluate the flows of sediment and water that influence aquatic and riparian habitat. Channel classification systems,...

Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

NASA Technical Reports Server (NTRS)

Fayyad, U.; Irani, K.

1993-01-01

Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuous-valued attribute into multiple intervals.

Fidelity of Automatic Speech Processing for Adult and Child Talker Classifications.

PubMed

VanDam, Mark; Silbert, Noah H

2016-01-01

Automatic speech processing (ASP) has recently been applied to very large datasets of naturalistically collected, daylong recordings of child speech via an audio recorder worn by young children. The system developed by the LENA Research Foundation analyzes children's speech for research and clinical purposes, with special focus on of identifying and tagging family speech dynamics and the at-home acoustic environment from the auditory perspective of the child. A primary issue for researchers, clinicians, and families using the Language ENvironment Analysis (LENA) system is to what degree the segment labels are valid. This classification study evaluates the performance of the computer ASP output against 23 trained human judges who made about 53,000 judgements of classification of segments tagged by the LENA ASP. Results indicate performance consistent with modern ASP such as those using HMM methods, with acoustic characteristics of fundamental frequency and segment duration most important for both human and machine classifications. Results are likely to be important for interpreting and improving ASP output.

Fidelity of Automatic Speech Processing for Adult and Child Talker Classifications

PubMed Central

2016-01-01

Automatic speech processing (ASP) has recently been applied to very large datasets of naturalistically collected, daylong recordings of child speech via an audio recorder worn by young children. The system developed by the LENA Research Foundation analyzes children's speech for research and clinical purposes, with special focus on of identifying and tagging family speech dynamics and the at-home acoustic environment from the auditory perspective of the child. A primary issue for researchers, clinicians, and families using the Language ENvironment Analysis (LENA) system is to what degree the segment labels are valid. This classification study evaluates the performance of the computer ASP output against 23 trained human judges who made about 53,000 judgements of classification of segments tagged by the LENA ASP. Results indicate performance consistent with modern ASP such as those using HMM methods, with acoustic characteristics of fundamental frequency and segment duration most important for both human and machine classifications. Results are likely to be important for interpreting and improving ASP output. PMID:27529813

Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

PubMed

Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

2014-04-01

In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

The use and abuse of standard stars

NASA Astrophysics Data System (ADS)

Garrison, R. F.

The 'mandate' of classification systems is examined with reference to spectral classification. In using a classification system, it is of the greatest importance to be aware of why it was created, how it was constructed, what its useful limits are, how it has evolved, and what credibility it has achieved in practice . . . all of which constitute the mandate of the system. In the particular case of the MK system of spectral classification, types are defined by the standard stars. They can be calibrated, and the calibration may evolve with time, but the types are relatively stable because they are defined by the standards. The autonomy of this powerful system is crucial to its success, but some astronomers do not understand the importance of this distinction. Recent suggestions to change the spectral type of the sun show an ignorance of the way the system works. The confrontation and complementary use of autonomous systems yield information which is not contained in any individual system.

Probabilistic classifiers with high-dimensional data

PubMed Central

Kim, Kyung In; Simon, Richard

2011-01-01

For medical classification problems, it is often desirable to have a probability associated with each class. Probabilistic classifiers have received relatively little attention for small n large p classification problems despite of their importance in medical decision making. In this paper, we introduce 2 criteria for assessment of probabilistic classifiers: well-calibratedness and refinement and develop corresponding evaluation measures. We evaluated several published high-dimensional probabilistic classifiers and developed 2 extensions of the Bayesian compound covariate classifier. Based on simulation studies and analysis of gene expression microarray data, we found that proper probabilistic classification is more difficult than deterministic classification. It is important to ensure that a probabilistic classifier is well calibrated or at least not “anticonservative” using the methods developed here. We provide this evaluation for several probabilistic classifiers and also evaluate their refinement as a function of sample size under weak and strong signal conditions. We also present a cross-validation method for evaluating the calibration and refinement of any probabilistic classifier on any data set. PMID:21087946

Analysis of television food advertising on children's programming on "free-to-air" broadcast stations in Brazil.

PubMed

Costa, Suzane Mota Marques; Horta, Paula Martins; Santos, Luana Caroline Dos

2013-12-01

To analyze the content of television food advertising on Brazilian 'free-to-air' broadcast stations during children's programming. This is a descriptive study which evaluated the content of food advertising between 08:00 a.m. and 06:00 p.m. on three Brazilian 'free-to-air' broadcast stations (A, B and C). Data collection was performed during 10 week days and weekends. Food advertising was organized according to the food group classification from the Food Guide for the Brazilian Population. The annual exposure to food advertising was obtained considering the national children average exposure to television of five daily hours. The χ2 and Fisher's exact test were conducted in order to identify differences in the content of television advertising in the morning and in the afternoon and between broadcast stations. One hundred and twenty six hours of programming were recorded, totalizing 1,369 commercials - 13.8% of food. There was major participation of 'sugars and sweets' (48.1%) and 'oils and fats' (29.1%) among food advertising and much food publicity in the afternoon (15.7%; morning: 12.2%, p = 0.037). Moreover, the broadcast with more audience was the one that advertised more food (A: 63.5%; B: 12.2%; C: 24.3%), especially 'sugar and sweets' (A: 59.2%; B: 43.5%; C: 21.7%). Finally, an annual average exposure to 2,735.5 commercials was obtained for Brazilian children, totalizing 2,106.3 of food rich in sugar and fat publicity. Food advertising is focused on poor nutritionally food, emphasizing the need for specific intervention strategies.

Space station assembly/servicing capabilities

NASA Technical Reports Server (NTRS)

Joyce, Joseph

1986-01-01

The aim is to place a permanently manned space station on-orbit around the Earth, which is international in scope. The program is nearing the close of the system definition and preliminary design phase. The first shuttle launch for space station assembly on-orbit is estimated for January 1993. Topics perceived to be important to on-orbit assembly and servicing are discussed. This presentation is represented by charts.

Space Station Initial Operational Concept (IOC) operations and safety view - Automation and robotics for Space Station

NASA Technical Reports Server (NTRS)

Bates, William V., Jr.

1989-01-01

The automation and robotics requirements for the Space Station Initial Operational Concept (IOC) are discussed. The amount of tasks to be performed by an eight-person crew, the need for an automated or directed fault analysis capability, and ground support requirements are considered. Issues important in determining the role of automation for the IOC are listed.

Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

The information extraction of Gannan citrus orchard based on the GF-1 remote sensing image

NASA Astrophysics Data System (ADS)

Wang, S.; Chen, Y. L.

2017-02-01

The production of Gannan oranges is the largest in China, which occupied an important part in the world. The extraction of citrus orchard quickly and effectively has important significance for fruit pathogen defense, fruit production and industrial planning. The traditional spectra extraction method of citrus orchard based on pixel has a lower classification accuracy, difficult to avoid the “pepper phenomenon”. In the influence of noise, the phenomenon that different spectrums of objects have the same spectrum is graveness. Taking Xunwu County citrus fruit planting area of Ganzhou as the research object, aiming at the disadvantage of the lower accuracy of the traditional method based on image element classification method, a decision tree classification method based on object-oriented rule set is proposed. Firstly, multi-scale segmentation is performed on the GF-1 remote sensing image data of the study area. Subsequently the sample objects are selected for statistical analysis of spectral features and geometric features. Finally, combined with the concept of decision tree classification, a variety of empirical values of single band threshold, NDVI, band combination and object geometry characteristics are used hierarchically to execute the information extraction of the research area, and multi-scale segmentation and hierarchical decision tree classification is implemented. The classification results are verified with the confusion matrix, and the overall Kappa index is 87.91%.

Ensemble methods with simple features for document zone classification

NASA Astrophysics Data System (ADS)

Obafemi-Ajayi, Tayo; Agam, Gady; Xie, Bingqing

2012-01-01

Document layout analysis is of fundamental importance for document image understanding and information retrieval. It requires the identification of blocks extracted from a document image via features extraction and block classification. In this paper, we focus on the classification of the extracted blocks into five classes: text (machine printed), handwriting, graphics, images, and noise. We propose a new set of features for efficient classifications of these blocks. We present a comparative evaluation of three ensemble based classification algorithms (boosting, bagging, and combined model trees) in addition to other known learning algorithms. Experimental results are demonstrated for a set of 36503 zones extracted from 416 document images which were randomly selected from the tobacco legacy document collection. The results obtained verify the robustness and effectiveness of the proposed set of features in comparison to the commonly used Ocropus recognition features. When used in conjunction with the Ocropus feature set, we further improve the performance of the block classification system to obtain a classification accuracy of 99.21%.

Molecular approaches for classifying endometrial carcinoma.

PubMed

Piulats, Josep M; Guerra, Esther; Gil-Martín, Marta; Roman-Canal, Berta; Gatius, Sonia; Sanz-Pamplona, Rebeca; Velasco, Ana; Vidal, August; Matias-Guiu, Xavier

2017-04-01

Endometrial carcinoma is the most common cancer of the female genital tract. This review article discusses the usefulness of molecular techniques to classify endometrial carcinoma. Any proposal for molecular classification of neoplasms should integrate morphological features of the tumors. For that reason, we start with the current histological classification of endometrial carcinoma, by discussing the correlation between genotype and phenotype, and the most significant recent improvements. Then, we comment on some of the possible flaws of this classification, by discussing also the value of molecular pathology in improving them, including interobserver variation in pathologic interpretation of high grade tumors. Third, we discuss the importance of applying TCGA molecular approach to clinical practice. We also comment on the impact of intratumor heterogeneity in classification, and finally, we will discuss briefly, the usefulness of TCGA classification in tailoring immunotherapy in endometrial cancer patients. We suggest combining pathologic classification and the surrogate TCGA molecular classification for high-grade endometrial carcinomas, as an option to improve assessment of prognosis. Copyright © 2016 Elsevier Inc. All rights reserved.

Pattern classification of kinematic and kinetic running data to distinguish gender, shod/barefoot and injury groups with feature ranking.

PubMed

Eskofier, Bjoern M; Kraus, Martin; Worobets, Jay T; Stefanyshyn, Darren J; Nigg, Benno M

2012-01-01

The identification of differences between groups is often important in biomechanics. This paper presents group classification tasks using kinetic and kinematic data from a prospective running injury study. Groups composed of gender, of shod/barefoot running and of runners who developed patellofemoral pain syndrome (PFPS) during the study, and asymptotic runners were classified. The features computed from the biomechanical data were deliberately chosen to be generic. Therefore, they were suited for different biomechanical measurements and classification tasks without adaptation to the input signals. Feature ranking was applied to reveal the relevance of each feature to the classification task. Data from 80 runners were analysed for gender and shod/barefoot classification, while 12 runners were investigated in the injury classification task. Gender groups could be differentiated with 84.7%, shod/barefoot running with 98.3%, and PFPS with 100% classification rate. For the latter group, one single variable could be identified that alone allowed discrimination.

Classification of weld defect based on information fusion technology for radiographic testing system

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

Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defectmore » feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.« less

Classification of weld defect based on information fusion technology for radiographic testing system.

PubMed

Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

2016-03-01

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

A fuzzy hill-climbing algorithm for the development of a compact associative classifier

NASA Astrophysics Data System (ADS)

Mitra, Soumyaroop; Lam, Sarah S.

2012-02-01

Classification, a data mining technique, has widespread applications including medical diagnosis, targeted marketing, and others. Knowledge discovery from databases in the form of association rules is one of the important data mining tasks. An integrated approach, classification based on association rules, has drawn the attention of the data mining community over the last decade. While attention has been mainly focused on increasing classifier accuracies, not much efforts have been devoted towards building interpretable and less complex models. This paper discusses the development of a compact associative classification model using a hill-climbing approach and fuzzy sets. The proposed methodology builds the rule-base by selecting rules which contribute towards increasing training accuracy, thus balancing classification accuracy with the number of classification association rules. The results indicated that the proposed associative classification model can achieve competitive accuracies on benchmark datasets with continuous attributes and lend better interpretability, when compared with other rule-based systems.

Desert plains classification based on Geomorphometrical parameters (Case study: Aghda, Yazd)

NASA Astrophysics Data System (ADS)

Tazeh, mahdi; Kalantari, Saeideh

2013-04-01

This research focuses on plains. There are several tremendous methods and classification which presented for plain classification. One of The natural resource based classification which is mostly using in Iran, classified plains into three types, Erosional Pediment, Denudation Pediment Aggradational Piedmont. The qualitative and quantitative factors to differentiate them from each other are also used appropriately. In this study effective Geomorphometrical parameters in differentiate landforms were applied for plain. Geomorphometrical parameters are calculable and can be extracted using mathematical equations and the corresponding relations on digital elevation model. Geomorphometrical parameters used in this study included Percent of Slope, Plan Curvature, Profile Curvature, Minimum Curvature, the Maximum Curvature, Cross sectional Curvature, Longitudinal Curvature and Gaussian Curvature. The results indicated that the most important affecting Geomorphometrical parameters for plain and desert classifications includes: Percent of Slope, Minimum Curvature, Profile Curvature, and Longitudinal Curvature. Key Words: Plain, Geomorphometry, Classification, Biophysical, Yazd Khezarabad.

