Cosmogenic 10Be Dating of Early and Latest Holocene Moraines on Nevado Salcantay in the Southern Peruvian Andes

Science.gov (United States)

Licciardi, J. M.; Schaefer, J. M.; Lund, D. C.

2007-12-01

A two-fold sequence of nested lateral and end moraines was mapped in a glacial trough emanating from the southwest flank of Nevado Salcantay (6271 m; ~13°S latitude), the highest peak in the Cordillera Vilcabamba of southern Peru. The field area is situated 25 km due south of the archaeological site of Machu Picchu. Outer and inner moraines in the sequence were deposited by valley glaciers that terminated ~5 km and ~3 km, respectively, from their headwall on the Salcantay summit massif. Cosmogenic 10Be surface exposure dating of granitic boulders sampled on the Salcantay moraines is underway and has provided the first numerical ages for these deposits. Initial results indicate ages of 8.1 ± 0.1 10Be ka for the outer moraine and 200 ± 20 10Be years for the sharp-crested inner moraine. These ages are derived using the CRONUS-Earth 10Be exposure age calculator (version 2.0) and expressed with respect to the Lal- Stone production rate scaling scheme using the standard atmosphere. The outer and inner moraine ages correspond to glacial events during the early and latest Holocene, respectively. Further 10Be dating of the mapped moraines and similar deposits observed in adjacent drainages on Nevado Salcantay is anticipated to yield a high-resolution chronology of valley glaciation in this segment of the southern Peruvian Andes. The new results bridge an important gap between existing Andean glacier records to the north and south, and complement available ice core and lacustrine paleoclimate records in the vicinity, thereby expanding spatial and temporal coverage for identifying patterns of Holocene climate change in the tropical Andes. Notably, the inner moraine age correlates with the timing of the Little Ice Age as defined in northern mid- and high latitude glacier records, and suggests considerable expansion of valley glaciers in the southern Peruvian Andes during this climatic minimum. Apart from their paleoclimatic significance, the initial results also demonstrate

The development of blue ice moraines from englacial debris bands as detected by GPR, Mt Achernar, central Transantarctic Mountains, Antarctica

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Kassab, C.; Lindback, K.; Pettersson, R.; Licht, K.; Graly, J. A.; Kaplan, M. R.

2016-12-01

Blue ice moraines cover a small percentage of Antarctica, but can contain a significant record of ice sheet dynamics and climate over multiple glacial cycles. Previous work has focused on the temporal and provenance record contained within these moraines and less on mechanisms by which such deposits form and their temporal evolution. In order to create a conceptual model of their formation, >25 km of ground penetrating radar transects at 25 and 100 MHz frequencies were collected at the Mt Achernar moraine adjacent to Law Glacier. Here, ice ablation causes debris bands to emerge and deliver sediment to the surface. Most transects were collected perpendicular to the ice-moraine margin, and extend from the actively flowing Law Glacier ice to a distance of 2 km into the moraine. The 25 and 100 MHz transects penetrate to a depth of 200 m and 60 m respectively and reveal a relatively complex internal stratigraphy. Closest to the ice-moraine margin, stratigraphy is not well resolved due to a high amount of clutter. Steeply dipping parallel reflections first emerge 400m away from the ice margin and dip toward Law Glacier. These reflections continue inwards to 1450m, where the reflections become more closely spaced. Hummocky topography and parallel ridge/trough topography dominate the geomorphic expression. The hummocky topography corresponds to the region where reflections are not well resolved. The ridges are interpreted to be debris bands that are emerging at the surface, similar to those along the margin of the Law Glacier where debris is newly emerging. The reflections in the GPR transects indicate that debris is transported from depth to the surface of the ice where it accumulates forming the Mt Achernar moraine. It appears that the various reflection patterns correspond to unique surface geomorphic expressions. The reflections also indicate that at least the first 2 km of debris rich buried ice in the moraine can be linked to the actively flowing Law Glacier

The last deglaciation in New Zealand ; revisiting the Misery moraines at Arthur's Pass in the Southern Alps of New Zealand

