Iron-Doped Zinc Selenide: Spectroscopy and Laser Development

DTIC Science & Technology

2014-03-27

guidance, Dr. Ken Schepler for many hours of discussion about transition- metal lasers, and Dr. Patrick Berry for direct, hands-on support of this work...lifetime of this material to approach 105 µs near 100 K. This measurement is consistent with De- loach [51] and Jeĺınková [52] (see Figure 22...However, Myoung et al. have reported maximum values of no more than 65 µs at the same temperature [21]. Adams, De- loach , and Jeĺınková measured the

KSC-02pd1296

NASA Image and Video Library

2002-08-30

KENNEDY SPACE CENTER, FLA. -- Workers help guide the final Jacking, Equalization and Leveling (JEL) cylinder into place on Crawler Transporter No. 2 (CT-2) for installation. During recent routine maintenance inspections, cracks were found on four bearings in two JEL cylinders. Further eddy current inspections indicated that cracks were present on 15 bearings. There are 16 cylinders and 32 bearings per crawler. CT-2 was repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1180

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- A crane lifts a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1186

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- Technicians supervise a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2 as it is lowered by a crane to a position on the ground. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1178

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- Technicians hook a crane to a jacking, equalization and leveling (JEL) cylinder and bearing on Crawler-Transporter No. 2 in preparation for its removal. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1181

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- A crane lowers a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2 to a position on the ground. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1177

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- Technicians hook a crane to a jacking, equalization and leveling (JEL) cylinder and bearing on Crawler-Transporter No. 2 in preparation for its removal. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1185

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- A technician steadies a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2 as it is lowered by a crane to a position on the ground. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1184

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- Technicians closely monitor a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2 as it lowered by a crane to a position on the ground. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1179

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- Technicians give the signal for a crane to begin lifting a jacking, equalization and leveling (JEL) cylinder and bearing on Crawler-Transporter No. 2. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1183

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- Technicians closely monitor a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2 as it lowered by a crane to a position on the ground. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1169

NASA Image and Video Library

2002-08-13

KENNEDY SPACE CENTER, FLA. -- Technicians check out a jacking, equalization and leveling (JEL) cylinders from Crawler-Transporter No. 2. During inspections, technicians removed two of the 16 JEL cylinders on the vehicle to gain access to the bearings for routine maintenance and found three of the four bearings had cracks. Of the three bearings, two had extensive damage. Further eddy current inspections indicate that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Although no cause for the cracks is known at this time, engineers are currently evaluating the situation to determine the most appropriate solution.

KSC-02pd1187

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- A technician holds a crane strap to steady and guide a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2 as it is lowered by a crane to a resting position on the ground. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1207

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- One of the repaired Jacking, Equalization and Leveling (JEL) cylinders is moved from the repair site for installation into Crawler Transporter No. 2. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings.. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1188

NASA Image and Video Library

2002-08-14

KENNEDY SPACE CENTER, FLA. -- Technicians remove the crane straps from a jacking, equalization and leveling (JEL) cylinder and bearing from Crawler-Transporter No. 2 after it is lowered by a crane to a resting position on the ground. During routine maintenance inspections last week, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Engineers are evaluating the situation to determine the cause of the cracks and an appropriate solution to the problem.

KSC-02pd1213

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- Workers on Crawler Transporter No. 2 help guide a repaired Jacking, Equalization and Leveling (JEL) cylinder into place. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1206

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- Jacking, Equalization and Leveling (JEL) cylinders with repaired bearings are ready to be moved to Crawler Transporter No. 2. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1214

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- Workers on Crawler Transporter No. 2 help guide a repaired Jacking, Equalization and Leveling (JEL) cylinder as it is lowered into place. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings.. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1170

NASA Image and Video Library

2002-08-13

KENNEDY SPACE CENTER, FLA. -- Technicians check out a jacking, equalization and leveling (JEL) cylinders from Crawler-Transporter No. 2. During inspections, technicians removed two of the 16 JEL cylinders on the vehicle to gain access to the bearings for routine maintenance and found three of the four bearings had cracks. Of the three bearings, two had extensive damage. Further eddy current inspections indicate that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Although no cause for the cracks is known at this time, engineers are currently evaluating the situation to determine the most appropriate solution. The crawler is in the background.

KSC-02pd1171

NASA Image and Video Library

2002-08-13

KENNEDY SPACE CENTER, FLA. -- A crane operator (center) talks with technicians (right) standing next to one of the jacking, equalization and leveling (JEL) cylinders from Crawler-Transporter No. 2. During inspections, technicians removed two of the 16 JEL cylinders on the vehicle to gain access to the bearings for routine maintenance and found three of the four bearings had cracks. Of the three bearings, two had extensive damage. Further eddy current inspections indicate that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Although no cause for the cracks is known at this time, engineers are currently evaluating the situation to determine the most appropriate solution.

KSC-02pd1215

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- Two workers help maneuver a repaired Jacking, Equalization and Leveling (JEL) cylinder as it is lowered into place on Crawler Transporter No. 2. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings.. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1211

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- A crane lifts the repaired Jacking, Equalization and Leveling (JEL) cylinder to move into to Crawler Transporter No. 2. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings.. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1166

NASA Image and Video Library

2002-08-13

KENNEDY SPACE CENTER, FLA. -- Perry Becker, an engineer with NASA, looks at a bearing from one of the jacking, equalization and leveling (JEL) cylinders on Crawler-Transporter No. 2. During inspections, technicians removed two of the 16 JEL cylinders on the vehicle to gain access to the bearings for routine maintenance and found three of the four bearings had cracks. Of the three bearings, two had extensive damage. Further eddy current inspections indicate that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Although no cause for the cracks is known at this time, engineers are currently evaluating the situation to determine the most appropriate solution.

KSC-02pd1167

NASA Image and Video Library

2002-08-13

KENNEDY SPACE CENTER, FLA. -- Perry Becker, an engineer with NASA, points to a crack in a bearing from one of the jacking, equalization and leveling (JEL) cylinders on Crawler-Transporter No. 2. During inspections, technicians removed two of the 16 JEL cylinders on the vehicle to gain access to the bearings for routine maintenance and found three of the four bearings had cracks. Of the three bearings, two had extensive damage. Further eddy current inspections indicate that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Although no cause for the cracks is known at this time, engineers are currently evaluating the situation to determine the most appropriate solution.

KSC-02pd1168

NASA Image and Video Library

2002-08-13

KENNEDY SPACE CENTER, FLA. -- Perry Becker, an engineer with NASA, looks at a spacer on the bearing in one of the jacking, equalization and leveling (JEL) cylinders on Crawler-Transporter No. 2. During inspections, technicians removed two of the 16 JEL cylinders on the vehicle to gain access to the bearings for routine maintenance and found three of the four bearings had cracks. Of the three bearings, two had extensive damage. Further eddy current inspections indicate that cracks are present on 15 of the bearings. There are 16 cylinders and 32 bearings per crawler. Although no cause for the cracks is known at this time, engineers are currently evaluating the situation to determine the most appropriate solution.

KSC-02pd1212

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- Supported by the overhead crane and maneuvered by several workers, a repaired Jacking, Equalization and Leveling (JEL) cylinder is lifted into position on Crawler Transporter No. 2. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings.. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

KSC-02pd1208

NASA Image and Video Library

2002-08-23

KENNEDY SPACE CENTER, FLA. -- Workers accompany the repaired Jacking, Equalization and Leveling (JEL) cylinder as it is moved from the repair site for installation into Crawler Transporter No. 2. There are 16 cylinders and 32 bearings per crawler. During recent routine maintenance inspections, technicians removed two of the 16 JEL cylinders on the crawler to gain access to the bearings and found three of the four bearings cracked. Further eddy current inspections indicated that cracks were present on 15 of the bearings.. Technicians have removed and replaced 14 of the bearings on CT-2, which is being repaired in order to enable Atlantis' rollout for mission STS-112, scheduled for launch no earlier than Oct. 2.

Planck-Benzinger thermal work function: Monoclonal antibody-DNA duplex binding interactions

NASA Astrophysics Data System (ADS)

Chun, Paul W.

We have reexamined the van't Hoff plots and delineation of thermodynamic data of the monoclonal antibodies of Jel 274 and Jel 241 binding to DNA duplex at high ionic strength using fluorescein-labeled oligonucleotide titration with increasing concentrations of the antibody as reported by Tanha and Lee (Nucleic Acid Res, 1997, 25, 1442). To compare the thermodynamic parameters from data over the experimental temperature range of 277-312.5 K, the binding constant from van't Hoff plots is used to evaluate ΔGo(T) from 0 to 400 K using our general linear T3 model, ΔGo(T) = α +βT2+γT3. The limited information provided by the van't Hoff plots and their extensions is not sufficient to describe the variations in the Gibbs free energy change as a function of temperature and other thermodynamic functions observed in these and other biological interactions. Rather, it is necessary to determine a number of thermodynamic parameters, including the heat of reaction, (Th), (Tm), and (TCp), and the thermal set point, (TS), all of which can be precisely assessed using our general linear T3 model. To date, no experimental measurement offers this degree of accuracy. In evaluating the thermodynamic parameters in the binding interaction of monoclonal IgG Jel 241-d[AT]20DNA duplex, it is apparent that at a high NaCl concentration, the range of the compensatory temperatures, (Th) = 155 K and (Tm) = 450 K, is much broader than observed in any other sample, whereas the thermal set points, (TS) = 330 K, is 20-30 K higher. The inherent chemical bond energy ΔHo(T0) is much lower in this sample. The values of thermal agitation energy (heat capacity integrals) are of similar magnitude for all the samples tested. It appears that increasing the NaCl concentration to 130 mM will greatly enhance the binding interaction between the monoclonal antibody and DNA duplex. It is not clear, however, from the limited data available, whether the binding interaction is sequence specific, although logic would suggest it is.

Magnesium Contamination in Soil at a Magnesite Mining Area of Jelšava-Lubeník (Slovakia)

NASA Astrophysics Data System (ADS)

Fazekašová, D.; Fazekaš, J.; Hronec, O.; Horňak, M.

2017-10-01

Magnesium contamination in soil at a magnesite mining area of Jelšava-Lubeník (Slovakia) and their effect to the soil characteristics were determined. Soil samples were collected in the area Jelšava - Lubeník with specific alkaline pollutants, it is one of the most devastated regions of Slovakia and with the alarming degree of environmental damage. Magnesite air pollutants are a mixture of MgO and MgCO3 due to which a soil reaction can move above pH 8. Production of clink accompanies the enormous emissions of dust particles of MgO into the air and the leakage of gaseous compounds, mainly SO2 and NOx. The total content of heavy metals in soils (Pb, Zn, Cr, Mn, Mg) were determined by atomic absorption spectrometry and X-ray fluorescence spectrometry. Soil reaction was determined in solution of 0.01 M CaCl2. The research showed that the investigated sites are mostly strongly alkaline. Based on the obtained results, it can be stated that the contents of Pb, Zn is below the level of toxicity but for Cr, Mn and Mg, it does not apply. Their significant exceedance points contamination in which we can take into account the harmfulness and toxicity.

Cost Savings Effects of Olanzapine as Long Term Treatment for Bipolar Disorder

PubMed Central

Zhang, Yuting

2007-01-01

Newer and more expensive drugs account for most of the recent rapid growth of spending on prescription drugs in the past nine years. But if more expensive drugs can reduce the use of other types of health care services, total health care costs might fall. In this paper, I investigate the “drug-offset” hypothesis for an atypical antipsychotic drug, olanzapine, compared to lithium, to treat bipolar disorder. I use a propensity-score method to match on observed variables. Then, using various identification strategies, namely interrupted time series, differencing strategies, and an instrument-variable approach, I find that olanzapine does not reduce spending on other types of medical care services, compared with lithium. Olanzapine users spend $330 per month more than lithium users on non-drug health care services after drug treatment and $470 more per month on total health care spending, contradicting the “drug-offset” hypothesis in this case. JEL classification: H51; I1; I18; C1; C2 PMID:18806303

Healthy vs. unhealthy food: a strategic choice for firms and consumers.

PubMed

Antoñanzas, Fernando; Rodríguez-Ibeas, Roberto

2011-07-20

In this paper, we carry out a theoretical analysis of the strategic choice made by firms regarding the type of food they market when they face consumers who care about the healthy/unhealthy attributes of the product but incur in emotional/health costs when the food they consume has unhealthy attributes. We consider a two-stage game. In the first stage, one of the firms chooses the unhealthy content of its product. In the second stage, both firms simultaneously decide their prices. We find that, depending on the parameters of the model, product differentiation can be maximal or less than maximal. The firm that produces the unhealthy food charges a higher price and obtains a larger share of the market unless the emotional/health costs and the unhealthy food production costs are relatively high. We also find that educational campaigns will not always reduce the demand for the unhealthy food or the degree of the unhealthy attribute.JEL Classification:I10, I18, L11.

Healthy vs. unhealthy food: a strategic choice for firms and consumers

PubMed Central

2011-01-01

In this paper, we carry out a theoretical analysis of the strategic choice made by firms regarding the type of food they market when they face consumers who care about the healthy/unhealthy attributes of the product but incur in emotional/health costs when the food they consume has unhealthy attributes. We consider a two-stage game. In the first stage, one of the firms chooses the unhealthy content of its product. In the second stage, both firms simultaneously decide their prices. We find that, depending on the parameters of the model, product differentiation can be maximal or less than maximal. The firm that produces the unhealthy food charges a higher price and obtains a larger share of the market unless the emotional/health costs and the unhealthy food production costs are relatively high. We also find that educational campaigns will not always reduce the demand for the unhealthy food or the degree of the unhealthy attribute. JEL Classification:I10, I18, L11 PMID:22828271

32 CFR 50.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... policy governing commercial sponsorship. 1 Copies may be obtained at http://www.dtic.mil/whs/directives... Dictionary of Military and Associated Terms.” 2 2 See http://www.dtic.mil/doctrine/jel/doddict/indexs.html...

Models of Care

ERIC Educational Resources Information Center

Wilson, Dottie C.; And Others

1978-01-01

This section describes hospice or palliative care programs for terminally ill patients and their families. The programs described are in Montreal, Quebec; Halifax, Nova Scotia; New Haven, Connecticut; Marin County, California; Tucson, Arizona; and Springfield, Illinois. (Author/JEL)

But when was it painted?

NASA Astrophysics Data System (ADS)

Lundstad, E.; Woll, G.

2009-04-01

The Munch Museum, Oslo, Norway, is dedicated to the visual works of the famous Norwegian painter Edvard Munch (1863 - 1944). Edvard Munch was a symbolist, expressionist painter and printmaker from Oslo, Norway. He was regarded as the pioneer of the amazing Expressionist movement. His art work from the late 1800's is the most well known, but his later work is gradually attracting more attention and is quite an inspiration of many of today's artists. The Munch Museum catalogue for 2008 contains about 1700 paintings of which virtually very few have a precise date. Even when the artist has written the year on the painting itself, there may be a significant uncertainty about this date, and partly due to unclear writing making it difficult to interpret the numbers. This means that other sources need to be applied to verify an accurate date. The climatologist at the Norwegian Meteorological Institute can help dating paintings of Munch. E. g. the painting "Standing Woman with Arms Folded". The painting shows a woman in front of a hill with much snow. The location is almost certainty Grimsrød on Jeløya, a property Munch began renting on March 1, 1913. Jeløya is an island at the southeastcoast of Norway near the town Moss. Jeløya has usually not so much snow because it is near by the sea and windy. The last digit in the date is unclear and has been read as both '3' and '5'. The woman in the portrait, Ingeborg Kaurin, was Munch's model up to the beginning of 1915, so both dates are possible. The year written on the painting has been read as both 1913 and 1915, and since 1974 it has usually been interpreted as 1913 (Stenersensamlingen's catalogue 1974). In the project "But when was it painted?" disclose that it could be another year. One way to reconsider when a painting was painted is to study geophysical characteristics and consider historical observations of snow. The method that is used here is to study daily meteorological snow data from this period from the meteorological station at Jeløya which has information about the precipitation and snow. The artist date "1913" is compared with meteorological snow data from the neighbouring years. The winter of that year 1913 was unusually mild with little snow, and it seems unlikely that there was this much snow lying in March. The winter of 1914 was similarly mild, with little snow in the area around Moss, while there was heavy snow in January 1915 (source: the Norwegian Meteorological institute). It therefore seems most likely that this was one of the last pictures Munch painted of his young model in the winter of 1914-15, before she married the painter Søren Onsager on January 28, 1915. The research for the catalogue raisonée implies that this date 1913 is probably wrong since the 1913 has less snow. This later examination concluded that in fact 1915 was more likely.

Synthesis of High-Speed Digital Systems.

DTIC Science & Technology

1985-11-08

1 (sub2 sub 16 2 (sub3 sub 16) 3 (sub4 sub 16) 4 (eub5 sub 16) 5 (sub6 sub 16) 6 ( sub7 sub 16) 7 (addi add 16) 8 (add2 add 16) 9 (add3 add 16) 10...seB uub5 J2 16 se5) 15 (se6 sub6 JI 16 soO) 18 (se7 sub7 J5 16 se7) 17 (aol addi Dl 16 aol) 18 (a921 add2 add7 18 a02) 19 (&922 add2 add5 16 a02) 20...de4l D4 add4 16 de4) 33 Wd942 D4 sub4 16 de4) 34 (de~i D5 sub7 16 de5) 35 (deS2 D5 add8 16 deS) 36 (jell Ji add7 16 jel) 37 (je12 JI D5 16 jel) 38 (je2

Learning by Living

ERIC Educational Resources Information Center

Kuhn, Margaret E.

1978-01-01

The Gray Panthers is an emerging national movement emphasizing the relationship of personal growth and self-development to pursuit of social goals. It is a coalition of old and young people working together for social change. Presented at the Gerontological Society meeting, Miami Beach Florida, 1973. (Author/JEL)

Interpersonal Conflict Management

ERIC Educational Resources Information Center

Roark, Albert E.

1978-01-01

The difference between constructive and destructive conflicts may be traced to the way in which they are managed. Third-party help is often utilized to achieve constructive conflict management. This article describes two models for conflict management consultation. Five guidelines are given for constructive conflict management. (Author/JEL)

Site-dependent proxy response to climate change during the last 140 years observed in varved lake sediments in Northern Poland

NASA Astrophysics Data System (ADS)

Ott, Florian; Kramkowski, Mateusz; Wulf, Sabine; Plessen, Birgit; Serb, Johanna; Tjallingii, Rik; Schwab, Markus; Słowiński, Michał; Brykała, Dariusz; Tyszkowski, Sebastian; Putyrskaya, Victoria; Appelt, Oona; Błaszkiewicz, Mirosław; Brauer, Achim

2017-04-01

This accurate dating and chronological correlation using crypto-tephras provide a powerful way to compare the varved sediment records of the lakes Głęboczek (JG), Czechowskie (JC) and Jelonek (JEL) (north-central Poland). For the last 140 years, high-resolution varve micro-facies analyses (seasonal layer composition and thickness) and µ-XRF element scanning as well as bulk geochemical analyses (TOC, CaCO3) at sub-decadal to decadal resolution were conducted for all three records. Varve chronologies have been independently established by means of annual layer counting. 137Cs activity concentration measurements confirmed the varve chronology from JC. The Askja AD1875 tephra has been used to synchronize the records. A comparison of sediment data with monthly temperature data from Koszalin since 1870 and daily temperature data from Chojnice since 1951 revealed different responses of lake deposition to recent temperature change. Varves are well-preserved over the entire 140 years only in the sediments of JG, while in the JC record two faintly varved intervals are intercalated and in JEL two non-varved intervals occur at the base and top of the profile. These differences likely are due to variations in lake characteristics. Climate changes at the demise of the Little Ice Age and the recent warming since the 1980s are expressed in varve micro-facies, CaCO3 and TOC contents in the three lakes with different response times and amplitudes. This allows us to discuss the role of local parameters like lake size, bathymetry and water depth in transferring climate change signals into lake sediment records. This study is a contribution to the Virtual Institute of Integrated Climate and Landscape Evolution Analyses - ICLEA - of the Helmholtz Association, grant number VH-VI-415.

Order-restricted inference for means with missing values.

PubMed

Wang, Heng; Zhong, Ping-Shou

2017-09-01

Missing values appear very often in many applications, but the problem of missing values has not received much attention in testing order-restricted alternatives. Under the missing at random (MAR) assumption, we impute the missing values nonparametrically using kernel regression. For data with imputation, the classical likelihood ratio test designed for testing the order-restricted means is no longer applicable since the likelihood does not exist. This article proposes a novel method for constructing test statistics for assessing means with an increasing order or a decreasing order based on jackknife empirical likelihood (JEL) ratio. It is shown that the JEL ratio statistic evaluated under the null hypothesis converges to a chi-bar-square distribution, whose weights depend on missing probabilities and nonparametric imputation. Simulation study shows that the proposed test performs well under various missing scenarios and is robust for normally and nonnormally distributed data. The proposed method is applied to an Alzheimer's disease neuroimaging initiative data set for finding a biomarker for the diagnosis of the Alzheimer's disease. © 2017, The International Biometric Society.

A Therapist's Perspective on Jewish Family Values

ERIC Educational Resources Information Center

Zuk, Gerald H.

1978-01-01

Family therapy has been deficient in accounting for the impact of ethnic, religious, and racial values on success or failure in treating families. Jewish families respond well in family therapy due to a set of values. An individual's neurotic disposition may evolve from conflicts between family values and independent identity. (Author/JEL)

The effect of bleaching agents on the microhardness of dental aesthetic restorative materials.

PubMed

Türker, S B; Biskin, T

2002-07-01

This study investigated the effects of three home bleaching agents on the microhardness of various dental aesthetic restorative materials. The restorative materials were: feldspatic porcelain, microfilled composite resin and light-cured modified glass-ionomer cement and the bleaching agents Nite-White (16% carbamide peroxide), Opalescence (10% carbamide peroxide and carbapol jel) and Rembrandt (10% carbamide peroxide jel). A total of 90 restorative material samples were prepared 1 cm diameter and 6 mm thick and kept in distilled water for 24 h before commencing bleaching which was carried out for 8 h day-1 for 4 weeks. Microhardness measurements were then made using a Tukon tester. Statistically significant differences with respect to unbleached controls were found only for the feldspatic porcelain and microfilled composite resins (P <0.05) for Nite-White and Opalescence. All the bleaching agents decreased the microhardness of the porcelain and increased that of the light cured modified glass-ionomer cement. For the composite resin, whereas Nite-White increased its microhardness, the other bleaching agents decreased it. There were no significant differences between the bleaching agents for any of the restorative materials.

Transactional Analysis and Gestalt Therapy Used in Conjunction with Group Counseling for Married Couples

ERIC Educational Resources Information Center

Sisson, P. Joe; And Others

1977-01-01

This study investigated the effects of combining Transactional Analysis and Gestalt therapy with group counseling for married couples. Six treatment couples and 12 control group members were pre/post administered the Tennessee Self-Concept Scale to assess changes in the level of their self-esteem. There were some significant results. (Author/JEL)

The impacts of recent smoking control policies on individual smoking choice: the case of Japan

PubMed Central

2013-01-01

Abstract This article comprehensively examines the impact of recent smoking control policies in Japan, increases in cigarette taxes and the enforcement of the Health Promotion Law, on individual smoking choice by using multi-year and nationwide individual survey data to overcome the analytical problems of previous Japanese studies. In the econometric analyses, I specify a simple binary choice model based on a random utility model to examine the effects of smoking control policies on individual smoking choice by employing the instrumental variable probit model to control for the endogeneity of cigarette prices. The empirical results show that an increase in cigarette prices statistically significantly reduces the smoking probability of males by 1.0 percent and that of females by 1.4 to 2.0 percent. The enforcement of the Health Promotion Law has a statistically significant effect on reducing the smoking probability of males by 15.2 percent and of females by 11.9 percent. Furthermore, an increase in cigarette prices has a statistically significant negative effect on the smoking probability of office workers, non-workers, male manual workers, and female unemployed people, and the enforcement of the Health Promotion Law has a statistically significant effect on decreasing the smoking probabilities of office workers, female manual workers, and male non-workers. JEL classification C25, C26, I18 PMID:23497490

Waiting time distribution in public health care: empirics and theory.

PubMed

Dimakou, Sofia; Dimakou, Ourania; Basso, Henrique S

2015-12-01

Excessive waiting times for elective surgery have been a long-standing concern in many national healthcare systems in the OECD. How do the hospital admission patterns that generate waiting lists affect different patients? What are the hospitals characteristics that determine waiting times? By developing a model of healthcare provision and analysing empirically the entire waiting time distribution we attempt to shed some light on those issues. We first build a theoretical model that describes the optimal waiting time distribution for capacity constraint hospitals. Secondly, employing duration analysis, we obtain empirical representations of that distribution across hospitals in the UK from 1997-2005. We observe important differences on the 'scale' and on the 'shape' of admission rates. Scale refers to how quickly patients are treated and shape represents trade-offs across duration-treatment profiles. By fitting the theoretical to the empirical distributions we estimate the main structural parameters of the model and are able to closely identify the main drivers of these empirical differences. We find that the level of resources allocated to elective surgery (budget and physical capacity), which determines how constrained the hospital is, explains differences in scale. Changes in benefits and costs structures of healthcare provision, which relate, respectively, to the desire to prioritise patients by duration and the reduction in costs due to delayed treatment, determine the shape, affecting short and long duration patients differently. JEL Classification I11; I18; H51.

Infrastructure and Private Sector Investment in Pakistan

DTIC Science & Technology

1997-03-01

manner in which the expansion in various types of infrastructural facilities interact with private sector investment, and whether there is a long run...passive role in the country’s development. That is public facilities have largely expanded in response to the needs created by private sector investment...tangible needs created by private sector expansion it has, no doubt, been very effective in alleviating real bottlenecks. (JEL F21, 053).

Characterization and sequence analysis of pilin from F-like plasmids.

PubMed Central

Frost, L S; Finlay, B B; Opgenorth, A; Paranchych, W; Lee, J S

1985-01-01

Conjugative pili are expressed by derepressed plasmids and initiate cell-to-cell contact during bacterial conjugation. They are also the site of attachment for pilus-specific phages (f1, f2, and QB). In this study, the number of pili per cell and their ability to retract in the presence of cyanide was estimated for 13 derepressed plasmids. Selected pilus types were further characterized for reactivity with anti-F and anti-ColB2 pilus antisera as well as two F pilus-specific monoclonal antibodies, one of which is specific for a sequence common to most F-like pilin types (JEL92) and one which is specific for the amino terminus of F pilin (JEL93). The pilin genes from eight of these plasmids were cloned and sequenced, and the results were compared with information on F, ColB2, and pED208 pilin. Six pilus groups were defined: I, was F-like [F, pED202(R386), ColV2-K94, and ColVBtrp]; IIA was ColB2-like in sequence but had a lowered sensitivity to f1 phage due to its decreased ability for pilus retraction [pED236(ColB2) and pED203(ColB4)]; IIB was ColB2-like but retained f1 sensitivity [pED200(R124) and pED207(R538-1)]; III contained R1-19, which had a ColB2-like amino terminus but had an additional lysine residue at its carboxy terminus which may affect its phage sensitivity pattern and its antigenicity; IV was R100-1-like [R100-1 and presumably pED241(R136) and pED204(R6)] which had a unique amino-terminal sequence combined with a carboxy terminus similar to that of F. pED208(Folac) formed group V, which was multipiliated and exhibited poor pilus retraction although it retained full sensitivity to f1 phage. The pED208 pilin gene could not be cloned at this time since it shared no homology with the pilin gene of the F plasmid. Images PMID:2999074

75 FR 47883 - Elimination of USDOT Number Registrant-Only Classification

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-09

... DEPARTMENT OF TRANSPORTATION Federal Motor Carrier Safety Administration Elimination of USDOT Number Registrant-Only Classification AGENCY: Federal Motor Carrier Safety Administration (FMCSA), DOT..., FMCSA created the ``registrant-only'' USDOT number classification to identify registered owners of CMVs...

Engineering and Design: Rock Mass Classification Data Requirements for Rippability

DTIC Science & Technology

1983-06-30

Engineering and Design ROCK MASS CLASSIFICATION DATA REQUIREMENTS FOR RIPPABILITY Distribution Restriction Statement Approved for public release...and Design: Rock Mass Classification Data Requirements for Rippability Contract Number Grant Number Program Element Number Author(s) Project...Technical Letter 1110-2-282 Engineering and Design ROCK MASS CLASSIFICATION DATA REQUIREMENTS FOR RIPPABILITY 1“ -“ This ETL contains information on data

Demonstration of Advanced EMI Models for Live-Site UXO Discrimination at Former Camp Butner, North Carolina

DTIC Science & Technology

2012-05-01

GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7 . PERFORMING ORGANIZATION NAME(S...2.3.3 Classification using template matching ...................................................... 7 2.4 Details of classification schemes... 7 2.4.1 Camp Butner TEMTADS data inversion and classification scheme .......... 9

77 FR 4403 - Proposed Collection; Comment Request for Form 8832

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-27

... 8832, Entity Classification Election. DATES: Written comments should be received on or before March 27... INFORMATION: Title: Entity Classification Election. OMB Number: 1545-1516. Form Number: Form 8832. Abstract... its current classification must file Form 8832 to elect a classification. Current Actions: Changes...

48 CFR 204.7107 - Contract accounting classification reference number (ACRN) and agency accounting identifier (AAI).

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Contract accounting classification reference number (ACRN) and agency accounting identifier (AAI). 204.7107 Section 204.7107 Federal... ADMINISTRATIVE MATTERS Uniform Contract Line Item Numbering System 204.7107 Contract accounting classification...

48 CFR 204.7107 - Contract accounting classification reference number (ACRN) and agency accounting identifier (AAI).

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false Contract accounting classification reference number (ACRN) and agency accounting identifier (AAI). 204.7107 Section 204.7107 Federal... ADMINISTRATIVE MATTERS Uniform Contract Line Item Numbering System 204.7107 Contract accounting classification...

Mechanization of Library Procedures in the Medium-Sized Medical Library: XIV. Correlations between National Library of Medicine Classification Numbers and MeSH Headings *

PubMed Central

Fenske, Ruth E.

1972-01-01

The purpose of this study was to determine the amount of correlation between National Library of Medicine classification numbers and MeSH headings in a body of cataloging which had already been done and then to find out which of two alternative methods of utilizing the correlation would be best. There was a correlation of 44.5% between classification numbers and subject headings in the data base studied, cataloging data covering 8,137 books. The results indicate that a subject heading index showing classification numbers would be the preferred method of utilization, because it would be more accurate than the alternative considered, an arrangement by classification numbers which would be consulted to obtain subject headings. PMID:16017607

(YIP) Detecting, Analyzing, Modeling Adversarial Propaganda in Social Media

DTIC Science & Technology

2015-10-26

SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a. REPORT b. ABSTRACT c . THIS PAGE 17. LIMITATION OF...numbers as they appear in the report, e.g. F33315-86- C -5169. 5b. GRANT NUMBER. Enter all grant numbers as they appear in the report. e.g. AFOSR...classification in accordance with security classification regulations, e.g. U, C , S, etc. If this form contains classified information, stamp classification

A Computerized English-Spanish Correlation Index to Five Biomedical Library Classification Schemes Based on MeSH*

PubMed Central

Muench, Eugene V.

1971-01-01

A computerized English/Spanish correlation index to five biomedical library classification schemes and a computerized English/Spanish, Spanish/English listings of MeSH are described. The index was accomplished by supplying appropriate classification numbers of five classification schemes (National Library of Medicine; Library of Congress; Dewey Decimal; Cunningham; Boston Medical) to MeSH and a Spanish translation of MeSH The data were keypunched, merged on magnetic tape, and sorted in a computer alphabetically by English and Spanish subject headings and sequentially by classification number. Some benefits and uses of the index are: a complete index to classification schemes based on MeSH terms; a tool for conversion of classification numbers when reclassifying collections; a Spanish index and a crude Spanish translation of five classification schemes; a data base for future applications, e.g., automatic classification. Other classification schemes, such as the UDC, and translations of MeSH into other languages can be added. PMID:5172471

Treatment-Based Classification versus Usual Care for Management of Low Back Pain

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-11-1-0657 TITLE: Treatment-Based Classification versus Usual Care for Management of Low Back Pain PRINCIPAL INVESTIGATOR...Treatment-Based Classification versus Usual Care for Management of Low Back Pain 5b. GRANT NUMBER W81XWH-11-1-0657 5c. PROGRAM ELEMENT NUMBER 6...AUTHOR(S) MAJ Daniel Rhon – daniel_rhon@baylor.edu 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S

MATCHING IN INFORMAL FINANCIAL INSTITUTIONS.

PubMed

Eeckhout, Jan; Munshi, Kaivan

2010-09-01

This paper analyzes an informal financial institution that brings heterogeneous agents together in groups. We analyze decentralized matching into these groups, and the equilibrium composition of participants that consequently arises. We find that participants sort remarkably well across the competing groups, and that they re-sort immediately following an unexpected exogenous regulatory change. These findings suggest that the competitive matching model might have applicability and bite in other settings where matching is an important equilibrium phenomenon. (JEL: O12, O17, G20, D40).

Agent-Based Modeling and Simulation: Proposal for Department of Defense Support to the Whole of Government Approach In Afghanistan

DTIC Science & Technology

2012-05-11

September 1, 2011). 5 Abraham Maslow , Motivation and Personality, Third Edition, Harper and Row Publishers, 1954, 91-236. 6 Joshua M. Epstein, “Why...Response Program." Joint Force Quarterly, no. 37 (2005): 46, http://www.dtic.mil/doctrine/jel/jfq_pubs/0937.pdf (accessed October 15, 2011). Maslow ... Abraham . Motivation and Personality. Third ed. New York, New York: Harper and Row, 1954. Mattis, James. US Central Command Commander’s Posture

Restrictions of Non Associated Plastic Flow Laws Imposed by Thermodynamics and Uniqueness

DTIC Science & Technology

1986-05-20

which have been discussed by Kestin and Rice (1970). Valanis (1971c) and Nemat-Nasser (1975b). lie in the concepts of entropy and temperature. As a...to the concept of entropy. As an example. consider the case of a rigid heat conductor in thermal equilibrium. If heat is added to the conductor, the...entropy for such systems mathematically. Using the concept of partial integrability of Pfaffian forms, Valanis finds the temperature 0 = 0(j.eL) > 0 as

MATCHING IN INFORMAL FINANCIAL INSTITUTIONS

PubMed Central

Eeckhout, Jan; Munshi, Kaivan

2013-01-01

This paper analyzes an informal financial institution that brings heterogeneous agents together in groups. We analyze decentralized matching into these groups, and the equilibrium composition of participants that consequently arises. We find that participants sort remarkably well across the competing groups, and that they re-sort immediately following an unexpected exogenous regulatory change. These findings suggest that the competitive matching model might have applicability and bite in other settings where matching is an important equilibrium phenomenon. (JEL: O12, O17, G20, D40) PMID:24027491

U.S. Coast Guard Fleet Mix Planning: A Decision Support System Prototype

DTIC Science & Technology

1991-03-01

91-16785 Al ’ 1 1 1 Unclassified SECURITY CLASSIFICATION OF ThIS PAGE REPORT DOCUMENTATION PAGE I L REPORTSECURITY CLASSIFICATION lb. RESTRICTIVE...MARKINGS Unclassified 2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/ AVAILABITY OF REPORT Approved for public release; distribution is inlimited...2b. DECIASSIFICATION/DOWNGRADING SCHEDULE 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) 6a. NAME OF

Low-Level Wind Systems in the Warsaw Pact Countries.

DTIC Science & Technology

1985-03-01

CLASSIFICATION OF THIS PAGE o i REPORT DOCUMENTATION PAGE I le. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS Unclassified 2e, SECURITY...CLASSIFICATION AUTHORITY 3. OISTRIBUTION/AVAI LAOBILfTY OF REPORT 2b. ECLSSIICAIONDOWNRADNG CHEULEApproved for public release; distribution * 2b OELASSFICTIO...OOWGRAING CHEULEunlimited * 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) USAFETAC/TN-85/0Ol 6a. NAME OF

Test of spectral/spatial classifier

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator); Kast, J. L.; Davis, B. J.

1977-01-01

The author has identified the following significant results. The supervised ECHO processor (which utilizes class statistics for object identification) successfully exploits the redundancy of states characteristic of sampled imagery of ground scenes to achieve better classification accuracy, reduce the number of classifications required, and reduce the variability of classification results. The nonsupervised ECHO processor (which identifies objects without the benefit of class statistics) successfully reduces the number of classifications required and the variability of the classification results.

Marriage Institutions and Sibling Competition: Evidence from South Asia*

PubMed

Vogl, Tom S

2013-08-01

Using data from South Asia, this article examines how arranged marriage cultivates rivalry among sisters. During marriage search, parents with multiple daughters reduce the reservation quality for an older daughter's groom, rushing her marriage to allow sufficient time to marry off her younger sisters. Relative to younger brothers, younger sisters increase a girl's marriage risk; relative to younger singleton sisters, younger twin sisters have the same effect. These effects intensify in marriage markets with lower sex ratios or greater parental involvement in marriage arrangements. In contrast, older sisters delay a girl's marriage. Because girls leave school when they marry and face limited earning opportunities when they reach adulthood, the number of sisters has well-being consequences over the life cycle. Younger sisters cause earlier school-leaving, lower literacy, a match to a husband with less education and a less skilled occupation, and (marginally) lower adult economic status. Data from a broader set of countries indicate that these cross-sister pressures on marriage age are common throughout the developing world, although the schooling costs vary by setting. JEL Codes: J1, I25, O15.

Marriage Institutions and Sibling Competition: Evidence from South Asia*

PubMed Central

Vogl, Tom S.

2013-01-01

Using data from South Asia, this article examines how arranged marriage cultivates rivalry among sisters. During marriage search, parents with multiple daughters reduce the reservation quality for an older daughter’s groom, rushing her marriage to allow sufficient time to marry off her younger sisters. Relative to younger brothers, younger sisters increase a girl’s marriage risk; relative to younger singleton sisters, younger twin sisters have the same effect. These effects intensify in marriage markets with lower sex ratios or greater parental involvement in marriage arrangements. In contrast, older sisters delay a girl’s marriage. Because girls leave school when they marry and face limited earning opportunities when they reach adulthood, the number of sisters has well-being consequences over the life cycle. Younger sisters cause earlier school-leaving, lower literacy, a match to a husband with less education and a less skilled occupation, and (marginally) lower adult economic status. Data from a broader set of countries indicate that these cross-sister pressures on marriage age are common throughout the developing world, although the schooling costs vary by setting. JEL Codes: J1, I25, O15. PMID:23966752

Examining the Effect of Transverse Motion on Retinal Biometric Identifiers Relating to Shipboard Security Mechanisms

DTIC Science & Technology

1986-03-01

CLASSIFICATION OF THIS PAGEZ-~-ft! -q 1 REPORT DOCUMENTATION PAGE a REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS . UNCLASSIFIED """ a. SECURITY...CLASSIFICATION AUTHORITY 3 DISTRiBUTION(/AVAILABILITY OF REPORT Approved for public release; 2b. DECLASSIFICATION/ DOWNGRADING SCHEDULE distribution...is un 1 im i ted 4 PERFORMING ORGANIZATION REPORT NUMBER(S) S. MONITORING ORGANIZATION REPOR•r NUMBER(S) j a.NAME OF PERFORMING ORGANIZATION 16b

The Hughes phenomenon in hyperspectral classification based on the ground spectrum of grasslands in the region around Qinghai Lake

NASA Astrophysics Data System (ADS)

Ma, Weiwei; Gong, Cailan; Hu, Yong; Meng, Peng; Xu, Feifei

2013-08-01

Hyperspectral data, consisting of hundreds of spectral bands with a high spectral resolution, enables acquisition of continuous spectral characteristic curves, and therefore have served as a powerful tool for vegetation classification. The difficulty of using hyperspectral data is that they are usually redundant, strongly correlated and subject to Hughes phenomenon where classification accuracy increases gradually in the beginning as the number of spectral bands or dimensions increases, but decreases dramatically when the band number reaches some value. In recent years，some algorithms have been proposed to overcome the Hughes phenomenon in classification, such as selecting several bands from full bands, PCA- and MNF-based feature transformations. Up to date, however, few studies have been conducted to investigate the turning point of Hughes phenomenon (i.e., the point at which the classification accuracy begins to decline). In this paper, we firstly analyze reasons for occurrence of Hughes phenomenon, and then based on the Mahalanobis classifier, classify the ground spectrum of several grasslands which were recorded in September 2012 using FieldSpec3 spectrometer in the regions around Qinghai Lake，a important pasturing area in the north of China. Before classification, we extract features from hyperspectral data by bands selecting and PCA- based feature transformations, and In the process of classification, we analyze how the correlation coefficient between wavebands, the number of waveband channels and the number of principal components affect the classification result. The results show that Hushes phenomenon may occur when the correlation coefficient between wavebands is greater than 94%，the number of wavebands is greater than 6, or the number of principal components is greater than 6. Best classification result can be achieved (overall accuracy of grasslands 90%) if the number of wavebands equals to 3 (the band positions are 370nm, 509nm and 886nm respectively) or the number of principal components ranges from 4 to 6.

Characterization of mutant histidine-containing proteins of the phosphoenolpyruvate:sugar phosphotransferase system of Escherichia coli and Salmonella typhimurium

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

Waygood, E.B.; Reiche, B.; Hengstenberg, W.

1987-06-01

Histidine-containing phosphocarrier protein (HPr) is common to all of the phosphoenolpyruvate:sugar phosphotransferase systems (PTS) in Escherichia coli and Salmonella typhimurium, except the fructose-specific PTS. Strains which lack HPr activity (ptsH) have been characterized in the past, and it has proved difficult to delineate between tight and leaky mutants. In this study four different parameters of ptsH strains were measured: in vitro sugar phosphorylation activity of the mutant HPr; detection of /sup 32/P-labeled P-HPr; ability of monoclonal antibodies to bind mutant HPr; and sensitivity of ptsH strains to fosfomycin. Tight ptsH strains could be defined; they were fosfomycin resistant and producedmore » no HPr protein or completely inactive mutant HPr. All leaky ptsH strains were fosfomycin sensitive, Usually produced normal amounts of mutant HPr protein, and had low but measurable activity, and HPr was detectable as a phosphoprotein. This indicates that the regulatory functions of the PTS require a very low level of HPr activity (about 1%). The antibodies used to detect mutant HPr in crude extracts were two monoclonal immunoglobulin G antibodies Jel42 and Jel44. Both antibodies, which have different pIs, inhibited PTS sugar phosphorylation assays, but the antibody-JPr complex could still be phosphorylated by enzyme I. Preliminary evidence suggests that the antibodies bind to two different epitopes which are in part located in a ..beta..-sheet structure.« less

47 CFR 64.2305 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... businesses. (c) Primary advertising classification. A primary advertising classification is the principal... advertising classification is the classification of a subscriber to telephone exchange service as a business...' telephone numbers, addresses, or primary advertising classifications (as such classifications are assigned...

47 CFR 64.2305 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... businesses. (c) Primary advertising classification. A primary advertising classification is the principal... advertising classification is the classification of a subscriber to telephone exchange service as a business...' telephone numbers, addresses, or primary advertising classifications (as such classifications are assigned...