Classification versus inference learning contrasted with real-world categories.

PubMed

Jones, Erin L; Ross, Brian H

2011-07-01

Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

An objective and parsimonious approach for classifying natural flow regimes at a continental scale

NASA Astrophysics Data System (ADS)

Archfield, S. A.; Kennen, J.; Carlisle, D.; Wolock, D.

2013-12-01

Hydroecological stream classification--the process of grouping streams by similar hydrologic responses and, thereby, similar aquatic habitat--has been widely accepted and is often one of the first steps towards developing ecological flow targets. Despite its importance, the last national classification of streamgauges was completed about 20 years ago. A new classification of 1,534 streamgauges in the contiguous United States is presented using a novel and parsimonious approach to understand similarity in ecological streamflow response. This new classification approach uses seven fundamental daily streamflow statistics (FDSS) rather than winnowing down an uncorrelated subset from 200 or more ecologically relevant streamflow statistics (ERSS) commonly used in hydroecological classification studies. The results of this investigation demonstrate that the distributions of 33 tested ERSS are consistently different among the classes derived from the seven FDSS. It is further shown that classification based solely on the 33 ERSS generally does a poorer job in grouping similar streamgauges than the classification based on the seven FDSS. This new classification approach has the additional advantages of overcoming some of the subjectivity associated with the selection of the classification variables and provides a set of robust continental-scale classes of US streamgauges.

ASSESSING THE HYDROGEOLOGIC CLASSIFICATION SYSTEM IN MID-ATLANTIC COASTAL PLAIN STREAMS USING BENTHIC MACROINVERTEBRATES

EPA Science Inventory

Assessing classification systems that describe natural variation across regions is an important first step for developing indicators. We evaluated a hydrogeologic framework for first order streams in the mid-Atlantic Coastal Plain as part of the LIPS-MACS (Landscape Indicators f...

Classifying Values by Categories

ERIC Educational Resources Information Center

Gündüz, Mevlüt

2016-01-01

The aim of this study is to make a new classification regarding the fact that the current classifications may change constantly because of values? gaining a different dimension and importance every single day. In this research descriptive research, which was used frequently in qualitative research methods, was preferred. This research was…

Identification of Putative Cardiovascular System Developmental Toxicants using a Classification Model based on Signaling Pathway-Adverse Outcome Pathways

EPA Science Inventory

An important challenge for an integrative approach to developmental systems toxicology is associating putative molecular initiating events (MIEs), cell signaling pathways, cell function and modeled fetal exposure kinetics. We have developed a chemical classification model based o...

13 CFR 124.3 - What definitions are important in the 8(a) BD program?

Code of Federal Regulations, 2013 CFR

2013-01-01

... the marketing, production, sales, and administrative functions of the firm. Immediate family member... Native Hawaiians. Negative control is defined in part 121 of this title. Non-disadvantaged individual.... Primary industry classification means the six digit North American Industry Classification System (NAICS...

13 CFR 124.3 - What definitions are important in the 8(a) BD program?

Code of Federal Regulations, 2012 CFR

2012-01-01

... the marketing, production, sales, and administrative functions of the firm. Immediate family member... Native Hawaiians. Negative control is defined in part 121 of this title. Non-disadvantaged individual.... Primary industry classification means the six digit North American Industry Classification System (NAICS...

Using VS30 to Estimate Station ML Adjustments (dML)

NASA Astrophysics Data System (ADS)

Yong, A.; Herrick, J.; Cochran, E. S.; Andrews, J. R.; Yu, E.

2017-12-01

Currently, new seismic stations added to a regional seismic network cannot be used to calculate local or Richter magnitude (ML) until a revised region-wide amplitude decay function is developed. The new station must record a minimum number of local and regional events that meet specific amplitude requirements prior to re-calibration of the amplitude decay function. Therefore, there can be significant delay between when a new station starts contributing real-time waveform packets and when the data can be included in magnitude estimation. The station component adjustments (dML; Uhrhammer et al., 2011) are calculated after first inverting for a new regional amplitude decay function, constrained by the sum of dML for long-running stations. Here, we propose a method to calculate an initial dML using known or proxy values of seismic site conditions. For site conditions, we use the time-averaged shear-wave velocity (VS) of the upper 30 m (VS30). We solve for dML as described in Equation (1) by Uhrhammer et al. (2011): ML = log (A) - log A0 (r) + dML, where A is the maximum Wood and Anderson (1925) trace amplitude (mm), r is the distance (km), and dML is the station adjustment. Measured VS30 and estimated dML data are comprised of records from 887 horizontal components (east-west and north-south orientations) from 93 seismic monitoring stations in the California Integrated Seismic Network. VS30 values range from 202 m/s to 1464 m/s and dML range from -1.10 to 0.39. VS30 and dML exhibit a positive correlation coefficient (R = 0.72), indicating that as VS30 increases, dML increases. This implies that greater site amplification (i.e., lower VS30) results in smaller ML. When we restrict VS30 < 760 m/s to focus on dML at soft soil to soft rock sites, R increases to 0.80. In locations where measured VS30 data are unavailable, we evaluate the use of proxy-based VS30 estimates based on geology, topographic slope and terrain classification, as well as other hybridized methods. Measured VS30 data or proxy-based VS30 estimates can be used for initial dML estimates that allow new stations to contribute to regional network ML estimates immediately without the need to wait until a minimum set of earthquake data has been recorded.

Surface Water Detection Using Fused Synthetic Aperture Radar, Airborne LiDAR and Optical Imagery

NASA Astrophysics Data System (ADS)

Braun, A.; Irwin, K.; Beaulne, D.; Fotopoulos, G.; Lougheed, S. C.

2016-12-01

Each remote sensing technique has its unique set of strengths and weaknesses, but by combining techniques the classification accuracy can be increased. The goal of this project is to underline the strengths and weaknesses of Synthetic Aperture Radar (SAR), LiDAR and optical imagery data and highlight the opportunities where integration of the three data types can increase the accuracy of identifying water in a principally natural landscape. The study area is located at the Queen's University Biological Station, Ontario, Canada. TerraSAR-X (TSX) data was acquired between April and July 2016, consisting of four single polarization (HH) staring spotlight mode backscatter intensity images. Grey-level thresholding is used to extract surface water bodies, before identifying and masking zones of radar shadow and layover by using LiDAR elevation models to estimate the canopy height and applying simple geometry algorithms. The airborne LiDAR survey was conducted in June 2014, resulting in a discrete return dataset with a density of 1 point/m2. Radiometric calibration to correct for range and incidence angle is applied, before classifying the points as water or land based on corrected intensity, elevation, roughness, and intensity density. Panchromatic and multispectral (4-band) imagery from Quickbird was collected in September 2005 at spatial resolutions of 0.6m and 2.5m respectively. Pixel-based classification is applied to identify and distinguish water bodies from land. A classification system which inputs SAR-, LiDAR- and optically-derived water presence models in raster formats is developed to exploit the strengths and weaknesses of each technique. The total percentage of water detected in the sample area for SAR backscatter, LiDAR intensity, and optical imagery was 27%, 19% and 18% respectively. The output matrix of the classification system indicates that in over 72% of the study area all three methods agree on the classification. Analysis was specifically targeted towards areas where the methods disagree, highlighting how each technique should be properly weighted over these areas to increase the classification accuracy of water. The conclusions and techniques developed in this study are applicable to other areas where similar environmental conditions and data availability exist.

Urban Heat Island phenomenon in extreme continental climate (Astana, Kazakhstan)

NASA Astrophysics Data System (ADS)

Konstantinov, Pavel; Akhmetova, Alina

2015-04-01

Urban Heat Island (UHI) phenomenon is well known in scientific literature since first half of the 19th century [1]. By now a wide number of world capitals is described from climatological point of view, especially in mid-latitudes. In beginning of XXI century new studies focus on heat island of tropical cities. However dynamics UHI in extreme continental climates is insufficiently investigated, due to the fact that there isn't large cities in Europe and Northern America within that climate type. In this paper we investigate seasonal and diurnal dynamics UHI intensity for Astana, capital city of Kazakhstan (population larger than 835 000 within the city) including UHI intensity changes on different time scales. Now (since 1998) Astana is the second coldest capital city in the world after Ulaanbaatar, Mongolia [3] For this study we use the UHI investigation technology, described in [2]. According to this paper, we selected three stations: one located into city in high and midrise buildings area (including extensive lowrise and high-energy industrial - LCZ classification) and two others located in rural site (sparsely built or open-set and lightweight lowrise according LCZ classification). Also these stations must be close by distance (less than 100 km) and altitude. Therefore, first for Astana city were obtained numerical evaluations for UHI climate dynamics, UHI dependence of synoptic situations and total UHI climatology on monthly and daily averages. References: 1.Howard, L. (1833) The Climate of London, Deduced from Meteorological Observations. Volume 2, London. 2.Kukanova E.A., Konstantinov P.I. An urban heat islands climatology in Russia and linkages to the climate change In Geophysical Research Abstracts, volume 16 of EGU General Assembly, pages EGU2014-10833-1, Germany, 2014. Germany. 3.www.pogoda.ru.net

Expert identification of visual primitives used by CNNs during mammogram classification

NASA Astrophysics Data System (ADS)

Wu, Jimmy; Peck, Diondra; Hsieh, Scott; Dialani, Vandana; Lehman, Constance D.; Zhou, Bolei; Syrgkanis, Vasilis; Mackey, Lester; Patterson, Genevieve

2018-02-01

This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms. We propose an expert-in-the-loop inter- pretation method to label the behavior of internal units in convolutional neural networks (CNNs). Expert radiologists identify that the visual patterns detected by the units are correlated with meaningful medical phenomena such as mass tissue and calcificated vessels. We demonstrate that several trained CNN models are able to produce explanatory descriptions to support the final classification decisions. We view this as an important first step toward interpreting the internal representations of medical classification CNNs and explaining their predictions.

Spectral band selection for classification of soil organic matter content

NASA Technical Reports Server (NTRS)

Henderson, Tracey L.; Szilagyi, Andrea; Baumgardner, Marion F.; Chen, Chih-Chien Thomas; Landgrebe, David A.

1989-01-01

This paper describes the spectral-band-selection (SBS) algorithm of Chen and Landgrebe (1987, 1988, and 1989) and uses the algorithm to classify the organic matter content in the earth's surface soil. The effectiveness of the algorithm was evaluated comparing the results of classification of the soil organic matter using SBS bands with those obtained using Landsat MSS bands and TM bands, showing that the algorithm was successful in finding important spectral bands for classification of organic matter content. Using the calculated bands, the probabilities of correct classification for climate-stratified data were found to range from 0.910 to 0.980.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Historical linguistics in Australia: trees, networks and their implications

PubMed Central

Bowern, Claire

2010-01-01

This paper presents an overview of the current state of historical linguistics in Australian languages. Australian languages have been important in theoretical debates about the nature of language change and the possibilities for reconstruction and classification in areas of intensive diffusion. Here are summarized the most important outstanding questions for Australian linguistic prehistory; I also present a case study of the Karnic subgroup of Pama–Nyungan, which illustrates the problems for classification in Australian languages and potential approaches using phylogenetic methods. PMID:21041209

Historical linguistics in Australia: trees, networks and their implications.

PubMed

Bowern, Claire

2010-12-12

This paper presents an overview of the current state of historical linguistics in Australian languages. Australian languages have been important in theoretical debates about the nature of language change and the possibilities for reconstruction and classification in areas of intensive diffusion. Here are summarized the most important outstanding questions for Australian linguistic prehistory; I also present a case study of the Karnic subgroup of Pama-Nyungan, which illustrates the problems for classification in Australian languages and potential approaches using phylogenetic methods.

Analysis on the Utility of Satellite Imagery for Detection of Agricultural Facility

NASA Astrophysics Data System (ADS)

Kang, J.-M.; Baek, S.-H.; Jung, K.-Y.