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Fink, David; Rother, Henrik; Woodward, Craig; Shulmeister, James; Wilcken, Klaus

2017-04-01

Recent debate on mid-latitude New Zealand glaciation has focused on reconstructing paleo-climate conditions leading into the (global) Last Glacial Maximum and subsequent deglaciation dynamics during the last termination. Paleo-environmental evidence coupled with reliable glacial chronologies supporting a Southern Hemisphere glacial readvance commensurate with Younger Dryas timing ( 11.5-12.5 ka) showing similar cooling as observed in the Northern Hemisphere has also been hotly debated. Many New Zealand lake and pollen records suggest a minor cooling or hiatus in warming during the period from 14.5 - 12.0 ka which pre-dates YD onset and is more commonly associated with the Antarctic Cold Reversal (ACR) (14.7 - 13.0 ka). Achieving the required sub-millennial temporal differentiation using in-situ cosmogenic exposure dating comes with numerous difficulties. The Arthur's Pass Moraine complex, deposited by an alpine glacier advancing out of the Otira Gorge splaying east and westward over the divide of the Southern Alps in New Zealand ( 950 masl), exhibits a full post-LGM glacial chronology. The moraines consist of multiple cross-valley terminal, lobate and discontinuous latero-terminal moraines up to 3 kilometres down valley from the proximal Misery moraines at the outlet of Otira Gorge. Within the gorge towards the headwall only 1 km up-valley from the Misery sequence, no other moraines are evident. We have determined paired 10-Be and 26-Al exposure ages from 58 greywacke samples taken from all major moraines, including repeat sampling from the Misery moraines. The new exposure ages show that the Arthur's Pass moraine system spans a period of 19.5 ka to 12.0 ka (Putnam local NZ production rate) with mean recessional moraine ages in chrono-stratigraphic sequence. The overall timing of deglaciation after peak LGM conditions is similar to that observed at down-valley terminal positions of the larger outlet river systems of the Rakaia, Waimakariri and Rangitata Valleys

Precise Surface Exposure Dating of Early Holocene and Little Ice Age Moraines in the Cordillera Vilcabamba of Southern Peru

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Licciardi, J. M.; Schaefer, J. M.; Lund, D. C.; Taggart, J. R.

2008-12-01

We have established precise ages of two glacial events in the tropical Andean highlands of southern Peru. The field site is located on the flanks of Nevado Salcantay (6271 m asl; 13°20'S latitude), the highest peak in the Cordillera Vilcabamba. A two-fold sequence of nested lateral and end moraines was mapped in a glacial trough emanating from the south face of Salcantay. Well-defined outer and inner moraines were deposited by valley glaciers that terminated 5 km and 3 km, respectively, from their head on the Salcantay massif. Cosmogenic 10Be surface exposure dating of boulders on the outer (n = 7) and inner (n = 7) moraine crests expands upon initial age control for these deposits and improves substantially on the precision of earlier 10Be measurements. The new results yield mean ages of 9.0 ± 0.3 ka for the outer moraine and 195 ± 24 years for the inner moraine, corresponding to glacial events during the early and latest Holocene. These ages are derived using the CRONUS-Earth 10Be exposure age calculator with Lal-Stone production rate scaling and the default height-pressure relationship. The inner moraine age correlates with the timing of the Little Ice Age as defined from northern mid- and high latitude records, and indicates considerable expansion of glaciers heading on Nevado Salcantay during this climatic minimum. Recent geomorphic mapping has identified similar sequences of moraines in adjacent drainages on and near Salcantay, suggesting a broader regional signal of two prominent Holocene glacial events in this segment of the southern Peruvian Andes; 10Be dating of these additional moraines is underway. Our new glacier chronologies complement ice core and lacustrine paleoclimate records in the vicinity, thereby increasing spatial and temporal coverage for identifying patterns of climate change in the tropical Andes during the Holocene. Apart from their paleoclimatic significance, the results also demonstrate a newly- developed capability of 10Be exposure

A national-scale model of linear features improves predictions of farmland biodiversity.

Science.gov (United States)

Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H

2017-12-01

Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.