SYMPLECTIC INVARIANTS AND FLOWERS' CLASSIFICATION OF SHELL MODEL STATES

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

Helmers, K.

1961-01-01

Flowers has given a classification of shell model states in j-j coupling for a fixed number of nucleons in a shell with respect to a symplectic group. The relation between these classifications for the various nucleon numbers is studied and is found to be governed by another symplectic group, the transformations of which in general change the nucleon number. (auth)

75 FR 7548 - Amendments to the Select Agents Controls in Export Control Classification Number (ECCN) 1C360 on...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-22

...-91434-01] RIN 0694-AE67 Amendments to the Select Agents Controls in Export Control Classification Number... controls on certain select agents identified in Export Control Classification Number (ECCN) 1C360 on the...) list of select agents and toxins. The changes made by APHIS were part of a biennial review and...

U.S. Geological Survey Library classification system

USGS Publications Warehouse

Sasscer, R. Scott

1992-01-01

The U.S. Geological Survey library classification system has been designed for an earth science library. It is a tool for assigning classification numbers to earth science and allied pure science library materials in order to collect these materials into related subject groups on the library shelves and arrange them alphabetically by author and title. It can also be used as a retrieval system to access these materials through the subject and visible geographic classification numbers.The classification scheme has been developed over the years since 1904 to meet the ever-changing needs of increased specialization and new areas of study in the earth sciences.This system contains seven schedules:Subject scheduleGeological survey scheduleEarth science periodical scheduleGovernment documents periodical scheduleGeneral science periodical scheduleEarth science maps scheduleGeographic scheduleA geographic number, from the geographic schedule, is distinguished from other numbers in the system in that it is always enclosed in parentheses; for example, (200) is the geographic number for the United States.The geographic number is used in conjunction with the six other previously listed schedules, and it represents slightly different nuances of meanings, in respect to geographic locale, for each schedule.When used with a subject number, the geographic number indicates the country, state, province, or region in which the research was made. The subject number, 203, geology, when combined with the geographic number, (200), for example 203(200), is the classification number for library materials on the geology of the United States.The geographic number, combined with the capital letter G, for example, G(211), is the classification number for an earth science periodical issued by a geological association or university geology department in the State of Maine.When the letter S is combined with a geographic number, for example, S(276), it represents a general science periodical for a university or association in California.When the letter P is combined with a geographic number, for example, P(200), it represents a governmental periodical issued by the United States Federal Government.Geographic numbers standing alone represent classification numbers for the publications of geological surveys; for example, (200) represents publications of the U.S. Geological Survey.Map call numbers have a geographic number preceded by the capital letter M, followed by an abbreviated subject number.For example:M(200)2where:M = Map(200) = Geographic region of the United States2 = Abbreviation for the subject number 203— geology.The introduction, which follows this abstract, provides detailed procedures on the construction of complete call numbers for works falling into the framework of the aforesaid classification schedules.The tables following the introduction can be quickly accessed through the use of the newly expanded subject index.The purpose of this publication is to provide the earth science community with a classification and retrieval system for earth science materials, to provide sufficient explanation of its structure and use, and to enable library staff and clientele to classify or access research materials in a library collection.

Analyses of genetic diversity of bacterial blight pathogen, Xanthomonas oryzae pv. oryzae using IS1112 in Bangladesh.

PubMed

Islam, Md Rashidul; Alam, Md Samiul; Khan, Ashik Iqbal; Hossain, Ismail; Adam, Lorne R; Daayf, Fouad

2016-01-01

Bacterial blight (BB) is caused by Xanthomonas oryzae pv. oryzae (Xoo), a most destructive disease of rice, mostly in Asia, including Bangladesh. Altogether 96 isolates of Xoo were collected from 19 rice-growing districts of Bangladesh in both the rain-fed and irrigated seasons of 2014 to assess their pathotypic and genetic variation. Pathotypic analyses were carried out on a set of 12 Near Isogenic Lines (NILs) of rice containing a single resistance gene and two check varieties IR24 and TN1 by the leaf clipping inoculation method. A total of 24 pathotypes were identified based on their virulence patterns on the NILs tested. Among these, pathotypes VII, XII and XIV, considered as major, containing a maximum number of isolates (9.38% each), are frequently distributed in seven northern to mid-eastern districts of Bangladesh. The most virulent pathotype I was recorded in the Habiganj and Brahmanbaria districts. The molecular analysis of variability among the isolates was carried out through PCR analysis using multi-locus primers Jel1 and Jel2 (based on the repetitive element IS1112 in the Xoo genome). Using the genotypic data, a dendrogram was constructed with 17 clusters along with 17 molecular haplotypes at the 65% similarity index. Cluster I was composed of 46 isolates considered as major, whereas clusters X, XI, XII and XVII were represented by a single isolate. A phenogram was constructed based on virulence to interpret the relationship between the pathotypes and the molecular haplotypes. At the 50% similarity level, among 10 clusters, cluster I, considered as major, consisted of a maximum of 10 pathotypes out of 24. In case of haplotypes, a maximum of 7 haplotypes were obtained from pathotype XII, whereas pathotypes IX, X, XV, XXII and XXIV were represented by a single haplotype. However, the present study revealed that different isolates belonging to the same pathotypes belonged to different haplotypes. Conversely, genetically similar haplotypes were also detected from different pathotypes collected from separate districts. This relationship appeared due to a high degree of DNA polymorphism among strains within many pathotypes existing in Bangladesh. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Multiclass classification of microarray data samples with a reduced number of genes

PubMed Central

2011-01-01

Background Multiclass classification of microarray data samples with a reduced number of genes is a rich and challenging problem in Bioinformatics research. The problem gets harder as the number of classes is increased. In addition, the performance of most classifiers is tightly linked to the effectiveness of mandatory gene selection methods. Critical to gene selection is the availability of estimates about the maximum number of genes that can be handled by any classification algorithm. Lack of such estimates may lead to either computationally demanding explorations of a search space with thousands of dimensions or classification models based on gene sets of unrestricted size. In the former case, unbiased but possibly overfitted classification models may arise. In the latter case, biased classification models unable to support statistically significant findings may be obtained. Results A novel bound on the maximum number of genes that can be handled by binary classifiers in binary mediated multiclass classification algorithms of microarray data samples is presented. The bound suggests that high-dimensional binary output domains might favor the existence of accurate and sparse binary mediated multiclass classifiers for microarray data samples. Conclusions A comprehensive experimental work shows that the bound is indeed useful to induce accurate and sparse multiclass classifiers for microarray data samples. PMID:21342522

75 FR 47897 - Proposed Collection; Comment Request for Regulation Project

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-09

...-Classification (Section 301.7701-4). DATES: Written comments should be received on or before October 8, 2010 to...: Title: Environmental Settlement Funds-Classification. OMB Number: 1545-1465. Regulation Project Number... classification of trusts formed to collect and disburse amounts for environmental remediation of an existing...

Research Symposium II

NASA Technical Reports Server (NTRS)

2004-01-01

Contents include the following: High power density motors. The training process of the organization development and training office. Modeling and analysis of a regenerative fuel cell propulsion system for a high altitude long endurance. Increasing the thermal stability of aluminum titanate for solid oxide mJEL cell anodes. Microstructural evaluation of forging parameters for superalloy disks. Epoxy adgesives for stator magnet assembly in stirling radioisotope generator. Nickel-Hydrogen and lithium ion space batteries. Statistical and prediction modeling of the Ka band using experimental results from ACTS propagation terminals at 20.185 and 27.505 GHz.

Young Adult Obesity and Household Income: Effects of Unconditional Cash Transfers†

PubMed Central

Akee, Randall; Simeonova, Emilia; Copeland, William; Angold, Adrian

2014-01-01

We investigate the effect of household cash transfers during childhood on young adult body mass indexes (BMI). The effects of extra income differ depending on the household’s initial socioeconomic status (SES). Children from the initially poorest households have a larger increase in BMI relative to children from initially wealthier households. Several alternative mechanisms are examined. Initial SES holds up as the most likely channel behind the heterogeneous effects of extra income on young adult BMI. (JEL D14, H23, H75, I12, J13, J15) PMID:24707346

78 FR 57870 - Agency Information Collection Activities: Registration for Classification as Refugee; Revision of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-20

... DEPARTMENT OF HOMELAND SECURITY U.S. Citizenship and Immigration Services [OMB Control Number 1615-0068; Form I-590] Agency Information Collection Activities: Registration for Classification as Refugee... Classification as Refuge. (3) Agency form number, if any, and the applicable component of the DHS sponsoring the...

76 FR 13449 - Proposed Collection; Comment Request for Revenue Procedure 2009-41 (Rev. Proc. 2002-59 Is...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-11

... Classification Elections. DATES: Written comments should be received on or before May 10, 2011 to be assured of... Classification Elections. OMB Number: 1545-1771. Revenue Procedure Number: Revenue Procedure 2009-41. (Rev. Proc... Internal Revenue Code for an eligible entity that requests relief for a late classification election filed...

Developing a case mix classification for child and adolescent mental health services: the influence of presenting problems, complexity factors and service providers on number of appointments.

PubMed

Martin, Peter; Davies, Roger; Macdougall, Amy; Ritchie, Benjamin; Vostanis, Panos; Whale, Andy; Wolpert, Miranda

2017-09-01

Case-mix classification is a focus of international attention in considering how best to manage and fund services, by providing a basis for fairer comparison of resource utilization. Yet there is little evidence of the best ways to establish case mix for child and adolescent mental health services (CAMHS). To develop a case mix classification for CAMHS that is clinically meaningful and predictive of number of appointments attended and to investigate the influence of presenting problems, context and complexity factors and provider variation. We analysed 4573 completed episodes of outpatient care from 11 English CAMHS. Cluster analysis, regression trees and a conceptual classification based on clinical best practice guidelines were compared regarding their ability to predict number of appointments, using mixed effects negative binomial regression. The conceptual classification is clinically meaningful and did as well as data-driven classifications in accounting for number of appointments. There was little evidence for effects of complexity or context factors, with the possible exception of school attendance problems. Substantial variation in resource provision between providers was not explained well by case mix. The conceptually-derived classification merits further testing and development in the context of collaborative decision making.

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.

GMM-based speaker age and gender classification in Czech and Slovak

NASA Astrophysics Data System (ADS)

Přibil, Jiří; Přibilová, Anna; Matoušek, Jindřich

2017-01-01

The paper describes an experiment with using the Gaussian mixture models (GMM) for automatic classification of the speaker age and gender. It analyses and compares the influence of different number of mixtures and different types of speech features used for GMM gender/age classification. Dependence of the computational complexity on the number of used mixtures is also analysed. Finally, the GMM classification accuracy is compared with the output of the conventional listening tests. The results of these objective and subjective evaluations are in correspondence.

A Study of United States Air Force Medical Central Processing and Distribution Systems.

DTIC Science & Technology

1981-06-01

5 M t2-8 13. IILL .i 2 5 I C. N SECURITY CLASSIFICATION OF THIS PAGE N,. LC, t,7EPORT DOCUMENTATION P AD-A 195 485 o Is. REPORT SECURITY...CLASSIFICATION lb. RlI𔃺KILIIV MAKKINib Unc lassif led 2a. SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTION /AVAILABILITY OF REPORT Approved for public release...8217b, DECLASSIFICATION I DOWNGRADING SCHEDULE Distribution unlimited 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER

Photodissociation Cross Sections and Spectroscopy of Atmospheric Positive Ions

DTIC Science & Technology

1979-03-13

MP 79-1 * ATNR~ e _____________________ CONTRAg T’. NUMNER(s) G. P. Smith, L. C. Lee, P. CCobJ. R. I . DA 9--C- /EPeter o J.: T.1 MoseASy PEFRMN...Photodissociation of positive ions can be an important power-loss process in e -beam and gas discharge lasers, and a genctal model should prove useful...monJel ca.l)olatioa i detibed is, Apm4i 0, 4 PHOTON ENERGY (eV) 1.5 2.0 2.5 3.0 3.5 24k NONO+ E 20E °This work Vanderhoff 0 . -Model calculation 16- z 0_ m

Union Lake Bourbeuse River, Missouri.

DTIC Science & Technology

1974-10-01

Indiana bat, Myotis sodalis, which is protected by the Endangered Species Act of 1973 (P.L. 95-204). All actions necessary to meet the requirements of...1r- (I 1 o r 1972) I-\\11 vine eXii it ai h ic Jel !W!’ I~a i i~ :’ I a- it The inver teb ratI I faanll o t he sprI:inlie isI he. I,.t~ Zi e oS spe-C i...have been reported from the Meramec Basin and are listed blow: Sp(ei Status Indiana bat Endangered in Missouri and nationally Small-footed m’otis

Flying insect detection and classification with inexpensive sensors.

PubMed

Chen, Yanping; Why, Adena; Batista, Gustavo; Mafra-Neto, Agenor; Keogh, Eamonn

2014-10-15

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect's flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.

Flying Insect Detection and Classification with Inexpensive Sensors

PubMed Central

Chen, Yanping; Why, Adena; Batista, Gustavo; Mafra-Neto, Agenor; Keogh, Eamonn

2014-01-01

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered. PMID:25350921

Semiotic indexing of digital resources

DOEpatents

Parker, Charles T; Garrity, George M

2014-12-02

A method of classifying a plurality of documents. The method includes steps of providing a first set of classification terms and a second set of classification terms, the second set of classification terms being different from the first set of classification terms; generating a first frequency array of a number of occurrences of each term from the first set of classification terms in each document; generating a second frequency array of a number of occurrences of each term from the second set of classification terms in each document; generating a first similarity matrix from the first frequency array; generating a second similarity matrix from the second frequency array; determining an entrywise combination of the first similarity matrix and the second similarity matrix; and clustering the plurality of documents based on the result of the entrywise combination.

Instrumentation for Linear and Nonlinear Optical Device Characterization

DTIC Science & Technology

2018-01-31

1998. 4. TITLE. Enter title and subtitle with volume number and part number, if applicable. On classified documents, enter the title classification...with security classification regulations, e.g. U, C, S, etc. If this form contains classified information, stamp classification level on the top...hundreds of picoseconds. Figure 3 illustrates example data taken from the oscilloscope. 0 5 10 15 Time (ns) 20 25 30 Figure 3. (a) A screen shot

Improved Co I log(gf) & hfs data and Abundance Determinations in the Photospheres of the Sun & Metal-poor Star HD 84937

NASA Astrophysics Data System (ADS)

Lawler, James E.; Sneden, Chris; Cowan, John J.

2016-01-01

New emission branching fraction measurements for 898 lines of the first spectrum of cobalt (Co I) from hollow cathode lamp spectra recorded with a 1m Fourier transform spectrometer (FTS) and a high resolution echelle spectrometer are reported. Radiative lifetimes from laser induced fluorescence measurements are combined with the branching fractions to determine accurate log(gf)s for the 898 lines. Selected published hyperfine structure (hfs) constants for levels of neutral Co are used to generate complete hfs component patterns for 195 transitions of Co I. These new laboratory data are applied to determine the Co abundance in the Sun and metal-poor star HD 84937, yielding log eps(Co) = 4.955 ± 0.007 (sigma = 0.059) based on 82 Co I lines and log eps(Co) = 2.785 ± 0.008 (sigma = 0.065) based on 66 Co I lines respectively. A Saha balance test on the photosphere of HD 84937 is performed using 16 UV lines of Co II, and good agreement is found with the Co I result in this metal-poor ([Fe I /H] = -2.32, [Fe II /H] = -2.32) dwarf star. The resulting value of [Co/Fe] = +0.14 supports a rise of Co/Fe at low metallicity that has been suggested in other studies. These new Co I data are part of a continuing effort to explore the limits of 1D/LTE photospheric models in metal-poor stars and to determine the relative abundance of Fe-group elements at low metallicity. This work is supported in part by NASA grant NNX10AN93G (J.E.L.), by NSF grant AST-1211055 (J.E.L.), and by NSF grant AST-1211585 (C.S.).

On the number of channels needed to classify vowels: Implications for cochlear implants

NASA Astrophysics Data System (ADS)

Fourakis, Marios; Hawks, John W.; Davis, Erin

2005-09-01

In cochlear implants the incoming signal is analyzed by a bank of filters. Each filter is associated with an electrode to constitute a channel. The present research seeks to determine the number of channels needed for optimal vowel classification. Formant measurements of vowels produced by men and women [Hillenbrand et al., J. Acoust. Soc. Am. 97, 3099-3111 (1995)] were converted to channel assignments. The number of channels varied from 4 to 20 over two frequency ranges (180-4000 and 180-6000 Hz) in equal bark steps. Channel assignments were submitted to linear discriminant analysis (LDA). Classification accuracy increased with the number of channels, ranging from 30% with 4 channels to 98% with 20 channels, both for the female voice. To determine asymptotic performance, LDA classification scores were plotted against the number of channels and fitted with quadratic equations. The number of channels at which no further improvement occurred was determined, averaging 19 across all conditions with little variation. This number of channels seems to resolve the frequency range spanned by the first three formants finely enough to maximize vowel classification. This resolution may not be achieved using six or eight channels as previously proposed. [Work supported by NIH.

The impact of star physicians on diffusion of a medical technology: the case of laparoscopic gastric bypass surgery.

PubMed

Shinn, Laura

2014-01-01

Using data on all bariatric surgeries performed in the state of Pennsylvania from 1995 through 2007, this article uses logistic and OLS regressions to measure the effect of star physicians and star hospitals on the diffusion of an innovation in bariatric surgery called laparoscopic gastric bypass surgery (LGBS). This article tests for effects at both the hospital and physician level. Compared to hospitals with no star physicians (11 percent adoption rate), those with star physicians on staff show a much higher adoption rate (89 percent). Compared to hospitals that are not classified as star hospitals (13 percent diffusion rate), hospitals with star status show a much higher diffusion rate (87 percent from first quarter 2000 to fourth quarter 2001); being a star hospital raises the likelihood of that hospital diffusing LCBS from 13 percent to 87 percent. At the physician level, the empirical results indicate that star physicians exert positive asymmetric influence on the adoption and utilization rates of nonstars at the same hospital. Stars are those who: (1) graduated from a Top 30 medical school, (2) completed residency at a Top 30 hospital, or (3) are included in a Castle Connolly Top Doctors publication. The results of this article support earlier work on the role of key individuals in technology diffusion. It extends research on medical technology diffusion by testing a new data set for a chronic disease treatment. JEL classifications: D2, I10, I11, L2, O33. D2 production and organizations; L2 firm objectives, organization and behavior; I10 health general; I11 Analysis of health care markets; O33 technological change: choices and consequences; diffusion processes.

DoD STINFO Manager Training Course. Training Manual

DTIC Science & Technology

1993-02-01

The Export Control Classification Number ( ECCN ) 2. Types of controls, e.g., COCOM 3. Requirements, such as: a. Country groups for which a validated...see Export Administration Act EAR - see Export Administration Regulations ECCN - Export Control Classification Number ELINT - Electronic

49 CFR 173.52 - Classification codes and compatibility groups of explosives.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 2 2014-10-01 2014-10-01 false Classification codes and compatibility groups of... Class 1 § 173.52 Classification codes and compatibility groups of explosives. (a) The classification..., consists of the division number followed by the compatibility group letter. Compatibility group letters are...

How Well Do Molecular and Pedigree Relatedness Correspond, in Populations with Diverse Mating Systems, and Various Types and Quantities of Molecular and Demographic Data?

PubMed

Kopps, Anna M; Kang, Jungkoo; Sherwin, William B; Palsbøll, Per J

2015-06-30

Kinship analyses are important pillars of ecological and conservation genetic studies with potentially far-reaching implications. There is a need for power analyses that address a range of possible relationships. Nevertheless, such analyses are rarely applied, and studies that use genetic-data-based-kinship inference often ignore the influence of intrinsic population characteristics. We investigated 11 questions regarding the correct classification rate of dyads to relatedness categories (relatedness category assignments; RCA) using an individual-based model with realistic life history parameters. We investigated the effects of the number of genetic markers; marker type (microsatellite, single nucleotide polymorphism SNP, or both); minor allele frequency; typing error; mating system; and the number of overlapping generations under different demographic conditions. We found that (i) an increasing number of genetic markers increased the correct classification rate of the RCA so that up to >80% first cousins can be correctly assigned; (ii) the minimum number of genetic markers required for assignments with 80 and 95% correct classifications differed between relatedness categories, mating systems, and the number of overlapping generations; (iii) the correct classification rate was improved by adding additional relatedness categories and age and mitochondrial DNA data; and (iv) a combination of microsatellite and single-nucleotide polymorphism data increased the correct classification rate if <800 SNP loci were available. This study shows how intrinsic population characteristics, such as mating system and the number of overlapping generations, life history traits, and genetic marker characteristics, can influence the correct classification rate of an RCA study. Therefore, species-specific power analyses are essential for empirical studies. Copyright © 2015 Kopps et al.

Crawler Transporter Steering and Jel Systems

NASA Technical Reports Server (NTRS)

Davis, V. L.

1975-01-01

The transporter weighing 2.8 million kilograms (6.3 million pounds) was used to lift a 5.7-million-kilogram (12.6-million-pound) combination of mobile launcher and space vehicle, transfer this load approximately 5.6 kilometers (3.5 miles) from its point of assembly, negotiate curves of 152-meter (500-foot) mean radius, climb a 5-percent grade while maintaining the 122-meter (400-foot) structure in a vertical position within 10 minutes of arc, and smoothly position this huge structure to within plus or minus 5.1 centimeters (plus or minus 2 inches) on support pedestals at the launch pad. The crawler-transporter is described in detail.

DO CONSUMER PRICE SUBSIDIES REALLY IMPROVE NUTRITION?*

PubMed Central

Jensen, Robert T.; Miller, Nolan H.

2010-01-01

Many developing countries use food-price subsidies or controls to improve nutrition. However, subsidizing goods on which households spend a high proportion of their budget can create large wealth effects. Consumers may then substitute towards foods with higher non-nutritional attributes (e.g., taste), but lower nutritional content per unit of currency, weakening or perhaps even reversing the subsidy’s intended impact. We analyze data from a randomized program of large price subsidies for poor households in two provinces of China and find no evidence that the subsidies improved nutrition. In fact, it may have had a negative impact for some households. (JEL I38; O12; Q18) PMID:22505779

Giffen Behavior and Subsistence Consumption

PubMed Central

Jensen, Robert T.

2010-01-01

This paper provides the first real-world evidence of Giffen behavior, i.e., upward sloping demand. Subsidizing the prices of dietary staples for extremely poor households in two provinces of China, we find strong evidence of Giffen behavior for rice in Hunan, and weaker evidence for wheat in Gansu. The data provide new insight into the consumption behavior of the poor, who act as though maximizing utility subject to subsistence concerns. We find that their elasticity of demand depends significantly, and nonlinearly, on the severity of their poverty. Understanding this heterogeneity is important for the effective design of welfare programs for the poor. (JEL D12, O12) PMID:21031158

Polytomous Adaptive Classification Testing: Effects of Item Pool Size, Test Termination Criterion, and Number of Cutscores

ERIC Educational Resources Information Center

Gnambs, Timo; Batinic, Bernad

2011-01-01

Computer-adaptive classification tests focus on classifying respondents in different proficiency groups (e.g., for pass/fail decisions). To date, adaptive classification testing has been dominated by research on dichotomous response formats and classifications in two groups. This article extends this line of research to polytomous classification…

Classification of polytype structures of zinc sulfide

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

Laptev, V.I.

1994-12-31

It is suggested that the existing classification of polytype structures of zinc sulfide be supplemented with an additional criterion: the characteristic of regular point systems (Wyckoff positions) including their type, number, and multiplicity. The consideration of the Wyckoff positions allowed the establishment of construction principles of known polytype series of different symmetries and the systematization (for the first time) of the polytypes with the same number of differently packed layers. the classification suggested for polytype structures of zinc sulfide is compact and provides a basis for creating search systems. The classification table obtained can also be used for numerous siliconmore » carbide polytypes. 8 refs., 4 tabs.« less

Autonomous self-configuration of artificial neural networks for data classification or system control

NASA Astrophysics Data System (ADS)

Fink, Wolfgang

2009-05-01

Artificial neural networks (ANNs) are powerful methods for the classification of multi-dimensional data as well as for the control of dynamic systems. In general terms, ANNs consist of neurons that are, e.g., arranged in layers and interconnected by real-valued or binary neural couplings or weights. ANNs try mimicking the processing taking place in biological brains. The classification and generalization capabilities of ANNs are given by the interconnection architecture and the coupling strengths. To perform a certain classification or control task with a particular ANN architecture (i.e., number of neurons, number of layers, etc.), the inter-neuron couplings and their accordant coupling strengths must be determined (1) either by a priori design (i.e., manually) or (2) using training algorithms such as error back-propagation. The more complex the classification or control task, the less obvious it is how to determine an a priori design of an ANN, and, as a consequence, the architecture choice becomes somewhat arbitrary. Furthermore, rather than being able to determine for a given architecture directly the corresponding coupling strengths necessary to perform the classification or control task, these have to be obtained/learned through training of the ANN on test data. We report on the use of a Stochastic Optimization Framework (SOF; Fink, SPIE 2008) for the autonomous self-configuration of Artificial Neural Networks (i.e., the determination of number of hidden layers, number of neurons per hidden layer, interconnections between neurons, and respective coupling strengths) for performing classification or control tasks. This may provide an approach towards cognizant and self-adapting computing architectures and systems.

XUV Frequency Comb Development for Precision Spectroscopy and Ultrafast Science

DTIC Science & Technology

2015-07-28

first time and provide insight to the underlying 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a...TERMS. Key words or phrases identifying major concepts in the report. 16. SECURITY CLASSIFICATION. Enter security classification in accordance with... security classification regulations, e.g. U, C, S, etc. If this form contains classified information, stamp classification level on the top and bottom

PACE: Probabilistic Assessment for Contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures.

PubMed

Marciano, Michael A; Adelman, Jonathan D

2017-03-01

The deconvolution of DNA mixtures remains one of the most critical challenges in the field of forensic DNA analysis. In addition, of all the data features required to perform such deconvolution, the number of contributors in the sample is widely considered the most important, and, if incorrectly chosen, the most likely to negatively influence the mixture interpretation of a DNA profile. Unfortunately, most current approaches to mixture deconvolution require the assumption that the number of contributors is known by the analyst, an assumption that can prove to be especially faulty when faced with increasingly complex mixtures of 3 or more contributors. In this study, we propose a probabilistic approach for estimating the number of contributors in a DNA mixture that leverages the strengths of machine learning. To assess this approach, we compare classification performances of six machine learning algorithms and evaluate the model from the top-performing algorithm against the current state of the art in the field of contributor number classification. Overall results show over 98% accuracy in identifying the number of contributors in a DNA mixture of up to 4 contributors. Comparative results showed 3-person mixtures had a classification accuracy improvement of over 6% compared to the current best-in-field methodology, and that 4-person mixtures had a classification accuracy improvement of over 20%. The Probabilistic Assessment for Contributor Estimation (PACE) also accomplishes classification of mixtures of up to 4 contributors in less than 1s using a standard laptop or desktop computer. Considering the high classification accuracy rates, as well as the significant time commitment required by the current state of the art model versus seconds required by a machine learning-derived model, the approach described herein provides a promising means of estimating the number of contributors and, subsequently, will lead to improved DNA mixture interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

76 FR 27753 - Proposed Collection; Comment Request for Regulation Project

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-12

... collection requirements related to Simplification of Entity Classification Rules. DATES: Written comments....gov . SUPPLEMENTARY INFORMATION: Title: Simplification of Entity Classification Rules. OMB Number... partnerships for federal tax purposes. The election is made by filing Form 8832, Entity Classification Election...

Discriminative Hierarchical K-Means Tree for Large-Scale Image Classification.

PubMed

Chen, Shizhi; Yang, Xiaodong; Tian, Yingli

2015-09-01

A key challenge in large-scale image classification is how to achieve efficiency in terms of both computation and memory without compromising classification accuracy. The learning-based classifiers achieve the state-of-the-art accuracies, but have been criticized for the computational complexity that grows linearly with the number of classes. The nonparametric nearest neighbor (NN)-based classifiers naturally handle large numbers of categories, but incur prohibitively expensive computation and memory costs. In this brief, we present a novel classification scheme, i.e., discriminative hierarchical K-means tree (D-HKTree), which combines the advantages of both learning-based and NN-based classifiers. The complexity of the D-HKTree only grows sublinearly with the number of categories, which is much better than the recent hierarchical support vector machines-based methods. The memory requirement is the order of magnitude less than the recent Naïve Bayesian NN-based approaches. The proposed D-HKTree classification scheme is evaluated on several challenging benchmark databases and achieves the state-of-the-art accuracies, while with significantly lower computation cost and memory requirement.

Stability and bias of classification rates in biological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.; Hines, J.E.

1990-01-01

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases

An evaluation of sampling and full enumeration strategies for Fisher Jenks classification in big data settings

USGS Publications Warehouse

Rey, Sergio J.; Stephens, Philip A.; Laura, Jason R.

2017-01-01

Large data contexts present a number of challenges to optimal choropleth map classifiers. Application of optimal classifiers to a sample of the attribute space is one proposed solution. The properties of alternative sampling-based classification methods are examined through a series of Monte Carlo simulations. The impacts of spatial autocorrelation, number of desired classes, and form of sampling are shown to have significant impacts on the accuracy of map classifications. Tradeoffs between improved speed of the sampling approaches and loss of accuracy are also considered. The results suggest the possibility of guiding the choice of classification scheme as a function of the properties of large data sets.

76 FR 9541 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-18

....S. Census Bureau. Title: 2012 Economic Census General Classification Report. OMB Control Number... Business Register is that establishments are assigned an accurate economic classification, based on the North American Industry Classification System (NAICS). The primary purpose of the ``2012 Economic Census...

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…

Local Area Network (LAN) Compatibility Issues

DTIC Science & Technology

1991-09-01

September, 1991 Thesis Advisor: Dr. Norman Schneidewind Approved for public release; distribution is unlimited 92 303s246 Unclassified SECURITY ...CLASSIFICATION OF THIS PAGE REPORT DOCUMENTATION PAGE Ia. REPORT SECURITY CLASSIFICATION 1 b. RESTRICTIVE MARKINGS unclassified 2a. SECURITY CLASSIFICATION...Work UiNt ACCeLUOn Number 11. TITLE (Include Security Classification) LOCAL AREA NETWORK (LAN) COMPATIBILITY ISSUES 12. PERSONAL AUTHOR(S) Rita V

On Classification in the Study of Failure, and a Challenge to Classifiers

NASA Technical Reports Server (NTRS)

Wasson, Kimberly S.

2003-01-01

Classification schemes are abundant in the literature of failure. They serve a number of purposes, some more successfully than others. We examine several classification schemes constructed for various purposes relating to failure and its investigation, and discuss their values and limits. The analysis results in a continuum of uses for classification schemes, that suggests that the value of certain properties of these schemes is dependent on the goals a classification is designed to forward. The contrast in the value of different properties for different uses highlights a particular shortcoming: we argue that while humans are good at developing one kind of scheme: dynamic, flexible classifications used for exploratory purposes, we are not so good at developing another: static, rigid classifications used to trap and organize data for specific analytic goals. Our lack of strong foundation in developing valid instantiations of the latter impedes progress toward a number of investigative goals. This shortcoming and its consequences pose a challenge to researchers in the study of failure: to develop new methods for constructing and validating static classification schemes of demonstrable value in promoting the goals of investigations. We note current productive activity in this area, and outline foundations for more.

Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides.

PubMed

Torrens, Francisco; Castellano, Gloria

2014-06-05

Pesticide residues in wine were analyzed by liquid chromatography-tandem mass spectrometry. Retentions are modelled by structure-property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy-morphological determination-natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.

Deep Multi-Task Learning for Tree Genera Classification

NASA Astrophysics Data System (ADS)

Ko, C.; Kang, J.; Sohn, G.

2018-05-01

The goal for our paper is to classify tree genera using airborne Light Detection and Ranging (LiDAR) data with Convolution Neural Network (CNN) - Multi-task Network (MTN) implementation. Unlike Single-task Network (STN) where only one task is assigned to the learning outcome, MTN is a deep learning architect for learning a main task (classification of tree genera) with other tasks (in our study, classification of coniferous and deciduous) simultaneously, with shared classification features. The main contribution of this paper is to improve classification accuracy from CNN-STN to CNN-MTN. This is achieved by introducing a concurrence loss (Lcd) to the designed MTN. This term regulates the overall network performance by minimizing the inconsistencies between the two tasks. Results show that we can increase the classification accuracy from 88.7 % to 91.0 % (from STN to MTN). The second goal of this paper is to solve the problem of small training sample size by multiple-view data generation. The motivation of this goal is to address one of the most common problems in implementing deep learning architecture, the insufficient number of training data. We address this problem by simulating training dataset with multiple-view approach. The promising results from this paper are providing a basis for classifying a larger number of dataset and number of classes in the future.

U.S. Geological Survey Library classification system

USGS Publications Warehouse

Sasscer, R. Scott

2000-01-01

The U.S. Geological Survey Library classification system has been designed for earth science libraries. It is a tool for assigning call numbers to earth science and allied pure science materials in order to collect these materials into related subject groups on the library shelves and arrange them alphabetically by author and title. The classification can be used as a retrieval system to access materials through the subject and geographic numbers.The classification scheme has been developed over the years since 1904 to meet the ever-changing needs of increased specialization and the development of new areas of research in the earth sciences. The system contains seven schedules: Subject scheduleGeological survey schedule Earth science periodical scheduleGovernment document periodical scheduleGeneral science periodical schedule Earth science map schedule Geographic schedule Introduction provides detailed instructions on the construction of call numbers for works falling into the framework of the classification schedules.The tables following the introduction can be quickly accessed through the use of the newly expanded subject index.The purpose of this publication is to provide the earth science community with a classification and retrieval system for earth science materials, to offer sufficient explanation of its structure and use, and to enable library staff and clientele to classify or access research materials in a library collection.

Multiple Signal Classification for Determining Direction of Arrival of Frequency Hopping Spread Spectrum Signals

DTIC Science & Technology

2014-03-27

42 4.2.3 Number of Hops Hs . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.2.4 Number of Sensors M... 45 4.5 Standard deviation vs. Ns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.6 Bias...laboratory MTM multiple taper method MUSIC multiple signal classification MVDR minimum variance distortionless reposnse PSK phase shift keying QAM

Nearest Neighbor Classification of Stationary Time Series: An Application to Anesthesia Level Classification by EEG Analysis.

DTIC Science & Technology

1980-12-05

classification procedures that are common in speech processing. The anesthesia level classification by EEG time series population screening problem example is in...formance. The use of the KL number type metric in NN rule classification, in a delete-one subj ect ’s EE-at-a-time KL-NN and KL- kNN classification of the...17 individual labeled EEG sample population using KL-NN and KL- kNN rules. The results obtained are shown in Table 1. The entries in the table indicate

The utility of rat jejunal permeability for biopharmaceutics classification system.

PubMed

Zakeri-Milani, Parvin; Valizadeh, Hadi; Tajerzadeh, Hosnieh; Islambulchilar, Ziba

2009-12-01

The biopharmaceutical classification system has been developed to provide a scientific approach for classifying drug compounds based on their dose/solubility ratio and human intestinal permeability. Therefore in this study a new classification is presented, which is based on a correlation between rat and human intestinal permeability values. In situ technique in rat jejunum was used to determine the effective intestinal permeability of tested drugs. Then three dimensionless parameters--dose number, absorption number, and dissolution number (D(o), A(n), and D(n))--were calculated for each drug. Four classes of drugs were defined, that is, class I, D(0) < 0.5, P(eff(rat)) > 5.09 x 10(-5) cm/s; class II, D(o) > 1, P(eff(rat)) > 5.09 x 10( -5) cm/s; class III, D(0) < 0.5, P(eff(rat)) < 4.2 x 10(-5) cm/s; and class IV, D(o) > 1, P(eff(rat)) < 4.2 x 10(-5) cm/s. A region of borderline drugs (0.5 < D(o) < 1, 4.2 x 10(-5) < P(eff(rat)) < 5.09 x 10(-5) cm/s) was also defined. According to obtained results and proposed classification for drugs, it is concluded that drugs could be categorized correctly based on dose number and their intestinal permeability values in rat model using single-pass intestinal perfusion technique. This classification enables us to remark defined characteristics for intestinal absorption of all four classes using suitable cutoff points for both dose number and rat effective intestinal permeability values.

Applications of remote sensing, volume 1

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1977-01-01

The author has identified the following significant results. ECHO successfully exploits the redundancy of states characteristics of sampled imagery of ground scenes to achieve better classification accuracy, reduce the number of classifications required, and reduce the variability of classification results. The information required to produce ECHO classifications are cell size, cell homogeneity, cell-to-field annexation parameters, input data, and a class conditional marginal density statistics deck.

Map Classification: A Comparison of Schemes with Special Reference to the Continent of Africa. Occasional Papers, Number 154.

ERIC Educational Resources Information Center

Merrett, Christopher E.

This guide to the theory and practice of map classification begins with a discussion of the filing of maps and the function of map classification based on area and theme as illustrated by four maps of Africa. The description of the various classification systems which follows is divided into book schemes with provision for maps (including Dewey…

The War on Drugs: Methamphetamine, Public Health, and Crime.

PubMed

Dobkin, Carlos; Nicosia, Nancy

2009-03-01

In mid-1995, a government effort to reduce the supply of methamphetamine precursors successfully disrupted the methamphetamine market and interrupted a trajectory of increasing usage. The price of methamphetamine tripled and purity declined from 90 percent to 20 percent. Simultaneously, amphetaminerelated hospital and treatment admissions dropped 50 percent and 35 percent, respectively. Methamphetamine use among arrestees declined 55 percent. Although felony methamphetamine arrests fell 50 percent, there is no evidence of substantial reductions in property or violent crime. The impact was largely temporary. The price returned to its original level within four months; purity, hospital admissions, treatment admissions, and arrests approached preintervention levels within eighteen months. (JEL I12, K42).

Crossing Party Lines: The Effects of Information on Redistributive Politics†

PubMed Central

Casey, Katherine

2017-01-01

Many lament that weak accountability and poor governance impede economic development in Africa. Politicians rely on ethnic allegiances that deliver the vote irrespective of performance, dampening electoral incentives. Giving voters information about candidate competence counters ethnic loyalty and strengthens accountability. I extend a canonical electoral model to show how information provision flows through voter behavior and ultimately impacts the distribution of political spending. I test the theory on data from Sierra Leone using decentralization and differential radio coverage to identify information’s effects. Estimates suggest that information increases voting across ethnic-party lines and induces a more equitable allocation of campaign spending. (JEL D72, D83, J15, O17, Z13) PMID:28935994

Personal Retirement Accounts and Saving†

PubMed Central

Aguila, Emma

2017-01-01

Aging populations are leading countries worldwide to social security reforms. Many countries are moving from pay-as-you-go to personal retirement account (PRA) systems because of their financial sustainability and positive impact on private savings. PRA systems boost private savings at a macro level by converting a government liability into financial wealth managed by private fund managers. However, at a micro level, changes in retirement wealth affect individuals' saving and consumption patterns through their working lives. Retirement wealth increased for lower-income workers after Mexico introduced PRAs, crowding out saving, increasing consumption, and offsetting some of the PRA effect on private savings. (JEL D14, E21, H55, J26, O16) PMID:28286607

The Environment and Directed Technical Change†

PubMed Central

Acemoglu, Daron; Aghion, Philippe; Bursztyn, Leonardo

2015-01-01

This paper introduces endogenous and directed technical change in a growth model with environmental constraints. The final good is produced from “dirty” and “clean” inputs. We show that: (i) when inputs are sufficiently substitutable, sustainable growth can be achieved with temporary taxes/subsidies that redirect innovation toward clean inputs; (ii) optimal policy involves both “carbon taxes” and research subsidies, avoiding excessive use of carbon taxes; (iii) delay in intervention is costly, as it later necessitates a longer transition phase with slow growth; and (iv) use of an exhaustible resource in dirty input production helps the switch to clean innovation under laissez-faire. (JEL O33, O44, Q30, Q54, Q56, Q58) PMID:26719595

Crawler Transporter 2 (CT-2) Trek from Pad 39B to VAB

NASA Image and Video Library

2017-03-21

Crawler-transport 2 (CT-2) moves slowly along the crawlerway on its way back to the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. The crawler took a trip to the pad A/B split to test upgrades recently completed that will allow the giant vehicle to handle the load of the agency's Space Launch System rocket and Orion spacecraft atop the mobile launcher. The Ground Systems Development and Operations Program oversaw upgrades to the 50-year-old CT-2. New generators, gear assemblies, jacking, equalizing and leveling (JEL) hydraulic cylinders, roller bearings and brakes were installed, and other components were upgraded to prepare for Exploration Mission 1.

Crawler Transporter 2 (CT-2) Trek from Pad 39B to VAB

NASA Image and Video Library

2017-03-21

Crawler-transporter 2 (CT-2) moves slowly along the crawlerway on its way back to the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. The crawler took a trip to the Pad A/B split to test upgrades recently completed that will allow the giant vehicle to handle the load of the agency's Space Launch System rocket and Orion spacecraft atop the mobile launcher. The Ground Systems Development and Operations Program oversaw upgrades to the 50-year-old CT-2. New generators, gear assemblies, jacking, equalizing and leveling (JEL) hydraulic cylinders, roller bearings and brakes were installed, and other components were upgraded to prepare for Exploration Mission 1.

Crawler Transporter 2 (CT-2) Trek from Pad 39B to VAB

NASA Image and Video Library

2017-03-21

Crawler-transporter 2 (CT-2) moves slowly along the crawlerway toward the Vehicle Assembly Building (in the background) at NASA's Kennedy Space Center in Florida. The crawler took a trip to the Pad A/B split to test upgrades recently completed that will allow the giant vehicle to handle the load of the agency's Space Launch System rocket and Orion spacecraft atop the mobile launcher. The Ground Systems Development and Operations Program oversaw upgrades to the 50-year-old CT-2. New generators, gear assemblies, jacking, equalizing and leveling (JEL) hydraulic cylinders, roller bearings and brakes were installed, and other components were upgraded to prepare for Exploration Mission 1.

The Environment and Directed Technical Change.

PubMed

Acemoglu, Daron; Aghion, Philippe; Bursztyn, Leonardo; Hemous, David

2012-02-01

This paper introduces endogenous and directed technical change in a growth model with environmental constraints. The final good is produced from "dirty" and "clean" inputs. We show that: (i) when inputs are sufficiently substitutable, sustainable growth can be achieved with temporary taxes/subsidies that redirect innovation toward clean inputs; (ii) optimal policy involves both "carbon taxes" and research subsidies, avoiding excessive use of carbon taxes; (iii) delay in intervention is costly, as it later necessitates a longer transition phase with slow growth; and (iv) use of an exhaustible resource in dirty input production helps the switch to clean innovation under laissez-faire. (JEL O33, O44, Q30, Q54, Q56, Q58).

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

Anatomical classification of breast sentinel lymph nodes using computed tomography-lymphography.