2012-07-01

Now that the agricultural facilities are being increase owing to development of technology and diversification of agriculture and the ratio of garden crops that are imported a lot and the crops cultivated in facilities are raised in Korea, the number of vinyl greenhouses is tending upward. So, it is important to grasp the distribution of vinyl greenhouses as much as that of rice fields, dry fields and orchards, but it is difficult to collect the information of wide areas economically and correctly. Remote sensing using satellite imagery is able to obtain data of wide area at the same time, quickly and cost-effectively collect, monitor and analyze information from every object on earth. In this study, in order to analyze the utilization of satellite imagery at detection of agricultural facility, image classification was performed about the agricultural facility, vinyl greenhouse using Formosat-2 satellite imagery. The training set of sea, vegetation, building, bare ground and vinyl greenhouse was set to monitor the agricultural facilities of the object area and the training set for the vinyl greenhouses that are main monitoring object was classified and set again into 3 types according the spectral characteristics. The image classification using 4 kinds of supervise classification methods applied by the same training set were carried out to grasp the image classification method which is effective for monitoring agricultural facilities. And, in order to minimize the misclassification appeared in the classification using the spectral information, the accuracy of classification was intended to be raised by adding texture information. The results of classification were analyzed regarding the accuracy comparing with that of naked-eyed detection. As the results of classification, the method of Mahalanobis distance was shown as more efficient than other methods and the accuracy of classification was higher when adding texture information. Hence the more effective monitoring of agricultural facilities is expected to be available if the characteristics such as texture information including satellite images or spatial pattern are studied in detail.

Machine learning algorithms for mode-of-action classification in toxicity assessment.

PubMed

Zhang, Yile; Wong, Yau Shu; Deng, Jian; Anton, Cristina; Gabos, Stephan; Zhang, Weiping; Huang, Dorothy Yu; Jin, Can

2016-01-01

Real Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period. Combining with different testing concentrations, the profiles have potential in probing the mode of action (MOA) of the testing substances. In this paper, we present machine learning approaches for MOA assessment. Computational tools based on artificial neural network (ANN) and support vector machine (SVM) are developed to analyze the time-concentration response curves (TCRCs) of human cell lines responding to tested chemicals. The techniques are capable of learning data from given TCRCs with known MOA information and then making MOA classification for the unknown toxicity. A novel data processing step based on wavelet transform is introduced to extract important features from the original TCRC data. From the dose response curves, time interval leading to higher classification success rate can be selected as input to enhance the performance of the machine learning algorithm. This is particularly helpful when handling cases with limited and imbalanced data. The validation of the proposed method is demonstrated by the supervised learning algorithm applied to the exposure data of HepG2 cell line to 63 chemicals with 11 concentrations in each test case. Classification success rate in the range of 85 to 95 % are obtained using SVM for MOA classification with two clusters to cases up to four clusters. Wavelet transform is capable of capturing important features of TCRCs for MOA classification. The proposed SVM scheme incorporated with wavelet transform has a great potential for large scale MOA classification and high-through output chemical screening.

A space-based classification system for RF transients

NASA Astrophysics Data System (ADS)

Moore, K. R.; Call, D.; Johnson, S.; Payne, T.; Ford, W.; Spencer, K.; Wilkerson, J. F.; Baumgart, C.

The FORTE (Fast On-Orbit Recording of Transient Events) small satellite is scheduled for launch in mid 1995. The mission is to measure and classify VHF (30-300 MHz) electromagnetic pulses, primarily due to lightning, within a high noise environment dominated by continuous wave carriers such as TV and FM stations. The FORTE Event Classifier will use specialized hardware to implement signal processing and neural network algorithms that perform onboard classification of RF transients and carriers. Lightning events will also be characterized with optical data telemetered to the ground. A primary mission science goal is to develop a comprehensive understanding of the correlation between the optical flash and the VHF emissions from lightning. By combining FORTE measurements with ground measurements and/or active transmitters, other science issues can be addressed. Examples include the correlation of global precipitation rates with lightning flash rates and location, the effects of large scale structures within the ionosphere (such as traveling ionospheric disturbances and horizontal gradients in the total electron content) on the propagation of broad bandwidth RF signals, and various areas of lightning physics. Event classification is a key feature of the FORTE mission. Neural networks are promising candidates for this application. The authors describe the proposed FORTE Event Classifier flight system, which consists of a commercially available digital signal processing board and a custom board, and discuss work on signal processing and neural network algorithms.

Towards catchment classification in data-scarce regions

DOE PAGES

Auerbach, Daniel A.; Buchanan, Brian P.; Alexiades, Alex V.; ...

2016-01-29

Assessing spatial variation in hydrologic processes can help to inform freshwater management and advance ecological understanding, yet many areas lack sufficient flow records on which to base classifications. Seeking to address this challenge, we apply concepts developed in data-rich settings to public, global data in order to demonstrate a broadly replicable approach to characterizing hydrologic variation. The proposed approach groups the basins associated with reaches in a river network according to key environmental drivers of hydrologic conditions. This initial study examines Colorado (USA), where long-term streamflow records permit comparison to previously distinguished flow regime types, and the Republic of Ecuador,more » where data limitations preclude such analysis. The flow regime types assigned to gages in Colorado corresponded reasonably well to the classes distinguished from environmental features. The divisions in Ecuador reflected major known biophysical gradients while also providing a higher resolution supplement to an existing depiction of freshwater ecoregions. Although freshwater policy and management decisions occur amidst uncertainty and imperfect knowledge, this classification framework offers a rigorous and transferrable means to distinguish catchments in data-scarce regions. The maps and attributes of the resulting ecohydrologic classes offer a departure point for additional study and data collection programs such as the placement of stations in under-monitored classes, and the divisions may serve as a preliminary template with which to structure conservation efforts such as environmental flow assessments.« less

Cross-entropy clustering framework for catchment classification

NASA Astrophysics Data System (ADS)

Tongal, Hakan; Sivakumar, Bellie

2017-09-01

There is an increasing interest in catchment classification and regionalization in hydrology, as they are useful for identification of appropriate model complexity and transfer of information from gauged catchments to ungauged ones, among others. This study introduces a nonlinear cross-entropy clustering (CEC) method for classification of catchments. The method specifically considers embedding dimension (m), sample entropy (SampEn), and coefficient of variation (CV) to represent dimensionality, complexity, and variability of the time series, respectively. The method is applied to daily streamflow time series from 217 gauging stations across Australia. The results suggest that a combination of linear and nonlinear parameters (i.e. m, SampEn, and CV), representing different aspects of the underlying dynamics of streamflows, could be useful for determining distinct patterns of flow generation mechanisms within a nonlinear clustering framework. For the 217 streamflow time series, nine hydrologically homogeneous clusters that have distinct patterns of flow regime characteristics and specific dominant hydrological attributes with different climatic features are obtained. Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method. The outcomes from this study provide a useful guideline for employing the nonlinear dynamic approaches based on hydrologic signatures and for gaining an improved understanding of streamflow variability at a large scale.

Application of Bayesian Classification to Content-Based Data Management

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Berrick, S.; Gopalan, A.; Hua, X.; Shen, S.; Smith, P.; Yang, K-Y.; Wheeler, K.; Curry, C.

2004-01-01

The high volume of Earth Observing System data has proven to be challenging to manage for data centers and users alike. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), about 1 TB of new data are archived each day. Distribution to users is also about 1 TB/day. A substantial portion of this distribution is MODIS calibrated radiance data, which has a wide variety of uses. However, much of the data is not useful for a particular user's needs: for example, ocean color users typically need oceanic pixels that are free of cloud and sun-glint. The GES DAAC is using a simple Bayesian classification scheme to rapidly classify each pixel in the scene in order to support several experimental content-based data services for near-real-time MODIS calibrated radiance products (from Direct Readout stations). Content-based subsetting would allow distribution of, say, only clear pixels to the user if desired. Content-based subscriptions would distribute data to users only when they fit the user's usability criteria in their area of interest within the scene. Content-based cache management would retain more useful data on disk for easy online access. The classification may even be exploited in an automated quality assessment of the geolocation product. Though initially to be demonstrated at the GES DAAC, these techniques have applicability in other resource-limited environments, such as spaceborne data systems.

Spotting Epidemic Keystones by R0 Sensitivity Analysis: High-Risk Stations in the Tokyo Metropolitan Area

PubMed Central

Yashima, Kenta; Sasaki, Akira

2016-01-01

How can we identify the epidemiologically high-risk communities in a metapopulation network? The network centrality measure, which quantifies the relative importance of each location, is commonly utilized for this purpose. As the disease invasion condition is given from the basic reproductive ratio R0, we have introduced a novel centrality measure based on the sensitivity analysis of this R0 and shown its capability of revealing the characteristics that has been overlooked by the conventional centrality measures. The epidemic dynamics over the commute network of the Tokyo metropolitan area is theoretically analyzed by using this centrality measure. We found that, the impact of countermeasures at the largest station is more than 1,000 times stronger compare to that at the second largest station, even though the population sizes are only around 1.5 times larger. Furthermore, the effect of countermeasures at every station is strongly dependent on the existence and the number of commuters to this largest station. It is well known that the hubs are the most influential nodes, however, our analysis shows that only the largest among the network plays an extraordinary role. Lastly, we also found that, the location that is important for the prevention of disease invasion does not necessarily match the location that is important for reducing the number of infected. PMID:27607239

Classification of ASKAP Vast Radio Light Curves

NASA Technical Reports Server (NTRS)

Rebbapragada, Umaa; Lo, Kitty; Wagstaff, Kiri L.; Reed, Colorado; Murphy, Tara; Thompson, David R.

2012-01-01

The VAST survey is a wide-field survey that observes with unprecedented instrument sensitivity (0.5 mJy or lower) and repeat cadence (a goal of 5 seconds) that will enable novel scientific discoveries related to known and unknown classes of radio transients and variables. Given the unprecedented observing characteristics of VAST, it is important to estimate source classification performance, and determine best practices prior to the launch of ASKAP's BETA in 2012. The goal of this study is to identify light curve characterization and classification algorithms that are best suited for archival VAST light curve classification. We perform our experiments on light curve simulations of eight source types and achieve best case performance of approximately 90% accuracy. We note that classification performance is most influenced by light curve characterization rather than classifier algorithm.

Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey.

PubMed

Ozge, C; Toros, F; Bayramkaya, E; Camdeviren, H; Sasmaz, T

2006-08-01

The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Using in-class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed.

The Ascension Island hydroacoustic experiment: purpose, data set features and plans for future analysis

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

Harben, P E; Rock, D; Rodgers, A J

1999-07-23

Calibration of hydroacoustic and T-phase stations for Comprehensive Nuclear-Test-Ban Treaty (CTBT) monitoring will be an important element in establishing new operational stations and upgrading existing stations. Calibration of hydroacoustic stations is herein defined as precision location of the hydrophones and determination of the amplitude response from a known source energy. T-phase station calibration is herein defined as a determination of station site attenuation as a function of frequency, bearing, and distance for known impulsive energy sources in the ocean. To understand how to best conduct calibration experiments for both hydroacoustic and T-phase stations, an experiment was conducted in May, 1999more » at Ascension Island in the South Atlantic Ocean. The experiment made use of a British oceanographic research vessel and collected data that will be used for CTBT issues and for fundamental understanding of the Ascension Island volcanic edifice.« less

Pathohistological classification systems in gastric cancer: Diagnostic relevance and prognostic value

PubMed Central

Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

2014-01-01

Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer. PMID:24914328

Energy consumption analysis for the Mars deep space station

NASA Technical Reports Server (NTRS)

Hayes, N. V.

1982-01-01

Results for the energy consumption analysis at the Mars deep space station are presented. It is shown that the major energy consumers are the 64-Meter antenna building and the operations support building. Verification of the antenna's energy consumption is highly dependent on an accurate knowlege of the tracking operations. The importance of a regular maintenance schedule for the watt hour meters installed at the station is indicated.

Single-Trial Classification of Multi-User P300-Based Brain-Computer Interface Using Riemannian Geometry.

PubMed

Korczowski, L; Congedo, M; Jutten, C

2015-08-01

The classification of electroencephalographic (EEG) data recorded from multiple users simultaneously is an important challenge in the field of Brain-Computer Interface (BCI). In this paper we compare different approaches for classification of single-trials Event-Related Potential (ERP) on two subjects playing a collaborative BCI game. The minimum distance to mean (MDM) classifier in a Riemannian framework is extended to use the diversity of the inter-subjects spatio-temporal statistics (MDM-hyper) or to merge multiple classifiers (MDM-multi). We show that both these classifiers outperform significantly the mean performance of the two users and analogous classifiers based on the step-wise linear discriminant analysis. More importantly, the MDM-multi outperforms the performance of the best player within the pair.

Disciplinary Variations in Publicly Engaged Scholarship: An Analysis Using the Biglan Classification of Academic Disciplines

ERIC Educational Resources Information Center

Doberneck, Diane M.; Schweitzer, John H.