A middle Pleistocene through middle Miocene moraine sequence in the central Transantarctic Mountains, Antarctica

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Balter, A.; Bromley, G. R.; Balco, G.; Thomas, H.; Jackson, M. S.

2017-12-01

Ice-free areas at high elevation in the central Transantarctic Mountains preserve extensive moraine sequences and drift deposits that comprise a geologic record of former East Antarctic Ice Sheet thickness and extent. We are applying cosmogenic-nuclide exposure dating to determine the ages of these moraine sequences at Roberts Massif and Otway Massif, at the heads of the Shackleton and Beardmore Glaciers, respectively. Moraines at these sites are for the most part openwork boulder belts characteristic of deposition by cold-based ice, which is consistent with present climate and glaciological conditions. To develop our chronology, we collected samples from 30 distinct ice-marginal landforms and have so far measured >100 3He, 10Be, and 21Ne exposure ages. Apparent exposure ages range from 1-14 Ma, which shows that these landforms record glacial events between the middle Pleistocene and middle Miocene. These data show that the thickness of the East Antarctic Ice Sheet in this region was similar to or thicker than present for long periods between the middle Miocene and today. The time range represented by these moraine sequences indicates that they may also provide direct geologic evidence for East Antarctic Ice Sheet behavior during past periods of warmer-than-present climate, specifically the Miocene and Pliocene. As the East Antarctic Ice Sheet is the largest ice sheet on earth, understanding its sensitivity to warm-climate conditions is critical for projections of ice sheet behavior and sea-level rise in future warm climates.

Climate change and the global pattern of moraine-dammed glacial lake outburst floods

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Harrison, Stephan; Kargel, Jeffrey S.; Huggel, Christian; Reynolds, John; Shugar, Dan H.; Betts, Richard A.; Emmer, Adam; Glasser, Neil; Haritashya, Umesh K.; Klimeš, Jan; Reinhardt, Liam; Schaub, Yvonne; Wiltshire, Andy; Regmi, Dhananjay; Vilímek, Vít

2018-04-01

Despite recent research identifying a clear anthropogenic impact on glacier recession, the effect of recent climate change on glacier-related hazards is at present unclear. Here we present the first global spatio-temporal assessment of glacial lake outburst floods (GLOFs) focusing explicitly on lake drainage following moraine dam failure. These floods occur as mountain glaciers recede and downwaste. GLOFs can have an enormous impact on downstream communities and infrastructure. Our assessment of GLOFs associated with the rapid drainage of moraine-dammed lakes provides insights into the historical trends of GLOFs and their distributions under current and future global climate change. We observe a clear global increase in GLOF frequency and their regularity around 1930, which likely represents a lagged response to post-Little Ice Age warming. Notably, we also show that GLOF frequency and regularity - rather unexpectedly - have declined in recent decades even during a time of rapid glacier recession. Although previous studies have suggested that GLOFs will increase in response to climate warming and glacier recession, our global results demonstrate that this has not yet clearly happened. From an assessment of the timing of climate forcing, lag times in glacier recession, lake formation and moraine-dam failure, we predict increased GLOF frequencies during the next decades and into the 22nd century.

Geomorphic domains and linear features on Landsat images, Circle Quadrangle, Alaska

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Simpson, S.L.

1984-01-01

A remote sensing study using Landsat images was undertaken as part of the Alaska Mineral Resource Assessment Program (AMRAP). Geomorphic domains A and B, identified on enhanced Landsat images, divide Circle quadrangle south of Tintina fault zone into two regional areas having major differences in surface characteristics. Domain A is a roughly rectangular, northeast-trending area of relatively low relief and simple, widely spaced drainages, except where igneous rocks are exposed. In contrast, domain B, which bounds two sides of domain A, is more intricately dissected showing abrupt changes in slope and relatively high relief. The northwestern part of geomorphic domain A includes a previously mapped tectonostratigraphic terrane. The southeastern boundary of domain A occurs entirely within the adjoining tectonostratigraphic terrane. The sharp geomorphic contrast along the southeastern boundary of domain A and the existence of known faults along this boundary suggest that the southeastern part of domain A may be a subdivision of the adjoining terrane. Detailed field studies would be necessary to determine the characteristics of the subdivision. Domain B appears to be divisible into large areas of different geomorphic terrains by east-northeast-trending curvilinear lines drawn on Landsat images. Segments of two of these lines correlate with parts of boundaries of mapped tectonostratigraphic terranes. On Landsat images prominent north-trending lineaments together with the curvilinear lines form a large-scale regional pattern that is transected by mapped north-northeast-trending high-angle faults. The lineaments indicate possible lithlogic variations and/or structural boundaries. A statistical strike-frequency analysis of the linear features data for Circle quadrangle shows that northeast-trending linear features predominate throughout, and that most northwest-trending linear features are found south of Tintina fault zone. A major trend interval of N.64-72E. in the linear