PubMed

Fujita, Tamaki; Miura, Hiroyuki; Seino, Hiroko; Ono, Shuichi; Nishi, Takashi; Nishimura, Akimasa; Hakamada, Kenichi; Aoki, Masahiko

2018-05-03

To evaluate the anatomical classification and location of breast sentinel lymph nodes, preoperative computed tomography-lymphography examinations were retrospectively reviewed for sentinel lymph nodes in 464 cases clinically diagnosed with node-negative breast cancer between July 2007 and June 2016. Anatomical classification was performed based on the numbers of lymphatic routes and sentinel lymph nodes, the flow direction of lymphatic routes, and the location of sentinel lymph nodes. Of the 464 cases reviewed, anatomical classification could be performed in 434 (93.5 %). The largest number of cases showed single route/single sentinel lymph node (n = 296, 68.2 %), followed by multiple routes/multiple sentinel lymph nodes (n = 59, 13.6 %), single route/multiple sentinel lymph nodes (n = 53, 12.2 %), and multiple routes/single sentinel lymph node (n = 26, 6.0 %). Classification based on the flow direction of lymphatic routes showed that 429 cases (98.8 %) had outward flow on the superficial fascia toward axillary lymph nodes, whereas classification based on the height of sentinel lymph nodes showed that 323 cases (74.4 %) belonged to the upper pectoral group of axillary lymph nodes. There was wide variation in the number of lymphatic routes and their branching patterns and in the number, location, and direction of flow of sentinel lymph nodes. It is clinically very important to preoperatively understand the anatomical morphology of lymphatic routes and sentinel lymph nodes for optimal treatment of breast cancer, and computed tomography-lymphography is suitable for this purpose.

Computerized Classification Testing with the Rasch Model

ERIC Educational Resources Information Center

Eggen, Theo J. H. M.

2011-01-01

If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…

Classification Structures for Career Information. Occupational Statements, Volume I. Part 1. SOC Numbers 1099 to 4490. Interim Edition.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. National Center for Research in Vocational Education.

"Classification Structures for Career Information" was created to provide Career Information Delivery Systems (CIDS) staff with pertinent and useful occupational information arranged according to the Standard Occupational Classification (SOC) structure. Through this publication, the National Occupational Information Coordinating…

Classification Structures for Career Information. Occupational Statements, Volume I. Part 2. SOC Numbers 4499 to 6560. Interim Edition.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. National Center for Research in Vocational Education.

"Classification Structures for Career Information" was created to provide Career Information Delivery Systems (CIDS) staff with pertinent and useful occupational information arranged according to the Standard Occupational Classification (SOC) structure. Through this publication, the National Occupational Information Coordinating…

Classification Structures for Career Information. Occupational Statements, Volume I. Part 3. SOC Numbers 6699 to 9900. Interim Edition.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. National Center for Research in Vocational Education.

"Classification Structures for Career Information" was created to provide Career Information Delivery Systems (CIDS) staff with pertinent and useful occupational information arranged according to the Standard Occupational Classification (SOC) structure. Through this publication, the National Occupational Information Coordinating…

32 CFR 732.25 - Accounting classifications for nonnaval medical and dental care expenses.

Code of Federal Regulations, 2010 CFR

2010-07-01

... and dental care expenses. 732.25 Section 732.25 National Defense Department of Defense (Continued) DEPARTMENT OF THE NAVY PERSONNEL NONNAVAL MEDICAL AND DENTAL CARE Accounting Classifications for Nonnaval Medical and Dental Care Expenses and Standard Document Numbers § 732.25 Accounting classifications for...

32 CFR 732.25 - Accounting classifications for nonnaval medical and dental care expenses.

Code of Federal Regulations, 2012 CFR

2012-07-01

... and dental care expenses. 732.25 Section 732.25 National Defense Department of Defense (Continued) DEPARTMENT OF THE NAVY PERSONNEL NONNAVAL MEDICAL AND DENTAL CARE Accounting Classifications for Nonnaval Medical and Dental Care Expenses and Standard Document Numbers § 732.25 Accounting classifications for...

32 CFR 732.25 - Accounting classifications for nonnaval medical and dental care expenses.

Code of Federal Regulations, 2013 CFR

2013-07-01

... and dental care expenses. 732.25 Section 732.25 National Defense Department of Defense (Continued) DEPARTMENT OF THE NAVY PERSONNEL NONNAVAL MEDICAL AND DENTAL CARE Accounting Classifications for Nonnaval Medical and Dental Care Expenses and Standard Document Numbers § 732.25 Accounting classifications for...

32 CFR 732.25 - Accounting classifications for nonnaval medical and dental care expenses.

Code of Federal Regulations, 2011 CFR

2011-07-01

... and dental care expenses. 732.25 Section 732.25 National Defense Department of Defense (Continued) DEPARTMENT OF THE NAVY PERSONNEL NONNAVAL MEDICAL AND DENTAL CARE Accounting Classifications for Nonnaval Medical and Dental Care Expenses and Standard Document Numbers § 732.25 Accounting classifications for...

32 CFR 732.25 - Accounting classifications for nonnaval medical and dental care expenses.

Code of Federal Regulations, 2014 CFR

2014-07-01

... and dental care expenses. 732.25 Section 732.25 National Defense Department of Defense (Continued) DEPARTMENT OF THE NAVY PERSONNEL NONNAVAL MEDICAL AND DENTAL CARE Accounting Classifications for Nonnaval Medical and Dental Care Expenses and Standard Document Numbers § 732.25 Accounting classifications for...

29 CFR 4.51 - Prevailing in the locality determinations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... determination is made. Such information is most frequently derived from area surveys made by the Bureau of Labor... classification data, patterns existing between survey periods, and the way the separate classification data... mean may be used include situations where: (1) The number of workers studied for the job classification...

Classifier fusion for VoIP attacks classification

NASA Astrophysics Data System (ADS)

Safarik, Jakub; Rezac, Filip

2017-05-01

SIP is one of the most successful protocols in the field of IP telephony communication. It establishes and manages VoIP calls. As the number of SIP implementation rises, we can expect a higher number of attacks on the communication system in the near future. This work aims at malicious SIP traffic classification. A number of various machine learning algorithms have been developed for attack classification. The paper presents a comparison of current research and the use of classifier fusion method leading to a potential decrease in classification error rate. Use of classifier combination makes a more robust solution without difficulties that may affect single algorithms. Different voting schemes, combination rules, and classifiers are discussed to improve the overall performance. All classifiers have been trained on real malicious traffic. The concept of traffic monitoring depends on the network of honeypot nodes. These honeypots run in several networks spread in different locations. Separation of honeypots allows us to gain an independent and trustworthy attack information.

Effective classification of the prevalence of Schistosoma mansoni.

PubMed

Mitchell, Shira A; Pagano, Marcello

2012-12-01

To present an effective classification method based on the prevalence of Schistosoma mansoni in the community. We created decision rules (defined by cut-offs for number of positive slides), which account for imperfect sensitivity, both with a simple adjustment of fixed sensitivity and with a more complex adjustment of changing sensitivity with prevalence. To reduce screening costs while maintaining accuracy, we propose a pooled classification method. To estimate sensitivity, we use the De Vlas model for worm and egg distributions. We compare the proposed method with the standard method to investigate differences in efficiency, measured by number of slides read, and accuracy, measured by probability of correct classification. Modelling varying sensitivity lowers the lower cut-off more significantly than the upper cut-off, correctly classifying regions as moderate rather than lower, thus receiving life-saving treatment. The classification method goes directly to classification on the basis of positive pools, avoiding having to know sensitivity to estimate prevalence. For model parameter values describing worm and egg distributions among children, the pooled method with 25 slides achieves an expected 89.9% probability of correct classification, whereas the standard method with 50 slides achieves 88.7%. Among children, it is more efficient and more accurate to use the pooled method for classification of S. mansoni prevalence than the current standard method. © 2012 Blackwell Publishing Ltd.

The minimum distance approach to classification

NASA Technical Reports Server (NTRS)

Wacker, A. G.; Landgrebe, D. A.

1971-01-01

The work to advance the state-of-the-art of miminum distance classification is reportd. This is accomplished through a combination of theoretical and comprehensive experimental investigations based on multispectral scanner data. A survey of the literature for suitable distance measures was conducted and the results of this survey are presented. It is shown that minimum distance classification, using density estimators and Kullback-Leibler numbers as the distance measure, is equivalent to a form of maximum likelihood sample classification. It is also shown that for the parametric case, minimum distance classification is equivalent to nearest neighbor classification in the parameter space.

Particle Swarm Optimization approach to defect detection in armour ceramics.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh

2017-03-01

In this research, various extracted features were used in the development of an automated ultrasonic sensor based inspection system that enables defect classification in each ceramic component prior to despatch to the field. Classification is an important task and large number of irrelevant, redundant features commonly introduced to a dataset reduces the classifiers performance. Feature selection aims to reduce the dimensionality of the dataset while improving the performance of a classification system. In the context of a multi-criteria optimization problem (i.e. to minimize classification error rate and reduce number of features) such as one discussed in this research, the literature suggests that evolutionary algorithms offer good results. Besides, it is noted that Particle Swarm Optimization (PSO) has not been explored especially in the field of classification of high frequency ultrasonic signals. Hence, a binary coded Particle Swarm Optimization (BPSO) technique is investigated in the implementation of feature subset selection and to optimize the classification error rate. In the proposed method, the population data is used as input to an Artificial Neural Network (ANN) based classification system to obtain the error rate, as ANN serves as an evaluator of PSO fitness function. Copyright © 2016. Published by Elsevier B.V.

Working Boards in Tertiary Education: Lessons from Three Case Studies. Professional File. Number 25

ERIC Educational Resources Information Center

Lang, Daniel W.

2005-01-01

There are a number of studies that classify governing boards into different types. Some classifications are based on management form. Some are based on the form in which authority is exercised. Some are based on the form of institution that the board serves. Most of these classifications include "working boards," but few offer a clear…

The Effect of Unequal Samples, Heterogeneity of Covariance Matrices, and Number of Variables on Discriminant Analysis Classification Tables and Related Statistics.

ERIC Educational Resources Information Center

Spearing, Debra; Woehlke, Paula

To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…

Hybrid Binary Imperialist Competition Algorithm and Tabu Search Approach for Feature Selection Using Gene Expression Data.

PubMed

Wang, Shuaiqun; Aorigele; Kong, Wei; Zeng, Weiming; Hong, Xiaomin

2016-01-01

Gene expression data composed of thousands of genes play an important role in classification platforms and disease diagnosis. Hence, it is vital to select a small subset of salient features over a large number of gene expression data. Lately, many researchers devote themselves to feature selection using diverse computational intelligence methods. However, in the progress of selecting informative genes, many computational methods face difficulties in selecting small subsets for cancer classification due to the huge number of genes (high dimension) compared to the small number of samples, noisy genes, and irrelevant genes. In this paper, we propose a new hybrid algorithm HICATS incorporating imperialist competition algorithm (ICA) which performs global search and tabu search (TS) that conducts fine-tuned search. In order to verify the performance of the proposed algorithm HICATS, we have tested it on 10 well-known benchmark gene expression classification datasets with dimensions varying from 2308 to 12600. The performance of our proposed method proved to be superior to other related works including the conventional version of binary optimization algorithm in terms of classification accuracy and the number of selected genes.

Hybrid Binary Imperialist Competition Algorithm and Tabu Search Approach for Feature Selection Using Gene Expression Data

PubMed Central

Aorigele; Zeng, Weiming; Hong, Xiaomin

2016-01-01

Gene expression data composed of thousands of genes play an important role in classification platforms and disease diagnosis. Hence, it is vital to select a small subset of salient features over a large number of gene expression data. Lately, many researchers devote themselves to feature selection using diverse computational intelligence methods. However, in the progress of selecting informative genes, many computational methods face difficulties in selecting small subsets for cancer classification due to the huge number of genes (high dimension) compared to the small number of samples, noisy genes, and irrelevant genes. In this paper, we propose a new hybrid algorithm HICATS incorporating imperialist competition algorithm (ICA) which performs global search and tabu search (TS) that conducts fine-tuned search. In order to verify the performance of the proposed algorithm HICATS, we have tested it on 10 well-known benchmark gene expression classification datasets with dimensions varying from 2308 to 12600. The performance of our proposed method proved to be superior to other related works including the conventional version of binary optimization algorithm in terms of classification accuracy and the number of selected genes. PMID:27579323

Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.

PubMed

Dai, Shengfa; Wei, Qingguo

2017-01-01

Common spatial pattern algorithm is widely used to estimate spatial filters in motor imagery based brain-computer interfaces. However, use of a large number of channels will make common spatial pattern tend to over-fitting and the classification of electroencephalographic signals time-consuming. To overcome these problems, it is necessary to choose an optimal subset of the whole channels to save computational time and improve the classification accuracy. In this paper, a novel method named backtracking search optimization algorithm is proposed to automatically select the optimal channel set for common spatial pattern. Each individual in the population is a N-dimensional vector, with each component representing one channel. A population of binary codes generate randomly in the beginning, and then channels are selected according to the evolution of these codes. The number and positions of 1's in the code denote the number and positions of chosen channels. The objective function of backtracking search optimization algorithm is defined as the combination of classification error rate and relative number of channels. Experimental results suggest that higher classification accuracy can be achieved with much fewer channels compared to standard common spatial pattern with whole channels.

Enhanced Patient Expectant and Antiemetic Drug Efficacy

DTIC Science & Technology

1999-07-01

Breast Cancer Nausea and Vomiting Expectancy Patient Information Antiemetic Side Effect 15. NUMBER OF PAGES 15 16. PRICE CODE 17. SECURITY ...CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS PAGE Unclassified 19. SECURITY CLASSIFICATION OF ABSTRACT...5-HT3 receptor antagonist class of antiemetics (ondansetron, granisetron , tropisitron) have greatly reduced chemotherapy-related vomiting, this has

Breaking the Cost Barrier in Automatic Classification.

ERIC Educational Resources Information Center

Doyle, L. B.

A low-cost automatic classification method is reported that uses computer time in proportion to NlogN, where N is the number of information items and the base is a parameter, some barriers besides cost are treated briefly in the opening section, including types of intellectual resistance to the idea of doing classification by content-word…

Entanglement classification with algebraic geometry

NASA Astrophysics Data System (ADS)

Sanz, M.; Braak, D.; Solano, E.; Egusquiza, I. L.

2017-05-01

We approach multipartite entanglement classification in the symmetric subspace in terms of algebraic geometry, its natural language. We show that the class of symmetric separable states has the structure of a Veronese variety and that its k-secant varieties are SLOCC invariants. Thus SLOCC classes gather naturally into families. This classification presents useful properties such as a linear growth of the number of families with the number of particles, and nesting, i.e. upward consistency of the classification. We attach physical meaning to this classification through the required interaction length of parent Hamiltonians. We show that the states W N and GHZ N are in the same secant family and that, effectively, the former can be obtained in a limit from the latter. This limit is understood in terms of tangents, leading to a refinement of the previous families. We compute explicitly the classification of symmetric states with N≤slant4 qubits in terms of both secant families and its refinement using tangents. This paves the way to further use of projective varieties in algebraic geometry to solve open problems in entanglement theory.

77 FR 37346 - Export Control Reform Transition Plan

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-21

... review the appropriate Export Control Classification Number (ECCN) to determine the classification of their item. Licensees who are unsure of the proper ECCN designation may request a Commodity...

On the classification of exoplanets according to Safronov number

NASA Astrophysics Data System (ADS)

Öztürk, O.; Erdem, A.

2018-02-01

We reexamine the classification of transiting exoplanets proposed by Hansen & Barman (2007) based on equilibrium temperatures and Safronov numbers. We used more sensitive data, namely, photometric and spectroscopic orbital solutions, of 263 well-known planets given in The Exoplanet Data Explorer, while Hansen & Barman (2007) used data on 18 transiting planets. Diagrams of the planet gravity vs. orbital period, planet gravity vs. equilibrium temperature, and Safronov number vs. equilibrium temperature of the 263 transiting planets show that the division of planets into two classes is indistinct.

Activity classification using the GENEA: optimum sampling frequency and number of axes.

PubMed

Zhang, Shaoyan; Murray, Peter; Zillmer, Ruediger; Eston, Roger G; Catt, Michael; Rowlands, Alex V

2012-11-01

The GENEA shows high accuracy for classification of sedentary, household, walking, and running activities when sampling at 80 Hz on three axes. It is not known whether it is possible to decrease this sampling frequency and/or the number of axes without detriment to classification accuracy. The purpose of this study was to compare the classification rate of activities on the basis of data from a single axis, two axes, and three axes, with sampling rates ranging from 5 to 80 Hz. Sixty participants (age, 49.4 yr (6.5 yr); BMI, 24.6 kg·m (3.4 kg·m)) completed 10-12 semistructured activities in the laboratory and outdoor environment while wearing a GENEA accelerometer on the right wrist. We analyzed data from single axis, dual axes, and three axes at sampling rates of 5, 10, 20, 40, and 80 Hz. Mathematical models based on features extracted from mean, SD, fast Fourier transform, and wavelet decomposition were built, which combined one of the numbers of axes with one of the sampling rates to classify activities into sedentary, household, walking, and running. Classification accuracy was high irrespective of the number of axes for data collected at 80 Hz (96.93% ± 0.97%), 40 Hz (97.4% ± 0.73%), 20 Hz (96.86% ± 1.12%), and 10 Hz (97.01% ± 1.01%) but dropped for data collected at 5 Hz (94.98% ± 1.36%). Sampling frequencies >10 Hz and/or more than one axis of measurement were not associated with greater classification accuracy. Lower sampling rates and measurement of a single axis would result in a lower data load, longer battery life, and higher efficiency of data processing. Further research should investigate whether a lower sampling rate and a single axis affects classification accuracy when considering a wider range of activities.

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please visit http://public.tgen.org/tamu/ofs/ e-dougherty@ee.tamu.edu.

Enhanced Patient Expectation and Antiemetic Drug Efficacy

DTIC Science & Technology

1999-07-01

NUMBER OF PAGES 15 Breast Cancer Expectancy Antiemetic Nausea and Vomiting Patient Information Side Effect 16. PRICE CODE 17. SECURITY CLASSIFICATION 18... SECURITY CLASSIFICATION OF THIS 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT PAGE OF ABSTRACT Unclassified Unclassified...by the introduction of the 5-HT 3 receptor antagonist class of antiemetics (ondansetron, granisetron , tropisitron) have greatly reduced chemotherapy

International Standard Classification of Education (ISCED) Three Stage Classification System: 1973; Part 2 - Definitions.

ERIC Educational Resources Information Center

United Nations Educational, Scientific, and Cultural Organization, Paris (France).

The seven levels of education, as classified numerically by International Standard Classification of Education (ISCED), are defined along with courses, programs, and fields of education listed under each level. Also contained is an alphabetical subject index indicating appropriate code numbers. For related documents see TM003535 and TM003536. (RC)

15 CFR 748.3 - Classification requests, advisory opinions, and encryption registrations.

Code of Federal Regulations, 2013 CFR

2013-01-01

... may ask BIS to provide you with the correct Export Control Classification Number (ECCN) down to the... identified in your classification request is either described by an ECCN in the Commerce Control List (CCL) in Supplement No. 1 to Part 774 of the EAR or not described by an ECCN and, therefore, an “EAR99...

15 CFR 748.3 - Classification requests, advisory opinions, and encryption registrations.

Code of Federal Regulations, 2012 CFR

2012-01-01

... may ask BIS to provide you with the correct Export Control Classification Number (ECCN) down to the... identified in your classification request is either described by an ECCN in the Commerce Control List (CCL) in Supplement No. 1 to Part 774 of the EAR or not described by an ECCN and, therefore, an “EAR99...

15 CFR 748.3 - Classification requests, advisory opinions, and encryption registrations.

Code of Federal Regulations, 2011 CFR

2011-01-01

... may ask BIS to provide you with the correct Export Control Classification Number (ECCN) down to the... identified in your classification request is either described by an ECCN in the Commerce Control List (CCL) in supplement No. 1 to part 774 of the EAR or not described by an ECCN and, therefore, an “EAR99...

A systematic review of the Robson classification for caesarean section: what works, doesn't work and how to improve it.

PubMed

Betrán, Ana Pilar; Vindevoghel, Nadia; Souza, Joao Paulo; Gülmezoglu, A Metin; Torloni, Maria Regina

2014-01-01

Caesarean sections (CS) rates continue to increase worldwide without a clear understanding of the main drivers and consequences. The lack of a standardized internationally-accepted classification system to monitor and compare CS rates is one of the barriers to a better understanding of this trend. The Robson's 10-group classification is based on simple obstetrical parameters (parity, previous CS, gestational age, onset of labour, fetal presentation and number of fetuses) and does not involve the indication for CS. This classification has become very popular over the last years in many countries. We conducted a systematic review to synthesize the experience of users on the implementation of this classification and proposed adaptations. Four electronic databases were searched. A three-step thematic synthesis approach and a qualitative metasummary method were used. 232 unique reports were identified, 97 were selected for full-text evaluation and 73 were included. These publications reported on the use of Robson's classification in over 33 million women from 31 countries. According to users, the main strengths of the classification are its simplicity, robustness, reliability and flexibility. However, missing data, misclassification of women and lack of definition or consensus on core variables of the classification are challenges. To improve the classification for local use and to decrease heterogeneity within groups, several subdivisions in each of the 10 groups have been proposed. Group 5 (women with previous CS) received the largest number of suggestions. The use of the Robson classification is increasing rapidly and spontaneously worldwide. Despite some limitations, this classification is easy to implement and interpret. Several suggested modifications could be useful to help facilities and countries as they work towards its implementation.

A Systematic Review of the Robson Classification for Caesarean Section: What Works, Doesn't Work and How to Improve It

PubMed Central

Betrán, Ana Pilar; Vindevoghel, Nadia; Souza, Joao Paulo; Gülmezoglu, A. Metin; Torloni, Maria Regina

2014-01-01

Background Caesarean sections (CS) rates continue to increase worldwide without a clear understanding of the main drivers and consequences. The lack of a standardized internationally-accepted classification system to monitor and compare CS rates is one of the barriers to a better understanding of this trend. The Robson's 10-group classification is based on simple obstetrical parameters (parity, previous CS, gestational age, onset of labour, fetal presentation and number of fetuses) and does not involve the indication for CS. This classification has become very popular over the last years in many countries. We conducted a systematic review to synthesize the experience of users on the implementation of this classification and proposed adaptations. Methods Four electronic databases were searched. A three-step thematic synthesis approach and a qualitative metasummary method were used. Results 232 unique reports were identified, 97 were selected for full-text evaluation and 73 were included. These publications reported on the use of Robson's classification in over 33 million women from 31 countries. According to users, the main strengths of the classification are its simplicity, robustness, reliability and flexibility. However, missing data, misclassification of women and lack of definition or consensus on core variables of the classification are challenges. To improve the classification for local use and to decrease heterogeneity within groups, several subdivisions in each of the 10 groups have been proposed. Group 5 (women with previous CS) received the largest number of suggestions. Conclusions The use of the Robson classification is increasing rapidly and spontaneously worldwide. Despite some limitations, this classification is easy to implement and interpret. Several suggested modifications could be useful to help facilities and countries as they work towards its implementation. PMID:24892928

Epithelial cancer detection by oblique-incidence optical spectroscopy

NASA Astrophysics Data System (ADS)

Garcia-Uribe, Alejandro; Balareddy, Karthik C.; Zou, Jun; Wang, Kenneth K.; Duvic, Madeleine; Wang, Lihong V.

2009-02-01

This paper presents a study on non-invasive detection of two common epithelial cancers (skin and esophagus) based on oblique incidence diffuse reflectance spectroscopy (OIDRS). An OIDRS measurement system, which combines fiber optics and MEMS technologies, was developed. In our pilot studies, a total number of 137 cases have been measured in-vivo for skin cancer detection and a total number of 20 biopsy samples have been measured ex-vivo for esophageal cancer detection. To automatically differentiate the cancerous cases from benign ones, a statistical software classification program was also developed. An overall classification accuracy of 90% and 100% has been achieved for skin and esophageal cancer classification, respectively.

78 FR 35085 - Small Business Size Standards: Waiver of the Nonmanufacturer Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-11

... Classification System (NAICS) code 332991, Products and Services Code (PSC) 3110, made available for public... American Industry Classification System (NAICS) Industry Number as established by the Office of Management...

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.

Crawler Transporter 2 (CT-2) Trek from Pad 39B to VAB

NASA Image and Video Library

2017-03-21

A full view of crawler-transporter 2 (CT-2) as it moves slowly along the crawlerway on its way back to the Vehicle Assembly Building at NASA's Kennedy Space Center in Florida. The crawler took a trip to the Pad A/B split to test upgrades recently completed that will allow the giant vehicle to handle the load of the agency's Space Launch System rocket and Orion spacecraft atop the mobile launcher. The Ground Systems Development and Operations Program oversaw upgrades to the 50-year-old CT-2. New generators, gear assemblies, jacking, equalizing and leveling (JEL) hydraulic cylinders, roller bearings and brakes were installed, and other components were upgraded to prepare for Exploration Mission 1.

Reexamining the Impact of Family Planning Programs on US Fertility: Evidence from the War on Poverty and the Early Years of Title X†

PubMed Central

Bailey, Martha J.

2012-01-01

Almost 50 years after domestic US family planning programs began, their effects on childbearing remain controversial. Using the county-level roll-out of these programs from 1964 to 1973, this paper reevaluates their shorter and longer term effects on US fertility rates. I find that the introduction of family planning is associated with significant and persistent reductions in fertility driven both by falling completed childbearing and childbearing delay. Although federally funded family planning accounted for a small portion of the post-baby boom US fertility decline, my estimates imply that they reduced childbearing among poor women by 19 to 30 percent. (JEL I38, J12, J13, J18) PMID:22582135

KSC-2013-4208

NASA Image and Video Library

2013-12-03

CAPE CANAVERAL, Fla. -- A truck sprays water along the crawlerway to reduce dust ahead of crawler-transporter 1 as it continues its trek to Launch Pad 39A at NASA’s Kennedy Space Center in Florida. New jacking, equalizing and leveling, or JEL, hydraulic cylinders were installed on CT-1 and will be tested for increased load carrying capacity and reliability. The Ground Systems Development and Operations Program at Kennedy continues to upgrade the crawler-transporter as part of its general maintenance. CT-1 could be available to carry a variety of launch vehicles to the launch pad. Two crawler-transporters were used to carry the mobile launcher platform and space shuttle to Launch Complex 39 for space shuttle launches for 30 years. Photo credit: NASA/Jim Grossmann

KSC-2013-4202

NASA Image and Video Library

2013-12-02

CAPE CANAVERAL, Fla. -- A truck sprays water along the crawlerway to reduce dust ahead of crawler-transporter 1 as it begins its trek to Launch Pad 39A at NASA’s Kennedy Space Center in Florida. New jacking, equalizing and leveling, or JEL, hydraulic cylinders were installed on CT-1 and are being tested for increased load carrying capacity and reliability. The Ground Systems Development and Operations Program at Kennedy continues to upgrade the crawler-transporter as part of its general maintenance. CT-1 could be available to carry a variety of launch vehicles to the launch pad. Two crawler-transporters were used to carry the mobile launcher platform and space shuttle to Launch Complex 39 for space shuttle launches for 30 years. Photo credit: NASA/Daniel Casper

Application of time series discretization using evolutionary programming for classification of precancerous cervical lesions.

PubMed

Acosta-Mesa, Héctor-Gabriel; Rechy-Ramírez, Fernando; Mezura-Montes, Efrén; Cruz-Ramírez, Nicandro; Hernández Jiménez, Rodolfo

2014-06-01

In this work, we present a novel application of time series discretization using evolutionary programming for the classification of precancerous cervical lesions. The approach optimizes the number of intervals in which the length and amplitude of the time series should be compressed, preserving the important information for classification purposes. Using evolutionary programming, the search for a good discretization scheme is guided by a cost function which considers three criteria: the entropy regarding the classification, the complexity measured as the number of different strings needed to represent the complete data set, and the compression rate assessed as the length of the discrete representation. This discretization approach is evaluated using a time series data based on temporal patterns observed during a classical test used in cervical cancer detection; the classification accuracy reached by our method is compared with the well-known times series discretization algorithm SAX and the dimensionality reduction method PCA. Statistical analysis of the classification accuracy shows that the discrete representation is as efficient as the complete raw representation for the present application, reducing the dimensionality of the time series length by 97%. This representation is also very competitive in terms of classification accuracy when compared with similar approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Multipartite Entanglement classes via Negativity Fonts

NASA Astrophysics Data System (ADS)

Sharma, Santosh Shelly; Sharma, Naresh Kumar

2012-02-01

The number and types of K-way negativity fonts in canonical form of an N-qubit state depends on the nature and amount of quantum coherences in the state. Non zero determinants of negativity fonts, characterizing a given state, are easily written down and reflect the entanglement microstructure of the superposition. A classification criterion for multipartite entangled states, based on negativity fonts in canonical state and decomposition of global partial transpose in terms of K-way partially transposed operators, is proposed. Inequivalent sub-classes are labelled by N-qubit local unitary invariants. A complete classification of four qubit states is obtained. The number of major families for N>3 is found to be 2^N-2N. Classification of four qubit states indicates that a small number of relevant polynomial invariants is enough to classify N-qubit states.

J-Plus: Morphological Classification Of Compact And Extended Sources By Pdf Analysis

NASA Astrophysics Data System (ADS)

López-Sanjuan, C.; Vázquez-Ramió, H.; Varela, J.; Spinoso, D.; Cristóbal-Hornillos, D.; Viironen, K.; Muniesa, D.; J-PLUS Collaboration

2017-10-01

We present a morphological classification of J-PLUS EDR sources into compact (i.e. stars) and extended (i.e. galaxies). Such classification is based on the Bayesian modelling of the concentration distribution, including observational errors and magnitude + sky position priors. We provide the star / galaxy probability of each source computed from the gri images. The comparison with the SDSS number counts support our classification up to r 21. The 31.7 deg² analised comprises 150k stars and 101k galaxies.

Littoral Combat Ship Manpower, an Overview of Officer Characteristics and Placement

DTIC Science & Technology

2013-03-01

15. NUMBER OF PAGES 103 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS PAGE...maritime force: 1.) Networks should be the central organizing principle of the fleet, and its sensing and fighting power should be distributed across...assured access” force; and 4.) Numbers of hulls count (quantity had its own quality) and consequently the fleet’s combat power should be

The Export Administration Act: Evolution, Provisions, and Debate

DTIC Science & Technology

2009-07-15

an export control classification number ( ECCN ) based on the above categories and functional group. Each ECCN is accompanied by a description of the...item and the reason for control. Currently, there are about 500 ECCN listings. In addition to discrete items on the CCL, nearly all U.S.-origin...establishment of new military end-use controls on 20 product categories consisting of 31 export control classification numbers ( ECCN ). Currently, these

Macrophage Responses to Epithelial Dysfunction Promote Lung Fibrosis in Aging

DTIC Science & Technology

2017-10-01

alveolar macrophages based on single cell molecular classification in patients with pulmonary fibrosis. We have recruited a planned number of patients...biomarkers expressed by human tissue-resident and monocyte-derived alveolar macrophages based on single cell molecular classification in patients with...identify novel biomarkers expressed by human tissue-resident and monocyte- derived alveolar macrophages based on single cell molecular classification

New Sources of Active Duty Military Personnel: The Prior Service Accessions Pool.

DTIC Science & Technology

1981-10-01

Age Group Classification 20...level. -30- Table 15 E.IPLOYMENT STATUS BY AGE AN[) RACE (Iii thotisands) Age Group Classification 20-23 24-29 30-34 35-39 40-49 50-60 Total White...alternative job than for full time workers. Table 17 NUMBER OF VETERANS WORKING LESS THAN 35 HOURS (In thousands) Age Group Classification 20-23

The Impact of Model Misspecification on Parameter Estimation and Item-Fit Assessment in Log-Linear Diagnostic Classification Models

ERIC Educational Resources Information Center

Kunina-Habenicht, Olga; Rupp, Andre A.; Wilhelm, Oliver

2012-01-01

Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item-fit statistics for correct and misspecified diagnostic classification models within a log-linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3…

Author-Editor Guide to Technical Publications Preparation. Revision

DTIC Science & Technology

1990-01-01

meteorology, climatology, military technical publications. ( ") <- 15: Number of Pages: 68 17. Security Classification of Report: Unclassified 1... Security Classification of this Page: Unclassified 19. Security Classification of Abstract: Unclassified 20. Limitation of Abstract: UL Standard Form 298...34 There are, however, February 1983. numerous exceptions. Although some technical material may not be classified in accordance with security AFR 83-2, Air

Retinal vasculature classification using novel multifractal features

NASA Astrophysics Data System (ADS)

Ding, Y.; Ward, W. O. C.; Duan, Jinming; Auer, D. P.; Gowland, Penny; Bai, L.

2015-11-01

Retinal blood vessels have been implicated in a large number of diseases including diabetic retinopathy and cardiovascular diseases, which cause damages to retinal blood vessels. The availability of retinal vessel imaging provides an excellent opportunity for monitoring and diagnosis of retinal diseases, and automatic analysis of retinal vessels will help with the processes. However, state of the art vascular analysis methods such as counting the number of branches or measuring the curvature and diameter of individual vessels are unsuitable for the microvasculature. There has been published research using fractal analysis to calculate fractal dimensions of retinal blood vessels, but so far there has been no systematic research extracting discriminant features from retinal vessels for classifications. This paper introduces new methods for feature extraction from multifractal spectra of retinal vessels for classification. Two publicly available retinal vascular image databases are used for the experiments, and the proposed methods have produced accuracies of 85.5% and 77% for classification of healthy and diabetic retinal vasculatures. Experiments show that classification with multiple fractal features produces better rates compared with methods using a single fractal dimension value. In addition to this, experiments also show that classification accuracy can be affected by the accuracy of vessel segmentation algorithms.

New wideband radar target classification method based on neural learning and modified Euclidean metric

NASA Astrophysics Data System (ADS)

Jiang, Yicheng; Cheng, Ping; Ou, Yangkui

2001-09-01

A new method for target classification of high-range resolution radar is proposed. It tries to use neural learning to obtain invariant subclass features of training range profiles. A modified Euclidean metric based on the Box-Cox transformation technique is investigated for Nearest Neighbor target classification improvement. The classification experiments using real radar data of three different aircraft have demonstrated that classification error can reduce 8% if this method proposed in this paper is chosen instead of the conventional method. The results of this paper have shown that by choosing an optimized metric, it is indeed possible to reduce the classification error without increasing the number of samples.

Mind the information gap: fertility rate and use of cesarean delivery and tocolytic hospitalizations in Taiwan.

PubMed

Ma, Ke-Zong M; Norton, Edward C; Lee, Shoou-Yih D

2011-12-12

Physician-induced demand (PID) is an important theory to test given the longstanding controversy surrounding it. Empirical health economists have been challenged to find natural experiments to test the theory because PID is tantamount to strong income effects. The data requirements are both a strong exogenous change in income and two types of treatment that are substitutes but have different net revenues. The theory implies that an exogenous fall in income would lead physicians to recoup their income by substituting a more expensive treatment for a less expensive treatment. This study takes advantages of the dramatic decline in the Taiwanese fertility rate to examine whether an exogenous and negative income shock to obstetricians and gynecologists (ob/gyns) affected the use of c-sections, which has a higher reimbursement rate than vaginal delivery under Taiwan's National Health Insurance system during the study period, and tocolytic hospitalizations. The primary data were obtained from the 1996 to 2004 National Health Insurance Research Database in Taiwan. We hypothesized that a negative income shock to ob/gyns would cause them to provide more c-sections and tocolytic hospitalizations to less medically-informed pregnant women. Multinomial probit and probit models were estimated and the marginal effects of the interaction term were conducted to estimate the impacts of ob/gyn to birth ratio and the information gap. Our results showed that a decline in fertility did not lead ob/gyns to supply more c-sections to less medically-informed pregnant women, and that during fertility decline ob/gyns may supply more tocolytic hospitalizations to compensate their income loss, regardless of pregnant women's access to health information. The exogenous decline in the Taiwanese fertility rate and the use of detailed medical information and demographic attributes of pregnant women allowed us to avoid the endogeneity problem that threatened the validity of prior research. They also provide more accurate estimates of PID.JEL Classification: I10, I19, C23, C25.

Health status convergence at the local level: empirical evidence from Austria

PubMed Central

2011-01-01

Introduction Health is an important dimension of welfare comparisons across individuals, regions and states. Particularly from a long-term perspective, within-country convergence of the health status has rarely been investigated by applying methods well established in other scientific fields. In the following paper we study the relation between initial levels of the health status and its improvement at the local community level in Austria in the time period 1969-2004. Methods We use age standardized mortality rates from 2381 Austrian communities as an indicator for the health status and analyze the convergence/divergence of overall mortality for (i) the whole population, (ii) females, (iii) males and (iv) the gender mortality gap. Convergence/Divergence is studied by applying different concepts of cross-regional inequality (weighted standard deviation, coefficient of variation, Theil-Coefficient of inequality). Various econometric techniques (weighted OLS, Quantile Regression, Kendall's Rank Concordance) are used to test for absolute and conditional beta-convergence in mortality. Results Regarding sigma-convergence, we find rather mixed results. While the weighted standard deviation indicates an increase in equality for all four variables, the picture appears less clear when correcting for the decreasing mean in the distribution. However, we find highly significant coefficients for absolute and conditional beta-convergence between the periods. While these results are confirmed by several robustness tests, we also find evidence for the existence of convergence clubs. Conclusions The highly significant beta-convergence across communities might be caused by (i) the efforts to harmonize and centralize the health policy at the federal level in Austria since the 1970s, (ii) the diminishing returns of the input factors in the health production function, which might lead to convergence, as the general conditions (e.g. income, education etc.) improve over time, and (iii) the mobility of people across regions, as people tend to move to regions/communities which exhibit more favorable living conditions. JEL classification: I10, I12, I18 PMID:21864364

A comprehensive simulation study on classification of RNA-Seq data.

PubMed

Zararsız, Gökmen; Goksuluk, Dincer; Korkmaz, Selcuk; Eldem, Vahap; Zararsiz, Gozde Erturk; Duru, Izzet Parug; Ozturk, Ahmet

2017-01-01

RNA sequencing (RNA-Seq) is a powerful technique for the gene-expression profiling of organisms that uses the capabilities of next-generation sequencing technologies. Developing gene-expression-based classification algorithms is an emerging powerful method for diagnosis, disease classification and monitoring at molecular level, as well as providing potential markers of diseases. Most of the statistical methods proposed for the classification of gene-expression data are either based on a continuous scale (eg. microarray data) or require a normal distribution assumption. Hence, these methods cannot be directly applied to RNA-Seq data since they violate both data structure and distributional assumptions. However, it is possible to apply these algorithms with appropriate modifications to RNA-Seq data. One way is to develop count-based classifiers, such as Poisson linear discriminant analysis and negative binomial linear discriminant analysis. Another way is to bring the data closer to microarrays and apply microarray-based classifiers. In this study, we compared several classifiers including PLDA with and without power transformation, NBLDA, single SVM, bagging SVM (bagSVM), classification and regression trees (CART), and random forests (RF). We also examined the effect of several parameters such as overdispersion, sample size, number of genes, number of classes, differential-expression rate, and the transformation method on model performances. A comprehensive simulation study is conducted and the results are compared with the results of two miRNA and two mRNA experimental datasets. The results revealed that increasing the sample size, differential-expression rate and decreasing the dispersion parameter and number of groups lead to an increase in classification accuracy. Similar with differential-expression studies, the classification of RNA-Seq data requires careful attention when handling data overdispersion. We conclude that, as a count-based classifier, the power transformed PLDA and, as a microarray-based classifier, vst or rlog transformed RF and SVM classifiers may be a good choice for classification. An R/BIOCONDUCTOR package, MLSeq, is freely available at https://www.bioconductor.org/packages/release/bioc/html/MLSeq.html.

Determining the saliency of feature measurements obtained from images of sedimentary organic matter for use in its classification

NASA Astrophysics Data System (ADS)

Weller, Andrew F.; Harris, Anthony J.; Ware, J. Andrew; Jarvis, Paul S.

2006-11-01

The classification of sedimentary organic matter (OM) images can be improved by determining the saliency of image analysis (IA) features measured from them. Knowing the saliency of IA feature measurements means that only the most significant discriminating features need be used in the classification process. This is an important consideration for classification techniques such as artificial neural networks (ANNs), where too many features can lead to the 'curse of dimensionality'. The classification scheme adopted in this work is a hybrid of morphologically and texturally descriptive features from previous manual classification schemes. Some of these descriptive features are assigned to IA features, along with several others built into the IA software (Halcon) to ensure that a valid cross-section is available. After an image is captured and segmented, a total of 194 features are measured for each particle. To reduce this number to a more manageable magnitude, the SPSS AnswerTree Exhaustive CHAID (χ 2 automatic interaction detector) classification tree algorithm is used to establish each measurement's saliency as a classification discriminator. In the case of continuous data as used here, the F-test is used as opposed to the published algorithm. The F-test checks various statistical hypotheses about the variance of groups of IA feature measurements obtained from the particles to be classified. The aim is to reduce the number of features required to perform the classification without reducing its accuracy. In the best-case scenario, 194 inputs are reduced to 8, with a subsequent multi-layer back-propagation ANN recognition rate of 98.65%. This paper demonstrates the ability of the algorithm to reduce noise, help overcome the curse of dimensionality, and facilitate an understanding of the saliency of IA features as discriminators for sedimentary OM classification.

Adaptive video-based vehicle classification technique for monitoring traffic.

DOT National Transportation Integrated Search

2015-08-01

This report presents a methodology for extracting two vehicle features, vehicle length and number of axles in order : to classify the vehicles from video, based on Federal Highway Administration (FHWA)s recommended vehicle : classification scheme....

High-Altitude Electromagnetic Pulse (HEMP) Testing

DTIC Science & Technology

2011-11-10

Security Classification Guide ( SCG ). b. The HEMP simulation facility shall have a measured map of the peak amplitude waveform of the...Quadripartite Standardization Agreement s, sec second SCG security classification guide SN serial number SOP Standard Operating Procedure

46 CFR Sec. 18 - Group classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION A-NATIONAL SHIPPING AUTHORITY PROCEDURE FOR ACCOMPLISHMENT OF VESSEL REPAIRS UNDER NATIONAL SHIPPING AUTHORITY MASTER LUMP SUM REPAIR CONTRACT-NSA-LUMPSUMREP... inserted thereon: Number Classification 41 Maintenance Repairs (deck, engine and stewards department...

46 CFR Sec. 18 - Group classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION A-NATIONAL SHIPPING AUTHORITY PROCEDURE FOR ACCOMPLISHMENT OF VESSEL REPAIRS UNDER NATIONAL SHIPPING AUTHORITY MASTER LUMP SUM REPAIR CONTRACT-NSA-LUMPSUMREP... inserted thereon: Number Classification 41 Maintenance Repairs (deck, engine and stewards department...

46 CFR Sec. 18 - Group classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION A-NATIONAL SHIPPING AUTHORITY PROCEDURE FOR ACCOMPLISHMENT OF VESSEL REPAIRS UNDER NATIONAL SHIPPING AUTHORITY MASTER LUMP SUM REPAIR CONTRACT-NSA-LUMPSUMREP... inserted thereon: Number Classification 41 Maintenance Repairs (deck, engine and stewards department...