2017-01-01

Although contemporary models of faculty involvement in publicly engaged scholarship recognize the important influence of disciplines on faculty members, few studies have investigated disciplinary variations empirically. This study used the Biglan classification of academic disciplines to analyze publicly engaged scholarly activities reported by…

Mapping land cover in urban residential landscapes using fine resolution imagery and object-oriented classification

USDA-ARS?s Scientific Manuscript database

A knowledge of different types of land cover in urban residential landscapes is important for building social and economic city-wide policies including landscape ordinances and water conservation programs. Urban landscapes are typically heterogeneous, so classification of land cover in these areas ...

An Illustration of Diagnostic Classification Modeling in Student Learning Outcomes Assessment

ERIC Educational Resources Information Center

Jurich, Daniel P.; Bradshaw, Laine P.

2014-01-01

The assessment of higher-education student learning outcomes is an important component in understanding the strengths and weaknesses of academic and general education programs. This study illustrates the application of diagnostic classification models, a burgeoning set of statistical models, in assessing student learning outcomes. To facilitate…

Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory

EPA Science Inventory

Efforts are increasingly being made to classify the world’s wetland resources, an important ecosystem and habitat that is diminishing in abundance. There are multiple remote sensing classification methods, including a suite of nonparametric classifiers such as decision-tree...

Nutrition Problem Classification for Children and Youth.

ERIC Educational Resources Information Center

Health Services Administration (DHEW/PHS), Rockville, MD. Bureau of Community Health Services.

This nutrition problem classification system is an attempt to classify the nutritional needs and problems of children and youth. Its two most important uses are problem identification and monitoring for individual patients and creation of an information base for developing program plans for intervention in a service population. The classification…

13 CFR 124.3 - What definitions are important in the 8(a) BD program?

Code of Federal Regulations, 2011 CFR

2011-01-01

... functions of the firm. Immediate family member means father, mother, husband, wife, son, daughter, brother... Native Hawaiians. Negative control is defined in part 121 of this title. Non-disadvantaged individual.... Primary industry classification means the four digit Standard Industrial Classification (SIC) code...

THE EFFECTS OF HABITAT RESOLUTION ON MODELS OF AVIAN DIVERSITY AND DISTRIBUTIONS: A COMPARISON OF TWO LAND-COVER CLASSIFICATIONS

EPA Science Inventory

The quantification of pattern is a key element of landscape analyses. One aspect of this quantification of particular importance to landscape ecologists regards the classification of continuous variables to produce categorical variables such as land-cover type or elevation strat...

A scientific role for Space Station Freedom: Research at the cellular level

NASA Technical Reports Server (NTRS)

Johnson, Terry C.; Brady, John N.

1993-01-01

The scientific importance of Space Station Freedom is discussed in light of the valuable information that can be gained in cellular and developmental biology with regard to the microgravity environment on the cellular cytoskeleton, cellular responses to extracellular signal molecules, morphology, events associated with cell division, and cellular physiology. Examples of studies in basic cell biology, as well as their potential importance to concerns for future enabling strategies, are presented.

Towards a robust framework for catchment classification

NASA Astrophysics Data System (ADS)

Deshmukh, A.; Samal, A.; Singh, R.

2017-12-01

Classification of catchments based on various measures of similarity has emerged as an important technique to understand regional scale hydrologic behavior. Classification of catchment characteristics and/or streamflow response has been used reveal which characteristics are more likely to explain the observed variability of hydrologic response. However, numerous algorithms for supervised or unsupervised classification are available, making it hard to identify the algorithm most suitable for the dataset at hand. Consequently, existing catchment classification studies vary significantly in the classification algorithms employed with no previous attempt at understanding the degree of uncertainty in classification due to this algorithmic choice. This hinders the generalizability of interpretations related to hydrologic behavior. Our goal is to develop a protocol that can be followed while classifying hydrologic datasets. We focus on a classification framework for unsupervised classification and provide a step-by-step classification procedure. The steps include testing the clusterabiltiy of original dataset prior to classification, feature selection, validation of clustered data, and quantification of similarity of two clusterings. We test several commonly available methods within this framework to understand the level of similarity of classification results across algorithms. We apply the proposed framework on recently developed datasets for India to analyze to what extent catchment properties can explain observed catchment response. Our testing dataset includes watershed characteristics for over 200 watersheds which comprise of both natural (physio-climatic) characteristics and socio-economic characteristics. This framework allows us to understand the controls on observed hydrologic variability across India.

Prostatitis: myths and realities.

PubMed

Nickel, J C

1998-03-01

To explore the myths surrounding the enigmatic syndrome that the urologic community has labeled as prostatitis and to determine the actual realities associated with this disease. A critical evaluation of the syndrome of prostatitis based on examination of the recent world literature, undisputed scientific facts, solid hypotheses, common sense, and the author's personal opinion. The most common myths surrounding the importance, etiology, diagnosis, classification, and treatment of prostatitis are in fact merely myths. Recent research has led to a new awareness of the importance of prostatitis, new insights into its pathogenesis, improved disease classification and symptom assessment, and will ultimately lead to more rational diagnostic and treatment strategies. The introduction of a new more rational classification system, the development and validation of reliable symptom assessment instruments, new funding initiatives by granting agencies and the pharmaceutical industry, and an awakening appeal for intellectual examination of this common prostate disease by academic urologists guarantees that prostatitis will find an important place on the urologic agenda as we enter the next millennium.

Space-Time Variability in River Flow Regimes of Northeast Turkey

NASA Astrophysics Data System (ADS)

Saris, F.; Hannah, D. M.; Eastwood, W. J.

2011-12-01

The northeast region of Turkey is characterised by relatively high annual precipitation totals and river flow. It is a mountainous region with high ecological status and also it is of prime interest to the energy sector. These characteristics make this region an important area for a hydroclimatology research in terms of future availability and management of water resources. However, there is not any previous research identifying hydroclimatological variability across the region. This study provides first comprehensive and detailed information on river flow regimes of northeast Turkey which is delimited by two major river basins namely East Black Sea (EBS) and Çoruh River (ÇRB) basins. A novel river flow classification is used that yields a large-scale perspective on hydroclimatology patterns of the region and allows interpretations regarding the controlling factors on river flow variability. River flow regimes are classified (with respect to timing and magnitude of flow) to examine spatial variability based on long-term average regimes, and also by grouping annual regimes for each station-year to identify temporal (between-year) variability. Results indicate that rivers in northeast Turkey are characterised by marked seasonal flow variation with an April-May-June maximum flow period. Spatial variability in flow regime seasonality is dependent largely on the topography of the study area. The EBS Basin, for which the North Anatolian Mountains cover the eastern part, is characterised by a May-June peak; whereas the ÇRB is defined by an April-May flow peak. The timing of river flows indicates that snowmelt is an important process and contributor of river flow maxima for both basins. The low flow season is January and February. Intermediate and low regime magnitude classes dominate in ÇRB and EBS basins, respectively, while high flow magnitude class is observed for one station only across the region. Result of regime stability analysis (year-to-year variation) shows that April-May and May-June peak shape classes together with low and intermediate magnitude classes are the most frequent and persistent flow regimes. This research has advanced understanding of hydroclimatological processes in northeast Turkey by identifying river flow regimes and together with explanations regarding the controlling factors on river flow variability.

Benthic nutrient fluxes and sediment oxygen consumption in a full-scale facultative pond in Patagonia, Argentina.

PubMed

Faleschini, M; Esteves, J L

2013-01-01

The study of benthic metabolism is an interesting tool to understand the process that occurs in bottom water at wastewater stabilization ponds. Here, rates of benthic oxygen consumption and nutrient exchange across the water-sludge interface were measured in situ using a benthic chamber. The research was carried out during autumn, winter, and summer at a municipal facultative stabilization pond working in a temperate region (Puerto Madryn city, Argentina). Both a site near the raw wastewater inlet (Inlet station) and a site near the outlet (Outlet station) were sampled. Important seasonal and spatial patterns were identified as being related to benthic fluxes. Ammonium release ranged from undetectable (autumn/summer - Inlet station) to +30.7 kg-NH4(+) ha(-1) d(-1) (autumn - Outlet station), denitrification ranged from undetectable (winter - in both sites) to -4.0 kg-NO3(-) ha(-1) d(-1) (autumn - Outlet station), and oxygen consumption ranged from 0.07 kg-O2ha(-1) d(-1) (autumn/summer - Outlet station) to 0.84 kg-O2ha(-1) d(-1) (autumn - Inlet station). During the warmer months, the mineralization of organic matter from the bottom pond acts as a source of nutrients, which seem to support the important development of phytoplankton and nitrification activity recorded in the surface water. Bottom processes could be related to the advanced degree and efficiency of the treatment, the temperature, and probably the strong and frequent wind present in the region.

Recycling of electrical motors by automatic disassembly

NASA Astrophysics Data System (ADS)

Karlsson, Björn; Järrhed, Jan-Ove

2000-04-01

This paper presents a robotized workstation for end-of-life treatment of electrical motors with an electrical effect of about 1 kW. These motors can, for example, be found in washing machines and in industry. There are two main steps in the work. The first step is an inspection whereby the functionality of the motor is checked and classification either for re-use or for disassembly is done. In the second step the motors classified for disassembly are disassembled in a robotized automatic station. In the initial step measurements are performed during a start-up sequence of about 1 s. By measuring the rotation speed and the current and voltage of the three phases of the motor classification for either reuse or disassembly can be done. During the disassembly work, vision data are fused in order to classify the motors according to their type. The vision system also feeds the control system of the robot with various object co-ordinates, to facilitate correct operation of the robot. Finally, tests with a vision system and eddy-current equipment are performed to decide whether all copper has been removed from the stator.

An automated cirrus classification

NASA Astrophysics Data System (ADS)

Gryspeerdt, Edward; Quaas, Johannes; Sourdeval, Odran; Goren, Tom

2017-04-01

Cirrus clouds play an important role in determining the radiation budget of the earth, but our understanding of the lifecycle and controls on cirrus clouds remains incomplete. Cirrus clouds can have very different properties and development depending on their environment, particularly during their formation. However, the relevant factors often cannot be distinguished using commonly retrieved satellite data products (such as cloud optical depth). In particular, the initial cloud phase has been identified as an important factor in cloud development, but although back-trajectory based methods can provide information on the initial cloud phase, they are computationally expensive and depend on the cloud parametrisations used in re-analysis products. In this work, a classification system (Identification and Classification of Cirrus, IC-CIR) is introduced. Using re-analysis and satellite data, cirrus clouds are separated in four main types: frontal, convective, orographic and in-situ. The properties of these classes show that this classification is able to provide useful information on the properties and initial phase of cirrus clouds, information that could not be provided by instantaneous satellite retrieved cloud properties alone. This classification is designed to be easily implemented in global climate models, helping to improve future comparisons between observations and models and reducing the uncertainty in cirrus clouds properties, leading to improved cloud parametrisations.

Classification of involuntary movements in dogs: Tremors and twitches.

PubMed

Lowrie, Mark; Garosi, Laurent

2016-08-01

This review focuses on important new findings in the field of involuntary movements (IM) in dogs and illustrates the importance of developing a clear classification tool for diagnosing tremor and twitches. Developments over the last decade have changed our understanding of IM and highlight several caveats in the current tremor classification. Given the ambiguous association between tremor phenomenology and tremor aetiology, a more cautious definition of tremors based on clinical assessment is required. An algorithm for the characterisation of tremors is presented herein. The classification of tremors is based on the distinction between tremors that occur at rest and tremors that are action-related; tremors associated with action are divided into postural or kinetic. Controversial issues are outlined and thus reflect the open questions that are yet to be answered from an evidence base of peer-reviewed published literature. Peripheral nerve hyper-excitability (PNH; cramps and twitches) may manifest as fasciculations, myokymia, neuromyotonia, cramps, tetany and tetanus. It is anticipated that as we learn more about the aetiology and pathogenesis of IMs, future revisions to the classification will be needed. It is therefore the intent of this work to stimulate discussions and thus contribute to the development of IM research. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

International Space Station (ISS)

NASA Image and Video Library

2001-03-01

Backdropped against water and clouds, the International Space Station was separated from the Space Shuttle Discovery after several days of joint activities and an important crew exchange. This photograph was taken by one of the crew of this mission from the aft flight deck of Discovery.

LOCATING MONITORING STATIONS IN WATER DISTRIBUTION SYSTEMS

EPA Science Inventory

Water undergoes changes in quality between the time it leaves the treatment plant and the time it reaches the customer's tap, making it important to select monitoring stations that will adequately monitor these changers. But because there is no uniform schedule or framework for ...

Brain tumor segmentation based on local independent projection-based classification.