Climate change and the global pattern of moraine-dammed glacial lake outburst floods

Directory of Open Access Journals (Sweden)

S. Harrison

2018-04-01

Full Text Available Despite recent research identifying a clear anthropogenic impact on glacier recession, the effect of recent climate change on glacier-related hazards is at present unclear. Here we present the first global spatio-temporal assessment of glacial lake outburst floods (GLOFs focusing explicitly on lake drainage following moraine dam failure. These floods occur as mountain glaciers recede and downwaste. GLOFs can have an enormous impact on downstream communities and infrastructure. Our assessment of GLOFs associated with the rapid drainage of moraine-dammed lakes provides insights into the historical trends of GLOFs and their distributions under current and future global climate change. We observe a clear global increase in GLOF frequency and their regularity around 1930, which likely represents a lagged response to post-Little Ice Age warming. Notably, we also show that GLOF frequency and regularity – rather unexpectedly – have declined in recent decades even during a time of rapid glacier recession. Although previous studies have suggested that GLOFs will increase in response to climate warming and glacier recession, our global results demonstrate that this has not yet clearly happened. From an assessment of the timing of climate forcing, lag times in glacier recession, lake formation and moraine-dam failure, we predict increased GLOF frequencies during the next decades and into the 22nd century.

Medial moraines of glaciers of the Copper River Basin, Alaska: Discrete landslides dominate over other sources

Science.gov (United States)

Kargel, J. S.; Fischer, L.; Furfaro, R.; Huggel, C.; Korup, O.; Leonard, G. J.; Uhlmann, M.; Wessels, R. L.; Wolfe, D. F.

2009-12-01

Medial moraines are visually dominant structures of most large valley glaciers in the Copper River Basin (CRB), Alaska. Areally extensive but thin (usually rock falls and talus creep; rocks delivered via snow and ice avalanches; ingestion of lateral moraines along tributary convergences; and basal erosional debris. Evidence indicates that in CRB glaciers, discrete large avalanches predominate as the major contributors of moraine mass. Subglacial erosional debris is predominantly pulverized to small grain sizes and flushed. Many large, young avalanches exist on CRB glaciers. Evidence from colorimetry indicates that many medial moraines actually are landslides that have been sheared and swept downglacier, thus mimicking the form of other types of medial moraines formed where tributaries coalesce and flow down valley. Landcover classification of ASTER imagery, qualitative observations from air photos, and semiquantitative field-based estimations of rock color types indicate that on Allen Glacier, and other CRB glaciers, landslides are the sources of most medial moraines. On Allen and Root Glacier, for example, we see very few boulders with obvious signs of basal abrasion, whereas nearly all boulders exhibit signs of irregular fracture, for example in landslides. Such landslides have large effects on the thermal and mass balance of CRB glaciers, sometimes opposing or in other cases accentuating the effects of global/regional climate change. Considering the link between landslides and seismicity, and that Magnitude 8-9 earthquakes may occur nearby only about once a century, which is also the characteristic response time of large glaciers to climate shifts, seismicity must be considered along with climate change induced glacier responses in the CRB. Ultimately, climate has the final word, and already this is evident in the glacier record. Glacial flour is probably almost entirely from bed erosion. We will present estimates of the contributions of landslides and

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation.