46 CFR Sec. 18 - Group classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION A-NATIONAL SHIPPING AUTHORITY PROCEDURE FOR ACCOMPLISHMENT OF VESSEL REPAIRS UNDER NATIONAL SHIPPING AUTHORITY MASTER LUMP SUM REPAIR CONTRACT-NSA-LUMPSUMREP... inserted thereon: Number Classification 41 Maintenance Repairs (deck, engine and stewards department...

46 CFR Sec. 18 - Group classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION A-NATIONAL SHIPPING AUTHORITY PROCEDURE FOR ACCOMPLISHMENT OF VESSEL REPAIRS UNDER NATIONAL SHIPPING AUTHORITY MASTER LUMP SUM REPAIR CONTRACT-NSA-LUMPSUMREP... inserted thereon: Number Classification 41 Maintenance Repairs (deck, engine and stewards department...

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.

Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.

2010-01-01

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

The uncertainty in the radon hazard classification of areas as a function of the number of measurements.

PubMed

Friedmann, H; Baumgartner, A; Gruber, V; Kaineder, H; Maringer, F J; Ringer, W; Seidel, C

2017-07-01

The administration in many countries demands a classification of areas concerning their radon risk taking into account the requirements of the EU Basic Safety Standards. The wide variation of indoor radon concentrations in an area which is caused by different house construction, different living style and different geological situations introduces large uncertainties for any classification scheme. Therefore, it is of importance to estimate the size of the experimental coefficient of variation (relative standard deviation) of the parameter which is used to classify an area. Besides the time period of measurement it is the number of measurements which strongly influences this uncertainty and it is important to find a compromise between the economic possibilities and the needed confidence level. Some countries do not use pure measurement results for the classification of areas but use derived quantities, usually called radon potential, which should reduce the influence of house construction, living style etc. and should rather represent the geological situation of an area. Here, radon indoor measurements in nearly all homes in three municipalities and its conversion into a radon potential were used to determine the uncertainty of the mean radon potential of an area as a function of the number of investigated homes. It could be shown that the coefficient of variation scales like 1/√n with n the number of measured dwellings. The question how to deal with uncertainties when using a classification scheme for the radon risk is discussed and a general procedure is proposed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chemical-Help Application for Classification and Identification of Stormwater Constituents

USGS Publications Warehouse

Granato, Gregory E.; Driskell, Timothy R.; Nunes, Catherine

2000-01-01

A computer application called Chemical Help was developed to facilitate review of reports for the National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS). The application provides a tool to quickly find a proper classification for any constituent in the NDAMS review sheets. Chemical Help contents include the name of each water-quality property, constituent, or parameter, the section number within the NDAMS review sheet, the organizational levels within a classification hierarchy, the database number, and where appropriate, the chemical formula, the Chemical Abstract Service number, and a list of synonyms (for the organic chemicals). Therefore, Chemical Help provides information necessary to research available reference data for the water-quality properties and constituents of potential interest in stormwater studies. Chemical Help is implemented in the Microsoft help-system interface. (Computer files for the use and documentation of Chemical Help are included on an accompanying diskette.)

National Library of Medicine Classification: A Scheme for the Shelf Arrangement of Books in a Field of Medicine and Its Related Sciences. Fourth Edition.

ERIC Educational Resources Information Center

Wiggins, Emilie, Ed.

Outlined is the National Library of Medicine classification system for medicine and related sciences. In this system each preclinical science, such as human anatomy, biochemistry or pathology, and each medical subject, such as infectious diseases or pediatrics, receives a two-letter classification. Under each of these main headings numbered minor…

A Mapping from the Human Factors Analysis and Classification System (DOD-HFACS) to the Domains of Human Systems Integration (HSI)

DTIC Science & Technology

2009-11-01

Equation Chapter 1 Section 1 A MAPPING FROM THE HUMAN FACTORS ANALYSIS AND CLASSIFICATION SYSTEM (DOD...OMB control number. 1. REPORT DATE NOV 2009 2. REPORT TYPE 3. DATES COVERED 4. TITLE AND SUBTITLE A Mapping from the Human Factors Analysis ...7 The Human Factors Analysis and Classification System .................................................. 7 Mapping of DoD

Study of Software Tools to Support Systems Engineering Management

DTIC Science & Technology

2015-06-01

Management 15. NUMBER OF PAGES 137 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS...AVAILABILITY STATEMENT Approved for public release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) According to a...PAGE Unclassified 19. SECURITY CLASSIFICATION OF ABSTRACT Unclassified 20. LIMITATION OF ABSTRACT UU NSN 7540–01–280–5500 Standard Form 298

Report on Gang Violence in Maryland

DTIC Science & Technology

1994-07-01

possession of a firearm, and drug kingpin statutes. 14 . Consider juvenile witness protection programs for youths under eighteen years of age. Scho... 14 . SUBJECT TERMS 15. NUMBER OF PAGES 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20 IIAINOF...limitations. Cite any Block 2. Report Date. Full publication date availability to the public. Enter additional including day, month, and year , if available

Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery.

PubMed

Crabtree, Nathaniel M; Moore, Jason H; Bowyer, John F; George, Nysia I

2017-01-01

A computational evolution system (CES) is a knowledge discovery engine that can identify subtle, synergistic relationships in large datasets. Pareto optimization allows CESs to balance accuracy with model complexity when evolving classifiers. Using Pareto optimization, a CES is able to identify a very small number of features while maintaining high classification accuracy. A CES can be designed for various types of data, and the user can exploit expert knowledge about the classification problem in order to improve discrimination between classes. These characteristics give CES an advantage over other classification and feature selection algorithms, particularly when the goal is to identify a small number of highly relevant, non-redundant biomarkers. Previously, CESs have been developed only for binary class datasets. In this study, we developed a multi-class CES. The multi-class CES was compared to three common feature selection and classification algorithms: support vector machine (SVM), random k-nearest neighbor (RKNN), and random forest (RF). The algorithms were evaluated on three distinct multi-class RNA sequencing datasets. The comparison criteria were run-time, classification accuracy, number of selected features, and stability of selected feature set (as measured by the Tanimoto distance). The performance of each algorithm was data-dependent. CES performed best on the dataset with the smallest sample size, indicating that CES has a unique advantage since the accuracy of most classification methods suffer when sample size is small. The multi-class extension of CES increases the appeal of its application to complex, multi-class datasets in order to identify important biomarkers and features.

An ant colony optimization based feature selection for web page classification.

PubMed

Saraç, Esra; Özel, Selma Ayşe

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives.

PubMed

Algamal, Z Y; Lee, M H

2017-01-01

A high-dimensional quantitative structure-activity relationship (QSAR) classification model typically contains a large number of irrelevant and redundant descriptors. In this paper, a new design of descriptor selection for the QSAR classification model estimation method is proposed by adding a new weight inside L1-norm. The experimental results of classifying the anti-hepatitis C virus activity of thiourea derivatives demonstrate that the proposed descriptor selection method in the QSAR classification model performs effectively and competitively compared with other existing penalized methods in terms of classification performance on both the training and the testing datasets. Moreover, it is noteworthy that the results obtained in terms of stability test and applicability domain provide a robust QSAR classification model. It is evident from the results that the developed QSAR classification model could conceivably be employed for further high-dimensional QSAR classification studies.

Computer classification of remotely sensed multispectral image data by extraction and classification of homogeneous objects

NASA Technical Reports Server (NTRS)

Kettig, R. L.

1975-01-01

A method of classification of digitized multispectral images is developed and experimentally evaluated on actual earth resources data collected by aircraft and satellite. The method is designed to exploit the characteristic dependence between adjacent states of nature that is neglected by the more conventional simple-symmetric decision rule. Thus contextual information is incorporated into the classification scheme. The principle reason for doing this is to improve the accuracy of the classification. For general types of dependence this would generally require more computation per resolution element than the simple-symmetric classifier. But when the dependence occurs in the form of redundance, the elements can be classified collectively, in groups, therby reducing the number of classifications required.

An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes

PubMed Central

2013-01-01

Background Gene expression data could likely be a momentous help in the progress of proficient cancer diagnoses and classification platforms. Lately, many researchers analyze gene expression data using diverse computational intelligence methods, for selecting a small subset of informative genes from the data for cancer classification. Many computational methods face difficulties in selecting small subsets due to the small number of samples compared to the huge number of genes (high-dimension), irrelevant genes, and noisy genes. Methods We propose an enhanced binary particle swarm optimization to perform the selection of small subsets of informative genes which is significant for cancer classification. Particle speed, rule, and modified sigmoid function are introduced in this proposed method to increase the probability of the bits in a particle’s position to be zero. The method was empirically applied to a suite of ten well-known benchmark gene expression data sets. Results The performance of the proposed method proved to be superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also requires lower computational time compared to BPSO. PMID:23617960

[Evaluation of the appropriateness of hospital admissions using the iso-gravity classification systems APR-DRG and Disease Staging and the Italian version of Appropriateness Evaluation Protocol (AEP)].

PubMed

D'Andrea, G; Capalbo, G; Volpe, M; Marchetti, M; Vicentini, F; Capelli, G; Cambieri, A; Cicchetti, A; Ricciardi, G; Catananti, C

2006-01-01

Our main purpose was to evaluate the organizational appropriateness of admissions made in a university hospital, by comparing two iso-gravity classification systems, APR-DRG and Disease Staging, with the Italian version of AEP (PRUO). Our analysis focused on admissions made in 2001, related to specific Diagnosis Related Groups (DRGs), which, according an Italian Law, would be considered at high risk of inappropriateness, if treated as ordinary admissions. The results obtained by using the 2 classification systems did not show statistically significant differences with respect to the total number of admissions. On the other hand, some DRGs showed statistically significant differences due to different algorithms of attribution of the severity levels used by the two systems. For almost all of the DRGs studied, the AEP-based analysis of a sample of medical records showed an higher number of inappropriate admissions in comparison with the number expected by iso-gravity classification methods. The difference is possibly due to the percentage limits of tolerability fixed by the Law for each DRG. Therefore, the authors suggest an integrated use of the two methods to evaluate organizational appropriateness of hospital admissions.

Relation between urbanization and water quality of streams in the Austin area, Texas

USGS Publications Warehouse

Veenhuis, J.E.; Slade, R.M.

1990-01-01

The ratio of the number of samples with detectable concentrations to the total number of samples analyzed for 18 inorganic trace elements and the concentrations of many of these minor constituents increased with increasing development classifications. Twenty-two of the 42 synthetic organic compounds for which samples were analyzed were detected in one or more samples. The compounds were detected more frequently and in larger concentrations at the sites with more urban classifications.

Detection And Classification Of Web Robots With Honeypots

DTIC Science & Technology

2016-03-01

CLASSIFICATION OF WEB ROBOTS WITH HONEYPOTS by Sean F. McKenna March 2016 Thesis Advisor: Neil Rowe Second Reader: Justin P. Rohrer THIS...Master’s thesis 4. TITLE AND SUBTITLE DETECTION AND CLASSIFICATION OF WEB ROBOTS WITH HONEYPOTS 5. FUNDING NUMBERS 6. AUTHOR(S) Sean F. McKenna 7...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Web robots are automated programs that systematically browse the Web , collecting information. Although

Materials for Adaptive Structural Acoustic Control. Volume 1

DTIC Science & Technology

1993-04-06

FOLLOWING PAGE 14. SUBJECT TERMS 15. NUMBER OF PAGES 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20...375 Rubber is a highly nonlinear clastic medium. In the unstressed compliant state, the molecules ate coiled and tangled . but under stress the molecules...one-dimensional system, \\\\here tangle (solid dots) and the oblique (open circle) states are the shaded area represents the level of thermal energy

Classification of maxillectomy defects: a systematic review and criteria necessary for a universal description.

PubMed

Bidra, Avinash S; Jacob, Rhonda F; Taylor, Thomas D

2012-04-01

Maxillectomy defects are complex and involve a number of anatomic structures. Several maxillectomy defect classifications have been proposed with no universal acceptance among surgeons and prosthodontists. Established criteria for describing the maxillectomy defect are lacking. This systematic review aimed to evaluate classification systems in the available literature, to provide a critical appraisal, and to identify the criteria necessary for a universal description of maxillectomy and midfacial defects. An electronic search of the English language literature between the periods of 1974 and June 2011 was performed by using PubMed, Scopus, and Cochrane databases with predetermined inclusion criteria. Key terms included in the search were maxillectomy classification, maxillary resection classification, maxillary removal classification, maxillary reconstruction classification, midfacial defect classification, and midfacial reconstruction classification. This was supplemented by a manual search of selected journals. After application of predetermined exclusion criteria, the final list of articles was reviewed in-depth to provide a critical appraisal and identify criteria for a universal description of a maxillectomy defect. The electronic database search yielded 261 titles. Systematic application of inclusion and exclusion criteria resulted in identification of 14 maxillectomy and midfacial defect classification systems. From these articles, 6 different criteria were identified as necessary for a universal description of a maxillectomy defect. Multiple deficiencies were noted in each classification system. Though most articles described the superior-inferior extent of the defect, only a small number of articles described the anterior-posterior and medial-lateral extent of the defect. Few articles listed dental status and soft palate involvement when describing maxillectomy defects. No classification system has accurately described the maxillectomy defect, based on criteria that satisfy both surgical and prosthodontic needs. The 6 criteria identified in this systematic review for a universal description of a maxillectomy defect are: 1) dental status; 2) oroantral/nasal communication status; 3) soft palate and other contiguous structure involvement; 4) superior-inferior extent; 5) anterior-posterior extent; and 6) medial-lateral extent of the defect. A criteria-based description appears more objective and amenable for universal use than a classification-based description. Copyright © 2012 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

The War on Poverty’s Experiment in Public Medicine: Community Health Centers and the Mortality of Older Americans†

PubMed Central

Bailey, Martha J.; Goodman-Bacon, Andrew

2015-01-01

This paper uses the rollout of the first Community Health Centers (CHCs) to study the longer-term health effects of increasing access to primary care. Within ten years, CHCs are associated with a reduction in age-adjusted mortality rates of 2 percent among those 50 and older. The implied 7 to 13 percent decrease in one-year mortality risk among beneficiaries amounts to 20 to 40 percent of the 1966 poor/non-poor mortality gap for this age group. Large effects for those 65 and older suggest that increased access to primary care has longer-term benefits, even for populations with near universal health insurance. (JEL H75, I12, I13, I18, I32, I38, J14) PMID:25999599

Leaders: Privilege, Sacrifice, Opportunity, and Personnel Economics in the American Civil War

PubMed Central

Costa, Dora L.

2014-01-01

US Civil War data allow examinations of theories of leadership. By observing both leaders and followers during the war and 40 years after it, I establish that the most able became wartime leaders, that leading by example from the front was an effective strategy in reducing desertion rates, and that leaders later migrated to the larger cities because this is where their superior skills would have had the highest payoffs. I find mixed evidence on whether leaders were created or born. I find that US cities were magnets for the most able and provided training opportunities for both leaders and followers: Men might start in a low social status occupation in a city but then move to a higher status occupation. (JEL M50, N31) PMID:25221788

Crawler Transporter 2 (CT-2) Trek from Pad 39B to VAB

NASA Image and Video Library

2017-03-21

Crawler-transporter 2 (CT-2) moves slowly along the crawlerway on its way back to the Vehicle Assembly Building (in view in the background) at NASA's Kennedy Space Center in Florida. Water sprayed by a truck in front to reduce dust creates a small rainbow. The crawler took a trip to the Pad A/B split to test upgrades recently completed that will allow the giant vehicle to handle the load of the agency's Space Launch System rocket and Orion spacecraft atop the mobile launcher. The Ground Systems Development and Operations Program oversaw upgrades to the 50-year-old CT-2. New generators, gear assemblies, jacking, equalizing and leveling (JEL) hydraulic cylinders, roller bearings and brakes were installed, and other components were upgraded to prepare for Exploration Mission 1.

Changing the diagnostic criteria for myocardial infarction in patients with a suspected heart attack affects the measurement of 30 day mortality but not long term survival

PubMed Central

Packham, C; Gray, D; Weston, C; Large, A; Silcocks, P; Hampton, J

2002-01-01

Objectives: To explore the effects of alternative methods of defining myocardial infarction on the numbers and survival patterns of patients identified as having sustained a confirmed myocardial infarct. Design: An inclusive historical cohort of patients admitted with a suspected heart attack. Patients were recoded from raw clinical data (collected at the index admission) to the epidemiological definitions of myocardial infarction used by the Nottingham heart attack register (NHAR), the World Health Organization (MONICA), and the UK heart attack study. Setting: Single health district. Patients: The NHAR identified all patients admitted in 1992 with suspected myocardial infarction. Outcome measures: Survival at 30 days and four year postdischarge. Results: 2739 patients were identified, of whom 90% survived to discharge. Recoding increased the numbers of patients defined as having confirmed myocardial infarction from 26% under the original NHAR classification to 69%, depending on the classification system used. In confirmed myocardial infarction, subsequent 30 day survival from admission varied from 77–86% depending on the classification system; four year survival after discharge was not affected. The distribution of important prognostic variables differed significantly between groups of patients with confirmed myocardial infarction defined by different systems. Patients with suspected but unconfirmed myocardial infarction under all classification systems had a worse postdischarge mortality. Conclusions: The classification system used had a substantial effect on the numbers of patients identified as having had a myocardial infarct, and on the 30 day survival. There were significant numbers of patients with more atypical presentations, not labelled as myocardial infarction, who did badly following discharge. More research is needed on these patients. PMID:12231586

Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination.

PubMed

Sørensen, Lauge; Nielsen, Mads

2018-05-15

The International Challenge for Automated Prediction of MCI from MRI data offered independent, standardized comparison of machine learning algorithms for multi-class classification of normal control (NC), mild cognitive impairment (MCI), converting MCI (cMCI), and Alzheimer's disease (AD) using brain imaging and general cognition. We proposed to use an ensemble of support vector machines (SVMs) that combined bagging without replacement and feature selection. SVM is the most commonly used algorithm in multivariate classification of dementia, and it was therefore valuable to evaluate the potential benefit of ensembling this type of classifier. The ensemble SVM, using either a linear or a radial basis function (RBF) kernel, achieved multi-class classification accuracies of 55.6% and 55.0% in the challenge test set (60 NC, 60 MCI, 60 cMCI, 60 AD), resulting in a third place in the challenge. Similar feature subset sizes were obtained for both kernels, and the most frequently selected MRI features were the volumes of the two hippocampal subregions left presubiculum and right subiculum. Post-challenge analysis revealed that enforcing a minimum number of selected features and increasing the number of ensemble classifiers improved classification accuracy up to 59.1%. The ensemble SVM outperformed single SVM classifications consistently in the challenge test set. Ensemble methods using bagging and feature selection can improve the performance of the commonly applied SVM classifier in dementia classification. This resulted in competitive classification accuracies in the International Challenge for Automated Prediction of MCI from MRI data. Copyright © 2018 Elsevier B.V. All rights reserved.

40 CFR 51.350 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-07-01

... population is allowed as long as an equal number of non-urban residents of the MSA containing the subject... monoxide (CO) nonattainment areas, depending upon population and nonattainment classification or design value. (a) Nonattainment area classification and population criteria. (1) States or areas within an...

40 CFR 51.350 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-07-01

... population is allowed as long as an equal number of non-urban residents of the MSA containing the subject... monoxide (CO) nonattainment areas, depending upon population and nonattainment classification or design value. (a) Nonattainment area classification and population criteria. (1) States or areas within an...

40 CFR 51.350 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-07-01

... population is allowed as long as an equal number of non-urban residents of the MSA containing the subject... monoxide (CO) nonattainment areas, depending upon population and nonattainment classification or design value. (a) Nonattainment area classification and population criteria. (1) States or areas within an...

40 CFR 51.350 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-07-01

... population is allowed as long as an equal number of non-urban residents of the MSA containing the subject... monoxide (CO) nonattainment areas, depending upon population and nonattainment classification or design value. (a) Nonattainment area classification and population criteria. (1) States or areas within an...

14 CFR 19-2 - Maintenance of data.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Operating Statistics Classifications Sec. 19-2 Maintenance of data. (a) Each air carrier required to file... in accordance with the uniform classifications prescribed. Codes are prescribed for each operating... flight numbers. The second grouping requires that the enplanement/deplanement information be broken out...

48 CFR 204.7101 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Definitions. Accounting classification reference number (ACRN) means any combination of a two position alpha/numeric code used as a method of relating the accounting classification citation to detailed line item... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false Definitions. 204.7101...

Divorcing Strain Classification from Species Names.

PubMed

Baltrus, David A

2016-06-01

Confusion about strain classification and nomenclature permeates modern microbiology. Although taxonomists have traditionally acted as gatekeepers of order, the numbers of, and speed at which, new strains are identified has outpaced the opportunity for professional classification for many lineages. Furthermore, the growth of bioinformatics and database-fueled investigations have placed metadata curation in the hands of researchers with little taxonomic experience. Here I describe practical challenges facing modern microbial taxonomy, provide an overview of complexities of classification for environmentally ubiquitous taxa like Pseudomonas syringae, and emphasize that classification can be independent of nomenclature. A move toward implementation of relational classification schemes based on inherent properties of whole genomes could provide sorely needed continuity in how strains are referenced across manuscripts and data sets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

PubMed

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance (similarity) measures. Results with the larger consistency will be more reliable.

Numeric pathologic lymph node classification shows prognostic superiority to topographic pN classification in esophageal squamous cell carcinoma.

PubMed

Sugawara, Kotaro; Yamashita, Hiroharu; Uemura, Yukari; Mitsui, Takashi; Yagi, Koichi; Nishida, Masato; Aikou, Susumu; Mori, Kazuhiko; Nomura, Sachiyo; Seto, Yasuyuki

2017-10-01

The current eighth tumor node metastasis lymph node category pathologic lymph node staging system for esophageal squamous cell carcinoma is based solely on the number of metastatic nodes and does not consider anatomic distribution. We aimed to assess the prognostic capability of the eighth tumor node metastasis pathologic lymph node staging system (numeric-based) compared with the 11th Japan Esophageal Society (topography-based) pathologic lymph node staging system in patients with esophageal squamous cell carcinoma. We retrospectively reviewed the clinical records of 289 patients with esophageal squamous cell carcinoma who underwent esophagectomy with extended lymph node dissection during the period from January 2006 through June 2016. We compared discrimination abilities for overall survival, recurrence-free survival, and cancer-specific survival between these 2 staging systems using C-statistics. The median number of dissected and metastatic nodes was 61 (25% to 75% quartile range, 45 to 79) and 1 (25% to 75% quartile range, 0 to 3), respectively. The eighth tumor node metastasis pathologic lymph node staging system had a greater ability to accurately determine overall survival (C-statistics: tumor node metastasis classification, 0.69, 95% confidence interval, 0.62-0.76; Japan Esophageal Society classification; 0.65, 95% confidence interval, 0.58-0.71; P = .014) and cancer-specific survival (C-statistics: tumor node metastasis classification, 0.78, 95% confidence interval, 0.70-0.87; Japan Esophageal Society classification; 0.72, 95% confidence interval, 0.64-0.80; P = .018). Rates of total recurrence rose as the eighth tumor node metastasis pathologic lymph node stage increased, while stratification of patients according to the topography-based node classification system was not feasible. Numeric nodal staging is an essential tool for stratifying the oncologic outcomes of patients with esophageal squamous cell carcinoma even in the cohort in which adequate numbers of lymph nodes were harvested. Copyright © 2017 Elsevier Inc. All rights reserved.

Hydrologic Landscape Regionalisation Using Deductive Classification and Random Forests

PubMed Central

Brown, Stuart C.; Lester, Rebecca E.; Versace, Vincent L.; Fawcett, Jonathon; Laurenson, Laurie

2014-01-01

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents. PMID:25396410

Hydrologic landscape regionalisation using deductive classification and random forests.

PubMed

Brown, Stuart C; Lester, Rebecca E; Versace, Vincent L; Fawcett, Jonathon; Laurenson, Laurie

2014-01-01

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis.

PubMed

Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir M; Helvie, Mark A; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

Hybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review.

PubMed

Hong, Keum-Shik; Khan, Muhammad Jawad

2017-01-01

In this article, non-invasive hybrid brain-computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain-computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

PubMed Central

Hong, Keum-Shik; Khan, Muhammad Jawad

2017-01-01

In this article, non-invasive hybrid brain–computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain–computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided. PMID:28790910

Research Support for the Laboratory for Lightwave Technology

DTIC Science & Technology

1992-12-31

34 .. . ."/ 12a. DISTRIBUTION AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE UNLIMITED 13. ABSTRACT (Mawimum 200words) 4 SEE ATTACHED ABSTRACT DT I 14. SUBJECT...8217TERMS 15. NUMBER OF PAGES 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT...temperature ceramic nano- phase single crystal oxides that may be produced at a high rate . The synthesis of both glasses and ceramics using novel techniques

41 CFR 105-62.102 - Authority to originally classify.

Code of Federal Regulations, 2013 CFR

2013-07-01

... originally classify. (a) Top secret, secret, and confidential. The authority to originally classify information as Top Secret, Secret, or Confidential may be exercised only by the Administrator and is delegable... classification authority. Delegations of original classification authority are limited to the minimum number...

41 CFR 105-62.102 - Authority to originally classify.

Code of Federal Regulations, 2011 CFR

2011-01-01

... originally classify. (a) Top secret, secret, and confidential. The authority to originally classify information as Top Secret, Secret, or Confidential may be exercised only by the Administrator and is delegable... classification authority. Delegations of original classification authority are limited to the minimum number...

41 CFR 105-62.102 - Authority to originally classify.

Code of Federal Regulations, 2014 CFR

2014-01-01

... originally classify. (a) Top secret, secret, and confidential. The authority to originally classify information as Top Secret, Secret, or Confidential may be exercised only by the Administrator and is delegable... classification authority. Delegations of original classification authority are limited to the minimum number...

Re-visiting protein-centric two-tier classification of existing DNA-protein complexes

PubMed Central

2012-01-01

Background Precise DNA-protein interactions play most important and vital role in maintaining the normal physiological functioning of the cell, as it controls many high fidelity cellular processes. Detailed study of the nature of these interactions has paved the way for understanding the mechanisms behind the biological processes in which they are involved. Earlier in 2000, a systematic classification of DNA-protein complexes based on the structural analysis of the proteins was proposed at two tiers, namely groups and families. With the advancement in the number and resolution of structures of DNA-protein complexes deposited in the Protein Data Bank, it is important to revisit the existing classification. Results On the basis of the sequence analysis of DNA binding proteins, we have built upon the protein centric, two-tier classification of DNA-protein complexes by adding new members to existing families and making new families and groups. While classifying the new complexes, we also realised the emergence of new groups and families. The new group observed was where β-propeller was seen to interact with DNA. There were 34 SCOP folds which were observed to be present in the complexes of both old and new classifications, whereas 28 folds are present exclusively in the new complexes. Some new families noticed were NarL transcription factor, Z-α DNA binding proteins, Forkhead transcription factor, AP2 protein, Methyl CpG binding protein etc. Conclusions Our results suggest that with the increasing number of availability of DNA-protein complexes in Protein Data Bank, the number of families in the classification increased by approximately three fold. The folds present exclusively in newly classified complexes is suggestive of inclusion of proteins with new function in new classification, the most populated of which are the folds responsible for DNA damage repair. The proposed re-visited classification can be used to perform genome-wide surveys in the genomes of interest for the presence of DNA-binding proteins. Further analysis of these complexes can aid in developing algorithms for identifying DNA-binding proteins and their family members from mere sequence information. PMID:22800292

Re-visiting protein-centric two-tier classification of existing DNA-protein complexes.

PubMed

Malhotra, Sony; Sowdhamini, Ramanathan

2012-07-16

Precise DNA-protein interactions play most important and vital role in maintaining the normal physiological functioning of the cell, as it controls many high fidelity cellular processes. Detailed study of the nature of these interactions has paved the way for understanding the mechanisms behind the biological processes in which they are involved. Earlier in 2000, a systematic classification of DNA-protein complexes based on the structural analysis of the proteins was proposed at two tiers, namely groups and families. With the advancement in the number and resolution of structures of DNA-protein complexes deposited in the Protein Data Bank, it is important to revisit the existing classification. On the basis of the sequence analysis of DNA binding proteins, we have built upon the protein centric, two-tier classification of DNA-protein complexes by adding new members to existing families and making new families and groups. While classifying the new complexes, we also realised the emergence of new groups and families. The new group observed was where β-propeller was seen to interact with DNA. There were 34 SCOP folds which were observed to be present in the complexes of both old and new classifications, whereas 28 folds are present exclusively in the new complexes. Some new families noticed were NarL transcription factor, Z-α DNA binding proteins, Forkhead transcription factor, AP2 protein, Methyl CpG binding protein etc. Our results suggest that with the increasing number of availability of DNA-protein complexes in Protein Data Bank, the number of families in the classification increased by approximately three fold. The folds present exclusively in newly classified complexes is suggestive of inclusion of proteins with new function in new classification, the most populated of which are the folds responsible for DNA damage repair. The proposed re-visited classification can be used to perform genome-wide surveys in the genomes of interest for the presence of DNA-binding proteins. Further analysis of these complexes can aid in developing algorithms for identifying DNA-binding proteins and their family members from mere sequence information.

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.

Vlsi implementation of flexible architecture for decision tree classification in data mining

NASA Astrophysics Data System (ADS)

Sharma, K. Venkatesh; Shewandagn, Behailu; Bhukya, Shankar Nayak

2017-07-01

The Data mining algorithms have become vital to researchers in science, engineering, medicine, business, search and security domains. In recent years, there has been a terrific raise in the size of the data being collected and analyzed. Classification is the main difficulty faced in data mining. In a number of the solutions developed for this problem, most accepted one is Decision Tree Classification (DTC) that gives high precision while handling very large amount of data. This paper presents VLSI implementation of flexible architecture for Decision Tree classification in data mining using c4.5 algorithm.

Tabu search and binary particle swarm optimization for feature selection using microarray data.

PubMed

Chuang, Li-Yeh; Yang, Cheng-Huei; Yang, Cheng-Hong

2009-12-01

Gene expression profiles have great potential as a medical diagnosis tool because they represent the state of a cell at the molecular level. In the classification of cancer type research, available training datasets generally have a fairly small sample size compared to the number of genes involved. This fact poses an unprecedented challenge to some classification methodologies due to training data limitations. Therefore, a good selection method for genes relevant for sample classification is needed to improve the predictive accuracy, and to avoid incomprehensibility due to the large number of genes investigated. In this article, we propose to combine tabu search (TS) and binary particle swarm optimization (BPSO) for feature selection. BPSO acts as a local optimizer each time the TS has been run for a single generation. The K-nearest neighbor method with leave-one-out cross-validation and support vector machine with one-versus-rest serve as evaluators of the TS and BPSO. The proposed method is applied and compared to the 11 classification problems taken from the literature. Experimental results show that our method simplifies features effectively and either obtains higher classification accuracy or uses fewer features compared to other feature selection methods.

An Ant Colony Optimization Based Feature Selection for Web Page Classification

PubMed Central

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods. PMID:25136678

Single classifier, OvO, OvA and RCC multiclass classification method in handheld based smartphone gait identification

NASA Astrophysics Data System (ADS)

Raziff, Abdul Rafiez Abdul; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran

2017-10-01

Gait recognition is widely used in many applications. In the application of the gait identification especially in people, the number of classes (people) is many which may comprise to more than 20. Due to the large amount of classes, the usage of single classification mapping (direct classification) may not be suitable as most of the existing algorithms are mostly designed for the binary classification. Furthermore, having many classes in a dataset may result in the possibility of having a high degree of overlapped class boundary. This paper discusses the application of multiclass classifier mappings such as one-vs-all (OvA), one-vs-one (OvO) and random correction code (RCC) on handheld based smartphone gait signal for person identification. The results is then compared with a single J48 decision tree for benchmark. From the result, it can be said that using multiclass classification mapping method thus partially improved the overall accuracy especially on OvO and RCC with width factor more than 4. For OvA, the accuracy result is worse than a single J48 due to a high number of classes.

Tumor taxonomy for the developmental lineage classification of neoplasms

PubMed Central

Berman, Jules J

2004-01-01

Background The new "Developmental lineage classification of neoplasms" was described in a prior publication. The classification is simple (the entire hierarchy is described with just 39 classifiers), comprehensive (providing a place for every tumor of man), and consistent with recent attempts to characterize tumors by cytogenetic and molecular features. A taxonomy is a list of the instances that populate a classification. The taxonomy of neoplasia attempts to list every known term for every known tumor of man. Methods The taxonomy provides each concept with a unique code and groups synonymous terms under the same concept. A Perl script validated successive drafts of the taxonomy ensuring that: 1) each term occurs only once in the taxonomy; 2) each term occurs in only one tumor class; 3) each concept code occurs in one and only one hierarchical position in the classification; and 4) the file containing the classification and taxonomy is a well-formed XML (eXtensible Markup Language) document. Results The taxonomy currently contains 122,632 different terms encompassing 5,376 neoplasm concepts. Each concept has, on average, 23 synonyms. The taxonomy populates "The developmental lineage classification of neoplasms," and is available as an XML file, currently 9+ Megabytes in length. A representation of the classification/taxonomy listing each term followed by its code, followed by its full ancestry, is available as a flat-file, 19+ Megabytes in length. The taxonomy is the largest nomenclature of neoplasms, with more than twice the number of neoplasm names found in other medical nomenclatures, including the 2004 version of the Unified Medical Language System, the Systematized Nomenclature of Medicine Clinical Terminology, the National Cancer Institute's Thesaurus, and the International Classification of Diseases Oncolology version. Conclusions This manuscript describes a comprehensive taxonomy of neoplasia that collects synonymous terms under a unique code number and assigns each tumor to a single class within the tumor hierarchy. The entire classification and taxonomy are available as open access files (in XML and flat-file formats) with this article. PMID:15571625

Improved Cr II log(gf)s and Cr Abundances in the Photospheres of the Sun and Metal-Poor Star HD 84937

NASA Astrophysics Data System (ADS)

Lawler, James E.; Sneden, Chris; Nave, Gillian; Den Hartog, Elizabeth; Emrahoglu, Nuri; Cowan, John J.

2017-01-01

New laser induced fluorescence (LIF) data for eight levels of singly ionized chromium (Cr) and emission branching fraction (BF) measurements for 183 lines of the second spectrum of chromium (Cr II) are reported. A goal of this study is to reconcile Solar and stellar Cr abundance values based on Cr I and Cr II lines. Analyses of eighteen spectra from three Fourier Transform Spectrometers supplemented with ultraviolet spectra from a high resolution echelle spectrometer yield the BF measurements. Radiative lifetimes from LIF measurements are used to convert the BFs to absolute transition probabilities. These new laboratory data are applied to determine the Cr abundance log eps in the Sun and metal-poor star HD 84937. The mean result in the Sun is = 5.624 ± 0.009 compared to = 5.644 ± 0.006 on a scale with the H abundance log eps(H) = 12. Similarily the photosphere of HD 84937 is found to be in Saha balance with = 3.417 ± 0.006 and 0 eV) > = 3.374 ± 0.011 for this dwarf star. The resonance (E.P. = 0 eV) lines of Cr I reveal overionization of the ground level of neutral Cr. We find a correlation of Cr with the iron-peak element Ti, suggesting an associated or related nucleosynthetic production. Four iron-peak elements (Cr along with Ti, V and Sc) appear to have a similar (or correlated) production history - other iron-peak elements appear not to be associated with Cr.This work is supported in part by NASA grant NNX16AE96G (J.E.L.), by NSF grant AST-1516182 (J.E.L. & E.D.H.), by NASA interagency agreement NNH10AN381 (G.N.), and NSF grant AST-1211585 (C.S.). Postdoctoral research support for N. E. is from the Technological and Scientific Research Council of Turkey (TUBITAK).

SVM-based tree-type neural networks as a critic in adaptive critic designs for control.

PubMed

Deb, Alok Kanti; Jayadeva; Gopal, Madan; Chandra, Suresh

2007-07-01

In this paper, we use the approach of adaptive critic design (ACD) for control, specifically, the action-dependent heuristic dynamic programming (ADHDP) method. A least squares support vector machine (SVM) regressor has been used for generating the control actions, while an SVM-based tree-type neural network (NN) is used as the critic. After a failure occurs, the critic and action are retrained in tandem using the failure data. Failure data is binary classification data, where the number of failure states are very few as compared to the number of no-failure states. The difficulty of conventional multilayer feedforward NNs in learning this type of classification data has been overcome by using the SVM-based tree-type NN, which due to its feature to add neurons to learn misclassified data, has the capability to learn any binary classification data without a priori choice of the number of neurons or the structure of the network. The capability of the trained controller to handle unforeseen situations is demonstrated.

Classification of almost toric singularities of Lagrangian foliations

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

Izosimov, Anton M

2011-07-31

The topological classification is given of almost toric singularities of integrable Hamiltonian systems with a large number of degrees of freedom, that is, of nondegenerate singularities without hyperbolic components. A descriptive geometric model is constructed, which makes it possible to perform effective calculations. Bibliography: 10 titles.

Test Operation Procedure (TOP) 01-1-010A Vehicle Test Course Severity (Surface Roughness)

DTIC Science & Technology

2017-12-12

Department of Agriculture (USDA) classifications, respectively. TABLE 10. PARTICLE SIZE CLASSES CLASS SIZE Cobble and Gravel >4.75 mm particle diameter...ABBREVIATIONS. USCS Unified Soil Classification System USDA United States Department of Agriculture UTM Universal Transverse Mercator WNS wave number

1961-1968 New Construction Report.

ERIC Educational Resources Information Center

National Association of Physical Plant Administrators of Universities and Colleges, Richmond, IN.

137 NAPPA colleges and universities provided data for this summary. Projects are summarized by thirteen building classifications. Under each classification the following information headings are used--(1) name of institution, (2) project completion date, (3) gross square feet, (4) net assignable area, (5) construction costs, (6) number of stories,…

Heuristic Classification. Technical Report Number 12.

ERIC Educational Resources Information Center

Clancey, William J.

A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic…

Analysis of steranes and triterpanes in geolipid extracts by automatic classification of mass spectra

NASA Technical Reports Server (NTRS)

Wardroper, A. M. K.; Brooks, P. W.; Humberston, M. J.; Maxwell, J. R.

1977-01-01

A computer method is described for the automatic classification of triterpanes and steranes into gross structural type from their mass spectral characteristics. The method has been applied to the spectra obtained by gas-chromatographic/mass-spectroscopic analysis of two mixtures of standards and of hydrocarbon fractions isolated from Green River and Messel oil shales. Almost all of the steranes and triterpanes identified previously in both shales were classified, in addition to a number of new components. The results indicate that classification of such alkanes is possible with a laboratory computer system. The method has application to diagenesis and maturation studies as well as to oil/oil and oil/source rock correlations in which rapid screening of large numbers of samples is required.

Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

PubMed

Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

2016-12-05

High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.

Multi-factorial analysis of class prediction error: estimating optimal number of biomarkers for various classification rules.

PubMed

Khondoker, Mizanur R; Bachmann, Till T; Mewissen, Muriel; Dickinson, Paul; Dobrzelecki, Bartosz; Campbell, Colin J; Mount, Andrew R; Walton, Anthony J; Crain, Jason; Schulze, Holger; Giraud, Gerard; Ross, Alan J; Ciani, Ilenia; Ember, Stuart W J; Tlili, Chaker; Terry, Jonathan G; Grant, Eilidh; McDonnell, Nicola; Ghazal, Peter

2010-12-01

Machine learning and statistical model based classifiers have increasingly been used with more complex and high dimensional biological data obtained from high-throughput technologies. Understanding the impact of various factors associated with large and complex microarray datasets on the predictive performance of classifiers is computationally intensive, under investigated, yet vital in determining the optimal number of biomarkers for various classification purposes aimed towards improved detection, diagnosis, and therapeutic monitoring of diseases. We investigate the impact of microarray based data characteristics on the predictive performance for various classification rules using simulation studies. Our investigation using Random Forest, Support Vector Machines, Linear Discriminant Analysis and k-Nearest Neighbour shows that the predictive performance of classifiers is strongly influenced by training set size, biological and technical variability, replication, fold change and correlation between biomarkers. Optimal number of biomarkers for a classification problem should therefore be estimated taking account of the impact of all these factors. A database of average generalization errors is built for various combinations of these factors. The database of generalization errors can be used for estimating the optimal number of biomarkers for given levels of predictive accuracy as a function of these factors. Examples show that curves from actual biological data resemble that of simulated data with corresponding levels of data characteristics. An R package optBiomarker implementing the method is freely available for academic use from the Comprehensive R Archive Network (http://www.cran.r-project.org/web/packages/optBiomarker/).

Emesis and Defecations Induced by the 5-Hydroxytryptamine (5-HT3) Receptor Anatagonist Zacopride in the Ferret

DTIC Science & Technology

1990-02-16

TERMS 8. NUMBER OF PAGES 8 16. PRICE CODE 17 SECURITY CLASSIFICATION is. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF OP...the Defense Nuclear erties, i.e., granisetron [BRL43694; Endo-N-[9-methyl-9-aza- Agency has been given or should be inferred. Research was conducted...BMY25801, batanopride; BRL43694, granisetron ; GI, gastrointestinal; ACh, acetylcholine. 1034 1990 Emetic Properties of Zacopnde 1035 benzamide HCI; Gylys et

A Review of Equation of State Models, Chemical Equilibrium Calculations and CERV Code Requirements for SHS Detonation Modelling

DTIC Science & Technology

2009-10-01

parameters for a large number of species. These authors provide many sample calculations with the JCZS database incorporated in CHEETAH 2.0, including...FORM (highest classification of Title, Abstract, Keywords) DOCUMENT CONTROL DATA (Security classification of title, body of abstract and...CLASSIFICATION OF FORM 13. ABSTRACT (a brief and factual summary of the document. It may also appear elsewhere in the body of the document itself

Role of Epidermal Growth Factor Receptors and Their Ligands in Normal Mammary Epithelial and Breast Cancer Cells

DTIC Science & Technology

1996-07-01

UNCLASSIFIED AD NUMBER ADB216343 NEW LIMITATION CHANGE TO Approved for public release, distribution unlimited FROM Distribution authorized to U.S...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 Limited NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39-1 8 DISCLAIMER

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

The Performance of Wavelets for Data Compression in Selected Military Applications

DTIC Science & Technology

1990-02-23

reported. 14. SUBJECT TERMS IS. NUMBER OF PAGES 56 16. PRICE CODE 17. SICURITY CLASSIFICATION I lL SECURITY CLASSIFICATION 19. SECURITY CLASSIF4CATION 20...compression ratio is conservative in the sense that it understates the theoretical compression ratio by taking into account the actual memory...effect of reducing the compresion ratios quoted in the table by the factor 7.8/8.0 = 0.975. AWARE, Inc. 14 registration was then calculated for each

The Effects of Evaluation and Production Blocking on the Performance of Brainstorming Groups

DTIC Science & Technology

1992-08-01

NUMBER OF PAGES 701 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LMIITATION OF ABSTRACT OF...special interest group. Once again, the people in the above examples share many things in common such as a sense of civil duty, an employer, a love for a...people respond differently in the presence of others, a phenomenon Zajonc refers to as compresence . In group settings, social facilitation can be

Discrimination of different sub-basins on Tajo River based on water influence factor

NASA Astrophysics Data System (ADS)

Bermudez, R.; Gascó, J. M.; Tarquis, A. M.; Saa-Requejo, A.