PubMed

Huang, Meiyan; Yang, Wei; Wu, Yao; Jiang, Jun; Chen, Wufan; Feng, Qianjin

2014-10-01

Brain tumor segmentation is an important procedure for early tumor diagnosis and radiotherapy planning. Although numerous brain tumor segmentation methods have been presented, enhancing tumor segmentation methods is still challenging because brain tumor MRI images exhibit complex characteristics, such as high diversity in tumor appearance and ambiguous tumor boundaries. To address this problem, we propose a novel automatic tumor segmentation method for MRI images. This method treats tumor segmentation as a classification problem. Additionally, the local independent projection-based classification (LIPC) method is used to classify each voxel into different classes. A novel classification framework is derived by introducing the local independent projection into the classical classification model. Locality is important in the calculation of local independent projections for LIPC. Locality is also considered in determining whether local anchor embedding is more applicable in solving linear projection weights compared with other coding methods. Moreover, LIPC considers the data distribution of different classes by learning a softmax regression model, which can further improve classification performance. In this study, 80 brain tumor MRI images with ground truth data are used as training data and 40 images without ground truth data are used as testing data. The segmentation results of testing data are evaluated by an online evaluation tool. The average dice similarities of the proposed method for segmenting complete tumor, tumor core, and contrast-enhancing tumor on real patient data are 0.84, 0.685, and 0.585, respectively. These results are comparable to other state-of-the-art methods.

Typecasting catchments: Classification, directionality, and the pursuit of universality

NASA Astrophysics Data System (ADS)

Smith, Tyler; Marshall, Lucy; McGlynn, Brian

2018-02-01

Catchment classification poses a significant challenge to hydrology and hydrologic modeling, restricting widespread transfer of knowledge from well-studied sites. The identification of important physical, climatological, or hydrologic attributes (to varying degrees depending on application/data availability) has traditionally been the focus for catchment classification. Classification approaches are regularly assessed with regard to their ability to provide suitable hydrologic predictions - commonly by transferring fitted hydrologic parameters at a data-rich catchment to a data-poor catchment deemed similar by the classification. While such approaches to hydrology's grand challenges are intuitive, they often ignore the most uncertain aspect of the process - the model itself. We explore catchment classification and parameter transferability and the concept of universal donor/acceptor catchments. We identify the implications of the assumption that the transfer of parameters between "similar" catchments is reciprocal (i.e., non-directional). These concepts are considered through three case studies situated across multiple gradients that include model complexity, process description, and site characteristics. Case study results highlight that some catchments are more successfully used as donor catchments and others are better suited as acceptor catchments. These results were observed for both black-box and process consistent hydrologic models, as well as for differing levels of catchment similarity. Therefore, we suggest that similarity does not adequately satisfy the underlying assumptions being made in parameter regionalization approaches regardless of model appropriateness. Furthermore, we suggest that the directionality of parameter transfer is an important factor in determining the success of parameter regionalization approaches.

ATS-F ground station integration

NASA Technical Reports Server (NTRS)

1975-01-01

The ATS ground stations were described, including a system description, operational frequencies and bandwidth, and a discussion of individual subsystems. Each station configuration is described as well as its floor plan. The station performance, as tested by the GSI, is displayed in chart form providing a summary of the more important parameters tested. This chart provides a listing of test data, by site, for comparison purposes. Also included is a description of the ATS-6 experiments, the equipment, and interfaces required to perform these experiments. The ADP subsystem and its role in the experiments is also described. A description of each program task and a summary of the activities performed were then given. These efforts were accomplished at the Rosman II Ground Station, located near Rosman N.C., the Mojave Ground Station, located near Barstow Ca., and the GSI Contractors plant located near Baltimore, Md.

Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

PubMed

Yang, Xiaoyan; Chen, Longgao; Li, Yingkui; Xi, Wenjia; Chen, Longqian

2015-07-01

Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

In-vivo determination of chewing patterns using FBG and artificial neural networks

NASA Astrophysics Data System (ADS)

Pegorini, Vinicius; Zen Karam, Leandro; Rocha Pitta, Christiano S.; Ribeiro, Richardson; Simioni Assmann, Tangriani; Cardozo da Silva, Jean Carlos; Bertotti, Fábio L.; Kalinowski, Hypolito J.; Cardoso, Rafael

2015-09-01

This paper reports the process of pattern classification of the chewing process of ruminants. We propose a simplified signal processing scheme for optical fiber Bragg grating (FBG) sensors based on machine learning techniques. The FBG sensors measure the biomechanical forces during jaw movements and an artificial neural network is responsible for the classification of the associated chewing pattern. In this study, three patterns associated to dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior studies were monitored, rumination and idle period. Experimental results show that the proposed approach for pattern classification has been capable of differentiating the materials involved in the chewing process with a small classification error.

[Current situation of toxicity classification of Chinese materia medica and its research thoughts].

PubMed

Sun, Wenyan; Hou, Xiujuan; Wang, Bin; Zhu, Yuelan; Zhang, Shuofeng; Chang, Hongsheng; Sun, Jianning

2012-08-01

Toxicity of Chinese materia medica (CMM) is an important part of Chinese herbal nature theory. In clinical application, the dosage, time limitation and compatibility of CMM is mainly determined by toxicity. At present, there is no uniform toxicity classification standard for the evaluation of Chinese herbal toxicity. Therefore, it is significant to research toxicity classification of CMM. The current situation of toxicity classification of CMM is reviewed in this paper, and proposed research thoughts are as follows: the measurement of toxicity parameters, the confirmation of poisoning target organs, the investigation on toxic mechanism by serum pharmacology and toxicokinetics, the comprehensive evaluation on toxicity based on quantitative theory.

Categorization in the wild.

PubMed

Glushko, Robert J; Maglio, Paul P; Matlock, Teenie; Barsalou, Lawrence W

2008-04-01

In studying categorization, cognitive science has focused primarily on cultural categorization, ignoring individual and institutional categorization. Because recent technological developments have made individual and institutional classification systems much more available and powerful, our understanding of the cognitive and social mechanisms that produce these systems is increasingly important. Furthermore, key aspects of categorization that have received little previous attention emerge from considering diverse types of categorization together, such as the social factors that create stability in classification systems, and the interoperability that shared conceptual systems establish between agents. Finally, the profound impact of recent technological developments on classification systems indicates that basic categorization mechanisms are highly adaptive, producing new classification systems as the situations in which they operate change.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

Bayesian Network Structure Learning for Urban Land Use Classification from Landsat ETM+ and Ancillary Data

NASA Astrophysics Data System (ADS)

Park, M.; Stenstrom, M. K.

2004-12-01

Recognizing urban information from the satellite imagery is problematic due to the diverse features and dynamic changes of urban landuse. The use of Landsat imagery for urban land use classification involves inherent uncertainty due to its spatial resolution and the low separability among land uses. To resolve the uncertainty problem, we investigated the performance of Bayesian networks to classify urban land use since Bayesian networks provide a quantitative way of handling uncertainty and have been successfully used in many areas. In this study, we developed the optimized networks for urban land use classification from Landsat ETM+ images of Marina del Rey area based on USGS land cover/use classification level III. The networks started from a tree structure based on mutual information between variables and added the links to improve accuracy. This methodology offers several advantages: (1) The network structure shows the dependency relationships between variables. The class node value can be predicted even with particular band information missing due to sensor system error. The missing information can be inferred from other dependent bands. (2) The network structure provides information of variables that are important for the classification, which is not available from conventional classification methods such as neural networks and maximum likelihood classification. In our case, for example, bands 1, 5 and 6 are the most important inputs in determining the land use of each pixel. (3) The networks can be reduced with those input variables important for classification. This minimizes the problem without considering all possible variables. We also examined the effect of incorporating ancillary data: geospatial information such as X and Y coordinate values of each pixel and DEM data, and vegetation indices such as NDVI and Tasseled Cap transformation. The results showed that the locational information improved overall accuracy (81%) and kappa coefficient (76%), and lowered the omission and commission errors compared with using only spectral data (accuracy 71%, kappa coefficient 62%). Incorporating DEM data did not significantly improve overall accuracy (74%) and kappa coefficient (66%) but lowered the omission and commission errors. Incorporating NDVI did not much improve the overall accuracy (72%) and k coefficient (65%). Including Tasseled Cap transformation reduced the accuracy (accuracy 70%, kappa 61%). Therefore, additional information from the DEM and vegetation indices was not useful as locational ancillary data.

Cholangiocarcinoma: classification, diagnosis, staging, imaging features, and management.

PubMed

Oliveira, Irai S; Kilcoyne, Aoife; Everett, Jamie M; Mino-Kenudson, Mari; Harisinghani, Mukesh G; Ganesan, Karthik

2017-06-01

Cholangiocarcinoma is a relatively uncommon malignant neoplasm with poor prognosis. The distinction between extrahepatic and intrahepatic subtypes is important as epidemiological features, biologic and pathologic characteristics, and clinical course are different for both entities. This review study focuses on the role imaging plays in the diagnosis, classification, staging, and post-treatment assessment of cholangiocarcinoma.

Classification of cryocoolers

NASA Technical Reports Server (NTRS)

Walker, G.

1985-01-01

A great diversity of methods and mechanisms were devised to effect cryogenic refrigeration. The basic parameters and considerations affecting the selection of a particular system are reviewed. A classification scheme for mechanical cryocoolers is presented. An important distinguishing feature is the incorporation or not of a regenerative heat exchanger, of valves, and of the method for achieving a pressure variation.

Forest site classification for cultural plant harvest by tribal weavers can inform management

Treesearch

S. Hummel; F.K. Lake

2015-01-01

Do qualitative classifications of ecological conditions for harvesting culturally important forest plants correspond to quantitative differences among sites? To address this question, we blended scientific methods (SEK) and traditional ecological knowledge (TEK) to identify conditions on sites considered good, marginal, or poor for harvesting the leaves of a plant (...

Machine Learning Classification Combining Multiple Features of A Hyper-Network of fMRI Data in Alzheimer's Disease

PubMed Central

Guo, Hao; Zhang, Fan; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

Exploring functional interactions among various brain regions is helpful for understanding the pathological underpinnings of neurological disorders. Brain networks provide an important representation of those functional interactions, and thus are widely applied in the diagnosis and classification of neurodegenerative diseases. Many mental disorders involve a sharp decline in cognitive ability as a major symptom, which can be caused by abnormal connectivity patterns among several brain regions. However, conventional functional connectivity networks are usually constructed based on pairwise correlations among different brain regions. This approach ignores higher-order relationships, and cannot effectively characterize the high-order interactions of many brain regions working together. Recent neuroscience research suggests that higher-order relationships between brain regions are important for brain network analysis. Hyper-networks have been proposed that can effectively represent the interactions among brain regions. However, this method extracts the local properties of brain regions as features, but ignores the global topology information, which affects the evaluation of network topology and reduces the performance of the classifier. This problem can be compensated by a subgraph feature-based method, but it is not sensitive to change in a single brain region. Considering that both of these feature extraction methods result in the loss of information, we propose a novel machine learning classification method that combines multiple features of a hyper-network based on functional magnetic resonance imaging in Alzheimer's disease. The method combines the brain region features and subgraph features, and then uses a multi-kernel SVM for classification. This retains not only the global topological information, but also the sensitivity to change in a single brain region. To certify the proposed method, 28 normal control subjects and 38 Alzheimer's disease patients were selected to participate in an experiment. The proposed method achieved satisfactory classification accuracy, with an average of 91.60%. The abnormal brain regions included the bilateral precuneus, right parahippocampal gyrus\\hippocampus, right posterior cingulate gyrus, and other regions that are known to be important in Alzheimer's disease. Machine learning classification combining multiple features of a hyper-network of functional magnetic resonance imaging data in Alzheimer's disease obtains better classification performance. PMID:29209156

Screening tests for hazard classification of complex waste materials - Selection of methods

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

Weltens, R., E-mail: reinhilde.weltens@vito.be; Vanermen, G.; Tirez, K.

In this study we describe the development of an alternative methodology for hazard characterization of waste materials. Such an alternative methodology for hazard assessment of complex waste materials is urgently needed, because the lack of a validated instrument leads to arbitrary hazard classification of such complex waste materials. False classification can lead to human and environmental health risks and also has important financial consequences for the waste owner. The Hazardous Waste Directive (HWD) describes the methodology for hazard classification of waste materials. For mirror entries the HWD classification is based upon the hazardous properties (H1-15) of the waste which canmore » be assessed from the hazardous properties of individual identified waste compounds or - if not all compounds are identified - from test results of hazard assessment tests performed on the waste material itself. For the latter the HWD recommends toxicity tests that were initially designed for risk assessment of chemicals in consumer products (pharmaceuticals, cosmetics, biocides, food, etc.). These tests (often using mammals) are not designed nor suitable for the hazard characterization of waste materials. With the present study we want to contribute to the development of an alternative and transparent test strategy for hazard assessment of complex wastes that is in line with the HWD principles for waste classification. It is necessary to cope with this important shortcoming in hazardous waste classification and to demonstrate that alternative methods are available that can be used for hazard assessment of waste materials. Next, by describing the pros and cons of the available methods, and by identifying the needs for additional or further development of test methods, we hope to stimulate research efforts and development in this direction. In this paper we describe promising techniques and argument on the test selection for the pilot study that we have performed on different types of waste materials. Test results are presented in a second paper. As the application of many of the proposed test methods is new in the field of waste management, the principles of the tests are described. The selected tests tackle important hazardous properties but refinement of the test battery is needed to fulfil the a priori conditions.« less

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems.