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Erica J Newton

Full Text Available Woodland caribou (Rangifer tarandus caribou in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism-a compensatory functional response to anthropogenic

Linear feature detection algorithm for astronomical surveys - I. Algorithm description

Science.gov (United States)

Bektešević, Dino; Vinković, Dejan

2017-11-01

Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.

Airborne LiDAR analysis and geochronology of faulted glacial moraines in the Tahoe-Sierra frontal fault zone reveal substantial seismic hazards in the Lake Tahoe region, California-Nevada USA

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Howle, James F.; Bawden, Gerald W.; Schweickert, Richard A.; Finkel, Robert C.; Hunter, Lewis E.; Rose, Ronn S.; von Twistern, Brent

2012-01-01

We integrated high-resolution bare-earth airborne light detection and ranging (LiDAR) imagery with field observations and modern geochronology to characterize the Tahoe-Sierra frontal fault zone, which forms the neotectonic boundary between the Sierra Nevada and the Basin and Range Province west of Lake Tahoe. The LiDAR imagery clearly delineates active normal faults that have displaced late Pleistocene glacial moraines and Holocene alluvium along 30 km of linear, right-stepping range front of the Tahoe-Sierra frontal fault zone. Herein, we illustrate and describe the tectonic geomorphology of faulted lateral moraines. We have developed new, three-dimensional modeling techniques that utilize the high-resolution LiDAR data to determine tectonic displacements of moraine crests and alluvium. The statistically robust displacement models combined with new ages of the displaced Tioga (20.8 ± 1.4 ka) and Tahoe (69.2 ± 4.8 ka; 73.2 ± 8.7 ka) moraines are used to estimate the minimum vertical separation rate at 17 sites along the Tahoe-Sierra frontal fault zone. Near the northern end of the study area, the minimum vertical separation rate is 1.5 ± 0.4 mm/yr, which represents a two- to threefold increase in estimates of seismic moment for the Lake Tahoe basin. From this study, we conclude that potential earthquake moment magnitudes (Mw) range from 6.3 ± 0.25 to 6.9 ± 0.25. A close spatial association of landslides and active faults suggests that landslides have been seismically triggered. Our study underscores that the Tahoe-Sierra frontal fault zone poses substantial seismic and landslide hazards.

RANSAC approach for automated registration of terrestrial laser scans using linear features

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K. Al-Durgham

2013-10-01

Full Text Available The registration process of terrestrial laser scans (TLS targets the problem of how to combine several laser scans in order to attain better information about features than what could be obtained through single scan. The main goal of the registration process is to estimate the parameters which determine geometrical variation between the origins of datasets collected from different locations. Scale, shifts, and rotation parameters are usually used to describe such variation. This paper presents a framework for the registration of overlapping terrestrial laser scans by establishing an automatic matching strategy that uses 3D linear features. More specifically, invariant separation characteristics between 3D linear features extracted from laser scans will be used to establish hypothesized conjugate linear features between the laser scans. These candidate matches are then used to geo-reference scans relative to a common reference frame. The registration workflow simulates the well-known RANndom Sample Consensus method (RANSAC for determining the registration parameters, whereas the iterative closest projected point (ICPP is utilized to determine the most probable solution of the transformation parameters from several solutions. The experimental results prove that the proposed methodology can be used for the automatic registration of terrestrial laser scans using linear features.

Multimodal Image Alignment via Linear Mapping between Feature Modalities.

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Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

2017-01-01

We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

COLOR IMAGE RETRIEVAL BASED ON FEATURE FUSION THROUGH MULTIPLE LINEAR REGRESSION ANALYSIS

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K. Seetharaman

2015-08-01

Full Text Available This paper proposes a novel technique based on feature fusion using multiple linear regression analysis, and the least-square estimation method is employed to estimate the parameters. The given input query image is segmented into various regions according to the structure of the image. The color and texture features are extracted on each region of the query image, and the features are fused together using the multiple linear regression model. The estimated parameters of the model, which is modeled based on the features, are formed as a vector called a feature vector. The Canberra distance measure is adopted to compare the feature vectors of the query and target images. The F-measure is applied to evaluate the performance of the proposed technique. The obtained results expose that the proposed technique is comparable to the other existing techniques.