2009-04-01

Numeric taxonomy has been applied to classify Tajo basin water (Spain) till Portugal border. Several stations, a total of 52, that estimate 15 water variables have been used in this study. The different groups have been obtained applying a Euclidean distance among stations (distance classification) and a Euclidean distance between each station and the centroid estimated among them (centroid classification), varying the number of parameters and with or without variable typification. In order to compare the classification a log-log relation has been established, between number of groups created and distances, to select the best one. It has been observed that centroid classification is more appropriate following in a more logic way the natural constrictions than the minimum distance among stations. Variable typification doesn't improve the classification except when the centroid method is applied. Taking in consideration the ions and the sum of them as variables, the classification improved. Stations are grouped based on electric conductivity (CE), total anions (TA), total cations (TC) and ions ratio (Na/Ca and Mg/Ca). For a given classification and comparing the different groups created a certain variation in ions concentration and ions ratio are observed. However, the variation in each ion among groups is different depending on the case. For the last group, regardless the classification, the increase in all ions is general. Comparing the dendrograms, and groups that originated, Tajo river basin can be sub dived in five sub-basins differentiated by the main influence on water: 1. With a higher ombrogenic influence (rain fed). 2. With ombrogenic and pedogenic influence (rain and groundwater fed). 3. With pedogenic influence. 4. With lithogenic influence (geological bedrock). 5. With a higher ombrogenic and lithogenic influence added.

Spectral-Spatial Classification of Hyperspectral Images Using Hierarchical Optimization

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.

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.

BOREAS TE-18 Landsat TM Maximum Likelihood Classification Image of the NSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David

2000-01-01

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 20-Aug-1988 was used to derive this classification. A standard supervised maximum likelihood classification approach was used to produce this classification. The data are provided in a binary image format file. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Galaxy Zoo 1: data release of morphological classifications for nearly 900 000 galaxies

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

Linott, C.; Slosar, A.; Lintott, C.

Morphology is a powerful indicator of a galaxy's dynamical and merger history. It is strongly correlated with many physical parameters, including mass, star formation history and the distribution of mass. The Galaxy Zoo project collected simple morphological classifications of nearly 900,000 galaxies drawn from the Sloan Digital Sky Survey, contributed by hundreds of thousands of volunteers. This large number of classifications allows us to exclude classifier error, and measure the influence of subtle biases inherent in morphological classification. This paper presents the data collected by the project, alongside measures of classification accuracy and bias. The data are now publicly availablemore » and full catalogues can be downloaded in electronic format from http://data.galaxyzoo.org.« less

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.

10 CFR 95.37 - Classification and preparation of documents.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Information must contain the identity of the source document or the classification guide, including the agency.../Exemption) Classifier: (Name/Title/Number) (2) For Restricted Data documents: (i) Identity of the classifier. The identity of the classifier must be shown by completion of the “Derivative Classifier” line. The...

10 CFR 95.37 - Classification and preparation of documents.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Information must contain the identity of the source document or the classification guide, including the agency.../Exemption) Classifier: (Name/Title/Number) (2) For Restricted Data documents: (i) Identity of the classifier. The identity of the classifier must be shown by completion of the “Derivative Classifier” line. The...

10 CFR 95.37 - Classification and preparation of documents.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Information must contain the identity of the source document or the classification guide, including the agency.../Exemption) Classifier: (Name/Title/Number) (2) For Restricted Data documents: (i) Identity of the classifier. The identity of the classifier must be shown by completion of the “Derivative Classifier” line. The...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... weighting factors to reflect changes in— (1) Treatment patterns; (2) Technology; (3) Number of discharges... 42 Public Health 2 2013-10-01 2013-10-01 false Patient classification system. 412.620 Section 412... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2012 CFR

2012-10-01

... weighting factors to reflect changes in— (1) Treatment patterns; (2) Technology; (3) Number of discharges... 42 Public Health 2 2012-10-01 2012-10-01 false Patient classification system. 412.620 Section 412... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... weighting factors to reflect changes in— (1) Treatment patterns; (2) Technology; (3) Number of discharges... 42 Public Health 2 2014-10-01 2014-10-01 false Patient classification system. 412.620 Section 412... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix...

Cataloguing and Classification Section. Bibliographic Control Division. Papers.

ERIC Educational Resources Information Center

International Federation of Library Associations, The Hague (Netherlands).

Papers on cataloging, classification, and coding systems which were presented at the 1982 International Federation of Library Associations (IFLA) conference include: (1) "Numbering and Coding Systems for Bibliographic Control in Use in North America" by Lois Mai Chan (United States); (2) "A Project Undertaken by the Library of…

77 FR 38627 - Agency Information Collection Activities; Submission to OMB for Review and Approval; Comment...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

....regulations.gov . Title: Criteria for Classification of Solid Waste Disposal Facilities and Practices (Renewal... Classification of Solid Waste Disposal Facilities and Practices'' (40 CFR part 257) are self implementing.... Respondents/Affected Entities: Private Solid Waste Disposal Facilities, States. Estimated Number of...

Error Detection in Mechanized Classification Systems

ERIC Educational Resources Information Center

Hoyle, W. G.

1976-01-01

When documentary material is indexed by a mechanized classification system, and the results judged by trained professionals, the number of documents in disagreement, after suitable adjustment, defines the error rate of the system. In a test case disagreement was 22 percent and, of this 22 percent, the computer correctly identified two-thirds of…

Multiclass fMRI data decoding and visualization using supervised self-organizing maps.

PubMed

Hausfeld, Lars; Valente, Giancarlo; Formisano, Elia

2014-08-01

When multivariate pattern decoding is applied to fMRI studies entailing more than two experimental conditions, a most common approach is to transform the multiclass classification problem into a series of binary problems. Furthermore, for decoding analyses, classification accuracy is often the only outcome reported although the topology of activation patterns in the high-dimensional features space may provide additional insights into underlying brain representations. Here we propose to decode and visualize voxel patterns of fMRI datasets consisting of multiple conditions with a supervised variant of self-organizing maps (SSOMs). Using simulations and real fMRI data, we evaluated the performance of our SSOM-based approach. Specifically, the analysis of simulated fMRI data with varying signal-to-noise and contrast-to-noise ratio suggested that SSOMs perform better than a k-nearest-neighbor classifier for medium and large numbers of features (i.e. 250 to 1000 or more voxels) and similar to support vector machines (SVMs) for small and medium numbers of features (i.e. 100 to 600voxels). However, for a larger number of features (>800voxels), SSOMs performed worse than SVMs. When applied to a challenging 3-class fMRI classification problem with datasets collected to examine the neural representation of three human voices at individual speaker level, the SSOM-based algorithm was able to decode speaker identity from auditory cortical activation patterns. Classification performances were similar between SSOMs and other decoding algorithms; however, the ability to visualize decoding models and underlying data topology of SSOMs promotes a more comprehensive understanding of classification outcomes. We further illustrated this visualization ability of SSOMs with a re-analysis of a dataset examining the representation of visual categories in the ventral visual cortex (Haxby et al., 2001). This analysis showed that SSOMs could retrieve and visualize topography and neighborhood relations of the brain representation of eight visual categories. We conclude that SSOMs are particularly suited for decoding datasets consisting of more than two classes and are optimally combined with approaches that reduce the number of voxels used for classification (e.g. region-of-interest or searchlight approaches). Copyright © 2014. Published by Elsevier Inc.

[Implementation of cytology images classification--the Bethesda 2001 System--in a group of screened women from Podlaskie region--effect evaluation].

PubMed

Zbroch, Tomasz; Knapp, Paweł Grzegorz; Knapp, Piotr Andrzej

2007-09-01

Increasing knowledge concerning carcinogenesis within cervical epithelium has forced us to make continues modifications of cytology classification of the cervical smears. Eventually, new descriptions of the submicroscopic cytomorphological abnormalities have enabled the implementation of Bethesda System which was meant to take place of the former Papanicolaou classification although temporarily both are sometimes used simultaneously. The aim of this study was to compare results of these two classification systems in the aspect of diagnostic accuracy verified by further tests of the diagnostic algorithm for the cervical lesion evaluation. The study was conducted in the group of women selected from general population, the criteria being the place of living and cervical cancer age risk group, in the consecutive periods of mass screening in Podlaski region. The performed diagnostic tests have been based on the commonly used algorithm, as well as identical laboratory and methodological conditions. Performed assessment revealed comparable diagnostic accuracy of both analyzing classifications, verified by histological examination, although with marked higher specificity for dysplastic lesions with decreased number of HSIL results and increased diagnosis of LSILs. Higher number of performed colposcopies and biopsies were an additional consequence of TBS classification. Results based on Bethesda System made it possible to find the sources and reasons of abnormalities with much greater precision, which enabled causing agent treatment. Two evaluated cytology classification systems, although not much different, depicted higher potential of TBS and better, more effective communication between cytology laboratory and gynecologist, making reasonable implementation of The Bethesda System in the daily cytology screening work.

41 CFR 101-30.101-3 - National stock number.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 41 Public Contracts and Property Management 2 2011-07-01 2007-07-01 true National stock number....1-General § 101-30.101-3 National stock number. The national stock number (NSN) is the identifying number assigned to each item of supply. The NSN consists of the 4-digit Federal Supply Classification...

SAVINGS BY AND FOR THE POOR: A RESEARCH REVIEW AND AGENDA

PubMed Central

Karlan, Dean; Ratan, Aishwarya Lakshmi; Zinman, Jonathan

2014-01-01

The poor can and do save, but often use formal or informal instruments that have high risk, high cost, and limited functionality. This could lead to undersaving compared to a world without market or behavioral frictions. Undersaving can have important welfare consequences: variable consumption, low resilience to shocks, and foregone profitable investments. We lay out five sets of constraints that may hinder the adoption and effective usage of savings products and services by the poor: transaction costs, lack of trust and regulatory barriers, information and knowledge gaps, social constraints, and behavioral biases. We discuss each in theory, and then summarize related empirical evidence, with a focus on recent field experiments. We then put forward key open areas for research and practice. JEL Codes: D12, D91, G21, O16 PMID:25792764

Concurrent credit portfolio losses

PubMed Central

Sicking, Joachim; Schäfer, Rudi

2018-01-01

We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable portfolio loss correlations. Anticipated idiosyncratic effects turn out to be negligible. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector. JEL codes: C32, F34, G21, G32, H81. PMID:29425246

Concurrent credit portfolio losses.

PubMed

Sicking, Joachim; Guhr, Thomas; Schäfer, Rudi

2018-01-01

We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable portfolio loss correlations. Anticipated idiosyncratic effects turn out to be negligible. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector. JEL codes: C32, F34, G21, G32, H81.

Classification and authentication of unknown water samples using machine learning algorithms.

PubMed

Kundu, Palash K; Panchariya, P C; Kundu, Madhusree

2011-07-01

This paper proposes the development of water sample classification and authentication, in real life which is based on machine learning algorithms. The proposed techniques used experimental measurements from a pulse voltametry method which is based on an electronic tongue (E-tongue) instrumentation system with silver and platinum electrodes. E-tongue include arrays of solid state ion sensors, transducers even of different types, data collectors and data analysis tools, all oriented to the classification of liquid samples and authentication of unknown liquid samples. The time series signal and the corresponding raw data represent the measurement from a multi-sensor system. The E-tongue system, implemented in a laboratory environment for 6 numbers of different ISI (Bureau of Indian standard) certified water samples (Aquafina, Bisleri, Kingfisher, Oasis, Dolphin, and McDowell) was the data source for developing two types of machine learning algorithms like classification and regression. A water data set consisting of 6 numbers of sample classes containing 4402 numbers of features were considered. A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system. A proposed partial least squares (PLS) based classifier, which was dedicated as well; to authenticate a specific category of water sample evolved out as an integral part of the E-tongue instrumentation system. The developed PCA and PLS based E-tongue system emancipated an overall encouraging authentication percentage accuracy with their excellent performances for the aforesaid categories of water samples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Mechanical topological insulator in zero dimensions

NASA Astrophysics Data System (ADS)

Lera, Natalia; Alvarez, J. V.

2018-04-01

We study linear vibrational modes in finite isostatic Maxwell lattices, mechanical systems where the number of degrees of freedom matches the number of constraints. Recent progress in topological mechanics exploits the nontrivial topology of BDI class Hamiltonians in one dimenson and arising topological floppy modes at the edges. A finite frame, or zero-dimensional system, also exhibits a nonzero topological index according to the classification table. We construct mechanical insulating models in zero dimensions that complete the BDI classification in the available real space dimensions. We compute and interpret its nontrivial invariant Z2.

Vitamin D3 Analogues with Low Vitamin D Receptor Binding Affinity Regulate Chondrocyte Proliferation, Proteoglycan Synthesis, and Protein Kinase C Activity

DTIC Science & Technology

1997-07-11

REPORT DOCUMENTATION PAGE Form ApprovedOMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour...DISTRIBUTION CODE 13. ABSTRACT (Maximum 200 words) 14. SUBJECT TERMS 15. NUMBER OF PAGES 50 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY...CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF THIS PAGE OF ABSTRACT Standard Form 298(Rev. 2-89) (EG) Prescribed byANSI

National Dam Safety Program. Lake Monocan Dam (ID VA-12502), James River Basin, Allen Creek. Nelson County, Virginia. Phase I Inspection Report.

DTIC Science & Technology

1980-04-01

P 114 June 1978 Mr. W. Douglas Wright *Wiley and Wilson, Inc. 2310 Langhorne Road ’ :5 1973 Lvnchburg, Virginia 24505 & LSON, INC. LYNCHF.U1G. VA. Dv...CLASSIFICATION OF THIS P Dat Entered)’ " ’ READ INSTRUCTIO)NS REPORT DOCUMENTATION PAGE BEFORE COMPLETING FORM . REPORT NUMBER - 12. GOVT ACCESSION...OBSOLETE Unclassified -SECUnclassified OI P nd SECURITY CLASSIFICATION OF THIS PAGE (Wfen Dis Entered) SECURITY CLASSIFICATION OF INIS PAOE(Whe Data

AVHRR composite period selection for land cover classification

USGS Publications Warehouse

Maxwell, S.K.; Hoffer, R.M.; Chapman, P.L.

2002-01-01

Multitemporal satellite image datasets provide valuable information on the phenological characteristics of vegetation, thereby significantly increasing the accuracy of cover type classifications compared to single date classifications. However, the processing of these datasets can become very complex when dealing with multitemporal data combined with multispectral data. Advanced Very High Resolution Radiometer (AVHRR) biweekly composite data are commonly used to classify land cover over large regions. Selecting a subset of these biweekly composite periods may be required to reduce the complexity and cost of land cover mapping. The objective of our research was to evaluate the effect of reducing the number of composite periods and altering the spacing of those composite periods on classification accuracy. Because inter-annual variability can have a major impact on classification results, 5 years of AVHRR data were evaluated. AVHRR biweekly composite images for spectral channels 1-4 (visible, near-infrared and two thermal bands) covering the entire growing season were used to classify 14 cover types over the entire state of Colorado for each of five different years. A supervised classification method was applied to maintain consistent procedures for each case tested. Results indicate that the number of composite periods can be halved-reduced from 14 composite dates to seven composite dates-without significantly reducing overall classification accuracy (80.4% Kappa accuracy for the 14-composite data-set as compared to 80.0% for a seven-composite dataset). At least seven composite periods were required to ensure the classification accuracy was not affected by inter-annual variability due to climate fluctuations. Concentrating more composites near the beginning and end of the growing season, as compared to using evenly spaced time periods, consistently produced slightly higher classification values over the 5 years tested (average Kappa) of 80.3% for the heavy early/late case as compared to 79.0% for the alternate dataset case).

Ensemble of sparse classifiers for high-dimensional biological data.

PubMed

Kim, Sunghan; Scalzo, Fabien; Telesca, Donatello; Hu, Xiao

2015-01-01

Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature selection method has been proposed utilising the sparsity of high-dimensional biological data where a small subset of features accounts for most variance of the dataset. In this study we propose a new classification method for high-dimensional biological data, which performs both feature selection and classification within a single framework. Our proposed method utilises a sparse linear solution technique and the bootstrap aggregating algorithm. We tested its performance on four public mass spectrometry cancer datasets along with two other conventional classification techniques such as Support Vector Machines and Adaptive Boosting. The results demonstrate that our proposed method performs more accurate classification across various cancer datasets than those conventional classification techniques.

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.

C-fuzzy variable-branch decision tree with storage and classification error rate constraints

NASA Astrophysics Data System (ADS)

Yang, Shiueng-Bien

2009-10-01

The C-fuzzy decision tree (CFDT), which is based on the fuzzy C-means algorithm, has recently been proposed. The CFDT is grown by selecting the nodes to be split according to its classification error rate. However, the CFDT design does not consider the classification time taken to classify the input vector. Thus, the CFDT can be improved. We propose a new C-fuzzy variable-branch decision tree (CFVBDT) with storage and classification error rate constraints. The design of the CFVBDT consists of two phases-growing and pruning. The CFVBDT is grown by selecting the nodes to be split according to the classification error rate and the classification time in the decision tree. Additionally, the pruning method selects the nodes to prune based on the storage requirement and the classification time of the CFVBDT. Furthermore, the number of branches of each internal node is variable in the CFVBDT. Experimental results indicate that the proposed CFVBDT outperforms the CFDT and other methods.

Lauren classification and individualized chemotherapy in gastric cancer.

PubMed

Ma, Junli; Shen, Hong; Kapesa, Linda; Zeng, Shan

2016-05-01

Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.

Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization.

PubMed

Yuan, Yuan; Lin, Jianzhe; Wang, Qi

2016-12-01

Hyperspectral image (HSI) classification is a crucial issue in remote sensing. Accurate classification benefits a large number of applications such as land use analysis and marine resource utilization. But high data correlation brings difficulty to reliable classification, especially for HSI with abundant spectral information. Furthermore, the traditional methods often fail to well consider the spatial coherency of HSI that also limits the classification performance. To address these inherent obstacles, a novel spectral-spatial classification scheme is proposed in this paper. The proposed method mainly focuses on multitask joint sparse representation (MJSR) and a stepwise Markov random filed framework, which are claimed to be two main contributions in this procedure. First, the MJSR not only reduces the spectral redundancy, but also retains necessary correlation in spectral field during classification. Second, the stepwise optimization further explores the spatial correlation that significantly enhances the classification accuracy and robustness. As far as several universal quality evaluation indexes are concerned, the experimental results on Indian Pines and Pavia University demonstrate the superiority of our method compared with the state-of-the-art competitors.

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.

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

NASA Technical Reports Server (NTRS)

Abbey, Craig K.; Eckstein, Miguel P.

2002-01-01

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Aggregation of Sentinel-2 time series classifications as a solution for multitemporal analysis

NASA Astrophysics Data System (ADS)

Lewiński, Stanislaw; Nowakowski, Artur; Malinowski, Radek; Rybicki, Marcin; Kukawska, Ewa; Krupiński, Michał

2017-10-01

The general aim of this work was to elaborate efficient and reliable aggregation method that could be used for creating a land cover map at a global scale from multitemporal satellite imagery. The study described in this paper presents methods for combining results of land cover/land use classifications performed on single-date Sentinel-2 images acquired at different time periods. For that purpose different aggregation methods were proposed and tested on study sites spread on different continents. The initial classifications were performed with Random Forest classifier on individual Sentinel-2 images from a time series. In the following step the resulting land cover maps were aggregated pixel by pixel using three different combinations of information on the number of occurrences of a certain land cover class within a time series and the posterior probability of particular classes resulting from the Random Forest classification. From the proposed methods two are shown superior and in most cases were able to reach or outperform the accuracy of the best individual classifications of single-date images. Moreover, the aggregations results are very stable when used on data with varying cloudiness. They also enable to reduce considerably the number of cloudy pixels in the resulting land cover map what is significant advantage for mapping areas with frequent cloud coverage.

Intelligent topical sentiment analysis for the classification of e-learners and their topics of interest.

PubMed

Ravichandran, M; Kulanthaivel, G; Chellatamilan, T

2015-01-01

Every day, huge numbers of instant tweets (messages) are published on Twitter as it is one of the massive social media for e-learners interactions. The options regarding various interesting topics to be studied are discussed among the learners and teachers through the capture of ideal sources in Twitter. The common sentiment behavior towards these topics is received through the massive number of instant messages about them. In this paper, rather than using the opinion polarity of each message relevant to the topic, authors focus on sentence level opinion classification upon using the unsupervised algorithm named bigram item response theory (BIRT). It differs from the traditional classification and document level classification algorithm. The investigation illustrated in this paper is of threefold which are listed as follows: (1) lexicon based sentiment polarity of tweet messages; (2) the bigram cooccurrence relationship using naïve Bayesian; (3) the bigram item response theory (BIRT) on various topics. It has been proposed that a model using item response theory is constructed for topical classification inference. The performance has been improved remarkably using this bigram item response theory when compared with other supervised algorithms. The experiment has been conducted on a real life dataset containing different set of tweets and topics.

Aerodynamic Classification of Swept-Wing Ice Accretion

NASA Technical Reports Server (NTRS)

Broeren, Andy; Diebold, Jeff; Bragg, Mike

2013-01-01

The continued design, certification and safe operation of swept-wing airplanes in icing conditions rely on the advancement of computational and experimental simulation methods for higher fidelity results over an increasing range of aircraft configurations and performance, and icing conditions. The current state-of-the-art in icing aerodynamics is mainly built upon a comprehensive understanding of two-dimensional geometries that does not currently exist for fundamentally three-dimensional geometries such as swept wings. The purpose of this report is to describe what is known of iced-swept-wing aerodynamics and to identify the type of research that is required to improve the current understanding. Following the method used in a previous review of iced-airfoil aerodynamics, this report proposes a classification of swept-wing ice accretion into four groups based upon unique flowfield attributes. These four groups are: ice roughness, horn ice, streamwise ice, and spanwise-ridge ice. For all of the proposed ice-shape classifications, relatively little is known about the three-dimensional flowfield and even less about the effect of Reynolds number and Mach number on these flowfields. The classifications and supporting data presented in this report can serve as a starting point as new research explores swept-wing aerodynamics with ice shapes. As further results are available, it is expected that these classifications will need to be updated and revised.

Soils [Chapter 4.2

Treesearch

Daniel G. Neary; Johannes W. A. Langeveld

2015-01-01

Soils are crucial for profitable and sustainable biomass feedstock production. They provide nutrients and water, give support for plants, and provide habitat for enormous numbers of biota. There are several systems for soil classification. FAO has provided a generic classification system that was used for a global soil map (Bot et al., 2000). The USDA Natural Resources...

An Examination of the Changing Rates of Autism in Special Education

ERIC Educational Resources Information Center

Brock, Stephen E.

2006-01-01

Using U.S. Department of Education data, the current study examined changes in the rates of special education eligibility classifications. This was done to determine if classification substitution might be an explanation for increases in the number of students being found eligible for special education using the Autism criteria. Results reveal…

Emotion recognition from multichannel EEG signals using K-nearest neighbor classification.

PubMed

Li, Mi; Xu, Hongpei; Liu, Xingwang; Lu, Shengfu

2018-04-27

Many studies have been done on the emotion recognition based on multi-channel electroencephalogram (EEG) signals. This paper explores the influence of the emotion recognition accuracy of EEG signals in different frequency bands and different number of channels. We classified the emotional states in the valence and arousal dimensions using different combinations of EEG channels. Firstly, DEAP default preprocessed data were normalized. Next, EEG signals were divided into four frequency bands using discrete wavelet transform, and entropy and energy were calculated as features of K-nearest neighbor Classifier. The classification accuracies of the 10, 14, 18 and 32 EEG channels based on the Gamma frequency band were 89.54%, 92.28%, 93.72% and 95.70% in the valence dimension and 89.81%, 92.24%, 93.69% and 95.69% in the arousal dimension. As the number of channels increases, the classification accuracy of emotional states also increases, the classification accuracy of the gamma frequency band is greater than that of the beta frequency band followed by the alpha and theta frequency bands. This paper provided better frequency bands and channels reference for emotion recognition based on EEG.

Algorithmic framework for group analysis of differential equations and its application to generalized Zakharov-Kuznetsov equations

NASA Astrophysics Data System (ADS)

Huang, Ding-jiang; Ivanova, Nataliya M.

2016-02-01

In this paper, we explain in more details the modern treatment of the problem of group classification of (systems of) partial differential equations (PDEs) from the algorithmic point of view. More precisely, we revise the classical Lie algorithm of construction of symmetries of differential equations, describe the group classification algorithm and discuss the process of reduction of (systems of) PDEs to (systems of) equations with smaller number of independent variables in order to construct invariant solutions. The group classification algorithm and reduction process are illustrated by the example of the generalized Zakharov-Kuznetsov (GZK) equations of form ut +(F (u)) xxx +(G (u)) xyy +(H (u)) x = 0. As a result, a complete group classification of the GZK equations is performed and a number of new interesting nonlinear invariant models which have non-trivial invariance algebras are obtained. Lie symmetry reductions and exact solutions for two important invariant models, i.e., the classical and modified Zakharov-Kuznetsov equations, are constructed. The algorithmic framework for group analysis of differential equations presented in this paper can also be applied to other nonlinear PDEs.

Classification of reflection-symmetry-protected topological semimetals and nodal superconductors

NASA Astrophysics Data System (ADS)

Chiu, Ching-Kai; Schnyder, Andreas P.

2014-11-01

While the topological classification of insulators, semimetals, and superconductors in terms of nonspatial symmetries is well understood, less is known about topological states protected by crystalline symmetries, such as mirror reflections and rotations. In this work, we systematically classify topological semimetals and nodal superconductors that are protected, not only by nonspatial (i.e., global) symmetries, but also by a crystal reflection symmetry. We find that the classification crucially depends on (i) the codimension of the Fermi surface (nodal line or point) of the semimetal (superconductor), (ii) whether the mirror symmetry commutes or anticommutes with the nonspatial symmetries, and (iii) how the Fermi surfaces (nodal lines or points) transform under the mirror reflection and nonspatial symmetries. The classification is derived by examining all possible symmetry-allowed mass terms that can be added to the Bloch or Bogoliubov-de Gennes Hamiltonian in a given symmetry class and by explicitly deriving topological invariants. We discuss several examples of reflection-symmetry-protected topological semimetals and nodal superconductors, including topological crystalline semimetals with mirror Z2 numbers and topological crystalline nodal superconductors with mirror winding numbers.

Looking at the ICF and human communication through the lens of classification theory.

PubMed

Walsh, Regina

2011-08-01

This paper explores the insights that classification theory can provide about the application of the International Classification of Functioning, Disability and Health (ICF) to communication. It first considers the relationship between conceptual models and classification systems, highlighting that classification systems in speech-language pathology (SLP) have not historically been based on conceptual models of human communication. It then overviews the key concepts and criteria of classification theory. Applying classification theory to the ICF and communication raises a number of issues, some previously highlighted through clinical application. Six focus questions from classification theory are used to explore these issues, and to propose the creation of an ICF-related conceptual model of communicating for the field of communication disability, which would address some of the issues raised. Developing a conceptual model of communication for SLP purposes closely articulated with the ICF would foster productive intra-professional discourse, while at the same time allow the profession to continue to use the ICF for purposes in inter-disciplinary discourse. The paper concludes by suggesting the insights of classification theory can assist professionals to apply the ICF to communication with the necessary rigour, and to work further in developing a conceptual model of human communication.

Topographic, bioclimatic, and vegetation characteristics of three ecoregion classification systems in North America: Comparisons along continent-wide transects

USGS Publications Warehouse

Thompson, R.S.; Shafer, S.L.; Anderson, K.H.; Strickland, L.E.; Pelltier, R.T.; Bartlein, P.J.; Kerwin, M.W.

2005-01-01

Ecoregion classification systems are increasingly used for policy and management decisions, particularly among conservation and natural resource managers. A number of ecoregion classification systems are currently available, with each system defining ecoregions using different classification methods and different types of data. As a result, each classification system describes a unique set of ecoregions. To help potential users choose the most appropriate ecoregion system for their particular application, we used three latitudinal transects across North America to compare the boundaries and environmental characteristics of three ecoregion classification systems [Ku??chler, World Wildlife Fund (WWF), and Bailey]. A variety of variables were used to evaluate the three systems, including woody plant species richness, normalized difference in vegetation index (NDVI), and bioclimatic variables (e.g., mean temperature of the coldest month) along each transect. Our results are dominated by geographic patterns in temperature, which are generally aligned north-south, and in moisture, which are generally aligned east-west. In the west, the dramatic changes in physiography, climate, and vegetation impose stronger controls on ecoregion boundaries than in the east. The Ku??chler system has the greatest number of ecoregions on all three transects, but does not necessarily have the highest degree of internal consistency within its ecoregions with regard to the bioclimatic and species richness data. In general, the WWF system appears to track climatic and floristic variables the best of the three systems, but not in all regions on all transects. ?? 2005 Springer Science+Business Media, Inc.

Improving Generalization Based on l1-Norm Regularization for EEG-Based Motor Imagery Classification

PubMed Central

Zhao, Yuwei; Han, Jiuqi; Chen, Yushu; Sun, Hongji; Chen, Jiayun; Ke, Ang; Han, Yao; Zhang, Peng; Zhang, Yi; Zhou, Jin; Wang, Changyong

2018-01-01

Multichannel electroencephalography (EEG) is widely used in typical brain-computer interface (BCI) systems. In general, a number of parameters are essential for a EEG classification algorithm due to redundant features involved in EEG signals. However, the generalization of the EEG method is often adversely affected by the model complexity, considerably coherent with its number of undetermined parameters, further leading to heavy overfitting. To decrease the complexity and improve the generalization of EEG method, we present a novel l1-norm-based approach to combine the decision value obtained from each EEG channel directly. By extracting the information from different channels on independent frequency bands (FB) with l1-norm regularization, the method proposed fits the training data with much less parameters compared to common spatial pattern (CSP) methods in order to reduce overfitting. Moreover, an effective and efficient solution to minimize the optimization object is proposed. The experimental results on dataset IVa of BCI competition III and dataset I of BCI competition IV show that, the proposed method contributes to high classification accuracy and increases generalization performance for the classification of MI EEG. As the training set ratio decreases from 80 to 20%, the average classification accuracy on the two datasets changes from 85.86 and 86.13% to 84.81 and 76.59%, respectively. The classification performance and generalization of the proposed method contribute to the practical application of MI based BCI systems. PMID:29867307

Serum C-reactive protein level in COPD patients stratified according to GOLD 2011 grading classification

PubMed Central

Lin, Yi-Hua; Wang, Wan-Yu; Hu, Su-Xian; Shi, Yong-Hong

2016-01-01

Background and Objective: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2011 grading classification has been used to evaluate the severity of patients with chronic obstructive pulmonary disease (COPD). However, little is known about the relationship between the systemic inflammation and this classification. We aimed to study the relationship between serum CRP and the components of the GOLD 2011 grading classification. Methods: C-reactive protein (CRP) levels were measured in 391 clinically stable COPD patients and in 50 controls from June 2, 2015 to October 31, 2015 in the First Affiliated Hospital of Xiamen University. The association between CRP levels and the components of the GOLD 2011 grading classification were assessed. Results: Correlation was found with the following variables: GOLD 2011 group (0.240), age (0.227), pack year (0.136), forced expiratory volume in one second % predicted (FEV1%; -0.267), forced vital capacity % predicted (-0.210), number of acute exacerbations in the past year (0.265), number of hospitalized exacerbations in the past year (0.165), British medical Research Council dyspnoea scale (0.121), COPD assessment test score (CAT, 0.233). Using multivariate analysis, FEV1% and CAT score manifested the strongest negative association with CRP levels. Conclusions: CRP levels differ in COPD patients among groups A-D based on GOLD 2011 grading classification. CRP levels are associated with several important clinical variables, of which FEV1% and CAT score manifested the strongest negative correlation. PMID:28083044

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

PubMed Central

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Volume 19, Issue8 (December 2004)Articles in the Current Issue:Research ArticleTowards automation of palynology 1: analysis of pollen shape and ornamentation using simple geometric measures, derived from scanning electron microscope images

NASA Astrophysics Data System (ADS)

Treloar, W. J.; Taylor, G. E.; Flenley, J. R.

2004-12-01

This is the first of a series of papers on the theme of automated pollen analysis. The automation of pollen analysis could result in numerous advantages for the reconstruction of past environments, with larger data sets made practical, objectivity and fine resolution sampling. There are also applications in apiculture and medicine. Previous work on the classification of pollen using texture measures has been successful with small numbers of pollen taxa. However, as the number of pollen taxa to be identified increases, more features may be required to achieve a successful classification. This paper describes the use of simple geometric measures to augment the texture measures. The feasibility of this new approach is tested using scanning electron microscope (SEM) images of 12 taxa of fresh pollen taken from reference material collected on Henderson Island, Polynesia. Pollen images were captured directly from a SEM connected to a PC. A threshold grey-level was set and binary images were then generated. Pollen edges were then located and the boundaries were traced using a chain coding system. A number of simple geometric variables were calculated directly from the chain code of the pollen and a variable selection procedure was used to choose the optimal subset to be used for classification. The efficiency of these variables was tested using a leave-one-out classification procedure. The system successfully split the original 12 taxa sample into five sub-samples containing no more than six pollen taxa each. The further subdivision of echinate pollen types was then attempted with a subset of four pollen taxa. A set of difference codes was constructed for a range of displacements along the chain code. From these difference codes probability variables were calculated. A variable selection procedure was again used to choose the optimal subset of probabilities that may be used for classification. The efficiency of these variables was again tested using a leave-one-out classification procedure. The proportion of correctly classified pollen ranged from 81% to 100% depending on the subset of variables used. The best set of variables had an overall classification rate averaging at about 95%. This is comparable with the classification rates from the earlier texture analysis work for other types of pollen. Copyright

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 comprehensive catalogue and classification of human thermal climate indices

NASA Astrophysics Data System (ADS)

de Freitas, C. R.; Grigorieva, E. A.

2015-01-01

The very large number of human thermal climate indices that have been proposed over the past 100 years or so is a manifestation of the perceived importance within the scientific community of the thermal environment and the desire to quantify it. Schemes used differ in approach according to the number of variables taken into account, the rationale employed, the relative sophistication of the underlying body-atmosphere heat exchange theory and the particular design for application. They also vary considerably in type and quality, as well as in several other aspects. Reviews appear in the literature, but they cover a limited number of indices. A project that produces a comprehensive documentation, classification and overall evaluation of the full range of existing human thermal climate indices has never been attempted. This paper deals with documentation and classification. A subsequent report will focus on evaluation. Here a comprehensive register of 162 thermal indices is assembled and a sorting scheme devised that groups them according to eight primary classification classes. It is the first stage in a project to organise and evaluate the full range of all human thermal climate indices. The work, when completed, will make it easier for users to reflect on the merits of all available thermal indices. It will be simpler to locate and compare indices and decide which is most appropriate for a particular application or investigation.

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

NASA Astrophysics Data System (ADS)

Phinyomark, A.; Hu, H.; Phukpattaranont, P.; Limsakul, C.

2012-01-01

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier.

A comprehensive catalogue and classification of human thermal climate indices.

PubMed

de Freitas, C R; Grigorieva, E A

2015-01-01

The very large number of human thermal climate indices that have been proposed over the past 100 years or so is a manifestation of the perceived importance within the scientific community of the thermal environment and the desire to quantify it. Schemes used differ in approach according to the number of variables taken into account, the rationale employed, the relative sophistication of the underlying body-atmosphere heat exchange theory and the particular design for application. They also vary considerably in type and quality, as well as in several other aspects. Reviews appear in the literature, but they cover a limited number of indices. A project that produces a comprehensive documentation, classification and overall evaluation of the full range of existing human thermal climate indices has never been attempted. This paper deals with documentation and classification. A subsequent report will focus on evaluation. Here a comprehensive register of 162 thermal indices is assembled and a sorting scheme devised that groups them according to eight primary classification classes. It is the first stage in a project to organise and evaluate the full range of all human thermal climate indices. The work, when completed, will make it easier for users to reflect on the merits of all available thermal indices. It will be simpler to locate and compare indices and decide which is most appropriate for a particular application or investigation.

Automated structural classification of lipids by machine learning.

PubMed

Taylor, Ryan; Miller, Ryan H; Miller, Ryan D; Porter, Michael; Dalgleish, James; Prince, John T

2015-03-01

Modern lipidomics is largely dependent upon structural ontologies because of the great diversity exhibited in the lipidome, but no automated lipid classification exists to facilitate this partitioning. The size of the putative lipidome far exceeds the number currently classified, despite a decade of work. Automated classification would benefit ongoing classification efforts by decreasing the time needed and increasing the accuracy of classification while providing classifications for mass spectral identification algorithms. We introduce a tool that automates classification into the LIPID MAPS ontology of known lipids with >95% accuracy and novel lipids with 63% accuracy. The classification is based upon simple chemical characteristics and modern machine learning algorithms. The decision trees produced are intelligible and can be used to clarify implicit assumptions about the current LIPID MAPS classification scheme. These characteristics and decision trees are made available to facilitate alternative implementations. We also discovered many hundreds of lipids that are currently misclassified in the LIPID MAPS database, strongly underscoring the need for automated classification. Source code and chemical characteristic lists as SMARTS search strings are available under an open-source license at https://www.github.com/princelab/lipid_classifier. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Permutation Entropy and Signal Energy Increase the Accuracy of Neuropathic Change Detection in Needle EMG

PubMed Central

2018-01-01

Background and Objective. Needle electromyography can be used to detect the number of changes and morphological changes in motor unit potentials of patients with axonal neuropathy. General mathematical methods of pattern recognition and signal analysis were applied to recognize neuropathic changes. This study validates the possibility of extending and refining turns-amplitude analysis using permutation entropy and signal energy. Methods. In this study, we examined needle electromyography in 40 neuropathic individuals and 40 controls. The number of turns, amplitude between turns, signal energy, and “permutation entropy” were used as features for support vector machine classification. Results. The obtained results proved the superior classification performance of the combinations of all of the above-mentioned features compared to the combinations of fewer features. The lowest accuracy from the tested combinations of features had peak-ratio analysis. Conclusion. Using the combination of permutation entropy with signal energy, number of turns and mean amplitude in SVM classification can be used to refine the diagnosis of polyneuropathies examined by needle electromyography. PMID:29606959

A system for analysis and classification of voice communications

NASA Technical Reports Server (NTRS)

Older, H. J.; Jenney, L. L.; Garland, L.

1973-01-01

A method for analysis and classification of verbal communications typically associated with manned space missions or simulations was developed. The study was carried out in two phases. Phase 1 was devoted to identification of crew tasks and activities which require voice communication for accomplishment or reporting. Phase 2 entailed development of a message classification system and a preliminary test of its feasibility. The classification system permits voice communications to be analyzed to three progressively more specific levels of detail and to be described in terms of message content, purpose, and the participants in the information exchange. A coding technique was devised to allow messages to be recorded by an eight-digit number.

Reader reaction: A note on the evaluation of group testing algorithms in the presence of misclassification.

PubMed

Malinovsky, Yaakov; Albert, Paul S; Roy, Anindya

2016-03-01

In the context of group testing screening, McMahan, Tebbs, and Bilder (2012, Biometrics 68, 287-296) proposed a two-stage procedure in a heterogenous population in the presence of misclassification. In earlier work published in Biometrics, Kim, Hudgens, Dreyfuss, Westreich, and Pilcher (2007, Biometrics 63, 1152-1162) also proposed group testing algorithms in a homogeneous population with misclassification. In both cases, the authors evaluated performance of the algorithms based on the expected number of tests per person, with the optimal design being defined by minimizing this quantity. The purpose of this article is to show that although the expected number of tests per person is an appropriate evaluation criteria for group testing when there is no misclassification, it may be problematic when there is misclassification. Specifically, a valid criterion needs to take into account the amount of correct classification and not just the number of tests. We propose, a more suitable objective function that accounts for not only the expected number of tests, but also the expected number of correct classifications. We then show how using this objective function that accounts for correct classification is important for design when considering group testing under misclassification. We also present novel analytical results which characterize the optimal Dorfman (1943) design under the misclassification. © 2015, The International Biometric Society.

Analysis of swallowing sounds using hidden Markov models.

PubMed

Aboofazeli, Mohammad; Moussavi, Zahra

2008-04-01

In recent years, acoustical analysis of the swallowing mechanism has received considerable attention due to its diagnostic potentials. This paper presents a hidden Markov model (HMM) based method for the swallowing sound segmentation and classification. Swallowing sound signals of 15 healthy and 11 dysphagic subjects were studied. The signals were divided into sequences of 25 ms segments each of which were represented by seven features. The sequences of features were modeled by HMMs. Trained HMMs were used for segmentation of the swallowing sounds into three distinct phases, i.e., initial quiet period, initial discrete sounds (IDS) and bolus transit sounds (BTS). Among the seven features, accuracy of segmentation by the HMM based on multi-scale product of wavelet coefficients was higher than that of the other HMMs and the linear prediction coefficient (LPC)-based HMM showed the weakest performance. In addition, HMMs were used for classification of the swallowing sounds of healthy subjects and dysphagic patients. Classification accuracy of different HMM configurations was investigated. When we increased the number of states of the HMMs from 4 to 8, the classification error gradually decreased. In most cases, classification error for N=9 was higher than that of N=8. Among the seven features used, root mean square (RMS) and waveform fractal dimension (WFD) showed the best performance in the HMM-based classification of swallowing sounds. When the sequences of the features of IDS segment were modeled separately, the accuracy reached up to 85.5%. As a second stage classification, a screening algorithm was used which correctly classified all the subjects but one healthy subject when RMS was used as characteristic feature of the swallowing sounds and the number of states was set to N=8.

Classification of hydrocephalus: critical analysis of classification categories and advantages of "Multi-categorical Hydrocephalus Classification" (Mc HC).

PubMed

Oi, Shizuo

2011-10-01

Hydrocephalus is a complex pathophysiology with disturbed cerebrospinal fluid (CSF) circulation. There are numerous numbers of classification trials published focusing on various criteria, such as associated anomalies/underlying lesions, CSF circulation/intracranial pressure patterns, clinical features, and other categories. However, no definitive classification exists comprehensively to cover the variety of these aspects. The new classification of hydrocephalus, "Multi-categorical Hydrocephalus Classification" (Mc HC), was invented and developed to cover the entire aspects of hydrocephalus with all considerable classification items and categories. Ten categories include "Mc HC" category I: onset (age, phase), II: cause, III: underlying lesion, IV: symptomatology, V: pathophysiology 1-CSF circulation, VI: pathophysiology 2-ICP dynamics, VII: chronology, VII: post-shunt, VIII: post-endoscopic third ventriculostomy, and X: others. From a 100-year search of publication related to the classification of hydrocephalus, 14 representative publications were reviewed and divided into the 10 categories. The Baumkuchen classification graph made from the round o'clock classification demonstrated the historical tendency of deviation to the categories in pathophysiology, either CSF or ICP dynamics. In the preliminary clinical application, it was concluded that "Mc HC" is extremely effective in expressing the individual state with various categories in the past and present condition or among the compatible cases of hydrocephalus along with the possible chronological change in the future.