PubMed

Oh, Sang-Il; Kang, Hang-Bong

2017-01-22

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226 × 370 image, whereas the original selective search method extracted approximately 10 6 × n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset.

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226×370 image, whereas the original selective search method extracted approximately 106×n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset. PMID:28117742

An assessment of the effectiveness of a random forest classifier for land-cover classification

NASA Astrophysics Data System (ADS)

Rodriguez-Galiano, V. F.; Ghimire, B.; Rogan, J.; Chica-Olmo, M.; Rigol-Sanchez, J. P.

2012-01-01

Land cover monitoring using remotely sensed data requires robust classification methods which allow for the accurate mapping of complex land cover and land use categories. Random forest (RF) is a powerful machine learning classifier that is relatively unknown in land remote sensing and has not been evaluated thoroughly by the remote sensing community compared to more conventional pattern recognition techniques. Key advantages of RF include: their non-parametric nature; high classification accuracy; and capability to determine variable importance. However, the split rules for classification are unknown, therefore RF can be considered to be black box type classifier. RF provides an algorithm for estimating missing values; and flexibility to perform several types of data analysis, including regression, classification, survival analysis, and unsupervised learning. In this paper, the performance of the RF classifier for land cover classification of a complex area is explored. Evaluation was based on several criteria: mapping accuracy, sensitivity to data set size and noise. Landsat-5 Thematic Mapper data captured in European spring and summer were used with auxiliary variables derived from a digital terrain model to classify 14 different land categories in the south of Spain. Results show that the RF algorithm yields accurate land cover classifications, with 92% overall accuracy and a Kappa index of 0.92. RF is robust to training data reduction and noise because significant differences in kappa values were only observed for data reduction and noise addition values greater than 50 and 20%, respectively. Additionally, variables that RF identified as most important for classifying land cover coincided with expectations. A McNemar test indicates an overall better performance of the random forest model over a single decision tree at the 0.00001 significance level.

Gender classification from face images by using local binary pattern and gray-level co-occurrence matrix

NASA Astrophysics Data System (ADS)

Uzbaş, Betül; Arslan, Ahmet

2018-04-01

Gender is an important step for human computer interactive processes and identification. Human face image is one of the important sources to determine gender. In the present study, gender classification is performed automatically from facial images. In order to classify gender, we propose a combination of features that have been extracted face, eye and lip regions by using a hybrid method of Local Binary Pattern and Gray-Level Co-Occurrence Matrix. The features have been extracted from automatically obtained face, eye and lip regions. All of the extracted features have been combined and given as input parameters to classification methods (Support Vector Machine, Artificial Neural Networks, Naive Bayes and k-Nearest Neighbor methods) for gender classification. The Nottingham Scan face database that consists of the frontal face images of 100 people (50 male and 50 female) is used for this purpose. As the result of the experimental studies, the highest success rate has been achieved as 98% by using Support Vector Machine. The experimental results illustrate the efficacy of our proposed method.

Classifying machinery condition using oil samples and binary logistic regression

NASA Astrophysics Data System (ADS)

Phillips, J.; Cripps, E.; Lau, John W.; Hodkiewicz, M. R.

2015-08-01

The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines.

A Partial Least Squares Based Procedure for Upstream Sequence Classification in Prokaryotes.

PubMed

Mehmood, Tahir; Bohlin, Jon; Snipen, Lars

2015-01-01

The upstream region of coding genes is important for several reasons, for instance locating transcription factor, binding sites, and start site initiation in genomic DNA. Motivated by a recently conducted study, where multivariate approach was successfully applied to coding sequence modeling, we have introduced a partial least squares (PLS) based procedure for the classification of true upstream prokaryotic sequence from background upstream sequence. The upstream sequences of conserved coding genes over genomes were considered in analysis, where conserved coding genes were found by using pan-genomics concept for each considered prokaryotic species. PLS uses position specific scoring matrix (PSSM) to study the characteristics of upstream region. Results obtained by PLS based method were compared with Gini importance of random forest (RF) and support vector machine (SVM), which is much used method for sequence classification. The upstream sequence classification performance was evaluated by using cross validation, and suggested approach identifies prokaryotic upstream region significantly better to RF (p-value < 0.01) and SVM (p-value < 0.01). Further, the proposed method also produced results that concurred with known biological characteristics of the upstream region.

Call-related factors influencing output power from mobile phones.

PubMed

Hillert, Lena; Ahlbom, Anders; Neasham, David; Feychting, Maria; Järup, Lars; Navin, Roshan; Elliott, Paul

2006-11-01

Mobile phone use is increasing but there is also concern for adverse health effects. Well-designed prospective studies to assess several health outcomes are required. In designing a study of mobile phone use, it is important to assess which factors need to be considered in classifying the exposure to radiofrequency fields (RF). A pilot study was performed in Sweden and in the UK 2002 to 2003 to test the feasibility of recruiting a cohort of mobile phone users from a random population sample and from mobile phone subscription lists for a prospective study. As one part of this pilot study, different factors were evaluated regarding possible influence on the output power of the phones. By local switch logging, information on calls made from predefined subscriptions or dedicated handsets were obtained and the output power of phones during calls made indoors and outdoors, in moving and stationary mode, and in rural as well in urban areas were compared. In this experiment, calls were either 1, 1.5 or 5 min long. The results showed that high mobile phone output power is more frequent in rural areas whereas the other factors (length of call, moving/stationary, indoor/outdoor) were of less importance. Urban and rural area should be considered in an exposure index for classification of the exposure to RF from mobile phones and may be assessed by first base station during mobile phone calls or, if this information is not available, possibly by using home address as a proxy.

Real-time Estimation of Fault Rupture Extent for Recent Large Earthquakes

NASA Astrophysics Data System (ADS)

Yamada, M.; Mori, J. J.

2009-12-01

Current earthquake early warning systems assume point source models for the rupture. However, for large earthquakes, the fault rupture length can be of the order of tens to hundreds of kilometers, and the prediction of ground motion at a site requires the approximated knowledge of the rupture geometry. Early warning information based on a point source model may underestimate the ground motion at a site, if a station is close to the fault but distant from the epicenter. We developed an empirical function to classify seismic records into near-source (NS) or far-source (FS) records based on the past strong motion records (Yamada et al., 2007). Here, we defined the near-source region as an area with a fault rupture distance less than 10km. If we have ground motion records at a station, the probability that the station is located in the near-source region is; P = 1/(1+exp(-f)) f = 6.046log10(Za) + 7.885log10(Hv) - 27.091 where Za and Hv denote the peak values of the vertical acceleration and horizontal velocity, respectively. Each observation provides the probability that the station is located in near-source region, so the resolution of the proposed method depends on the station density. The information of the fault rupture location is a group of points where the stations are located. However, for practical purposes, the 2-dimensional configuration of the fault is required to compute the ground motion at a site. In this study, we extend the methodology of NS/FS classification to characterize 2-dimensional fault geometries and apply them to strong motion data observed in recent large earthquakes. We apply a cosine-shaped smoothing function to the probability distribution of near-source stations, and convert the point fault location to 2-dimensional fault information. The estimated rupture geometry for the 2007 Niigata-ken Chuetsu-oki earthquake 10 seconds after the origin time is shown in Figure 1. Furthermore, we illustrate our method with strong motion data of the 2007 Noto-hanto earthquake, 2008 Iwate-Miyagi earthquake, and 2008 Wenchuan earthquake. The on-going rupture extent can be estimated for all datasets as the rupture propagates. For earthquakes with magnitude about 7.0, the determination of the fault parameters converges to the final geometry within 10 seconds.

MESSOC capabilities and results. [Model for Estimating Space Station Opertions Costs

NASA Technical Reports Server (NTRS)

Shishko, Robert

1990-01-01

MESSOC (Model for Estimating Space Station Operations Costs) is the result of a multi-year effort by NASA to understand and model the mature operations cost of Space Station Freedom. This paper focuses on MESSOC's ability to contribute to life-cycle cost analyses through its logistics equations and databases. Together, these afford MESSOC the capability to project not only annual logistics costs for a variety of Space Station scenarios, but critical non-cost logistics results such as annual Station maintenance crewhours, upweight/downweight, and on-orbit sparing availability as well. MESSOC results using current logistics databases and baseline scenario have already shown important implications for on-orbit maintenance approaches, space transportation systems, and international operations cost sharing.

Apollo 15 clastic materials and their relationship to local geologic features

NASA Technical Reports Server (NTRS)

Fruchter, J. S.; Stoeser, J. W.; Lindstrom, M. M.; Goles, G. G.

1973-01-01

Ninety sub-samples of Apollo 15 materials have been analyzed by instrumental neutron activation analysis techniques for as many as 21 elements. Soil and soil breccia compositions show considerable variation from station to station although at any given station the soils and soil breccias were compositionally very similar to one another. Mixing model calculations show that the station-to-station variations can be related to important local geologic features. These features include the Apennine Front, Hadley Rille and the ray from the craters Aristillus or Autolycus. Compositional similarities between soils and soil breccias at the Apollo 15 site indicate that the breccias and soils are related in some fundamental way, although the exact nature of this relationship is not yet fully understood.

Early use of Space Station Freedom for NASA's Microgravity Science and Applications Program

NASA Technical Reports Server (NTRS)

Rhome, Robert C.; O'Malley, Terence F.

1992-01-01

The paper describes microgravity science opportunities inherent to the restructured Space Station and presents a synopsis of the scientific utilization plan for the first two years of ground-tended operations. In the ground-tended utilization mode the Space Station is a large free-flyer providing a continuous microgravity environment unmatched by any other platform within any existing U.S. program. It is pointed out that the importance of this period of early Space Station mixed-mode utilization between crew-tended and ground-tended approaches is of such magnitude that Station-based microgravity science experiments many become benchmarks to the disciplines involved. The traffic model that is currently being pursued is designed to maximize this opportunity for the U.S. microgravity science community.

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps.

PubMed

Jin, Y-H; Kawamura, A; Park, S-C; Nakagawa, N; Amaguchi, H; Olsson, J

2011-10-01

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.

Taxonomic diversity and structure of benthic macroinvertebrates in Aby Lagoon (Ivory Coast, West Africa).

PubMed

Kouadio, K N; Diomandé, D; Ouattara, A; Koné, Y J M; Gourène, G

2008-09-15

The benthic macroinvertebrates of Aby lagoon (West Africa: Ivory coast) was studied during four seasons (high dry season, high rainy season, low dry season and low rainy season, respectively) from June 2006 to March 2007. The distribution of the benthic macroinvertebrates species was recorded at 13 stations on the whole of the lagoon. A total of 62 taxa of benthic macroinvertebrates belonging to 28 families and 10 orders were listed. The molluscs and crustaceans dominate qualitatively by adding up 51 and 24%, respectively of the total number of organisms. Five taxa (Corbula trigona (20%), Pachymelania aurita (12%), Clibernhardius cooki (7%), Oligochaeta (7%) and Crassostrea gasar (6%) accounted for 52% of total abundance. Classification analysis used to perform the characterisation of the lagoon on the basis of benthic macroinvertebrates showed the existence of four main clusters in which the seasonal pattern in benthic macroinvertebrates were very similar in the four seasons. In contrast the species richness and diversity indices were significantly different. Furthermore these indices where higher in the stations closer to the sea and surrounded by mangrove trees (southern area) compared to the inland ones.

Circulation weather types and their influence on precipitation in Serbia

NASA Astrophysics Data System (ADS)

Putniković, Suzana; Tošić, Ivana; Đurđević, Vladimir

2016-10-01

An objective classification scheme of atmospheric circulation, in which daily circulation is determined by the strength, direction, and vorticity of geostrophic flow, has been applied to the atmosphere over Serbia for the time period 1961-2010. The results for the sea level and isobaric level of 500 hPa for winter and summer are presented. The 26 circulation types (eight pure direction, 16 hybrid, cyclonic, and anticyclonic types) are determined and described. Each of the circulation types has a distinct underlying synoptic pattern that produces the expected type and direction of flow over the study area. The relative frequencies of the circulation types, and the relationship between the precipitation and circulation types at three stations on a seasonal time scale are analyzed. The anticyclonic weather type dominates in winter (18.93 %) and summer (18.70 %), followed by the northeasterly type (16.65 %) in summer, and the cyclonic type (12.83 %) in winter. The cyclonic types (C and hybrid) have a higher than average probability of rain at all stations. Conversely, the anticyclonic types are associated with a lower than average probability and intensity of rainfall.