Genetic variability of HEV isolates: inconsistencies of current classification.

PubMed

Oliveira-Filho, Edmilson F; König, Matthias; Thiel, Heinz-Jürgen

2013-07-26

Many HEV and HEV-like sequences have been reported during the last years, including isolates which may represent a number of potential new genera, new genotypes or new subtypes within the family Hepeviridae. Using the most common classification system, difficulties in the establishment of subtypes have been reported. Moreover the relevance of subtype classification for epidemiology can be questioned. In this study we have performed phylogenetic analyses based on whole capsid gene and complete HEV genomic sequences in order to evaluate the current classification of HEV at genotype and subtype levels. The results of our analyses modify the current taxonomy of genotype 3 and refine the established system for typing of HEV. In addition we suggest a classification for hepeviruses recently isolated from bats, ferrets, rats and wild boar. Copyright © 2013 Elsevier B.V. All rights reserved.

Classifications for carcinogenesis of antitumoral drugs.

PubMed

Binetti, R; Costamagna, F M; Marcello, I

2003-12-01

The aim of this review is to support the medical staff engaged in tumor therapy with the carcinogenicity, mutagenicity, developmental toxicity classification of a large number of chemiotherapic drugs by national and international Agencies; it also gives their rationale and the few cases for which the classification varies among, for example, the European Union and the United States of America. A large list of such drugs, producers, commercial names, CAS numbers and chemical names is reported. This list is subject to changes for the quick development in this field: many drugs are retired and many more are introduced in clinical practice. The list is updated to the summer 2003 and retains many drugs which have more than one use or have limited use. The protection of the medical personnel using antitumor chemiotherapics can need retrospective epidemiological investigations and obsolete drugs are of importance for some of the past exposures.

T-ray relevant frequencies for osteosarcoma classification

NASA Astrophysics Data System (ADS)

Withayachumnankul, W.; Ferguson, B.; Rainsford, T.; Findlay, D.; Mickan, S. P.; Abbott, D.

2006-01-01

We investigate the classification of the T-ray response of normal human bone cells and human osteosarcoma cells, grown in culture. Given the magnitude and phase responses within a reliable spectral range as features for input vectors, a trained support vector machine can correctly classify the two cell types to some extent. Performance of the support vector machine is deteriorated by the curse of dimensionality, resulting from the comparatively large number of features in the input vectors. Feature subset selection methods are used to select only an optimal number of relevant features for inputs. As a result, an improvement in generalization performance is attainable, and the selected frequencies can be used for further describing different mechanisms of the cells, responding to T-rays. We demonstrate a consistent classification accuracy of 89.6%, while the only one fifth of the original features are retained in the data set.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

An improved SRC method based on virtual samples for face recognition

NASA Astrophysics Data System (ADS)

Fu, Lijun; Chen, Deyun; Lin, Kezheng; Li, Ao

2018-07-01

The sparse representation classifier (SRC) performs classification by evaluating which class leads to the minimum representation error. However, in real world, the number of available training samples is limited due to noise interference, training samples cannot accurately represent the test sample linearly. Therefore, in this paper, we first produce virtual samples by exploiting original training samples at the aim of increasing the number of training samples. Then, we take the intra-class difference as data representation of partial noise, and utilize the intra-class differences and training samples simultaneously to represent the test sample in a linear way according to the theory of SRC algorithm. Using weighted score level fusion, the respective representation scores of the virtual samples and the original training samples are fused together to obtain the final classification results. The experimental results on multiple face databases show that our proposed method has a very satisfactory classification performance.

An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests

ERIC Educational Resources Information Center

Strobl, Carolin; Malley, James; Tutz, Gerhard

2009-01-01

Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and…

Linguistic Relativity in Japanese and English: Is Language the Primary Determinant in Object Classification?

ERIC Educational Resources Information Center

Mazuka, Reiko; Friedman, Ronald S.

2000-01-01

Tested claims by Lucy (1992a, 1992b) that differences between the number marking systems used by Yucatec Maya and English lead speakers of these languages to differentially attend to either the material composition or the shape of objects. Replicated Lucy's critical objects' classification experiments using speakers of English and Japanese.…

Application of the Covalent Bond Classification Method for the Teaching of Inorganic Chemistry

ERIC Educational Resources Information Center

Green, Malcolm L. H.; Parkin, Gerard

2014-01-01

The Covalent Bond Classification (CBC) method provides a means to classify covalent molecules according to the number and types of bonds that surround an atom of interest. This approach is based on an elementary molecular orbital analysis of the bonding involving the central atom (M), with the various interactions being classified according to the…

75 FR 45052 - The Jurisdictional Scope of Commodity Classification Determinations and Advisory Opinions Issued...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-02

... the authority to issue determinations about the ECCN that applies to an item. Because BIS assigns all... Control Classification Number (ECCN) down to the paragraph (or subparagraph) level, if appropriate. BIS... described by an ECCN in the Commerce Control List (CCL) in Supplement No. 1 to Part 774 of the EAR or not...

The DMON2: A Commercially Available Broadband Acoustic Monitoring Instrument

DTIC Science & Technology

2014-09-30

Assignment of Export Control Classification Number ( ECCN ) of 6A991 by the Department of Commerce for the DMON2 (July 30, 2014), allowing the DMON2 to be...The ECCN 6A991 classification requires that an external pressure transducer be mounted in the head so that the hydrophone output can be disabled

Pluricentric Views towards English and Implications for ELT in China

ERIC Educational Resources Information Center

Jianli, Liang

2015-01-01

Descriptions of the classifications or models of English language have been proposed by a number of scholars who attempt to explain the differences in the ways English is used in different localities. This paper reviews three models of classification of English language, with an aim of drawing implications on how English Language Teaching (ELT) in…

The 2016 revision of the World Health Organization classification of lymphoid neoplasms | Center for Cancer Research

Cancer.gov

A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities.

Practical Procedures for Constructing Mastery Tests to Minimize Errors of Classification and to Maximize or Optimize Decision Reliability.

ERIC Educational Resources Information Center

Byars, Alvin Gregg

The objectives of this investigation are to develop, describe, assess, and demonstrate procedures for constructing mastery tests to minimize errors of classification and to maximize decision reliability. The guidelines are based on conditions where item exchangeability is a reasonable assumption and the test constructor can control the number of…

Mutual information-based analysis of JPEG2000 contexts.

PubMed

Liu, Zhen; Karam, Lina J

2005-04-01

Context-based arithmetic coding has been widely adopted in image and video compression and is a key component of the new JPEG2000 image compression standard. In this paper, the contexts used in JPEG2000 are analyzed using the mutual information, which is closely related to the compression performance. We first show that, when combining the contexts, the mutual information between the contexts and the encoded data will decrease unless the conditional probability distributions of the combined contexts are the same. Given I, the initial number of contexts, and F, the final desired number of contexts, there are S(I, F) possible context classification schemes where S(I, F) is called the Stirling number of the second kind. The optimal classification scheme is the one that gives the maximum mutual information. Instead of using an exhaustive search, the optimal classification scheme can be obtained through a modified generalized Lloyd algorithm with the relative entropy as the distortion metric. For binary arithmetic coding, the search complexity can be reduced by using dynamic programming. Our experimental results show that the JPEG2000 contexts capture the correlations among the wavelet coefficients very well. At the same time, the number of contexts used as part of the standard can be reduced without loss in the coding performance.

Inter-comparison of weather and circulation type classifications for hydrological drought development

NASA Astrophysics Data System (ADS)

Fleig, Anne K.; Tallaksen, Lena M.; Hisdal, Hege; Stahl, Kerstin; Hannah, David M.

Classifications of weather and circulation patterns are often applied in research seeking to relate atmospheric state to surface environmental phenomena. However, numerous procedures have been applied to define the patterns, thus limiting comparability between studies. The COST733 Action “ Harmonisation and Applications of Weather Type Classifications for European regions” tests 73 different weather type classifications (WTC) and their associate weather types (WTs) and compares the WTCs’ utility for various applications. The objective of this study is to evaluate the potential of these WTCs for analysis of regional hydrological drought development in north-western Europe. Hydrological drought is defined in terms of a Regional Drought Area Index (RDAI), which is based on deficits derived from daily river flow series. RDAI series (1964-2001) were calculated for four homogeneous regions in Great Britain and two in Denmark. For each region, WTs associated with hydrological drought development were identified based on antecedent and concurrent WT-frequencies for major drought events. The utility of the different WTCs for the study of hydrological drought development was evaluated, and the influence of WTC attributes, i.e. input variables, number of defined WTs and general classification concept, on WTC performance was assessed. The objective Grosswetterlagen (OGWL), the objective Second-Generation Lamb Weather Type Classification (LWT2) with 18 WTs and two implementations of the objective Wetterlagenklassifikation (WLK; with 40 and 28 WTs) outperformed all other WTCs. In general, WTCs with more WTs (⩾27) were found to perform better than WTCs with less (⩽18) WTs. The influence of input variables was not consistent across the different classification procedures, and the performance of a WTC was determined primarily by the classification procedure itself. Overall, classification procedures following the relatively simple general classification concept of predefining WTs based on thresholds, performed better than those based on more sophisticated classification concepts such as deriving WTs by cluster analysis or artificial neural networks. In particular, PCA based WTCs with 9 WTs and automated WTCs with a high number of predefined WTs (subjectively and threshold based) performed well. It is suggested that the explicit consideration of the air flow characteristics of meridionality, zonality and cyclonicity in the definition of WTs is a useful feature for a WTC when analysing regional hydrological drought development.

A review of supervised object-based land-cover image classification

NASA Astrophysics Data System (ADS)

Ma, Lei; Li, Manchun; Ma, Xiaoxue; Cheng, Liang; Du, Peijun; Liu, Yongxue

2017-08-01

Object-based image classification for land-cover mapping purposes using remote-sensing imagery has attracted significant attention in recent years. Numerous studies conducted over the past decade have investigated a broad array of sensors, feature selection, classifiers, and other factors of interest. However, these research results have not yet been synthesized to provide coherent guidance on the effect of different supervised object-based land-cover classification processes. In this study, we first construct a database with 28 fields using qualitative and quantitative information extracted from 254 experimental cases described in 173 scientific papers. Second, the results of the meta-analysis are reported, including general characteristics of the studies (e.g., the geographic range of relevant institutes, preferred journals) and the relationships between factors of interest (e.g., spatial resolution and study area or optimal segmentation scale, accuracy and number of targeted classes), especially with respect to the classification accuracy of different sensors, segmentation scale, training set size, supervised classifiers, and land-cover types. Third, useful data on supervised object-based image classification are determined from the meta-analysis. For example, we find that supervised object-based classification is currently experiencing rapid advances, while development of the fuzzy technique is limited in the object-based framework. Furthermore, spatial resolution correlates with the optimal segmentation scale and study area, and Random Forest (RF) shows the best performance in object-based classification. The area-based accuracy assessment method can obtain stable classification performance, and indicates a strong correlation between accuracy and training set size, while the accuracy of the point-based method is likely to be unstable due to mixed objects. In addition, the overall accuracy benefits from higher spatial resolution images (e.g., unmanned aerial vehicle) or agricultural sites where it also correlates with the number of targeted classes. More than 95.6% of studies involve an area less than 300 ha, and the spatial resolution of images is predominantly between 0 and 2 m. Furthermore, we identify some methods that may advance supervised object-based image classification. For example, deep learning and type-2 fuzzy techniques may further improve classification accuracy. Lastly, scientists are strongly encouraged to report results of uncertainty studies to further explore the effects of varied factors on supervised object-based image classification.

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm.

PubMed

Al-Saffar, Ahmed; Awang, Suryanti; Tao, Hai; Omar, Nazlia; Al-Saiagh, Wafaa; Al-Bared, Mohammed

2018-01-01

Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm

PubMed Central

Awang, Suryanti; Tao, Hai; Omar, Nazlia; Al-Saiagh, Wafaa; Al-bared, Mohammed

2018-01-01

Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach. PMID:29684036

Comparing the usefulness of the 1997 and 2009 WHO dengue case classification: a systematic literature review.

PubMed

Horstick, Olaf; Jaenisch, Thomas; Martinez, Eric; Kroeger, Axel; See, Lucy Lum Chai; Farrar, Jeremy; Ranzinger, Silvia Runge

2014-09-01

The 1997 and 2009 WHO dengue case classifications were compared in a systematic review with 12 eligible studies (4 prospective). Ten expert opinion articles were used for discussion. For the 2009 WHO classification studies show: when determining severe dengue sensitivity ranges between 59-98% (88%/98%: prospective studies), specificity between 41-99% (99%: prospective study) - comparing the 1997 WHO classification: sensitivity 24.8-89.9% (24.8%/74%: prospective studies), specificity: 25%/100% (100%: prospective study). The application of the 2009 WHO classification is easy, however for (non-severe) dengue there may be a risk of monitoring increased case numbers. Warning signs validation studies are needed. For epidemiological/pathogenesis research use of the 2009 WHO classification, opinion papers show that ease of application, increased sensitivity (severe dengue) and international comparability are advantageous; 3 severe dengue criteria (severe plasma leakage, severe bleeding, severe organ manifestation) are useful research endpoints. The 2009 WHO classification has clear advantages for clinical use, use in epidemiology is promising and research use may at least not be a disadvantage. © The American Society of Tropical Medicine and Hygiene.

Evaluation of gene expression classification studies: factors associated with classification performance.

PubMed

Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

2014-01-01

Classification methods used in microarray studies for gene expression are diverse in the way they deal with the underlying complexity of the data, as well as in the technique used to build the classification model. The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. A systematic literature review was used to extract the information from 48 published articles on non-cancer microarray classification studies. The impact of the various factors on the reported classification accuracy was analyzed through random-intercept logistic regression. The type of medical question and method of cross validation dominated the explained variation in accuracy among studies, followed by disease category and microarray platform. In total, 42% of the between study variation was explained by all the study specific and problem specific factors that we studied together.

Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification

NASA Astrophysics Data System (ADS)

Sharif, I.; Khare, S.

2014-11-01

With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.

CNN universal machine as classificaton platform: an art-like clustering algorithm.

PubMed

Bálya, David

2003-12-01

Fast and robust classification of feature vectors is a crucial task in a number of real-time systems. A cellular neural/nonlinear network universal machine (CNN-UM) can be very efficient as a feature detector. The next step is to post-process the results for object recognition. This paper shows how a robust classification scheme based on adaptive resonance theory (ART) can be mapped to the CNN-UM. Moreover, this mapping is general enough to include different types of feed-forward neural networks. The designed analogic CNN algorithm is capable of classifying the extracted feature vectors keeping the advantages of the ART networks, such as robust, plastic and fault-tolerant behaviors. An analogic algorithm is presented for unsupervised classification with tunable sensitivity and automatic new class creation. The algorithm is extended for supervised classification. The presented binary feature vector classification is implemented on the existing standard CNN-UM chips for fast classification. The experimental evaluation shows promising performance after 100% accuracy on the training set.

VizieR Online Data Catalog: LAMOST-Kepler MKCLASS spectral classification (Gray+, 2016)

NASA Astrophysics Data System (ADS)

Gray, R. O.; Corbally, C. J.; De Cat, P.; Fu, J. N.; Ren, A. B.; Shi, J. R.; Luo, A. L.; Zhang, H. T.; Wu, Y.; Cao, Z.; Li, G.; Zhang, Y.; Hou, Y.; Wang, Y.

2016-07-01

The data for the LAMOST-Kepler project are supplied by the Large Sky Area Multi Object Fiber Spectroscopic Telescope (LAMOST, also known as the Guo Shou Jing Telescope). This unique astronomical instrument is located at the Xinglong observatory in China, and combines a large aperture (4 m) telescope with a 5° circular field of view (Wang et al. 1996ApOpt..35.5155W). Our role in this project is to supply accurate two-dimensional spectral types for the observed targets. The large number of spectra obtained for this project (101086) makes traditional visual classification techniques impractical, so we have utilized the MKCLASS code to perform these classifications. The MKCLASS code (Gray & Corbally 2014AJ....147...80G, v1.07 http://www.appstate.edu/~grayro/mkclass/), an expert system designed to classify blue-violet spectra on the MK Classification system, was employed to produce the spectral classifications reported in this paper. MKCLASS was designed to reproduce the steps skilled human classifiers employ in the classification process. (2 data files).

Classification and reduction of pilot error

NASA Technical Reports Server (NTRS)

Rogers, W. H.; Logan, A. L.; Boley, G. D.

1989-01-01

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses.

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.

Diversity and food web structure of nematode communities under high soil salinity and alkaline pH.

PubMed

Salamún, Peter; Kucanová, Eva; Brázová, Tímea; Miklisová, Dana; Renčo, Marek; Hanzelová, Vladimíra

2014-10-01

A long-term and intensive magnesium (Mg) ore processing in Slovenské Magnezitové Závody a.s. in Jelšava has resulted in a high Mg content and alkaline pH of the soil environment, noticeable mainly in the close vicinity of the smelter. Nematode communities strongly reacted to the contamination mostly by a decrease in abundance of the sensitive groups. Nematodes from c-p 1 group and bacterivores, tolerant to pollution played a significant role in establishing the dominance at all sites. With increasing distance from the pollution source, the nematode communities were more structured and complex, with an increase in proportion of sensitive c-p 4 and 5 nematodes, composed mainly of carnivores and omnivores. Various ecological indices (e.g. MI2-5, SI, H') indicated similar improvement of farther soil ecosystems.

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.

[Proposals for social class classification based on the Spanish National Classification of Occupations 2011 using neo-Weberian and neo-Marxist approaches].

PubMed

Domingo-Salvany, Antònia; Bacigalupe, Amaia; Carrasco, José Miguel; Espelt, Albert; Ferrando, Josep; Borrell, Carme

2013-01-01

In Spain, the new National Classification of Occupations (Clasificación Nacional de Ocupaciones [CNO-2011]) is substantially different to the 1994 edition, and requires adaptation of occupational social classes for use in studies of health inequalities. This article presents two proposals to measure social class: the new classification of occupational social class (CSO-SEE12), based on the CNO-2011 and a neo-Weberian perspective, and a social class classification based on a neo-Marxist approach. The CSO-SEE12 is the result of a detailed review of the CNO-2011 codes. In contrast, the neo-Marxist classification is derived from variables related to capital and organizational and skill assets. The proposed CSO-SEE12 consists of seven classes that can be grouped into a smaller number of categories according to study needs. The neo-Marxist classification consists of 12 categories in which home owners are divided into three categories based on capital goods and employed persons are grouped into nine categories composed of organizational and skill assets. These proposals are complemented by a proposed classification of educational level that integrates the various curricula in Spain and provides correspondences with the International Standard Classification of Education. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.

Economic efficiency of primary care for CVD prevention and treatment in Eastern European countries

PubMed Central

2013-01-01

Background Cardiovascular disease (CVD) is the main cause of morbidity and mortality worldwide, but it also is highly preventable. The prevention rate mainly depends on the patients’ readiness to follow recommendations and the state’s capacity to support patients. Our study aims to show that proper primary care can decrease the CVD-related morbidity rate and increase the economic efficiency of the healthcare system. Since their admission to the European Union (EU), the Eastern European countries have been in a quest to achieve the Western European standards of living. As a representative Eastern European country, Romania implemented the same strategies as the rest of Eastern Europe, reflected in the health status and lifestyle of its inhabitants. Thus, a valid health policy implemented in Romania should be valid for the rest of the Eastern European countries. Methods Based on the data collected during the EUROASPIRE III Romania Follow Up study, the potential costs of healthcare were estimated for various cases over a 10-year time period. The total costs were split into patient-supported costs and state-supported costs. The state-supported costs were used to deduce the rate of patients with severe CVD that can be treated yearly. A statistical model for the evolution of this rate was computed based on the readiness of the patients to comply with proper primary care treatment. Results We demonstrate that for patients ignoring the risks, a severe CVD has disadvantageous economic consequences, leading to increased healthcare expenses and even poverty. In contrast, performing appropriate prevention activities result in a decrease of the expenses allocated to a (eventual) CVD. In the long-term, the number of patients with severe CVD that can be treated increases as the number of patients receiving proper primary care increases. Conclusions Proper primary care can not only decrease the risk of major CVD but also decrease the healthcare costs and increase the number of patients that can be treated. Most importantly, the health standards of the EU can be achieved more rapidly when primary care is delivered appropriately. JEL I18, H51 PMID:23433501

A Hybrid Semi-supervised Classification Scheme for Mining Multisource Geospatial Data

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

Vatsavai, Raju; Bhaduri, Budhendra L

2011-01-01

Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of large number of accurate training samples (10 to 30 |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, itmore » is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 25 to 35% improvement in overall classification accuracy over conventional classification schemes.« less

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

An Updated Taxonomy and a Graphical Summary Tool for Optimal Classification and Comprehension of Omics Research.

PubMed

Pirih, Nina; Kunej, Tanja

2018-05-01

The volume of publications and the type of research approaches used in omics system sciences are vast and continue to expand rapidly. This increased complexity and heterogeneity of omics data are challenging data extraction, sensemaking, analyses, knowledge translation, and interpretation. An extended and dynamic taxonomy for the classification and summary of omics studies are essential. We present an updated taxonomy for classification of omics research studies based on four criteria: (1) type and number of genomic loci in a research study, (2) number of species and biological samples, (3) the type of omics technology (e.g., genomics, transcriptomics, and proteomics) and omics technology application type (e.g., pharmacogenomics and nutrigenomics), and (4) phenotypes. In addition, we present a graphical summary approach that enables the researchers to define the main characteristics of their study in a single figure, and offers the readers to rapidly grasp the published study and omics data. We searched the PubMed and the Web of Science from 09/2002 to 02/2018, including research and review articles, and identified 90 scientific publications. We propose a call toward omics studies' standardization for reporting in scientific literature. We anticipate the proposed classification scheme will usefully contribute to improved classification of published reports in genomics and other omics fields, and help data extraction from publications for future multiomics data integration.

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2012 CFR

2012-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2011 CFR

2011-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2013 CFR

2013-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2014 CFR

2014-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

Classification of Birds and Bats Using Flight Tracks

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

Cullinan, Valerie I.; Matzner, Shari; Duberstein, Corey A.

Classification of birds and bats that use areas targeted for offshore wind farm development and the inference of their behavior is essential to evaluating the potential effects of development. The current approach to assessing the number and distribution of birds at sea involves transect surveys using trained individuals in boats or airplanes or using high-resolution imagery. These approaches are costly and have safety concerns. Based on a limited annotated library extracted from a single-camera thermal video, we provide a framework for building models that classify birds and bats and their associated behaviors. As an example, we developed a discriminant modelmore » for theoretical flight paths and applied it to data (N = 64 tracks) extracted from 5-min video clips. The agreement between model- and observer-classified path types was initially only 41%, but it increased to 73% when small-scale jitter was censored and path types were combined. Classification of 46 tracks of bats, swallows, gulls, and terns on average was 82% accurate, based on a jackknife cross-validation. Model classification of bats and terns (N = 4 and 2, respectively) was 94% and 91% correct, respectively; however, the variance associated with the tracks from these targets is poorly estimated. Model classification of gulls and swallows (N ≥ 18) was on average 73% and 85% correct, respectively. The models developed here should be considered preliminary because they are based on a small data set both in terms of the numbers of species and the identified flight tracks. Future classification models would be greatly improved by including a measure of distance between the camera and the target.« less

Fuzzy support vector machine for microarray imbalanced data classification

NASA Astrophysics Data System (ADS)

Ladayya, Faroh; Purnami, Santi Wulan; Irhamah

2017-11-01

DNA microarrays are data containing gene expression with small sample sizes and high number of features. Furthermore, imbalanced classes is a common problem in microarray data. This occurs when a dataset is dominated by a class which have significantly more instances than the other minority classes. Therefore, it is needed a classification method that solve the problem of high dimensional and imbalanced data. Support Vector Machine (SVM) is one of the classification methods that is capable of handling large or small samples, nonlinear, high dimensional, over learning and local minimum issues. SVM has been widely applied to DNA microarray data classification and it has been shown that SVM provides the best performance among other machine learning methods. However, imbalanced data will be a problem because SVM treats all samples in the same importance thus the results is bias for minority class. To overcome the imbalanced data, Fuzzy SVM (FSVM) is proposed. This method apply a fuzzy membership to each input point and reformulate the SVM such that different input points provide different contributions to the classifier. The minority classes have large fuzzy membership so FSVM can pay more attention to the samples with larger fuzzy membership. Given DNA microarray data is a high dimensional data with a very large number of features, it is necessary to do feature selection first using Fast Correlation based Filter (FCBF). In this study will be analyzed by SVM, FSVM and both methods by applying FCBF and get the classification performance of them. Based on the overall results, FSVM on selected features has the best classification performance compared to SVM.

Effective Sequential Classifier Training for SVM-Based Multitemporal Remote Sensing Image Classification

NASA Astrophysics Data System (ADS)

Guo, Yiqing; Jia, Xiuping; Paull, David

2018-06-01

The explosive availability of remote sensing images has challenged supervised classification algorithms such as Support Vector Machines (SVM), as training samples tend to be highly limited due to the expensive and laborious task of ground truthing. The temporal correlation and spectral similarity between multitemporal images have opened up an opportunity to alleviate this problem. In this study, a SVM-based Sequential Classifier Training (SCT-SVM) approach is proposed for multitemporal remote sensing image classification. The approach leverages the classifiers of previous images to reduce the required number of training samples for the classifier training of an incoming image. For each incoming image, a rough classifier is firstly predicted based on the temporal trend of a set of previous classifiers. The predicted classifier is then fine-tuned into a more accurate position with current training samples. This approach can be applied progressively to sequential image data, with only a small number of training samples being required from each image. Experiments were conducted with Sentinel-2A multitemporal data over an agricultural area in Australia. Results showed that the proposed SCT-SVM achieved better classification accuracies compared with two state-of-the-art model transfer algorithms. When training data are insufficient, the overall classification accuracy of the incoming image was improved from 76.18% to 94.02% with the proposed SCT-SVM, compared with those obtained without the assistance from previous images. These results demonstrate that the leverage of a priori information from previous images can provide advantageous assistance for later images in multitemporal image classification.

Is there any correlation between the ATS, BTS, ERS and GOLD COPD's severity scales and the frequency of hospital admissions?

PubMed

Tsoumakidou, Maria; Tzanakis, Nikolaos; Voulgaraki, Olga; Mitrouska, Ioanna; Chrysofakis, Georgios; Samiou, Maria; Siafakas, Nikolaos M

2004-02-01

Disagreement exists between different COPD guidelines considering classification of severity of the disease. The aim of our study was to determine whether there is any correlation between severity scales of various COPD guidelines (ATS, BTS, ERS and GOLD) and the frequency of hospitalisations for COPD exacerbation. A cohort of 67 COPD patients (65 male 2 female, 45 ex-smokers, 22 current smokers, aged (69.4 +/- 1.1)) was recruited from those admitted in the pulmonary clinic of the University Hospital of Heraklion, Crete for an acute exacerbation. Lung function tests and arterial blood gases analyses were performed during stable conditions at a scheduled visit 2 months after discharge. The patients were stratified using the FEV1 percent-predicted measurement of this visit into mild, moderate and severe in accordance to the ATS, BTS, ERS and GOLD scales of severity. The number of hospitalisations for acute exacerbation was recorded for the following 18 months. A total of 165 exacerbations were recorded. The correlation between the severity of COPD and the number of hospitalisations per year was statistically significant using the GOLD classification system of severity (P = 0.02 and r = 0.294). A weak correlation was also found between the number of hospitalisations and the ERS classification system (P = 0.05 and r = 0.24). No statistically significant correlation was found between the number of hospitalisations and the ATS or BTS severity scales. In conclusion the GOLD and ERS classification systems of severity of COPD correlated to exacerbations causing hospitalisation. The same was not true for the ATS and BTS severity scales. Better correlation was achieved with the GOLD scale.

Use of the UPOINT Classification in Turkish Chronic Prostatitis or Chronic Pelvic Pain Syndrome Patients.

PubMed

Arda, Ersan; Cakiroglu, Basri; Tas, Tuncay; Ekici, Sinan; Uyanik, Bekir Sami

2016-11-01

To determine the positive subdomain numbers and distribution of the UPOINT classification in chronic prostatitis and to compare the erectile dysfunction (ED) pattern. From 2008 to 2013, 839 patients with symptomatic chronic prostatitis or chronic pelvic pain syndrome were included in this study. The correlation between UPOINT domains and National Institutes of Health chronic prostatitis symptom index (NIH-CPSI) total score, subscores, and the 5-item International Index of Erectile Function scores were evaluated retrospectively. The mean patient age was calculated as 37.7 ± 7.4 (range 21-65). The average total NIH-CPSI score was determined as 9.07 (range 1-40) and the average positive UPOINT subdomain number was determined as 2.87 ± 0.32 (range 1-6). Subdomain patient numbers and rates were calculated as 529 urinary (63%), 462 psychosocial (55%), 382 organ specific (45%), 290 infection (34%), 288 neurological or systemic (34%), and 418 tenderness (skeletal muscle) (50%), respectively. It was determined that ED, determining the subdomain of sexual dysfunction in patients, was positive in a total of 326 (39.9%) patients, with 220 patients having mild (26.2%), 76 mild to moderate (9.1%), 19 moderate (2.3%), and 5 with severe (0.6%) ED. A statistically significant correlation was not determined between the 5-item International Index of Erectile Function score and UPOINT subdomain number and NIH-CPSI score. It has been determined that although there is a strong and significant correlation between UPOINT classification and NIH-CPSI score in Turkish patients with chronic prostatitis or chronic pelvic pain syndrome, the inclusion of ED as an independent subdomain to the UPOINT classification is not statistically significant. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparison of geometric morphometric outline methods in the discrimination of age-related differences in feather shape

PubMed Central

Sheets, H David; Covino, Kristen M; Panasiewicz, Joanna M; Morris, Sara R

2006-01-01

Background Geometric morphometric methods of capturing information about curves or outlines of organismal structures may be used in conjunction with canonical variates analysis (CVA) to assign specimens to groups or populations based on their shapes. This methodological paper examines approaches to optimizing the classification of specimens based on their outlines. This study examines the performance of four approaches to the mathematical representation of outlines and two different approaches to curve measurement as applied to a collection of feather outlines. A new approach to the dimension reduction necessary to carry out a CVA on this type of outline data with modest sample sizes is also presented, and its performance is compared to two other approaches to dimension reduction. Results Two semi-landmark-based methods, bending energy alignment and perpendicular projection, are shown to produce roughly equal rates of classification, as do elliptical Fourier methods and the extended eigenshape method of outline measurement. Rates of classification were not highly dependent on the number of points used to represent a curve or the manner in which those points were acquired. The new approach to dimensionality reduction, which utilizes a variable number of principal component (PC) axes, produced higher cross-validation assignment rates than either the standard approach of using a fixed number of PC axes or a partial least squares method. Conclusion Classification of specimens based on feather shape was not highly dependent of the details of the method used to capture shape information. The choice of dimensionality reduction approach was more of a factor, and the cross validation rate of assignment may be optimized using the variable number of PC axes method presented herein. PMID:16978414

Drug-induced sedation endoscopy (DISE) classification systems: a systematic review and meta-analysis.

PubMed

Dijemeni, Esuabom; D'Amone, Gabriele; Gbati, Israel

2017-12-01

Drug-induced sedation endoscopy (DISE) classification systems have been used to assess anatomical findings on upper airway obstruction, and decide and plan surgical treatments and act as a predictor for surgical treatment outcome for obstructive sleep apnoea management. The first objective is to identify if there is a universally accepted DISE grading and classification system for analysing DISE findings. The second objective is to identify if there is one DISE grading and classification treatment planning framework for deciding appropriate surgical treatment for obstructive sleep apnoea (OSA). The third objective is to identify if there is one DISE grading and classification treatment outcome framework for determining the likelihood of success for a given OSA surgical intervention. A systematic review was performed to identify new and significantly modified DISE classification systems: concept, advantages and disadvantages. Fourteen studies proposing a new DISE classification system and three studies proposing a significantly modified DISE classification were identified. None of the studies were based on randomised control trials. DISE is an objective method for visualising upper airway obstruction. The classification and assessment of clinical findings based on DISE is highly subjective due to the increasing number of DISE classification systems. Hence, this creates a growing divergence in surgical treatment planning and treatment outcome. Further research on a universally accepted objective DISE assessment is critically needed.

Mind the information gap: fertility rate and use of cesarean delivery and tocolytic hospitalizations in Taiwan

PubMed Central

2011-01-01

Background Physician-induced demand (PID) is an important theory to test given the longstanding controversy surrounding it. Empirical health economists have been challenged to find natural experiments to test the theory because PID is tantamount to strong income effects. The data requirements are both a strong exogenous change in income and two types of treatment that are substitutes but have different net revenues. The theory implies that an exogenous fall in income would lead physicians to recoup their income by substituting a more expensive treatment for a less expensive treatment. This study takes advantages of the dramatic decline in the Taiwanese fertility rate to examine whether an exogenous and negative income shock to obstetricians and gynecologists (ob/gyns) affected the use of c-sections, which has a higher reimbursement rate than vaginal delivery under Taiwan's National Health Insurance system during the study period, and tocolytic hospitalizations. Methods The primary data were obtained from the 1996 to 2004 National Health Insurance Research Database in Taiwan. We hypothesized that a negative income shock to ob/gyns would cause them to provide more c-sections and tocolytic hospitalizations to less medically-informed pregnant women. Multinomial probit and probit models were estimated and the marginal effects of the interaction term were conducted to estimate the impacts of ob/gyn to birth ratio and the information gap. Results Our results showed that a decline in fertility did not lead ob/gyns to supply more c-sections to less medically-informed pregnant women, and that during fertility decline ob/gyns may supply more tocolytic hospitalizations to compensate their income loss, regardless of pregnant women's access to health information. Conclusion The exogenous decline in the Taiwanese fertility rate and the use of detailed medical information and demographic attributes of pregnant women allowed us to avoid the endogeneity problem that threatened the validity of prior research. They also provide more accurate estimates of PID. JEL Classification: I10, I19, C23, C25 PMID:22828182

An Efficient Conflict Detection Algorithm for Packet Filters

NASA Astrophysics Data System (ADS)

Lee, Chun-Liang; Lin, Guan-Yu; Chen, Yaw-Chung

Packet classification is essential for supporting advanced network services such as firewalls, quality-of-service (QoS), virtual private networks (VPN), and policy-based routing. The rules that routers use to classify packets are called packet filters. If two or more filters overlap, a conflict occurs and leads to ambiguity in packet classification. This study proposes an algorithm that can efficiently detect and resolve filter conflicts using tuple based search. The time complexity of the proposed algorithm is O(nW+s), and the space complexity is O(nW), where n is the number of filters, W is the number of bits in a header field, and s is the number of conflicts. This study uses the synthetic filter databases generated by ClassBench to evaluate the proposed algorithm. Simulation results show that the proposed algorithm can achieve better performance than existing conflict detection algorithms both in time and space, particularly for databases with large numbers of conflicts.

Terrain-Moisture Classification Using GPS Surface-Reflected Signals

NASA Technical Reports Server (NTRS)

Grant, Michael S.; Acton, Scott T.; Katzberg, Stephen J.

2006-01-01

In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

Minimalist approach to the classification of symmetry protected topological phases

NASA Astrophysics Data System (ADS)

Xiong, Zhaoxi

A number of proposals with differing predictions (e.g. group cohomology, cobordisms, group supercohomology, spin cobordisms, etc.) have been made for the classification of symmetry protected topological (SPT) phases. Here we treat various proposals on equal footing and present rigorous, general results that are independent of which proposal is correct. We do so by formulating a minimalist Generalized Cohomology Hypothesis, which is satisfied by existing proposals and captures essential aspects of SPT classification. From this Hypothesis alone, formulas relating classifications in different dimensions and/or protected by different symmetry groups are derived. Our formalism is expected to work for fermionic as well as bosonic phases, Floquet as well as stationary phases, and spatial as well as on-site symmetries.

Algorithms for Hyperspectral Endmember Extraction and Signature Classification with Morphological Dendritic Networks

NASA Astrophysics Data System (ADS)

Schmalz, M.; Ritter, G.

Accurate multispectral or hyperspectral signature classification is key to the nonimaging detection and recognition of space objects. Additionally, signature classification accuracy depends on accurate spectral endmember determination [1]. Previous approaches to endmember computation and signature classification were based on linear operators or neural networks (NNs) expressed in terms of the algebra (R, +, x) [1,2]. Unfortunately, class separation in these methods tends to be suboptimal, and the number of signatures that can be accurately classified often depends linearly on the number of NN inputs. This can lead to poor endmember distinction, as well as potentially significant classification errors in the presence of noise or densely interleaved signatures. In contrast to traditional CNNs, autoassociative morphological memories (AMM) are a construct similar to Hopfield autoassociatived memories defined on the (R, +, ?,?) lattice algebra [3]. Unlimited storage and perfect recall of noiseless real valued patterns has been proven for AMMs [4]. However, AMMs suffer from sensitivity to specific noise models, that can be characterized as erosive and dilative noise. On the other hand, the prior definition of a set of endmembers corresponds to material spectra lying on vertices of the minimum convex region covering the image data. These vertices can be characterized as morphologically independent patterns. It has further been shown that AMMs can be based on dendritic computation [3,6]. These techniques yield improved accuracy and class segmentation/separation ability in the presence of highly interleaved signature data. In this paper, we present a procedure for endmember determination based on AMM noise sensitivity, which employs morphological dendritic computation. We show that detected endmembers can be exploited by AMM based classification techniques, to achieve accurate signature classification in the presence of noise, closely spaced or interleaved signatures, and simulated camera optical distortions. In particular, we examine two critical cases: (1) classification of multiple closely spaced signatures that are difficult to separate using distance measures, and (2) classification of materials in simulated hyperspectral images of spaceborne satellites. In each case, test data are derived from a NASA database of space material signatures. Additional analysis pertains to computational complexity and noise sensitivity, which are superior to classical NN based techniques.

Towards an Artificial Space Object Taxonomy

DTIC Science & Technology

2013-09-01

demonstrate how to implement this taxonomy in Figaro, an open source probabilistic programming language. 2. INTRODUCTION Currently, US Space Command...Taxonomy 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7...demonstrate how to implement this taxonomy in Figaro, an open source probabilistic programming language. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF

Independent Assessment Plan: LAV-25

DTIC Science & Technology

1989-06-27

Pages. Enter the total Block 7. Performing Organization Name(s) and number of pages. Address(es. Self -explanatory. Block 16. Price Code, Enter...organization Blocks 17. - 19. Security Classifications. performing the report. Self -explanatory. Enter U.S. Security Classification in accordance with U.S...Security Block 9. S oonsorina/Monitoring Acenc Regulations (i.e., UNCLASSIFIED). If form .Names(s) and Address(es). Self -explanatory. contains classified

Theoretical Interpretation of the Fluorescence Spectra of Toluene and P- Cresol

DTIC Science & Technology

1994-07-01

NUMBER OF PAGES Toluene Geometrica 25 p-Cresol Fluorescence Is. PRICE CODE Spectra 17. SECURITY CLASSIFICATION 13. SECURITY CLASSIFICATION 19...State Frequencies of Toluene ................ 19 6 Computed and exp" Ground State Frequencies of p-Cresol ............... 20 7 Correction Factors for...Computed Ground State Vibrational Frequencies ....... 21 8 Computed and Corrected Excited State Frequencies of Toluene ............. 22 9 Computed and

Evaluating the Generality and Limits of Blind Return-Oriented Programming Attacks

DTIC Science & Technology

2015-12-01

consider a recently proposed information disclosure vulnerability called blind return-oriented programming (BROP). Under certain conditions, this...implementation disclosure attacks 15. NUMBER OF PAGES 75 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF...Science iii THIS PAGE INTENTIONALLY LEFT BLANK iv ABSTRACT We consider a recently proposed information disclosure vulnerability called blind return

How Should Children with Speech Sound Disorders be Classified? A Review and Critical Evaluation of Current Classification Systems

ERIC Educational Resources Information Center

Waring, R.; Knight, R.

2013-01-01

Background: Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of…

Freeware Versus Commercial Office Productivity Software

DTIC Science & Technology

2016-12-01

adapting Google’s widely popular freeware for government agency usage. This study analyzes the proposed benefits of using freeware, specifically... computing , ESI 15. NUMBER OF PAGES 73 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF...announced the launch of Google Apps for Government, adapting Google’s widely popular freeware for government agency usage. This study analyzes the

Guide to the TANDEM System for the Modern Languages Department Tape Library: A Non-Technical Guide for Teachers.

ERIC Educational Resources Information Center

Hounsell, D.; And Others

This guide for teachers to the tape indexing system (TANDEM) in use at the Modern Languages Department at Portsmouth Polytechnic focuses on tape classification, numbering, labeling, and shelving system procedures. The appendixes contain information on: (1) the classification system and related codes, (2) color and letter codes, (3) marking of tape…

Extinguishing the Southern Fire: Developing a Solution to Thailand’s Insurgency

DTIC Science & Technology

2010-03-01

Counterinsurgency, Violence, Rebellions, Social Conflict 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES...32 KEY TERMS: Terrorism, Counterinsurgency, Violence, Rebellions, Social Conflict CLASSIFICATION: Unclassified The insurgency in...wisdom, social - economic development does not seem to be a major cause of the recent increase in violence. In spite of the dismal HAI, confidential

RAZOR: A Compression and Classification Solution for the Internet of Things

PubMed Central

Danieletto, Matteo; Bui, Nicola; Zorzi, Michele

2014-01-01

The Internet of Things is expected to increase the amount of data produced and exchanged in the network, due to the huge number of smart objects that will interact with one another. The related information management and transmission costs are increasing and becoming an almost unbearable burden, due to the unprecedented number of data sources and the intrinsic vastness and variety of the datasets. In this paper, we propose RAZOR, a novel lightweight algorithm for data compression and classification, which is expected to alleviate both aspects by leveraging the advantages offered by data mining methods for optimizing communications and by enhancing information transmission to simplify data classification. In particular, RAZOR leverages the concept of motifs, recurrent features used for signal categorization, in order to compress data streams: in such a way, it is possible to achieve compression levels of up to an order of magnitude, while maintaining the signal distortion within acceptable bounds and allowing for simple lightweight distributed classification. In addition, RAZOR is designed to keep the computational complexity low, in order to allow its implementation in the most constrained devices. The paper provides results about the algorithm configuration and a performance comparison against state-of-the-art signal processing techniques. PMID:24451454

Reduction in training time of a deep learning model in detection of lesions in CT

NASA Astrophysics Data System (ADS)

Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

2018-02-01

Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

The new WHO 2016 classification of brain tumors-what neurosurgeons need to know.

PubMed

Banan, Rouzbeh; Hartmann, Christian

2017-03-01

The understanding of molecular alterations of tumors has severely changed the concept of classification in all fields of pathology. The availability of high-throughput technologies such as next-generation sequencing allows for a much more precise definition of tumor entities. Also in the field of brain tumors a dramatic increase of knowledge has occurred over the last years partially calling into question the purely morphologically based concepts that were used as exclusive defining criteria in the WHO 2007 classification. Review of the WHO 2016 classification of brain tumors as well as a search and review of publications in the literature relevant for brain tumor classification from 2007 up to now. The idea of incorporating the molecular features in classifying tumors of the central nervous system led the authors of the new WHO 2016 classification to encounter inevitable conceptual problems, particularly with respect to linking morphology to molecular alterations. As a solution they introduced the concept of a "layered diagnosis" to the classification of brain tumors that still allows at a lower level a purely morphologically based diagnosis while partially forcing the incorporation of molecular characteristics for an "integrated diagnosis" at the highest diagnostic level. In this context the broad availability of molecular assays was debated. On the one hand molecular antibodies specifically targeting mutated proteins should be available in nearly all neuropathological laboratories. On the other hand, different high-throughput assays are accessible only in few first-world neuropathological institutions. As examples oligodendrogliomas are now primarily defined by molecular characteristics since the required assays are generally established, whereas molecular grouping of ependymomas, found to clearly outperform morphologically based tumor interpretation, was rejected from inclusion in the WHO 2016 classification because the required assays are currently only established in a small number of institutions. In summary, while neuropathologists have now encountered various challenges in the transitional phase from the previous WHO 2007 version to the new WHO 2016 classification of brain tumors, clinical neurooncologists now face many new diagnoses allowing a clearly improved understanding that could offer them more effective therapeutic opportunities in neurooncological treatment. The new WHO 2016 classification presumably presents the highest number of modifications since the initial WHO classification of 1979 and thereby forces all professionals in the field of neurooncology to intensively understand the new concepts. This review article aims to present the basic concepts of the new WHO 2016 brain tumor classification for neurosurgeons with a focus on neurooncology.

The Landscape of long non-coding RNA classification

PubMed Central

St Laurent, Georges; Wahlestedt, Claes; Kapranov, Philipp

2015-01-01

Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long non-coding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the non-coding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual un-ambiguous classification framework results in a number of challenges in the annotation and interpretation of non-coding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. PMID:25869999

Spectral classification with the International Ultraviolet Explorer: An atlas of B-type spectra

NASA Technical Reports Server (NTRS)

Rountree, Janet; Sonneborn, George

1993-01-01

New criteria for the spectral classification of B stars in the ultraviolet show that photospheric absorption lines in the 1200-1900A wavelength region can be used to classify the spectra of B-type dwarfs, subgiants, and giants on a 2-D system consistent with the optical MK system. This atlas illustrates a large number of such spectra at the scale used for classification. These spectra provide a dense matrix of standard stars, and also show the effects of rapid stellar rotation and stellar winds on the spectra and their classification. The observational material consists of high-dispersion spectra from the International Ultraviolet Explorer archives, resampled to a resolution of 0.25 A, uniformly normalized, and plotted at 10 A/cm. The atlas should be useful for the classification of other IUE high-dispersion spectra, especially for stars that have not been observed in the optical.

International Headache Society classification: new proposals about chronic headache.

PubMed

Manzoni, G C; Torelli, P

2003-05-01

In the International Headache Society (IHS) classification of 1988, chronic daily headache (CDH) forms are not exhaustively categorized. The forthcoming revision of the classification will include a number of CDH forms that had been reported prior to 1988 or have been identified after that date. In particular, chronic migraine will be added to the classification as a complication of migraine, provided that use of symptomatic drugs does not exceed 10 days per month. In addition to chronic cluster headache and chronic paroxysmal hemicrania, short-lasting unilateral neuralgiform headache with conjunctival injection and tearing (SUNCT) and hemicrania continua will be comprised among CDH forms with short-lived attacks. Hypnic headache will be included in Group 4 ("Other primary headaches"). No additions will be made to the new IHS classification for forms such as new daily persistent headache (NDPH) and cervicogenic headache as proposed by Sjaastad.

Active Learning of Classification Models with Likert-Scale Feedback.

PubMed

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone.

Active Learning of Classification Models with Likert-Scale Feedback

PubMed Central

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone. PMID:28979827

Reactive Collisions and Interactions of Ultracold Dipolar Atoms

DTIC Science & Technology

2014-10-29

DATE (DD-MM-YYYY) 2. REPORT TYPE 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER 6. AUTHOR( S ) 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) 9...SPONSORING/MONITORING AGENCY NAME( S ) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER 10. SPONSOR/MONITOR’S ACRONYM( S ) 13. SUPPLEMENTARY...NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 11. SPONSOR/MONITOR’S REPORT NUMBER( S ) 16. SECURITY CLASSIFICATION OF: 19b. TELEPHONE NUMBER

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

Galaxy Zoo: quantitative visual morphological classifications for 48 000 galaxies from CANDELS

NASA Astrophysics Data System (ADS)

Simmons, B. D.; Lintott, Chris; Willett, Kyle W.; Masters, Karen L.; Kartaltepe, Jeyhan S.; Häußler, Boris; Kaviraj, Sugata; Krawczyk, Coleman; Kruk, S. J.; McIntosh, Daniel H.; Smethurst, R. J.; Nichol, Robert C.; Scarlata, Claudia; Schawinski, Kevin; Conselice, Christopher J.; Almaini, Omar; Ferguson, Henry C.; Fortson, Lucy; Hartley, William; Kocevski, Dale; Koekemoer, Anton M.; Mortlock, Alice; Newman, Jeffrey A.; Bamford, Steven P.; Grogin, N. A.; Lucas, Ray A.; Hathi, Nimish P.; McGrath, Elizabeth; Peth, Michael; Pforr, Janine; Rizer, Zachary; Wuyts, Stijn; Barro, Guillermo; Bell, Eric F.; Castellano, Marco; Dahlen, Tomas; Dekel, Avishai; Ownsworth, Jamie; Faber, Sandra M.; Finkelstein, Steven L.; Fontana, Adriano; Galametz, Audrey; Grützbauch, Ruth; Koo, David; Lotz, Jennifer; Mobasher, Bahram; Mozena, Mark; Salvato, Mara; Wiklind, Tommy

2017-02-01

We present quantified visual morphologies of approximately 48 000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90 per cent of galaxies have z ≤ 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifications, which we combine into detailed morphological information on galaxy features such as clumpiness, bar instabilities, spiral structure, and merger and tidal signatures. We apply a consensus-based classifier weighting method that preserves classifier independence while effectively down-weighting significantly outlying classifications. After analysing the effect of varying image depth on reported classifications, we also provide depth-corrected classifications which both preserve the information in the deepest observations and also enable the use of classifications at comparable depths across the full survey. Comparing the Galaxy Zoo classifications to previous classifications of the same galaxies shows very good agreement; for some applications, the high number of independent classifications provided by Galaxy Zoo provides an advantage in selecting galaxies with a particular morphological profile, while in others the combination of Galaxy Zoo with other classifications is a more promising approach than using any one method alone. We combine the Galaxy Zoo classifications of `smooth' galaxies with parametric morphologies to select a sample of featureless discs at 1 ≤ z ≤ 3, which may represent a dynamically warmer progenitor population to the settled disc galaxies seen at later epochs.

Morphometric Identification of Queens, Workers and Intermediates in In Vitro Reared Honey Bees (Apis mellifera).

PubMed

De Souza, Daiana A; Wang, Ying; Kaftanoglu, Osman; De Jong, David; Amdam, Gro V; Gonçalves, Lionel S; Francoy, Tiago M

2015-01-01

In vitro rearing is an important and useful tool for honey bee (Apis mellifera L.) studies. However, it often results in intercastes between queens and workers, which are normally are not seen in hive-reared bees, except when larvae older than three days are grafted for queen rearing. Morphological classification (queen versus worker or intercastes) of bees produced by this method can be subjective and generally depends on size differences. Here, we propose an alternative method for caste classification of female honey bees reared in vitro, based on weight at emergence, ovariole number, spermatheca size and size and shape, and features of the head, mandible and basitarsus. Morphological measurements were made with both traditional morphometric and geometric morphometrics techniques. The classifications were performed by principal component analysis, using naturally developed queens and workers as controls. First, the analysis included all the characters. Subsequently, a new analysis was made without the information about ovariole number and spermatheca size. Geometric morphometrics was less dependent on ovariole number and spermatheca information for caste and intercaste identification. This is useful, since acquiring information concerning these reproductive structures requires time-consuming dissection and they are not accessible when abdomens have been removed for molecular assays or in dried specimens. Additionally, geometric morphometrics divided intercastes into more discrete phenotype subsets. We conclude that morphometric geometrics are superior to traditional morphometrics techniques for identification and classification of honey bee castes and intermediates.

Morphometric Identification of Queens, Workers and Intermediates in In Vitro Reared Honey Bees (Apis mellifera)

PubMed Central

A. De Souza, Daiana; Wang, Ying; Kaftanoglu, Osman; De Jong, David; V. Amdam, Gro; S. Gonçalves, Lionel; M. Francoy, Tiago

2015-01-01

In vitro rearing is an important and useful tool for honey bee (Apis mellifera L.) studies. However, it often results in intercastes between queens and workers, which are normally are not seen in hive-reared bees, except when larvae older than three days are grafted for queen rearing. Morphological classification (queen versus worker or intercastes) of bees produced by this method can be subjective and generally depends on size differences. Here, we propose an alternative method for caste classification of female honey bees reared in vitro, based on weight at emergence, ovariole number, spermatheca size and size and shape, and features of the head, mandible and basitarsus. Morphological measurements were made with both traditional morphometric and geometric morphometrics techniques. The classifications were performed by principal component analysis, using naturally developed queens and workers as controls. First, the analysis included all the characters. Subsequently, a new analysis was made without the information about ovariole number and spermatheca size. Geometric morphometrics was less dependent on ovariole number and spermatheca information for caste and intercaste identification. This is useful, since acquiring information concerning these reproductive structures requires time-consuming dissection and they are not accessible when abdomens have been removed for molecular assays or in dried specimens. Additionally, geometric morphometrics divided intercastes into more discrete phenotype subsets. We conclude that morphometric geometrics are superior to traditional morphometrics techniques for identification and classification of honey bee castes and intermediates. PMID:25894528

Adaptive sequential Bayesian classification using Page's test

NASA Astrophysics Data System (ADS)

Lynch, Robert S., Jr.; Willett, Peter K.

2002-03-01

In this paper, the previously introduced Mean-Field Bayesian Data Reduction Algorithm is extended for adaptive sequential hypothesis testing utilizing Page's test. In general, Page's test is well understood as a method of detecting a permanent change in distribution associated with a sequence of observations. However, the relationship between detecting a change in distribution utilizing Page's test with that of classification and feature fusion is not well understood. Thus, the contribution of this work is based on developing a method of classifying an unlabeled vector of fused features (i.e., detect a change to an active statistical state) as quickly as possible given an acceptable mean time between false alerts. In this case, the developed classification test can be thought of as equivalent to performing a sequential probability ratio test repeatedly until a class is decided, with the lower log-threshold of each test being set to zero and the upper log-threshold being determined by the expected distance between false alerts. It is of interest to estimate the delay (or, related stopping time) to a classification decision (the number of time samples it takes to classify the target), and the mean time between false alerts, as a function of feature selection and fusion by the Mean-Field Bayesian Data Reduction Algorithm. Results are demonstrated by plotting the delay to declaring the target class versus the mean time between false alerts, and are shown using both different numbers of simulated training data and different numbers of relevant features for each class.

Monitoring of peri-distal gastrectomy carbohydrate antigen 19-9 level in gastric juice and its significance

PubMed Central

Xu, A-Man; Huang, Lei; Han, Wen-Xiu; Wei, Zhi-Jian

2014-01-01

Gastric carcinoma is one of the most common and deadly malignancies nowadays, and carbohydrate antigen 19-9 (CA 19-9) in gastric juice has been rarely studied. To compare peri-distal gastrectomy (DG) gastric juice and serum CA 19-9 and reveal its significance, we selected 67 patients diagnosed with gastric carcinoma who underwent DG, and collected their perioperative gastric juice whose CA 19-9 was detected, with serum CA 19-9 monitored as a comparison. We found that: gastric juice CA 19-9 pre-gastrectomy was significantly correlated with tumor TNM classification, regarding tumor size, level of gastric wall invaded, differentiated grade and number of metastatic lymph nodes as influencing factors, while serum CA 19-9 revealed little information; gastric juice CA 19-9 was significantly correlated with radical degree, and regarded number of resected lymph nodes and classification of cutting edge as impact factors; thirteen patients whose gastric juice CA 19-9 rose post-DG showed features indicating poor prognosis; the difference of gastric juice CA 19-9 between pre- and post-gastrectomy was correlated with tumor TNM classification and radical degree, and regarded tumor size, number of resected metastatic and normal lymph nodes, sum of distances from tumor to cutting edges and classification of cutting edge as influential factors. We conclude that peri-DG gastric juice CA 19-9 reveals much information about tumor and radical gastrectomy, and may indicate prognosis; while serum CA 19-9 has limited significance. PMID:24482710

Localization of Acoustic Transients in Shallow Water Environments

DTIC Science & Technology

1992-12-01

effect of the source signal uncertainty (in localizer performance . The localization process consists of two parts. First, a time domain propagation...for public release; distribution is unlimited 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) E OF PERFORMING ...SOURCE OF FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO. ACCESSION NO. 11. TITLE (Include Security Classification) LOCALIZATION OF

Multistep method to deal with large datasets in asteroid family classification

NASA Astrophysics Data System (ADS)

Knežević, Z.; Milani, A.; Cellino, A.; Novaković, B.; Spoto, F.; Paolicchi, P.

2014-07-01

A fast increase in the number of asteroids with accurately determined orbits and with known physical properties makes it more and more challenging to perform, maintain, and update a classification of asteroids into families. We have therefore developed a new approach to the family classification by combining the Hierarchical Clustering Method (HCM) [1] to identify the families with an automated method to add members to already known families. This procedure makes use of the maximum available information, in particular, of that contained in the proper elements catalog [2]. The catalog of proper elements and absolute magnitudes used in our study contains 336 319 numbered asteroids with an information content of 16.31 Mb. The WISE catalog of albedos [3] and SDSS catalog of color indexes [4] contain 94 632 and 59 975 entries, respectively, with a total amount of information of 0.93 Mb. Our procedure makes use of the segmentation of the proper elements catalog by semimajor axis, to deal with a manageable number of objects in each zone, and by inclination, to account for lower density of high-inclination objects. By selecting from the catalog a much smaller number of large asteroids, in the first step, we identify a number of core families; to these, in the second step, we attribute the next layer of smaller objects. In the third step, we remove all the family members from the catalog, and reapply the HCM to the rest; this gives both satellite families which extend the core families and new independent families, consisting mainly of small asteroids. These two cases are separated in the fourth step by attribution of another layer of new members and by merging intersecting families. This leads to a classification with 128 families and 87 095 members. The list of members is updated automatically with each update of the proper elements catalog, and this represents the final and repetitive step of the procedure. Changes in the list of families are not automated.

Hodge numbers for CICYs with symmetries of order divisible by 4

NASA Astrophysics Data System (ADS)

Candelas, Philip; Constantin, Andrei; Mishra, Challenger

2016-06-01

We compute the Hodge numbers for the quotients of complete intersection Calabi-Yau three-folds by groups of orders divisible by 4. We make use of the polynomial deformation method and the counting of invariant K\\"ahler classes. The quotients studied here have been obtained in the automated classification of V. Braun. Although the computer search found the freely acting groups, the Hodge numbers of the quotients were not calculated. The freely acting groups, $G$, that arise in the classification are either $Z_2$ or contain $Z_4$, $Z_2 \\times Z_2$, $Z_3$ or $Z_5$ as a subgroup. The Hodge numbers for the quotients for which the group $G$ contains $Z_3$ or $Z_5$ have been computed previously. This paper deals with the remaining cases, for which $G \\supseteq Z_4$ or $G\\supseteq Z_2 \\times Z_2$. We also compute the Hodge numbers for 99 of the 166 CICY's which have $Z_2$ quotients.

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.

Energy-efficient algorithm for classification of states of wireless sensor network using machine learning methods

NASA Astrophysics Data System (ADS)

Yuldashev, M. N.; Vlasov, A. I.; Novikov, A. N.

2018-05-01

This paper focuses on the development of an energy-efficient algorithm for classification of states of a wireless sensor network using machine learning methods. The proposed algorithm reduces energy consumption by: 1) elimination of monitoring of parameters that do not affect the state of the sensor network, 2) reduction of communication sessions over the network (the data are transmitted only if their values can affect the state of the sensor network). The studies of the proposed algorithm have shown that at classification accuracy close to 100%, the number of communication sessions can be reduced by 80%.

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.

National Dam Safety Program. J. Bristow Lake Dam (MO 30985), Mississippi - Kaskaskia - St. Louis River Basin, Crawford County, Missouri. Phase I Inspection Report.

DTIC Science & Technology

1980-08-01

8217 m’-* k TOW LAKE DAM -- CRAWFORD COUNTY, MISSOURI * ~MO 30MS PHASE 1 INSPECTION REPORT NATIONAL DAM SAFETY PROGRAM Unkd Ska AnviV €Ow" of Ifntineers I...REPORT NUMBER Crawford County, Missouri 7. AUTHOR() 1 . CONTRACT OR GRANT NUMBER(@) Anderson Engineering, Inc. D6ACW4 3-8j-C-#73 9. PERFORMING ORGANIZATION...oF 1 MOV SS IS O~LET’E 𔄃UNCLASSIFIED SECUFITY CLASSIFICATION OF THIS PAGE (When Dote Entered) SI ’ SECURITY CLASSIFICATION OF THIS PAOR(3SOM DOS a

Bibliometric trend and patent analysis in nano-alloys research for period 2000-2013.

PubMed

Živković, Dragana; Niculović, Milica; Manasijević, Dragan; Minić, Duško; Ćosović, Vladan; Sibinović, Maja

2015-05-04

This paper presents an overview of current situation in nano-alloys investigations based on bibliometric and patent analysis. Bibliometric analysis data, for period from 2000 to September 2013, were obtained using Scopus database as selected index database, whereas analyzed parameters were: number of scientific papers per years, authors, countries, affiliations, subject areas and document types. Analysis of nano-alloys patents was done with specific database, using the International Patent Classification and Patent Scope for the period from 2003 to 2013 year. Information found in this database was the number of patents, patent classification by country, patent applicators, main inventors and pub date.

Bibliometric trend and patent analysis in nano-alloys research for period 2000-2013.

PubMed

Živković, Dragana; Niculović, Milica; Manasijević, Dragan; Minić, Duško; Ćosović, Vladan; Sibinović, Maja

2015-01-01

This paper presents an overview of current situation in nano-alloys investigations based on bibliometric and patent analysis. Bibliometric analysis data, for the period 2000 to 2013, were obtained using Scopus database as selected index database, whereas analyzed parameters were: number of scientific papers per year, authors, countries, affiliations, subject areas and document types. Analysis of nano-alloys patents was done with specific database, using the International Patent Classification and Patent Scope for the period 2003 to 2013. Information found in this database was the number of patents, patent classification by country, patent applicators, main inventors and publication date.

Multiclass Classification by Adaptive Network of Dendritic Neurons with Binary Synapses Using Structural Plasticity

PubMed Central

Hussain, Shaista; Basu, Arindam

2016-01-01

The development of power-efficient neuromorphic devices presents the challenge of designing spike pattern classification algorithms which can be implemented on low-precision hardware and can also achieve state-of-the-art performance. In our pursuit of meeting this challenge, we present a pattern classification model which uses a sparse connection matrix and exploits the mechanism of nonlinear dendritic processing to achieve high classification accuracy. A rate-based structural learning rule for multiclass classification is proposed which modifies a connectivity matrix of binary synaptic connections by choosing the best “k” out of “d” inputs to make connections on every dendritic branch (k < < d). Because learning only modifies connectivity, the model is well suited for implementation in neuromorphic systems using address-event representation (AER). We develop an ensemble method which combines several dendritic classifiers to achieve enhanced generalization over individual classifiers. We have two major findings: (1) Our results demonstrate that an ensemble created with classifiers comprising moderate number of dendrites performs better than both ensembles of perceptrons and of complex dendritic trees. (2) In order to determine the moderate number of dendrites required for a specific classification problem, a two-step solution is proposed. First, an adaptive approach is proposed which scales the relative size of the dendritic trees of neurons for each class. It works by progressively adding dendrites with fixed number of synapses to the network, thereby allocating synaptic resources as per the complexity of the given problem. As a second step, theoretical capacity calculations are used to convert each neuronal dendritic tree to its optimal topology where dendrites of each class are assigned different number of synapses. The performance of the model is evaluated on classification of handwritten digits from the benchmark MNIST dataset and compared with other spike classifiers. We show that our system can achieve classification accuracy within 1 − 2% of other reported spike-based classifiers while using much less synaptic resources (only 7%) compared to that used by other methods. Further, an ensemble classifier created with adaptively learned sizes can attain accuracy of 96.4% which is at par with the best reported performance of spike-based classifiers. Moreover, the proposed method achieves this by using about 20% of the synapses used by other spike algorithms. We also present results of applying our algorithm to classify the MNIST-DVS dataset collected from a real spike-based image sensor and show results comparable to the best reported ones (88.1% accuracy). For VLSI implementations, we show that the reduced synaptic memory can save upto 4X area compared to conventional crossbar topologies. Finally, we also present a biologically realistic spike-based version for calculating the correlations required by the structural learning rule and demonstrate the correspondence between the rate-based and spike-based methods of learning. PMID:27065782

Multicategory Composite Least Squares Classifiers

PubMed Central

Park, Seo Young; Liu, Yufeng; Liu, Dacheng; Scholl, Paul

2010-01-01

Classification is a very useful statistical tool for information extraction. In particular, multicategory classification is commonly seen in various applications. Although binary classification problems are heavily studied, extensions to the multicategory case are much less so. In view of the increased complexity and volume of modern statistical problems, it is desirable to have multicategory classifiers that are able to handle problems with high dimensions and with a large number of classes. Moreover, it is necessary to have sound theoretical properties for the multicategory classifiers. In the literature, there exist several different versions of simultaneous multicategory Support Vector Machines (SVMs). However, the computation of the SVM can be difficult for large scale problems, especially for problems with large number of classes. Furthermore, the SVM cannot produce class probability estimation directly. In this article, we propose a novel efficient multicategory composite least squares classifier (CLS classifier), which utilizes a new composite squared loss function. The proposed CLS classifier has several important merits: efficient computation for problems with large number of classes, asymptotic consistency, ability to handle high dimensional data, and simple conditional class probability estimation. Our simulated and real examples demonstrate competitive performance of the proposed approach. PMID:21218128

Automatic classification of blank substrate defects

NASA Astrophysics Data System (ADS)

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

2014-10-01

Mask preparation stages are crucial in mask manufacturing, since this mask is to later act as a template for considerable number of dies on wafer. Defects on the initial blank substrate, and subsequent cleaned and coated substrates, can have a profound impact on the usability of the finished mask. This emphasizes the need for early and accurate identification of blank substrate defects and the risk they pose to the patterned reticle. While Automatic Defect Classification (ADC) is a well-developed technology for inspection and analysis of defects on patterned wafers and masks in the semiconductors industry, ADC for mask blanks is still in the early stages of adoption and development. Calibre ADC is a powerful analysis tool for fast, accurate, consistent and automatic classification of defects on mask blanks. Accurate, automated classification of mask blanks leads to better usability of blanks by enabling defect avoidance technologies during mask writing. Detailed information on blank defects can help to select appropriate job-decks to be written on the mask by defect avoidance tools [1][4][5]. Smart algorithms separate critical defects from the potentially large number of non-critical defects or false defects detected at various stages during mask blank preparation. Mechanisms used by Calibre ADC to identify and characterize defects include defect location and size, signal polarity (dark, bright) in both transmitted and reflected review images, distinguishing defect signals from background noise in defect images. The Calibre ADC engine then uses a decision tree to translate this information into a defect classification code. Using this automated process improves classification accuracy, repeatability and speed, while avoiding the subjectivity of human judgment compared to the alternative of manual defect classification by trained personnel [2]. This paper focuses on the results from the evaluation of Automatic Defect Classification (ADC) product at MP Mask Technology Center (MPMask). The Calibre ADC tool was qualified on production mask blanks against the manual classification. The classification accuracy of ADC is greater than 95% for critical defects with an overall accuracy of 90%. The sensitivity to weak defect signals and locating the defect in the images is a challenge we are resolving. The performance of the tool has been demonstrated on multiple mask types and is ready for deployment in full volume mask manufacturing production flow. Implementation of Calibre ADC is estimated to reduce the misclassification of critical defects by 60-80%.

Comparing performance of mothers using simplified mid-upper arm circumference (MUAC) classification devices with an improved MUAC insertion tape in Isiolo County, Kenya.

PubMed

Grant, Angeline; Njiru, James; Okoth, Edgar; Awino, Imelda; Briend, André; Murage, Samuel; Abdirahman, Saida; Myatt, Mark

2018-01-01

A novel approach for improving community case-detection of acute malnutrition involves mothers/caregivers screening their children for acute malnutrition using a mid-upper arm circumference (MUAC) insertion tape. The objective of this study was to test three simple MUAC classification devices to determine whether they improved the sensitivity of mothers/caregivers at detecting acute malnutrition. Prospective, non-randomised, partially-blinded, clinical diagnostic trial describing and comparing the performance of three "Click-MUAC" devices and a MUAC insertion tape. The study took place in twenty-one health facilities providing integrated management of acute malnutrition (IMAM) services in Isiolo County, Kenya. Mothers/caregivers classified their child ( n =1040), aged 6-59 months, using the "Click-MUAC" devices and a MUAC insertion tape. These classifications were compared to a "gold standard" classification (the mean of three measurements taken by a research assistant using the MUAC insertion tape). The sensitivity of mother/caregiver classifications was high for all devices (>93% for severe acute malnutrition (SAM), defined by MUAC < 115 mm, and > 90% for global acute malnutrition (GAM), defined by MUAC < 125 mm). Mother/caregiver sensitivity for SAM and GAM classification was higher using the MUAC insertion tape (100% sensitivity for SAM and 99% sensitivity for GAM) than using "Click-MUAC" devices. Younden's J for SAM classification, and sensitivity for GAM classification, were significantly higher for the MUAC insertion tape (99% and 99% respectively). Specificity was high for all devices (>96%) with no significant difference between the "Click-MUAC" devices and the MUAC insertion tape. The results of this study indicate that, although the "Click-MUAC" devices performed well, the MUAC insertion tape performed best. The results for sensitivity are higher than found in previous studies. The high sensitivity for both SAM and GAM classification by mothers/caregivers with the MUAC insertion tape could be due to the use of an improved MUAC tape design which has a number of new design features. The one-on-one demonstration provided to mothers/caregivers on the use of the devices may also have helped improve sensitivity. The results of this study provide evidence that mothers/caregivers can perform sensitive and specific classifications of their child's nutritional status using MUAC. Clinical trials registration number: NCT02833740.

Preparation of Chemical Samples On Relevant Surfaces Using Inkjet Technology

DTIC Science & Technology

2013-04-01

PREPARATION OF CHEMICAL SAMPLES ON RELEVANT SURFACES USING INKJET TECHNOLOGY...2012 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Preparation of Chemical Samples on Relevant Surfaces Using Inkjet Technology 5b. GRANT NUMBER...SUBJECT TERMS Surface detection Inkjet Simulant deposition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF

A novel channel selection method for optimal classification in different motor imagery BCI paradigms.

PubMed

Shan, Haijun; Xu, Haojie; Zhu, Shanan; He, Bin

2015-10-21

For sensorimotor rhythms based brain-computer interface (BCI) systems, classification of different motor imageries (MIs) remains a crucial problem. An important aspect is how many scalp electrodes (channels) should be used in order to reach optimal performance classifying motor imaginations. While the previous researches on channel selection mainly focus on MI tasks paradigms without feedback, the present work aims to investigate the optimal channel selection in MI tasks paradigms with real-time feedback (two-class control and four-class control paradigms). In the present study, three datasets respectively recorded from MI tasks experiment, two-class control and four-class control experiments were analyzed offline. Multiple frequency-spatial synthesized features were comprehensively extracted from every channel, and a new enhanced method IterRelCen was proposed to perform channel selection. IterRelCen was constructed based on Relief algorithm, but was enhanced from two aspects: change of target sample selection strategy and adoption of the idea of iterative computation, and thus performed more robust in feature selection. Finally, a multiclass support vector machine was applied as the classifier. The least number of channels that yield the best classification accuracy were considered as the optimal channels. One-way ANOVA was employed to test the significance of performance improvement among using optimal channels, all the channels and three typical MI channels (C3, C4, Cz). The results show that the proposed method outperformed other channel selection methods by achieving average classification accuracies of 85.2, 94.1, and 83.2 % for the three datasets, respectively. Moreover, the channel selection results reveal that the average numbers of optimal channels were significantly different among the three MI paradigms. It is demonstrated that IterRelCen has a strong ability for feature selection. In addition, the results have shown that the numbers of optimal channels in the three different motor imagery BCI paradigms are distinct. From a MI task paradigm, to a two-class control paradigm, and to a four-class control paradigm, the number of required channels for optimizing the classification accuracy increased. These findings may provide useful information to optimize EEG based BCI systems, and further improve the performance of noninvasive BCI.

Do Adverse Childhood Experiences Increase the Risk of Postdeployment Posttraumatic Stress Disorder in US Marines

DTIC Science & Technology

2010-01-01

GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND...REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME( S ) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM( S ) 11. SPONSOR/MONITOR’S REPORT NUMBER( S ) 12...retardation, and substance abuse or dependence. Coding was based on the International Classification of Diseases , Ninth Revision, Clinical

Continuous robust sound event classification using time-frequency features and deep learning

PubMed Central

Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification. PMID:28892478

Continuous robust sound event classification using time-frequency features and deep learning.

PubMed

McLoughlin, Ian; Zhang, Haomin; Xie, Zhipeng; Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification.

Modified Angle's Classification for Primary Dentition.

PubMed

Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita

2017-01-01

This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3-6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry.

Computer Recognition of Facial Profiles

DTIC Science & Technology

1974-08-01

facial recognition 20. ABSTRACT (Continue on reverse side It necessary and Identify by block number) A system for the recognition of human faces from...21 2.6 Classification Algorithms ........... ... 32 III FACIAL RECOGNITION AND AUTOMATIC TRAINING . . . 37 3.1 Facial Profile Recognition...provide a fair test of the classification system. The work of Goldstein, Harmon, and Lesk [81 indicates, however, that for facial recognition , a ten class

Program for Critical Technologies in Breast Oncology

DTIC Science & Technology

1999-07-01

the tissues, and in a ethical manner that respects the patients’ rights . The Program for Critical Technologies in Breast Oncology helps address all of...diagnosis, database 15. NUMBER OF PAGES 148 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS...closer to clinical utility. Page 17 References Adida C. Crotty PL. McGrath J. Berrebi D. Diebold J. Altieri DC. Developmentally regulated

Identification of Protein Components of Yeast Telomerase

DTIC Science & Technology

2000-09-01

cells past this limit senesce, or stop growing (reviewed in Hayflick 1997). This limit is imposed by the inactivity of telomerase, which results in...CLASSIFICATION OF THIS PAGE Unclassified 19. SECURITY CLASSIFICATION OF ABSTRACT Unclassified 15. NUMBER OF PAGES 55 16. PRICE CODE 20. LIMITATION ...one of which is the acquired capability of limitless replicative potential. Normal mammalian cells have an intrinsic limit to cellular division, and

The NAICS Code Selection Process And Small Business Participation

DTIC Science & Technology

2016-03-01

specialist 15. NUMBER OF PAGES 59 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS PAGE...FPDS-NG) website and information gathered from interviews with small business specialists . The data include contract actions from 276 contracts with...used interviews to determine if small businesses are affected by inappropriate NAICS code selection. None of the six small business specialists we

North American vegetation model for land-use planning in a changing climate: A solution to large classification problems

Treesearch

Gerald E. Rehfeldt; Nicholas L. Crookston; Cuauhtemoc Saenz-Romero; Elizabeth M. Campbell

2012-01-01

Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of...

The Development of Classification at the Library of Congress. Occasional Papers, Number 164.

ERIC Educational Resources Information Center

Miksa, Francis

This paper traces the development of classification at the Library of Congress in terms of its broader context and by accounting for changes in the present system since its initial period of creation between 1898 and 1910 and the present. Topics covered include: (1) Early Growth of the Collections; (2) Subject Access During the Early Years; (3) A.…

Unionization and Monetary Compensation at America's Access Institutions: Assessing the Impact of Frames That Do or Do Not Consider Geography

ERIC Educational Resources Information Center

Shedd, Louis; Katsinas, Stephen; Bray, Nathaniel

2018-01-01

This article categorizes institutions under both the 2015 Carnegie Basic Classification system and the mission-driven classification system, and further analyzes both by the presence of a collective bargaining agreement. The goal of this article was to use the presentation of data on revenue, employment numbers, salary outlays, and the presence or…

Assessing College Student Interest in Math and/or Computer Science in a Cross-National Sample Using Classification and Regression Trees

ERIC Educational Resources Information Center

Kitsantas, Anastasia; Kitsantas, Panagiota; Kitsantas, Thomas

2012-01-01

The purpose of this exploratory study was to assess the relative importance of a number of variables in predicting students' interest in math and/or computer science. Classification and regression trees (CART) were employed in the analysis of survey data collected from 276 college students enrolled in two U.S. and Greek universities. The results…

OTH Radar Surveillance at WARF During the LRAPP Church Opal Exercise

DTIC Science & Technology

1976-11-01

UNCLASSIFIED AD NUMBER ADC010483 CLASSIFICATION CHANGES TO: unclassified FROM: secret LIMITATION CHANGES TO: Approved for public release... DDC SRI STANFORD RESEARCH INSTITUTE Menlo Park, California 94025 U.S.A.D SECRET UNCLASSIFIED The views and conclusions contained in this document are...3 SRI 6-4696 DECLASSIFIED ON 31 December 2005 SECRET (This page is UNCLASSIFIED) . ... ..... .. SECRET SECURITY CLASSIFICATION OF THIS PAGE (When

48 CFR 204.7101 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 3 2013-10-01 2013-10-01 false Definitions. 204.7101... OF DEFENSE GENERAL ADMINISTRATIVE MATTERS Uniform Contract Line Item Numbering System 204.7101 Definitions. Accounting classification reference number (ACRN) means any combination of a two position alpha...

48 CFR 204.7101 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Definitions. 204.7101... OF DEFENSE GENERAL ADMINISTRATIVE MATTERS Uniform Contract Line Item Numbering System 204.7101 Definitions. Accounting classification reference number (ACRN) means any combination of a two position alpha...

Environmental Assessment for US 98 (SR 30) at the Entrance to Hurlburt Field

DTIC Science & Technology

2010-09-01

CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER ...SUBJECT TERMS 16. SECURITY CLASSIFICATION OF : 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18. NUMBER OF PAGES 176 19a. NAME OF RESPONSIBLE... contract quarters off-base. Due to land constraints at Hurlburt Field, an estimated two- thirds of its military personnel are housed off of

Molecular Identification of the Schwannomatosis Locus

DTIC Science & Technology

2005-07-01

AD Award Number: DAMD17-03-1-0445 TITLE: Molecular Identification of the Schwannomatosis Locus PRINCIPAL INVESTIGATOR: Mia M. MacCollin, M.D...NUMBER Molecular Identification of the Schwannomatosis Locus 5b. GRANT NUMBER DAMD17-03-1-0445 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER...can be found on next page. 15. SUBJECT TERMS schwannomatosis , tumor suppressor gene, NF2, molecular genetics 16. SECURITY CLASSIFICATION OF: 17

Multiple-rule bias in the comparison of classification rules

PubMed Central

Yousefi, Mohammadmahdi R.; Hua, Jianping; Dougherty, Edward R.

2011-01-01

Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of reported results. Two approaches contributing to overoptimism in classification are (i) the reporting of results on datasets for which a proposed classification rule performs well and (ii) the comparison of multiple classification rules on a single dataset that purports to show the advantage of a certain rule. Results: This article provides a careful probabilistic analysis of the second issue and the ‘multiple-rule bias’, resulting from choosing a classification rule having minimum estimated error on the dataset. It quantifies this bias corresponding to estimating the expected true error of the classification rule possessing minimum estimated error and it characterizes the bias from estimating the true comparative advantage of the chosen classification rule relative to the others by the estimated comparative advantage on the dataset. The analysis is applied to both synthetic and real data using a number of classification rules and error estimators. Availability: We have implemented in C code the synthetic data distribution model, classification rules, feature selection routines and error estimation methods. The code for multiple-rule analysis is implemented in MATLAB. The source code is available at http://gsp.tamu.edu/Publications/supplementary/yousefi11a/. Supplementary simulation results are also included. Contact: edward@ece.tamu.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21546390

Statistical learning from nonrecurrent experience with discrete input variables and recursive-error-minimization equations

NASA Astrophysics Data System (ADS)

Carter, Jeffrey R.; Simon, Wayne E.

1990-08-01

Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and

Ototoxicity (cochleotoxicity) classifications: A review.

PubMed

Crundwell, Gemma; Gomersall, Phil; Baguley, David M

2016-01-01

Drug-mediated ototoxicity, specifically cochleotoxicity, is a concern for patients receiving medications for the treatment of serious illness. A number of classification schemes exist, most of which are based on pure-tone audiometry, in order to assist non-audiological/non-otological specialists in the identification and monitoring of iatrogenic hearing loss. This review identifies the primary classification systems used in cochleototoxicity monitoring. By bringing together classifications published in discipline-specific literature, the paper aims to increase awareness of their relative strengths and limitations in the assessment and monitoring of ototoxic hearing loss and to indicate how future classification systems may improve upon the status-quo. Literature review. PubMed identified 4878 articles containing the search term ototox*. A systematic search identified 13 key classification systems. Cochleotoxicity classification systems can be divided into those which focus on hearing change from a baseline audiogram and those that focus on the functional impact of the hearing loss. Common weaknesses of these grading scales included a lack of sensitivity to small adverse changes in hearing thresholds, a lack of high-frequency audiometry (>8 kHz), and lack of indication of which changes are likely to be clinically significant for communication and quality of life.

Rotationally Invariant Image Representation for Viewing Direction Classification in Cryo-EM

PubMed Central

Zhao, Zhizhen; Singer, Amit

2014-01-01

We introduce a new rotationally invariant viewing angle classification method for identifying, among a large number of cryo-EM projection images, similar views without prior knowledge of the molecule. Our rotationally invariant features are based on the bispectrum. Each image is denoised and compressed using steerable principal component analysis (PCA) such that rotating an image is equivalent to phase shifting the expansion coefficients. Thus we are able to extend the theory of bispectrum of 1D periodic signals to 2D images. The randomized PCA algorithm is then used to efficiently reduce the dimensionality of the bispectrum coefficients, enabling fast computation of the similarity between any pair of images. The nearest neighbors provide an initial classification of similar viewing angles. In this way, rotational alignment is only performed for images with their nearest neighbors. The initial nearest neighbor classification and alignment are further improved by a new classification method called vector diffusion maps. Our pipeline for viewing angle classification and alignment is experimentally shown to be faster and more accurate than reference-free alignment with rotationally invariant K-means clustering, MSA/MRA 2D classification, and their modern approximations. PMID:24631969

Classification of visible and infrared hyperspectral images based on image segmentation and edge-preserving filtering

NASA Astrophysics Data System (ADS)

Cui, Binge; Ma, Xiudan; Xie, Xiaoyun; Ren, Guangbo; Ma, Yi

2017-03-01

The classification of hyperspectral images with a few labeled samples is a major challenge which is difficult to meet unless some spatial characteristics can be exploited. In this study, we proposed a novel spectral-spatial hyperspectral image classification method that exploited spatial autocorrelation of hyperspectral images. First, image segmentation is performed on the hyperspectral image to assign each pixel to a homogeneous region. Second, the visible and infrared bands of hyperspectral image are partitioned into multiple subsets of adjacent bands, and each subset is merged into one band. Recursive edge-preserving filtering is performed on each merged band which utilizes the spectral information of neighborhood pixels. Third, the resulting spectral and spatial feature band set is classified using the SVM classifier. Finally, bilateral filtering is performed to remove "salt-and-pepper" noise in the classification result. To preserve the spatial structure of hyperspectral image, edge-preserving filtering is applied independently before and after the classification process. Experimental results on different hyperspectral images prove that the proposed spectral-spatial classification approach is robust and offers more classification accuracy than state-of-the-art methods when the number of labeled samples is small.

Information extraction with object based support vector machines and vegetation indices

NASA Astrophysics Data System (ADS)

Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

2016-07-01

Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

Towards an Automated Classification of Transient Events in Synoptic Sky Surveys

NASA Technical Reports Server (NTRS)

Djorgovski, S. G.; Donalek, C.; Mahabal, A. A.; Moghaddam, B.; Turmon, M.; Graham, M. J.; Drake, A. J.; Sharma, N.; Chen, Y.

2011-01-01

We describe the development of a system for an automated, iterative, real-time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly using Bayesian approaches, due to the sparse nature, heterogeneity, and variable incompleteness of the available data. The classifications are improved iteratively as the new measurements are obtained. One novel featrue is the development of an automated follow-up recommendation engine, that suggest those measruements that would be the most advantageous in terms of resolving classification ambiguities and/or characterization of the astrophysically most interesting objects, given a set of available follow-up assets and their cost funcations. This illustrates the symbiotic relationship of astronomy and applied computer science through the emerging disciplne of AstroInformatics.

A scheme for the classification of explosions in the chemical process industry.

PubMed

Abbasi, Tasneem; Pasman, H J; Abbasi, S A

2010-02-15

All process industry accidents fall under three broad categories-fire, explosion, and toxic release. Of these fire is the most common, followed by explosions. Within these broad categories occur a large number of sub-categories, each depicting a specific sub-type of a fire/explosion/toxic release. But whereas clear and self-consistent sub-classifications exist for fires and toxic releases, the situation is not as clear vis a vis explosions. In this paper the inconsistencies and/or shortcomings associated with the classification of different types of explosions, which are seen even in otherwise highly authentic and useful reference books on process safety, are reviewed. In its context a new classification is attempted which may, hopefully, provide a frame-of-reference for the future.

exprso: an R-package for the rapid implementation of machine learning algorithms.

PubMed

Quinn, Thomas; Tylee, Daniel; Glatt, Stephen

2016-01-01

Machine learning plays a major role in many scientific investigations. However, non-expert programmers may struggle to implement the elaborate pipelines necessary to build highly accurate and generalizable models. We introduce exprso , a new R package that is an intuitive machine learning suite designed specifically for non-expert programmers. Built initially for the classification of high-dimensional data, exprso uses an object-oriented framework to encapsulate a number of common analytical methods into a series of interchangeable modules. This includes modules for feature selection, classification, high-throughput parameter grid-searching, elaborate cross-validation schemes (e.g., Monte Carlo and nested cross-validation), ensemble classification, and prediction. In addition, exprso also supports multi-class classification (through the 1-vs-all generalization of binary classifiers) and the prediction of continuous outcomes.