Cyanobacterial Diversity in Biological Soil Crusts along a Precipitation Gradient, Northwest Negev Desert, Israel.

PubMed

Hagemann, Martin; Henneberg, Manja; Felde, Vincent J M N L; Drahorad, Sylvie L; Berkowicz, Simon M; Felix-Henningsen, Peter; Kaplan, Aaron

2015-07-01

Cyanobacteria occur worldwide but play an important role in the formation and primary activity of biological soil crusts (BSCs) in arid and semi-arid ecosystems. The cyanobacterial diversity in BSCs of the northwest Negev desert of Israel was surveyed at three fixed sampling stations situated along a precipitation gradient in the years 2010 to 2012. The three stations also are characterized by marked differences in soil features such as soil carbon, nitrogen, or electrical conductivity. The cyanobacterial biodiversity was analyzed by sequencing inserts of clone libraries harboring partial 16S rRNA gene sequences obtained with cyanobacteria-specific primers. Filamentous, non-diazotrophic strains (subsection III), particularly Microcoleus-like, dominated the cyanobacterial community (30% proportion) in all years. Specific cyanobacterial groups showed increased (e.g., Chroococcidiopsis, Leptolyngbya, and Nostoc strains) or decreased (e.g., unicellular strains belonging to the subsection I and Scytonema strains) abundances with declining water availability at the most arid, southern station, whereas many cyanobacterial strains were frequently found in the soils of all three stations. The cyanobacterial diversity at the three sampling stations appears dependent on the available precipitation, whereas the differences in soil chemistry were of lower importance.

Space-to-Ground: Teacher On Board: 10/20/2017

NASA Image and Video Library

2017-10-20

The crew completed their third and final spacewalk for the month...We kicked off a year of education on station...and we talk about the importance of astronaut photography. Space to Ground is your weekly update on what's happening aboard the International Space Station.

Chinese Sentence Classification Based on Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Gu, Chengwei; Wu, Ming; Zhang, Chuang

2017-10-01

Sentence classification is one of the significant issues in Natural Language Processing (NLP). Feature extraction is often regarded as the key point for natural language processing. Traditional ways based on machine learning can not take high level features into consideration, such as Naive Bayesian Model. The neural network for sentence classification can make use of contextual information to achieve greater results in sentence classification tasks. In this paper, we focus on classifying Chinese sentences. And the most important is that we post a novel architecture of Convolutional Neural Network (CNN) to apply on Chinese sentence classification. In particular, most of the previous methods often use softmax classifier for prediction, we embed a linear support vector machine to substitute softmax in the deep neural network model, minimizing a margin-based loss to get a better result. And we use tanh as an activation function, instead of ReLU. The CNN model improve the result of Chinese sentence classification tasks. Experimental results on the Chinese news title database validate the effectiveness of our model.

Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in Slovenia.

PubMed

Selih, Vid S; Sala, Martin; Drgan, Viktor

2014-06-15

Inductively coupled plasma mass spectrometry and optical emission were used to determine the multi-element composition of 272 bottled Slovenian wines. To achieve geographical classification of the wines by their elemental composition, principal component analysis (PCA) and counter-propagation artificial neural networks (CPANN) have been used. From 49 elements measured, 19 were used to build the final classification models. CPANN was used for the final predictions because of its superior results. The best model gave 82% correct predictions for external set of the white wine samples. Taking into account the small size of whole Slovenian wine growing regions, we consider the classification results were very good. For the red wines, which were mostly represented from one region, even-sub region classification was possible with great precision. From the level maps of the CPANN model, some of the most important elements for classification were identified. Copyright © 2013 Elsevier Ltd. All rights reserved.

Classification of hepatocellular carcinoma stages from free-text clinical and radiology reports

PubMed Central

Yim, Wen-wai; Kwan, Sharon W; Johnson, Guy; Yetisgen, Meliha

2017-01-01

Cancer stage information is important for clinical research. However, they are not always explicitly noted in electronic medical records. In this paper, we present our work on automatic classification of hepatocellular carcinoma (HCC) stages from free-text clinical and radiology notes. To accomplish this, we defined 11 stage parameters used in the three HCC staging systems, American Joint Committee on Cancer (AJCC), Barcelona Clinic Liver Cancer (BCLC), and Cancer of the Liver Italian Program (CLIP). After aggregating stage parameters to the patient-level, the final stage classifications were achieved using an expert-created decision logic. Each stage parameter relevant for staging was extracted using several classification methods, e.g. sentence classification and automatic information structuring, to identify and normalize text as cancer stage parameter values. Stage parameter extraction for the test set performed at 0.81 F1. Cancer stage prediction for AJCC, BCLC, and CLIP stage classifications were 0.55, 0.50, and 0.43 F1.

Classification of childhood epilepsies in a tertiary pediatric neurology clinic using a customized classification scheme from the international league against epilepsy 2010 report.

PubMed

Khoo, Teik-Beng

2013-01-01

In its 2010 report, the International League Against Epilepsy Commission on Classification and Terminology had made a number of changes to the organization, terminology, and classification of seizures and epilepsies. This study aims to test the usefulness of this revised classification scheme on children with epilepsies aged between 0 and 18 years old. Of 527 patients, 75.1% only had 1 type of seizure and the commonest was focal seizure (61.9%). A specific electroclinical syndrome diagnosis could be made in 27.5%. Only 2.1% had a distinctive constellation. In this cohort, 46.9% had an underlying structural, metabolic, or genetic etiology. Among the important causes were pre-/perinatal insults, malformation of cortical development, intracranial infections, and neurocutaneous syndromes. However, 23.5% of the patients in our cohort were classified as having "epilepsies of unknown cause." The revised classification scheme is generally useful for pediatric patients. To make it more inclusive and clinically meaningful, some local customizations are required.

The Role of Facial Attractiveness and Facial Masculinity/Femininity in Sex Classification of Faces

PubMed Central

Hoss, Rebecca A.; Ramsey, Jennifer L.; Griffin, Angela M.; Langlois, Judith H.

2005-01-01

We tested whether adults (Experiment 1) and 4–5-year-old children (Experiment 2) identify the sex of high attractive faces faster and more accurately than low attractive faces in a reaction time task. We also assessed whether facial masculinity/femininity facilitated identification of sex. Results showed that attractiveness facilitated adults’ sex classification of both female and male faces and children’s sex classification of female, but not male, faces. Moreover, attractiveness affected the speed and accuracy of sex classification independent of masculinity/femininity. High masculinity in male faces, but not high femininity in female faces, also facilitated sex classification for both adults and children. These findings provide important new data on how the facial cues of attractiveness and masculinity/femininity contribute to the task of sex classification and provide evidence for developmental differences in how adults and children use these cues. Additionally, these findings provide support for Langlois and Roggman’s (1990) averageness theory of attractiveness. PMID:16457167

The Effect of Normalization in Violence Video Classification Performance

NASA Astrophysics Data System (ADS)

Ali, Ashikin; Senan, Norhalina

2017-08-01

Basically, data pre-processing is an important part of data mining. Normalization is a pre-processing stage for any type of problem statement, especially in video classification. Challenging problems that arises in video classification is because of the heterogeneous content, large variations in video quality and complex semantic meanings of the concepts involved. Therefore, to regularize this problem, it is thoughtful to ensure normalization or basically involvement of thorough pre-processing stage aids the robustness of classification performance. This process is to scale all the numeric variables into certain range to make it more meaningful for further phases in available data mining techniques. Thus, this paper attempts to examine the effect of 2 normalization techniques namely Min-max normalization and Z-score in violence video classifications towards the performance of classification rate using Multi-layer perceptron (MLP) classifier. Using Min-Max Normalization range of [0,1] the result shows almost 98% of accuracy, meanwhile Min-Max Normalization range of [-1,1] accuracy is 59% and for Z-score the accuracy is 50%.

Measuring market share of petrol stations using conditional probability approach

NASA Astrophysics Data System (ADS)

Sharif, Shamshuritawati; Lwee, Xue Yin

2017-05-01

Oil and gas production is the strength of Malaysia's growth over past decades. It is one of the most strategic economic branches in the world. Since the oil industry is essential for the economic growth of a country, only a few undertakings have been achieved to establish. It is a very risky business. Therefore the dealer must have some information in hand before setting up a new business plan. Understanding the current business situation is an important strategy to avoid risky ventures. In this study, the aim is to deliver a very simple but essential way to identify the market share based on customer's choice factors. This approach is presented to encourage the non-statisticians to use it easily in helping their business performance. From this study, the most important factors differ from one station to another station. The results show that the factors of customer's choice for BHPetrol, Caltex, PETRON, PETRONAS and SHELL are site location, service quality, service quality, size of the petrol station, and brand image, respectively.

Species composition, distribution and abundance of chaetodontidae along reef transects in the Flores Sea

NASA Astrophysics Data System (ADS)

Adrim, Mohammad; Hutomo, Malikusworo

Observations on chaetodontid fishes were made by applying a visual census technique at 13 coral reef locations in the Flores Sea region in October and November 1984. These observations were made along 50 m transect lines, parallel to the shore or the reef edge at depths between 3 to 12 m. Twenty-three species of Chaetodontidae were observed, representing three genera: Chaetodon (20 species), Heniochus (2 species) and Forcipiger (1 species). Chaetodon kleini, C. trifasciatus, C. melannotus and C. baronessa proved to be the most abundant species, and among them C. kleini and C. trifasciatus were the most widely distributed ones. Chaetodon semeion and C. mertensi were the rarest species. The greatest number of individuals (77) was counted at station 4.268 near Tanjung Burung, Sumbawa, while the greatest number of species (14) was observed at station 4.257, north of Komodo. The lowest number of individuals (17) was counted at station 4.175 near P. Bahuluang, Salayer, while station 4.251 near Teluk Slawi, Komodo, was inhabited by the smallest numbver of species (2). Numerical classification by using the Bray Curtis dissimilarity index resulted in three groups of entities. The first group was characterized by predomination of C. kleini and the second by predomination of C. melannotus. The third one was a loose group not characterized by any predominant species. The analyses indicated that the similarities of the chaetodontid communities between locations are not related to the distance between them, but rather to habitat conditions. For example predomination of C. melannotus is strongly related to the predomination of soft coral. Compared to other areas of Indonesia, e.g. Bali, Seribu Islands, Batam, Sunda Strait, and Ambon Bay, the Flores Sea reefs have a more abundant and more diverse chaetodontid fauna.

Cluster Analysis of Velocity Field Derived from Dense GNSS Network of Japan

NASA Astrophysics Data System (ADS)

Takahashi, A.; Hashimoto, M.

2015-12-01

Dense GNSS networks have been widely used to observe crustal deformation. Simpson et al. (2012) and Savage and Simpson (2013) have conducted cluster analyses of GNSS velocity field in the San Francisco Bay Area and Mojave Desert, respectively. They have successfully found velocity discontinuities. They also showed an advantage of cluster analysis for classifying GNSS velocity field. Since in western United States, strike-slip events are dominant, geometry is simple. However, the Japanese Islands are tectonically complicated due to subduction of oceanic plates. There are many types of crustal deformation such as slow slip event and large postseismic deformation. We propose a modified clustering method of GNSS velocity field in Japan to separate time variant and static crustal deformation. Our modification is performing cluster analysis every several months or years, then qualifying cluster member similarity. If a GNSS station moved differently from its neighboring GNSS stations, the station will not belong to in the cluster which includes its surrounding stations. With this method, time variant phenomena were distinguished. We applied our method to GNSS data of Japan from 1996 to 2015. According to the analyses, following conclusions were derived. The first is the clusters boundaries are consistent with known active faults. For examples, the Arima-Takatsuki-Hanaore fault system and the Shimane-Tottori segment proposed by Nishimura (2015) are recognized, though without using prior information. The second is improving detectability of time variable phenomena, such as a slow slip event in northern part of Hokkaido region detected by Ohzono et al. (2015). The last one is the classification of postseismic deformation caused by large earthquakes. The result suggested velocity discontinuities in postseismic deformation of the Tohoku-oki earthquake. This result implies that postseismic deformation is not continuously decaying proportional to distance from its epicenter.

Chondrule formation, metamorphism, brecciation, an important new primary chondrule group, and the classification of chondrules

NASA Technical Reports Server (NTRS)

Sears, Derek W. G.; Shaoxiong, Huang; Benoit, Paul H.