Asteroid families classification: Exploiting very large datasets

NASA Astrophysics Data System (ADS)

Milani, Andrea; Cellino, Alberto; Knežević, Zoran; Novaković, Bojan; Spoto, Federica; Paolicchi, Paolo

2014-09-01

The number of asteroids with accurately determined orbits increases fast, and this increase is also accelerating. The catalogs of asteroid physical observations have also increased, although the number of objects is still smaller than in the orbital catalogs. Thus it becomes more and more challenging to perform, maintain and update a classification of asteroids into families. To cope with these challenges we developed a new approach to the asteroid family classification by combining the Hierarchical Clustering Method (HCM) with a method to add new members to existing families. This procedure makes use of the much larger amount of information contained in the proper elements catalogs, with respect to classifications using also physical observations for a smaller number of asteroids. Our work is based on a large catalog of high accuracy synthetic proper elements (available from AstDyS), containing data for >330,000 numbered asteroids. By selecting from the catalog a much smaller number of large asteroids, we first identify a number of core families; to these we attribute the next layer of smaller objects. Then, we remove all the family members from the catalog, and reapply the HCM to the rest. This gives both satellite families which extend the core families and new independent families, consisting mainly of small asteroids. These two cases are discriminated by another step of attribution of new members and by merging intersecting families. This leads to a classification with 128 families and currently 87,095 members. The number of members can be increased automatically with each update of the proper elements catalog; changes in the list of families are not automated. By using information from absolute magnitudes, we take advantage of the larger size range in some families to analyze their shape in the proper semimajor axis vs. inverse diameter plane. This leads to a new method to estimate the family age, or ages in cases where we identify internal structures. The analysis of the plot above evidences some open problems but also the possibility of obtaining further information of the geometrical properties of the impact process. The results from the previous steps are then analyzed, using also auxiliary information on physical properties including WISE albedos and SDSS color indexes. This allows to solve some difficult cases of families overlapping in the proper elements space but generated by different collisional events. The families formed by one or more cratering events are found to be more numerous than previously believed because the fragments are smaller. We analyze some examples of cratering families (Massalia, Vesta, Eunomia) which show internal structures, interpreted as multiple collisions. We also discuss why Ceres has no family.

Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control.

PubMed

Olives, Casey; Valadez, Joseph J; Brooker, Simon J; Pagano, Marcello

2012-01-01

Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa. We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n=15 and n=25 via a weighted kappa-statistic using S. mansoni data collected in 388 schools from four studies in East Africa. Overall performance of MC-LQAS classification was high (kappa-statistic of 0.87). In three of the studies, the kappa-statistic for a design with n=15 was greater than 0.75. In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error. This work provides the needed analytics to understand the properties of MC-LQAS for assessing the prevalance of S. mansoni and shows that in most settings a sample size of 15 children provides a reliable classification of schools.

Population-based evaluation of a suggested anatomic and clinical classification of congenital heart defects based on the International Paediatric and Congenital Cardiac Code.

PubMed

Houyel, Lucile; Khoshnood, Babak; Anderson, Robert H; Lelong, Nathalie; Thieulin, Anne-Claire; Goffinet, François; Bonnet, Damien

2011-10-03

Classification of the overall spectrum of congenital heart defects (CHD) has always been challenging, in part because of the diversity of the cardiac phenotypes, but also because of the oft-complex associations. The purpose of our study was to establish a comprehensive and easy-to-use classification of CHD for clinical and epidemiological studies based on the long list of the International Paediatric and Congenital Cardiac Code (IPCCC). We coded each individual malformation using six-digit codes from the long list of IPCCC. We then regrouped all lesions into 10 categories and 23 subcategories according to a multi-dimensional approach encompassing anatomic, diagnostic and therapeutic criteria. This anatomic and clinical classification of congenital heart disease (ACC-CHD) was then applied to data acquired from a population-based cohort of patients with CHD in France, made up of 2867 cases (82% live births, 1.8% stillbirths and 16.2% pregnancy terminations). The majority of cases (79.5%) could be identified with a single IPCCC code. The category "Heterotaxy, including isomerism and mirror-imagery" was the only one that typically required more than one code for identification of cases. The two largest categories were "ventricular septal defects" (52%) and "anomalies of the outflow tracts and arterial valves" (20% of cases). Our proposed classification is not new, but rather a regrouping of the known spectrum of CHD into a manageable number of categories based on anatomic and clinical criteria. The classification is designed to use the code numbers of the long list of IPCCC but can accommodate ICD-10 codes. Its exhaustiveness, simplicity, and anatomic basis make it useful for clinical and epidemiologic studies, including those aimed at assessment of risk factors and outcomes.

Examining the effectiveness of discriminant function analysis and cluster analysis in species identification of male field crickets based on their calling songs.

PubMed

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage.

PubMed

Kimura, Shinya; Sato, Toshihiko; Ikeda, Shunya; Noda, Mitsuhiko; Nakayama, Takeo

2010-01-01

Health insurance claims (ie, receipts) record patient health care treatments and expenses and, although created for the health care payment system, are potentially useful for research. Combining different types of receipts generated for the same patient would dramatically increase the utility of these receipts. However, technical problems, including standardization of disease names and classifications, and anonymous linkage of individual receipts, must be addressed. In collaboration with health insurance societies, all information from receipts (inpatient, outpatient, and pharmacy) was collected. To standardize disease names and classifications, we developed a computer-aided post-entry standardization method using a disease name dictionary based on International Classification of Diseases (ICD)-10 classifications. We also developed an anonymous linkage system by using an encryption code generated from a combination of hash values and stream ciphers. Using different sets of the original data (data set 1: insurance certificate number, name, and sex; data set 2: insurance certificate number, date of birth, and relationship status), we compared the percentage of successful record matches obtained by using data set 1 to generate key codes with the percentage obtained when both data sets were used. The dictionary's automatic conversion of disease names successfully standardized 98.1% of approximately 2 million new receipts entered into the database. The percentage of anonymous matches was higher for the combined data sets (98.0%) than for data set 1 (88.5%). The use of standardized disease classifications and anonymous record linkage substantially contributed to the construction of a large, chronologically organized database of receipts. This database is expected to aid in epidemiologic and health services research using receipt information.

An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph

NASA Astrophysics Data System (ADS)

Zagouras, Athanassios; Argiriou, Athanassios A.; Flocas, Helena A.; Economou, George; Fotopoulos, Spiros

2012-11-01

Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850 hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters.

Adverse events following cervical manipulative therapy: consensus on classification among Dutch medical specialists, manual therapists, and patients.

PubMed

Kranenburg, Hendrikus A; Lakke, Sandra E; Schmitt, Maarten A; Van der Schans, Cees P

2017-12-01

To obtain consensus-based agreement on a classification system of adverse events (AE) following cervical spinal manipulation. The classification system should be comprised of clear definitions, include patients' and clinicians' perspectives, and have an acceptable number of categories. Design : A three-round Delphi study. Participants : Thirty Dutch participants (medical specialists, manual therapists, and patients) participated in an online survey. Procedure : Participants inventoried AE and were asked about their preferences for either a three- or a four-category classification system. The identified AE were classified by two analysts following the International Classification of Functioning, Disability and Health (ICF), and the International Classification of Diseases and Related Health Problems (ICD-10). Participants were asked to classify the severity for all AE in relation to the time duration. Consensus occurred in a three-category classification system. There was strong consensus for 16 AE in all severities (no, minor, and major AE) and all three time durations [hours, days, weeks]. The 16 AE included anxiety, flushing, skin rash, fainting, dizziness, coma, altered sensation, muscle tenderness, pain, increased pain during movement, radiating pain, dislocation, fracture, transient ischemic attack, stroke, and death. Mild to strong consensus was reached for 13 AE. A consensus-based classification system of AE is established which includes patients' and clinicians' perspectives and has three categories. The classification comprises a precise description of potential AE in accordance with internationally accepted classifications. After international validation, clinicians and researchers may use this AE classification system to report AE in clinical practice and research.

Aerodynamic Classification of Swept-Wing Ice Accretion

NASA Technical Reports Server (NTRS)

Diebold, Jeff M.; Broeren, Andy P.; Bragg, Michael B.

2013-01-01

The continued design, certification and safe operation of swept-wing airplanes in icing conditions rely on the advancement of computational and experimental simulation methods for higher fidelity results over an increasing range of aircraft configurations and performance, and icing conditions. The current stateof- the-art in icing aerodynamics is mainly built upon a comprehensive understanding of two-dimensional geometries that does not currently exist for fundamentally three-dimensional geometries such as swept wings. The purpose of this report is to describe what is known of iced-swept-wing aerodynamics and to identify the type of research that is required to improve the current understanding. Following the method used in a previous review of iced-airfoil aerodynamics, this report proposes a classification of swept-wing ice accretion into four groups based upon unique flowfield attributes. These four groups are: ice roughness, horn ice, streamwise ice and spanwise-ridge ice. In the case of horn ice it is shown that a further subclassification of "nominally 3D" or "highly 3D" horn ice may be necessary. For all of the proposed ice-shape classifications, relatively little is known about the three-dimensional flowfield and even less about the effect of Reynolds number and Mach number on these flowfields. The classifications and supporting data presented in this report can serve as a starting point as new research explores swept-wing aerodynamics with ice shapes. As further results are available, it is expected that these classifications will need to be updated and revised.

Aerodynamic Classification of Swept-Wing Ice Accretion

NASA Technical Reports Server (NTRS)

Diebold, Jeff M.; Broeren, Andy P.; Bragg, Michael B.

2013-01-01

The continued design, certification and safe operation of swept-wing airplanes in icing conditions rely on the advancement of computational and experimental simulation methods for higher fidelity results over an increasing range of aircraft configurations and performance, and icing conditions. The current state-of-the-art in icing aerodynamics is mainly built upon a comprehensive understanding of two-dimensional geometries that does not currently exist for fundamentally three-dimensional geometries such as swept wings. The purpose of this report is to describe what is known of iced-swept-wing aerodynamics and to identify the type of research that is required to improve the current understanding. Following the method used in a previous review of iced-airfoil aerodynamics, this report proposes a classification of swept-wing ice accretion into four groups based upon unique flowfield attributes. These four groups are: ice roughness, horn ice, streamwise ice and spanwise-ridge ice. In the case of horn ice it is shown that a further subclassification of nominally 3D or highly 3D horn ice may be necessary. For all of the proposed ice-shape classifications, relatively little is known about the three-dimensional flowfield and even less about the effect of Reynolds number and Mach number on these flowfields. The classifications and supporting data presented in this report can serve as a starting point as new research explores swept-wing aerodynamics with ice shapes. As further results are available, it is expected that these classifications will need to be updated and revised.

Neuropsychological Test Selection for Cognitive Impairment Classification: A Machine Learning Approach

PubMed Central

Williams, Jennifer A.; Schmitter-Edgecombe, Maureen; Cook, Diane J.

2016-01-01

Introduction Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI) or dementia using a suite of classification techniques. Methods Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis, clinical dementia rating; CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. Twenty-seven demographic, psychological, and neuropsychological variables were available for variable selection. Results No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0 – 99.1%), geometric mean (60.9 – 98.1%), sensitivity (44.2 – 100%), and specificity (52.7 – 100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2 – 9 variables were required for classification and varied between datasets in a clinically meaningful way. Conclusions The current study results reveal that machine learning techniques can accurately classifying cognitive impairment and reduce the number of measures required for diagnosis. PMID:26332171

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Compensation for Asbestos-Related Diseases in Japan: Utilization of Standard Classifications of Industry and Occupations

PubMed

Sawanyawisuth, Kittisak; Furuya, Sugio; Park, Eun-Kee; Myong, Jun-Pyo; Ramos-Bonilla, Juan Pablo; Chimed Ochir, Odgerel; Takahashi, Ken

2017-07-27

Background: Asbestos-related diseases (ARD) are occupational hazards with high mortality rates. To identify asbestos exposure by previous occupation is the main issue for ARD compensation for workers. This study aimed to identify risk groups by applying standard classifications of industries and occupations to a national database of compensated ARD victims in Japan. Methods: We identified occupations that carry a risk of asbestos exposure according to the International Standard Industrial Classification of All Economic Activities (ISIC). ARD compensation data from Japan between 2006 and 2013 were retrieved. Each compensated worker was classified by job section and group according to the ISIC code. Risk ratios for compensation were calculated according to the percentage of workers compensated because of ARD in each ISIC category. Results: In total, there were 6,916 workers with ARD who received compensation in Japan between 2008 and 2013. ISIC classification section F (construction) had the highest compensated risk ratio of 6.3. Section C (manufacturing) and section F (construction) had the largest number of compensated workers (2,868 and 3,463, respectively). In the manufacturing section C, 9 out of 13 divisions had a risk ratio of more than 1. For ISIC divisions in the construction section, construction of buildings (division 41) had the highest number of workers registering claims (2,504). Conclusion: ISIC classification of occupations that are at risk of developing ARD can be used to identify the actual risk of workers’ compensation at the national level. Creative Commons Attribution License

Classification of polycystic ovary based on ultrasound images using competitive neural network

NASA Astrophysics Data System (ADS)

Dewi, R. M.; Adiwijaya; Wisesty, U. N.; Jondri

2018-03-01

Infertility in the women reproduction system due to inhibition of follicles maturation process causing the number of follicles which is called polycystic ovaries (PCO). PCO detection is still operated manually by a gynecologist by counting the number and size of follicles in the ovaries, so it takes a long time and needs high accuracy. In general, PCO can be detected by calculating stereology or feature extraction and classification. In this paper, we designed a system to classify PCO by using the feature extraction (Gabor Wavelet method) and Competitive Neural Network (CNN). CNN was selected because this method is the combination between Hemming Net and The Max Net so that the data classification can be performed based on the specific characteristics of ultrasound data. Based on the result of system testing, Competitive Neural Network obtained the highest accuracy is 80.84% and the time process is 60.64 seconds (when using 32 feature vectors as well as weight and bias values respectively of 0.03 and 0.002).

A New Data Mining Scheme Using Artificial Neural Networks

PubMed Central

Kamruzzaman, S. M.; Jehad Sarkar, A. M.

2011-01-01

Classification is one of the data mining problems receiving enormous attention in the database community. Although artificial neural networks (ANNs) have been successfully applied in a wide range of machine learning applications, they are however often regarded as black boxes, i.e., their predictions cannot be explained. To enhance the explanation of ANNs, a novel algorithm to extract symbolic rules from ANNs has been proposed in this paper. ANN methods have not been effectively utilized for data mining tasks because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or interpretation by human experts. With the proposed approach, concise symbolic rules with high accuracy, that are easily explainable, can be extracted from the trained ANNs. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the accuracy. The effectiveness of the proposed approach is clearly demonstrated by the experimental results on a set of benchmark data mining classification problems. PMID:22163866

A Genealogy of Convex Solids Via Local and Global Bifurcations of Gradient Vector Fields

NASA Astrophysics Data System (ADS)

Domokos, Gábor; Holmes, Philip; Lángi, Zsolt

2016-12-01

Three-dimensional convex bodies can be classified in terms of the number and stability types of critical points on which they can balance at rest on a horizontal plane. For typical bodies, these are non-degenerate maxima, minima, and saddle points, the numbers of which provide a primary classification. Secondary and tertiary classifications use graphs to describe orbits connecting these critical points in the gradient vector field associated with each body. In previous work, it was shown that these classifications are complete in that no class is empty. Here, we construct 1- and 2-parameter families of convex bodies connecting members of adjacent primary and secondary classes and show that transitions between them can be realized by codimension 1 saddle-node and saddle-saddle (heteroclinic) bifurcations in the gradient vector fields. Our results indicate that all combinatorially possible transitions can be realized in physical shape evolution processes, e.g., by abrasion of sedimentary particles.

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm.

PubMed

Mao, Yong; Zhou, Xiao-Bo; Pi, Dao-Ying; Sun, You-Xian; Wong, Stephen T C

2005-10-01

In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two representative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method performs well in selecting genes and achieves high classification accuracies with these genes.

TomoMiner and TomoMinerCloud: A software platform for large-scale subtomogram structural analysis

PubMed Central

Frazier, Zachary; Xu, Min; Alber, Frank

2017-01-01

SUMMARY Cryo-electron tomography (cryoET) captures the 3D electron density distribution of macromolecular complexes in close to native state. With the rapid advance of cryoET acquisition technologies, it is possible to generate large numbers (>100,000) of subtomograms, each containing a macromolecular complex. Often, these subtomograms represent a heterogeneous sample due to variations in structure and composition of a complex in situ form or because particles are a mixture of different complexes. In this case subtomograms must be classified. However, classification of large numbers of subtomograms is a time-intensive task and often a limiting bottleneck. This paper introduces an open source software platform, TomoMiner, for large-scale subtomogram classification, template matching, subtomogram averaging, and alignment. Its scalable and robust parallel processing allows efficient classification of tens to hundreds of thousands of subtomograms. Additionally, TomoMiner provides a pre-configured TomoMinerCloud computing service permitting users without sufficient computing resources instant access to TomoMiners high-performance features. PMID:28552576

Emotional modelling and classification of a large-scale collection of scene images in a cluster environment

PubMed Central

Li, Yanfei; Tian, Yun

2018-01-01

The development of network technology and the popularization of image capturing devices have led to a rapid increase in the number of digital images available, and it is becoming increasingly difficult to identify a desired image from among the massive number of possible images. Images usually contain rich semantic information, and people usually understand images at a high semantic level. Therefore, achieving the ability to use advanced technology to identify the emotional semantics contained in images to enable emotional semantic image classification remains an urgent issue in various industries. To this end, this study proposes an improved OCC emotion model that integrates personality and mood factors for emotional modelling to describe the emotional semantic information contained in an image. The proposed classification system integrates the k-Nearest Neighbour (KNN) algorithm with the Support Vector Machine (SVM) algorithm. The MapReduce parallel programming model was used to adapt the KNN-SVM algorithm for parallel implementation in the Hadoop cluster environment, thereby achieving emotional semantic understanding for the classification of a massive collection of images. For training and testing, 70,000 scene images were randomly selected from the SUN Database. The experimental results indicate that users with different personalities show overall consistency in their emotional understanding of the same image. For a training sample size of 50,000, the classification accuracies for different emotional categories targeted at users with different personalities were approximately 95%, and the training time was only 1/5 of that required for the corresponding algorithm with a single-node architecture. Furthermore, the speedup of the system also showed a linearly increasing tendency. Thus, the experiments achieved a good classification effect and can lay a foundation for classification in terms of additional types of emotional image semantics, thereby demonstrating the practical significance of the proposed model. PMID:29320579

Emotional modelling and classification of a large-scale collection of scene images in a cluster environment.

PubMed

Cao, Jianfang; Li, Yanfei; Tian, Yun

2018-01-01

The development of network technology and the popularization of image capturing devices have led to a rapid increase in the number of digital images available, and it is becoming increasingly difficult to identify a desired image from among the massive number of possible images. Images usually contain rich semantic information, and people usually understand images at a high semantic level. Therefore, achieving the ability to use advanced technology to identify the emotional semantics contained in images to enable emotional semantic image classification remains an urgent issue in various industries. To this end, this study proposes an improved OCC emotion model that integrates personality and mood factors for emotional modelling to describe the emotional semantic information contained in an image. The proposed classification system integrates the k-Nearest Neighbour (KNN) algorithm with the Support Vector Machine (SVM) algorithm. The MapReduce parallel programming model was used to adapt the KNN-SVM algorithm for parallel implementation in the Hadoop cluster environment, thereby achieving emotional semantic understanding for the classification of a massive collection of images. For training and testing, 70,000 scene images were randomly selected from the SUN Database. The experimental results indicate that users with different personalities show overall consistency in their emotional understanding of the same image. For a training sample size of 50,000, the classification accuracies for different emotional categories targeted at users with different personalities were approximately 95%, and the training time was only 1/5 of that required for the corresponding algorithm with a single-node architecture. Furthermore, the speedup of the system also showed a linearly increasing tendency. Thus, the experiments achieved a good classification effect and can lay a foundation for classification in terms of additional types of emotional image semantics, thereby demonstrating the practical significance of the proposed model.

Joint Feature Selection and Classification for Multilabel Learning.

PubMed

Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

Classification of ligand molecules in PDB with graph match-based structural superposition.

PubMed

Shionyu-Mitsuyama, Clara; Hijikata, Atsushi; Tsuji, Toshiyuki; Shirai, Tsuyoshi

2016-12-01

The fast heuristic graph match algorithm for small molecules, COMPLIG, was improved by adding a structural superposition process to verify the atom-atom matching. The modified method was used to classify the small molecule ligands in the Protein Data Bank (PDB) by their three-dimensional structures, and 16,660 types of ligands in the PDB were classified into 7561 clusters. In contrast, a classification by a previous method (without structure superposition) generated 3371 clusters from the same ligand set. The characteristic feature in the current classification system is the increased number of singleton clusters, which contained only one ligand molecule in a cluster. Inspections of the singletons in the current classification system but not in the previous one implied that the major factors for the isolation were differences in chirality, cyclic conformations, separation of substructures, and bond length. Comparisons between current and previous classification systems revealed that the superposition-based classification was effective in clustering functionally related ligands, such as drugs targeted to specific biological processes, owing to the strictness of the atom-atom matching.

Towards a consensus on a hearing preservation classification system.

PubMed

Skarzynski, Henryk; van de Heyning, P; Agrawal, S; Arauz, S L; Atlas, M; Baumgartner, W; Caversaccio, M; de Bodt, M; Gavilan, J; Godey, B; Green, K; Gstoettner, W; Hagen, R; Han, D M; Kameswaran, M; Karltorp, E; Kompis, M; Kuzovkov, V; Lassaletta, L; Levevre, F; Li, Y; Manikoth, M; Martin, J; Mlynski, R; Mueller, J; O'Driscoll, M; Parnes, L; Prentiss, S; Pulibalathingal, S; Raine, C H; Rajan, G; Rajeswaran, R; Rivas, J A; Rivas, A; Skarzynski, P H; Sprinzl, G; Staecker, H; Stephan, K; Usami, S; Yanov, Y; Zernotti, M E; Zimmermann, K; Lorens, A; Mertens, G

2013-01-01

The comprehensive Hearing Preservation classification system presented in this paper is suitable for use for all cochlear implant users with measurable pre-operative residual hearing. If adopted as a universal reporting standard, as it was designed to be, it should prove highly beneficial by enabling future studies to quickly and easily compare the results of previous studies and meta-analyze their data. To develop a comprehensive Hearing Preservation classification system suitable for use for all cochlear implant users with measurable pre-operative residual hearing. The HEARRING group discussed and reviewed a number of different propositions of a HP classification systems and reviewed critical appraisals to develop a qualitative system in accordance with the prerequisites. The Hearing Preservation Classification System proposed herein fulfills the following necessary criteria: 1) classification is independent from users' initial hearing, 2) it is appropriate for all cochlear implant users with measurable pre-operative residual hearing, 3) it covers the whole range of pure tone average from 0 to 120 dB; 4) it is easy to use and easy to understand.

Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

2017-09-01

With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

Text Classification for Organizational Researchers

PubMed Central

Kobayashi, Vladimer B.; Mol, Stefan T.; Berkers, Hannah A.; Kismihók, Gábor; Den Hartog, Deanne N.

2017-01-01

Organizations are increasingly interested in classifying texts or parts thereof into categories, as this enables more effective use of their information. Manual procedures for text classification work well for up to a few hundred documents. However, when the number of documents is larger, manual procedures become laborious, time-consuming, and potentially unreliable. Techniques from text mining facilitate the automatic assignment of text strings to categories, making classification expedient, fast, and reliable, which creates potential for its application in organizational research. The purpose of this article is to familiarize organizational researchers with text mining techniques from machine learning and statistics. We describe the text classification process in several roughly sequential steps, namely training data preparation, preprocessing, transformation, application of classification techniques, and validation, and provide concrete recommendations at each step. To help researchers develop their own text classifiers, the R code associated with each step is presented in a tutorial. The tutorial draws from our own work on job vacancy mining. We end the article by discussing how researchers can validate a text classification model and the associated output. PMID:29881249

Improving the performance of extreme learning machine for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Li, Jiaojiao; Du, Qian; Li, Wei; Li, Yunsong

2015-05-01

Extreme learning machine (ELM) and kernel ELM (KELM) can offer comparable performance as the standard powerful classifier―support vector machine (SVM), but with much lower computational cost due to extremely simple training step. However, their performance may be sensitive to several parameters, such as the number of hidden neurons. An empirical linear relationship between the number of training samples and the number of hidden neurons is proposed. Such a relationship can be easily estimated with two small training sets and extended to large training sets so as to greatly reduce computational cost. Other parameters, such as the steepness parameter in the sigmodal activation function and regularization parameter in the KELM, are also investigated. The experimental results show that classification performance is sensitive to these parameters; fortunately, simple selections will result in suboptimal performance.

40 CFR 164.1 - Number of words.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 24 2011-07-01 2011-07-01 false Number of words. 164.1 Section 164.1 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS RULES OF PRACTICE... REGISTER, CANCELLATIONS OF REGISTRATIONS, CHANGES OF CLASSIFICATIONS, SUSPENSIONS OF REGISTRATIONS AND...

78 FR 319 - Agency Information Collection Activities: Submission for the Office of Management and Budget (OMB...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-03

... following proposal for the collection of information under the provisions of the Paperwork Reduction Act of..., Classification Record. 3. Current OMB approval number: 3150-0052. 4. The form number if applicable: NRC Form 790...

Assessment of the correlation between serum prolidase and alpha-fetoprotein levels in patients with hepatocellular carcinoma

PubMed Central

Uygun Ilikhan, Sevil; Bilici, Muammer; Sahin, Hatice; Demir Akca, Ayşe Semra; Can, Murat; Oz, Ibrahim Ilker; Guven, Berrak; Buyukuysal, M Cagatay; Ustundag, Yucel

2015-01-01

AIM: To determine the predictive value of increased prolidase activity that reflects increased collagen turnover in patients with hepatocellular carcinoma (HCC). METHODS: Sixty-eight patients with HCC (mean age of 69.1 ± 10.1), 31 cirrhosis patients (mean age of 59.3 ± 6.3) and 33 healthy volunteers (mean age of 51.4 ± 12.6) were enrolled in this study. Univariate and multivariate analysis were used to evaluate the association of serum α-fetoprotein (AFP) values with HCC clinicopathological features, such as tumor size, number and presence of vascular and macrovascular invasion. The patients with HCC were divided into groups according to tumor size, number and presence of vascular invasion (diameters; ≤ 3 cm, 3-5 cm and ≥ 5 cm, number; 1, 2 and ≥ 3, macrovascular invasion; yes/no). Barcelona-clinic liver cancer (BCLC) criteria were used to stage HCC patients. Serum samples for measurement of prolidase and alpha-fetoprotein levels were kept at -80 °C until use. Prolidase levels were measured spectrophotometrically and AFP concentrations were determined by a chemiluminescence immunometric commercial diagnostic assay. RESULTS: In patients with HCC, prolidase and AFP values were evaluated according to tumor size, number, presence of macrovascular invasion and BCLC staging classification. Prolidase values were significantly higher in patients with HCC compared with controls (P < 0.001). Prolidase levels were significantly associated with tumor size and number (P < 0.001, P = 0.002, respectively). Prolidase levels also differed in patients in terms of BCLC staging classification (P < 0.001). Furthermore the prolidase levels in HCC patients showed a significant difference compared with patients with cirrhosis (P < 0.001). In HCC patients grouped according to tumor size, number and BCLC staging classification, AFP values differed separately (P = 0.032, P = 0.038, P = 0.015, respectively). In patients with HCC, there was a significant correlation (r = 0.616; P < 0.001) between prolidase and AFP values in terms of tumor size, number and BCLC staging classification, whereas the presence of macrovascular invasion did not show a positive association with serum prolidase and AFP levels. CONCLUSION: Considering the levels of both serum prolidase and AFP could contribute to the early diagnosing of hepatocellular carcinoma. PMID:26078578

Assessment of the correlation between serum prolidase and alpha-fetoprotein levels in patients with hepatocellular carcinoma.

PubMed

Ilikhan, Sevil Uygun; Bilici, Muammer; Sahin, Hatice; Akca, Ayşe Semra Demir; Can, Murat; Oz, Ibrahim Ilker; Guven, Berrak; Buyukuysal, M Cagatay; Ustundag, Yucel

2015-06-14

To determine the predictive value of increased prolidase activity that reflects increased collagen turnover in patients with hepatocellular carcinoma (HCC). Sixty-eight patients with HCC (mean age of 69.1 ± 10.1), 31 cirrhosis patients (mean age of 59.3 ± 6.3) and 33 healthy volunteers (mean age of 51.4 ± 12.6) were enrolled in this study. Univariate and multivariate analysis were used to evaluate the association of serum α-fetoprotein (AFP) values with HCC clinicopathological features, such as tumor size, number and presence of vascular and macrovascular invasion. The patients with HCC were divided into groups according to tumor size, number and presence of vascular invasion (diameters; ≤ 3 cm, 3-5 cm and ≥ 5 cm, number; 1, 2 and ≥ 3, macrovascular invasion; yes/no). Barcelona-clinic liver cancer (BCLC) criteria were used to stage HCC patients. Serum samples for measurement of prolidase and alpha-fetoprotein levels were kept at -80 °C until use. Prolidase levels were measured spectrophotometrically and AFP concentrations were determined by a chemiluminescence immunometric commercial diagnostic assay. In patients with HCC, prolidase and AFP values were evaluated according to tumor size, number, presence of macrovascular invasion and BCLC staging classification. Prolidase values were significantly higher in patients with HCC compared with controls (P < 0.001). Prolidase levels were significantly associated with tumor size and number (P < 0.001, P = 0.002, respectively). Prolidase levels also differed in patients in terms of BCLC staging classification (P < 0.001). Furthermore the prolidase levels in HCC patients showed a significant difference compared with patients with cirrhosis (P < 0.001). In HCC patients grouped according to tumor size, number and BCLC staging classification, AFP values differed separately (P = 0.032, P = 0.038, P = 0.015, respectively). In patients with HCC, there was a significant correlation (r = 0.616; P < 0.001) between prolidase and AFP values in terms of tumor size, number and BCLC staging classification, whereas the presence of macrovascular invasion did not show a positive association with serum prolidase and AFP levels. Considering the levels of both serum prolidase and AFP could contribute to the early diagnosing of hepatocellular carcinoma.

Hodge numbers for all CICY quotients

NASA Astrophysics Data System (ADS)

Constantin, Andrei; Gray, James; Lukas, Andre

2017-01-01

We present a general method for computing Hodge numbers for Calabi-Yau manifolds realised as discrete quotients of complete intersections in products of projective spaces. The method relies on the computation of equivariant cohomologies and is illustrated for several explicit examples. In this way, we compute the Hodge numbers for all discrete quotients obtained in Braun's classification [1].

Coalition Warfare: the Leadership Challenges

DTIC Science & Technology

2011-05-19

Approved for Public Release; Distribution is Unlimited Coalition Warfare: The leadership challenges A Monograph by Colonel Mark J Thornhill...The leadership challenges . 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Colonel Mark J. Thornhill...multinational operations, leadership challenges , leadership attributes, unity of command. 16. SECURITY CLASSIFICATION OF: UNCLASSIFIED 17. LIMITATION OF

Cerebrovascular Injury in Blast Loading

DTIC Science & Technology

2010-01-01

TITLE: Cerebrovascular injury in blast loading PRINCIPAL INVESTIGATOR: Kenneth L. Monson, PhD...SUBTITLE Cerebrovascular injury in blast loading 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6...and pH control. 15. SUBJECT TERMS Blast brain injury; cerebrovascular injury and dysfunction; shock tube 16. SECURITY CLASSIFICATION OF: 17

Long-term outcome of 2920 patients with cancers of the esophagus and esophagogastric junction: evaluation of the New Union Internationale Contre le Cancer/American Joint Cancer Committee staging system.

PubMed

Gertler, Ralf; Stein, Hubert J; Langer, Rupert; Nettelmann, Marc; Schuster, Tibor; Hoefler, Heinz; Siewert, Joerg-Ruediger; Feith, Marcus

2011-04-01

We analyzed the long-term outcome of patients operated for esophageal cancer and evaluated the new seventh edition of the tumor-node-metastasis classification for cancers of the esophagus. Retrospective analysis and new classification. Data of a single-center cohort of 2920 patients operated for cancers of the esophagus according to the seventh edition are presented. Statistical methods to evaluate survival and the prognostic performance of the staging systems included Kaplan-Meier analyses and time-dependent receiver-operating-characteristic-analysis. Union Internationale Contre le Cancer stage, R-status, histologic tumor type and age were identified as independent prognostic factors for cancers of the esophagus. Grade and tumor site, additional parameters in the new American Joint Cancer Committee prognostic groupings, were not significantly correlated with survival. Esophageal adenocarcinoma showed a significantly better long-term prognosis after resection than squamous cell carcinoma (P < 0.0001). The new number-dependent N-classification proved superior to the former site-dependent classification with significantly decreasing prognosis with the increasing number of lymph node metastases (P < 0.001). The new subclassification of T1 tumors also revealed significant differences in prognosis between pT1a and pT1b patients (P < 0.001). However, the multiple new Union Internationale Contre le Cancer and American Joint Cancer Committee subgroupings did not prove distinctive for survival between stages IIA and IIB, between IIIA and IIIB, and between IIIC and IV. The new seventh edition of the tumor-node-metastasis classification improved the predictive ability for cancers of the esophagus; however, stage groups could be condensed to a clinically relevant number. Differences in patient characteristics, pathogenesis, and especially survival clearly identify adenocarcinomas and squamous cell carcinoma of the esophagus as 2 separate tumor entities requiring differentiated therapeutic concepts.

ML-o-Scope: A Diagnostic Visualization System for Deep Machine Learning Pipelines

DTIC Science & Technology

2014-05-16

ML-o-scope: a diagnostic visualization system for deep machine learning pipelines Daniel Bruckner Electrical Engineering and Computer Sciences... machine learning pipelines 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f...the system as a support for tuning large scale object-classification pipelines. 1 Introduction A new generation of pipelined machine learning models

Novel Therapeutic Target for the Treatment of Lupus

DTIC Science & Technology

2014-09-01

AWARD NUMBER: W81XWH-12-1-0205 TITLE: Novel Therapeutic Target for the Treatment of Lupus PRINCIPAL INVESTIGATOR: Lisa Laury-Kleintop...SUBTITLE 5a. CONTRACT NUMBER Novel Therapeutic Target for the Treatment of Lupus 5b. GRANT NUMBER W81XWH-12-1-0205 5c. PROGRAM ELEMENT NUMBER 6...Systemic lupus erythematosus, autoantibodies. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 7 19a. NAME OF

Nasal Irrigation for Chronic Rhinosinusitis and Fatigue in Patients with Gulf War Syndrome

DTIC Science & Technology

2015-07-01

Syndrome ” PRINCIPAL INVESTIGATOR: David Rabago, MD CONTRACTING ORGANIZATION: University of Wisconsin Systems Board of Regents REPORT DATE...Patients with Gulf War Syndrome ” 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) David Rabago, MD 5d. PROJECT NUMBER 5e. TASK NUMBER...Rhinosinusitis, Fatigue, Gulf War Syndrome , Nasal Irrigation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a

RF number as a new index for assessing combustion hazard of flammable gases.

PubMed

Kondo, Shigeo; Takahashi, Akifumi; Tokuhashi, Kazuaki; Sekiya, Akira

2002-08-05

A new index called RF number has been proposed for assessing the combustion hazard of all sorts of flammable gases and their mixtures. RF number represents the total expectancy of combustion hazard in terms of flammability limits and heat of combustion for each known and unknown compounds. The advantage of RF number over others such as R-index and F-number for classification of combustion hazard has been highlighted.

Debugging Techniques Used by Experienced Programmers to Debug Their Own Code.

DTIC Science & Technology

1990-09-01

IS. NUMBER OF PAGES code debugging 62 computer programmers 16. PRICE CODE debug programming 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 119...Davis, and Schultz (1987) also compared experts and novices, but focused on the way a computer program is represented cognitively and how that...of theories in the emerging computer programming domain (Fisher, 1987). In protocol analysis, subjects are asked to talk/think aloud as they solve

Discrete Event Simulation for the Analysis of Artillery Fired Projectiles from Shore

DTIC Science & Technology

2017-06-01

a designed experiment indicate artillery systems provide commanders a limited area denial capability, and should be employed where naval forces are... Design 15. NUMBER OF PAGES 85 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS PAGE Unclassified 19...to deny freedom of navigation (area denial) and stop an amphibious naval convoy (anti-access). Results from a designed experiment indicate artillery

Statistical classification techniques for engineering and climatic data samples

NASA Technical Reports Server (NTRS)

Temple, E. C.; Shipman, J. R.

1981-01-01

Fisher's sample linear discriminant function is modified through an appropriate alteration of the common sample variance-covariance matrix. The alteration consists of adding nonnegative values to the eigenvalues of the sample variance covariance matrix. The desired results of this modification is to increase the number of correct classifications by the new linear discriminant function over Fisher's function. This study is limited to the two-group discriminant problem.

A Randomized Clinical Trial of Cognitive-Behavioral Treatment for PTSD in Women

DTIC Science & Technology

2003-10-01

Post Traumatic Stress Disorder ( PTSD ) in 384 female veterans and active duty personnel at 11 sites. This is a VA Cooperative Study. Walter...14. SUBJECT TERMS 15. NUMBER OF PAGES Post - Traumatic Stress Disorder 6 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19...Clinical Trial of Cognitive-Behavioral Treatment for Post Traumatic Stress Disorder in Women for this study, from the protocol Additionally, a new

Assassination: A Military View.

DTIC Science & Technology

1987-03-23

Assassination: A Military View Individual Essay S. PERFORMING ORG. REPORT NUMBER 7. AUTI4OR(e) S. CONTRACT OR GRANT NUMGER(e) COL Charles K. Eden S...CLASSIFICATION OF THIS PAGE(hen Data Entered) USAWC MILITARY STUDIES PROGRAM PAPER ASSASSINATION: A MILITARY VILW An Individual Essay hceess ’. :’r by...Military View FORMAT: Individual Essay DATE: 23 March 1987 PAGES: 17 CLASSIFICATION: Unclassified -Assassination is a topic with which most Americans

Is DOD on the Right Path to Financial Auditability?

DTIC Science & Technology

2012-03-22

and DOD decision-making. Moreover, most of the 10 ERPs run the same software applications (i.e. SAP [Systems Applications and Programs] or PeopleSoft...Financial Readiness; GFEBS; DEAMS; Navy ERP 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF...Navy ERP CLASSIFICATION: Unclassified To make every dollar count, the Department of Defense (DOD) must be able to account for every dollar

An Automatic Vehicle Classification System.

DTIC Science & Technology

1981-07-01

addi- tion, various portions of the system design can be used by other vehicle study projects, e.g. for projects concerned with vehicle speed or for...traffic study projects that require an axle counter or vehicle height indicator. A *4 UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE(W1en Data Enrerod...optoelectronic components as the basis for detection. Factors of vehicle length, height, and number of axles are used as identification characteristics. In

Munitions Classification With Portable Advanced Electromagnetic Sensors, Demonstration at the former Camp Beale, CA, Summer 2011

DTIC Science & Technology

2012-07-01

Engineering Service Center, Port Hueneme, CA Robert Kirgan, Army Environmental Command Doug Maddox, US Environmental Protection Agency Doug Murray...FINAL REPORT MUNITIONS CLASSIFICATION WITH PORTABLE ADVANCED ELECTROMAGNETIC SENSORS Demonstration at the former Camp Beale, CA , Summer...if it does not display a currently valid OMB control number. 1. REPORT DATE JUL 2012 2 . REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND

Spirituality and the International Classification of Functioning, Disability and Health: content comparison of questionnaires measuring mindfulness based on the International Classification of Functioning.

PubMed

Offenbächer, Martin; Sauer, Sebastian; Hieblinger, Robin; Hufford, David J; Walach, Harald; Kohls, Niko

2011-01-01

To identify and compare the concepts contained in questionnaires measuring mindfulness using the International Classification of Functioning (ICF) as external reference. Questionnaires which are published in peer-reviewed journals and listed in Pubmed or PsycInfo were included. The questionnaires were analysed and, using a content-analytical approach, the respective items were categorised and linked to the ICF. Ten questionnaires were included. Ninety-four per cent (N = 341) of the concepts could be linked to 37 different ICF categories. One hundred and seventy-one (50.1%) concepts were linked to ICF categories of the component Body Function, 74 (21.7%) to categories of the component Activity and Participation and none to categories of the component Environmental Factors. In total, 28.2% of the linked concepts belonged to Personal factors, which are not yet classified in the ICF. The questionnaires exhibited considerable differences regarding content density (i.e. the average number of concepts per item) and content diversity (i.e. the number of ICF categories per concept). The ICF provides an useful external reference to identify and compare the concepts contained in mindfulness questionnaires. Also, mindfulness questionnaire concepts suggest potentially useful factors for classification within the ICF.

Simultaneous Force Regression and Movement Classification of Fingers via Surface EMG within a Unified Bayesian Framework.

PubMed

Baldacchino, Tara; Jacobs, William R; Anderson, Sean R; Worden, Keith; Rowson, Jennifer

2018-01-01

This contribution presents a novel methodology for myolectric-based control using surface electromyographic (sEMG) signals recorded during finger movements. A multivariate Bayesian mixture of experts (MoE) model is introduced which provides a powerful method for modeling force regression at the fingertips, while also performing finger movement classification as a by-product of the modeling algorithm. Bayesian inference of the model allows uncertainties to be naturally incorporated into the model structure. This method is tested using data from the publicly released NinaPro database which consists of sEMG recordings for 6 degree-of-freedom force activations for 40 intact subjects. The results demonstrate that the MoE model achieves similar performance compared to the benchmark set by the authors of NinaPro for finger force regression. Additionally, inherent to the Bayesian framework is the inclusion of uncertainty in the model parameters, naturally providing confidence bounds on the force regression predictions. Furthermore, the integrated clustering step allows a detailed investigation into classification of the finger movements, without incurring any extra computational effort. Subsequently, a systematic approach to assessing the importance of the number of electrodes needed for accurate control is performed via sensitivity analysis techniques. A slight degradation in regression performance is observed for a reduced number of electrodes, while classification performance is unaffected.

Reduction of Topographic Effect for Curve Number Estimated from Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Zhang, Wen-Yan; Lin, Chao-Yuan

2016-04-01

The Soil Conservation Service Curve Number (SCS-CN) method is commonly used in hydrology to estimate direct runoff volume. The CN is the empirical parameter which corresponding to land use/land cover, hydrologic soil group and antecedent soil moisture condition. In large watersheds with complex topography, satellite remote sensing is the appropriate approach to acquire the land use change information. However, the topographic effect have been usually found in the remotely sensed imageries and resulted in land use classification. This research selected summer and winter scenes of Landsat-5 TM during 2008 to classified land use in Chen-You-Lan Watershed, Taiwan. The b-correction, the empirical topographic correction method, was applied to Landsat-5 TM data. Land use were categorized using K-mean classification into 4 groups i.e. forest, grassland, agriculture and river. Accuracy assessment of image classification was performed with national land use map. The results showed that after topographic correction, the overall accuracy of classification was increased from 68.0% to 74.5%. The average CN estimated from remotely sensed imagery decreased from 48.69 to 45.35 where the average CN estimated from national LULC map was 44.11. Therefore, the topographic correction method was recommended to normalize the topographic effect from the satellite remote sensing data before estimating the CN.