1995-01-01

The recently proposed compositional classification scheme for meteoritic chondrules divides the chondrules into groups depending on the composition of their two major phases, olivine (or pyroxene) and the mesostasis, both of which are genetically important. The scheme is here applied to discussions of three topics: the petrographic classification of Roosevelt County 075 (the least-metamorphosed H chondrite known), brecciation (an extremely important and ubiquitous process probably experienced by greater than 40% of all unequilibrated ordinary chondrites), and the group A5 chondrules in the least metamorphosed ordinary chondrites which have many similarities to chondrules in the highly metamorphosed 'equilibrated' chondrites. Since composition provides insights into both primary formation properties of the chondruies and the effects of metamorphism on the entire assemblage it is possible to determine the petrographic type of RC075 as 3.1 with unique certainty. Similarly, the near scheme can be applied to individual chondrules without knowledge of the petrographic type of the host chondrite, which makes it especially suitable for studying breccias. Finally, the new scheme has revealed the existence of chondrules not identified by previous techniques and which appear to be extremely important. Like group A1 and A2 chondrules (but unlike group B1 chondrules) the primitive group A5 chondruies did not supercool during formation, but unlike group A1 and A2 chondrules (and like group B1 chondrules) they did not suffer volatile loss and reduction during formation. It is concluded that the compositional classification scheme provides important new insights into the formation and history of chondrules and chondrites which would be overlooked by previous schemes.

Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey

PubMed Central

Özge, C; Toros, F; Bayramkaya, E; Çamdeviren, H; Şaşmaz, T

2006-01-01

Background The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Methods Using in‐class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. Results The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. Conclusions It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed. PMID:16891446

Network-based high level data classification.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2012-06-01

Traditional supervised data classification considers only physical features (e.g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

About decomposition approach for solving the classification problem

NASA Astrophysics Data System (ADS)

Andrianova, A. A.

2016-11-01

This article describes the features of the application of an algorithm with using of decomposition methods for solving the binary classification problem of constructing a linear classifier based on Support Vector Machine method. Application of decomposition reduces the volume of calculations, in particular, due to the emerging possibilities to build parallel versions of the algorithm, which is a very important advantage for the solution of problems with big data. The analysis of the results of computational experiments conducted using the decomposition approach. The experiment use known data set for binary classification problem.

[TNM 2010. What's new?].

PubMed

Wittekind, C

2010-10-01

In the seventh edition of the TNM Classification of Malignant Tumours there are several entirely new classifications: upper aerodigestive mucosal melanoma, gastrointestinal stromal tumour, gastrointestinal carcinoid (neuroendocrine tumour), intrahepatic cholangiocarcinoma, Merkel cell carcinoma, uterine sarcomas, and adrenal cortical carcinoma. Significant modifications concern carcinomas of the oesophagus, oesophagogastric junction, stomach, appendix, biliary tract, lung, skin, prostate and ophthalmic tumours, which will be not addressed in this article. For several tumour entities only minor changes were introduced which might be of importance in daily practice. The new classifications and changes will be commented on without going into details.

Study on the construction of Intelligent Courier Station Model

NASA Astrophysics Data System (ADS)

zhao, Ce; lu, Jia xin; li, Zhuang zhuang; shao, Zi rong; pi, Kun yi

2018-06-01

Campus Express is an important window to observe the city consumption logistics service "last kilometer".The research on Campus Express service is not only conducive to campus environment improvement and service quality promotion, but also provides all types of community, agglomeration areas such as urban terminal "last kilometer" logistics with reference.This article first proposed the main problems of campus express service,analyzed the mode of smart express station and finally built a smart express station.

Species composition and assemblages of ichthyoplankton during summer in the East China Sea

NASA Astrophysics Data System (ADS)

Lin, Han-Yang; Chiu, Mei-Yun; Shih, Yu-Ming; Chen, I.-Shiung; Lee, Ming-An; Shao, Kwang-Tsao

2016-09-01

The East China Sea (ECS) is one of the most important fish spawning and nursery grounds in the north Pacific. Even though summer is an important spawning season for many fishes in the region, large-scale molecular identification studies on ichthyoplankton during this season are few. In this study, we sampled 8,933 fish eggs and 12,161 fish larvae from 25 stations during the summer of 2009. Using DNA barcoding, a number of the fish eggs and larvae were identified and classified into 45 and 124 taxa, respectively. Principal component analysis (PCA) categorized the inshore stations of the Changjiang Diluted Water area as having the hydrographic features of low sea surface temperature (SST), salinity (SSS) and high chlorophyll a (SSC) contents, whereas the continental shelf and offshore stations under the influence of the Kuroshio Current displayed the opposite results. Ichthyoplankton was more abundant at the inshore stations than the offshore stations, but species diversity was lower at the former locations. Species compositions of both fish eggs and fish larvae at the 25 stations were categorized into three different assemblages based on a non-metric multidimensional scaling analysis. Combining the assemblage patterns of ichthyoplankton with the results of the PCA and satellite images of SST and SSC showed that the assemblage patterns of fish eggs were correlated with water mass, while those of the fish larvae were not.

Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization

PubMed Central

Niu, Liyong; Zhang, Di

2015-01-01

Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly. PMID:26236770

Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization.

PubMed

Niu, Liyong; Zhang, Di

2015-01-01

Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly.

Developing classification criteria for polymyalgia rheumatica: comparison of views from an expert panel and wider survey.

PubMed

Dasgupta, Bhaskar; Salvarani, Carlo; Schirmer, Michael; Crowson, Cynthia S; Maradit-Kremers, Hilal; Hutchings, Andrew; Matteson, Eric L

2008-02-01

This report summarizes the findings from a consensus process to identify potential classification criteria for polymyalgia rheumatica (PMR). A 3-stage hybrid consensus approach was used to develop potential PMR classification criteria. The first stage consisted of a facilitated meeting of 27 international experts who anonymously rated the importance of 68 potential criteria. The second stage involved a meeting of the experts, who were provided with the results of the first round of ratings and were then asked to re-rate the criteria. In the third stage, the wider acceptance of the 43 criteria that received > 50% support at round 2 was evaluated using an extended mailed survey of 111 rheumatologists and 53 nonrheumatologists in the United States, Canada, and Northern and Western Europe. A total of 68 and 50 criteria were identified and rated in round 1 and round 2, respectively. In round 2, 43 of the 50 items achieved at least 50% support, including 10 core criteria achieving 100% support. In round 3, over 70% of survey respondents agreed on the importance of 7 core criteria. These were age >or=50 years, duration >or=2 weeks, bilateral shoulder and/or pelvic girdle aching, duration of morning stiffness > 45 min, elevated erythrocyte sedimentation rate, elevated C-reactive protein, and rapid steroid response (> 75% global response within 1 wk to prednisolone/prednisone 15 20 mg daily). Among physical signs, more than 70% of survey respondents agreed on the importance of assessing pain and limitation of shoulder (84%) and/or hip (76%) on motion, but agreement was low for peripheral signs like carpal tunnel, tenosynovitis, and peripheral arthritis. There are differences in opinion as to what PMR is and how it should be treated. These findings make it important to develop classification criteria for PMR. The next step is to perform an international prospective study to evaluate the utility of candidate classification criteria for PMR in patients presenting with the polymyalgic syndrome.

Optimization of the Number and Location of Tsunami Stations in a Tsunami Warning System

NASA Astrophysics Data System (ADS)

An, C.; Liu, P. L. F.; Pritchard, M. E.

2014-12-01

Optimizing the number and location of tsunami stations in designing a tsunami warning system is an important and practical problem. It is always desirable to maximize the capability of the data obtained from the stations for constraining the earthquake source parameters, and to minimize the number of stations at the same time. During the 2011 Tohoku tsunami event, 28 coastal gauges and DART buoys in the near-field recorded tsunami waves, providing an opportunity for assessing the effectiveness of those stations in identifying the earthquake source parameters. Assuming a single-plane fault geometry, inversions of tsunami data from combinations of various number (1~28) of stations and locations are conducted and evaluated their effectiveness according to the residues of the inverse method. Results show that the optimized locations of stations depend on the number of stations used. If the stations are optimally located, 2~4 stations are sufficient to constrain the source parameters. Regarding the optimized location, stations must be uniformly spread in all directions, which is not surprising. It is also found that stations within the source region generally give worse constraint of earthquake source than stations farther from source, which is due to the exaggeration of model error in matching large amplitude waves at near-source stations. Quantitative discussions on these findings will be given in the presentation. Applying similar analysis to the Manila Trench based on artificial scenarios of earthquakes and tsunamis, the optimal location of tsunami stations are obtained, which provides guidance of deploying a tsunami warning system in this region.

Temporal optimisation of image acquisition for land cover classification with Random Forest and MODIS time-series

NASA Astrophysics Data System (ADS)

Nitze, Ingmar; Barrett, Brian; Cawkwell, Fiona

2015-02-01

The analysis and classification of land cover is one of the principal applications in terrestrial remote sensing. Due to the seasonal variability of different vegetation types and land surface characteristics, the ability to discriminate land cover types changes over time. Multi-temporal classification can help to improve the classification accuracies, but different constraints, such as financial restrictions or atmospheric conditions, may impede their application. The optimisation of image acquisition timing and frequencies can help to increase the effectiveness of the classification process. For this purpose, the Feature Importance (FI) measure of the state-of-the art machine learning method Random Forest was used to determine the optimal image acquisition periods for a general (Grassland, Forest, Water, Settlement, Peatland) and Grassland specific (Improved Grassland, Semi-Improved Grassland) land cover classification in central Ireland based on a 9-year time-series of MODIS Terra 16 day composite data (MOD13Q1). Feature Importances for each acquisition period of the Enhanced Vegetation Index (EVI) and Normalised Difference Vegetation Index (NDVI) were calculated for both classification scenarios. In the general land cover classification, the months December and January showed the highest, and July and August the lowest separability for both VIs over the entire nine-year period. This temporal separability was reflected in the classification accuracies, where the optimal choice of image dates outperformed the worst image date by 13% using NDVI and 5% using EVI on a mono-temporal analysis. With the addition of the next best image periods to the data input the classification accuracies converged quickly to their limit at around 8-10 images. The binary classification schemes, using two classes only, showed a stronger seasonal dependency with a higher intra-annual, but lower inter-annual variation. Nonetheless anomalous weather conditions, such as the cold winter of 2009/2010 can alter the temporal separability pattern significantly. Due to the extensive use of the NDVI for land cover discrimination, the findings of this study should be transferrable to data from other optical sensors with a higher spatial resolution. However, the high impact of outliers from the general climatic pattern highlights the limitation of spatial transferability to locations with different climatic and land cover conditions. The use of high-temporal, moderate resolution data such as MODIS in conjunction with machine-learning techniques proved to be a good base for the prediction of image acquisition timing for optimal land cover classification results.

Public Broadcasting and the Public Forum Doctrine.

ERIC Educational Resources Information Center

Kleiman, Howard

A compelling argument can be made for the "public forum doctrine," which states that public broadcasting stations licensed to government bodies have a greater obligation than commercial stations under the First Amendment to transcend political and personal biases in making programing decisions. It is also equally important that…

Train users’ perceptions of walking distance to train station and attributes of paratransit service: understanding their association with decision using paratransit or not towards the train station

NASA Astrophysics Data System (ADS)

Syafriharti, R.; Kombaitan, B.; Kusumantoro, I. P.; Syabri, I.

2018-05-01

Access mode is an important factor in public transport systems. Most of the train users from Cicalengka to Padalarang via Bandung use paratransit as access mode. Access modes under this study are only paratransit and walking. This study aims to explore the relationship between access mode choice to the station and the perception about walking distance to station, perception about attributes of paratransit service quality which consist of accessibility, cheapness, comfortable, swiftness, safety, security and easiness. Of all the variables tested, walking distance to the station is the only variable relating to the mode access choice. So, a person will tend to use paratransit when his/her perception of walking distance to station is relatively far away. While perceptions about the quality of paratransit service can not determine whether a person will choose paratransit or not.

Stability of Coordinates of The Slr Stations On A Basis of Lageos-1 and Lageos-2 Laser Ranging In 2000

NASA Astrophysics Data System (ADS)

Schillak, S.; Wnuk, E.

Determination of the stations coordinates and the control of their stability is one of the most important task in the satellite geodesy and geodynamics. This work is continu- ation of the similar paper about coordinates stability of the all SLR stations in 1999. The paper present results of positions determination for all SLR stations in 2000 cal- culated in the ITRF2000 system on the basis of data provided by the LAGEOS-1 and LAGEOS-2 laser ranging. The calculations were performed with the usage of the GEODYN II program. Coordinates of the stations were determined from monthly arcs for 2000. Typical RMS of (O-C) values for the monthly orbital arcs was on a level of 1.7 cm. The final stability of the geocentric coordinates of SLR stations per one year for all components varies from 5 millimetres to several centimetres.