Linear Regression on Sparse Features for Single-Channel Speech Separation

DEFF Research Database (Denmark)

Schmidt, Mikkel N.; Olsson, Rasmus Kongsgaard

2007-01-01

In this work we address the problem of separating multiple speakers from a single microphone recording. We formulate a linear regression model for estimating each speaker based on features derived from the mixture. The employed feature representation is a sparse, non-negative encoding of the speech...... mixture in terms of pre-learned speaker-dependent dictionaries. Previous work has shown that this feature representation by itself provides some degree of separation. We show that the performance is significantly improved when regression analysis is performed on the sparse, non-negative features, both...

Individual Identification Using Linear Projection of Heartbeat Features

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Yogendra Narain Singh

2014-01-01

Full Text Available This paper presents a novel method to use the electrocardiogram (ECG signal as biometrics for individual identification. The ECG characterization is performed using an automated approach consisting of analytical and appearance methods. The analytical method extracts the fiducial features from heartbeats while the appearance method extracts the morphological features from the ECG trace. We linearly project the extracted features into a subspace of lower dimension using an orthogonal basis that represent the most significant features for distinguishing heartbeats among the subjects. Result demonstrates that the proposed characterization of the ECG signal and subsequently derived eigenbeat features are insensitive to signal variations and nonsignal artifacts. The proposed system utilizing ECG biometric method achieves the best identification rates of 85.7% for the subjects of MIT-BIH arrhythmia database and 92.49% for the healthy subjects of our IIT (BHU database. These results are significantly better than the classification accuracies of 79.55% and 84.9%, reported using support vector machine on the tested subjects of MIT-BIH arrhythmia database and our IIT (BHU database, respectively.

Reinterpretation of the formation of the "crooked moraine" of the debris-covered Hatunraju Glacier (Cordillera Blanca, Perú)

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Iturrizaga, L.

2012-04-01

The Hatunraju Glacier (9°00'S/70°40'W) is located in the Parón valley in the northern part of the Cordillera Blanca. The almost 4 km long and steeply inclined glacier flows down from the Huandoy-N-Side (6395 m) into the Parón valley to an elevation of 4250 m a.s.l.. The extremely narrow glacier is in its entire ablation area heavily debris-covered. It is one of the few glaciers, which dam with its debris-mantled glacier tongue a main river in this mountain range. In this case the Hatunraju glacier produces the largest glacier-dammed lake in the Cordillera Blanca, the Laguna Parón. In some other aspects, this glacier proves to be distinct from the majority of the glaciers in the Cordillera Blanca: It is flowing on an almost up to 250 m high moraine pedestal ("moraine-dammed raised bed glacier") and the glacier makes a bend of almost 90° when entering into the main valley. The present paper focuses in particular on the last point: the formation of the so called "crooked moraine". It has been explained by Lliboutry (1977) as a result of a glacier lake outburst and the subsequent destruction of the latero-frontal moraine. The later process supposed to be the trigger of the abrupt change in the flow direction of the lower part of the glacier. Recent investigations suggest an alternative genesis of the crooked moraine considering the distinct phases of the glaciation history of the Parón valley. The here proposed formation pattern is also paradigmatic for other crooked debris-covered glaciers, especially in High Asia. Comparative examples will be provided from the Karakoram and Himalayas. The research work on the Hatunraju Glacier is part of a project on the glacial geomorphology in the Tropical Andes financed by the Alexander von Humboldt-Foundation.

Cosmogenic nuclide age estimate for Laurentide Ice Sheet recession from the terminal moraine, New Jersey, USA, and constraints on latest Pleistocene ice sheet history

Science.gov (United States)

Corbett, Lee B.; Bierman, Paul R.; Stone, Byron D.; Caffee, Marc W.; Larsen, Patrick L.

2017-01-01

The time at which the Laurentide Ice Sheet reached its maximum extent and subsequently retreated from its terminal moraine in New Jersey has been constrained by bracketing radiocarbon ages on preglacial and postglacial sediments. Here, we present measurements of in situ produced 10Be and 26Al in 16 quartz-bearing samples collected from bedrock outcrops and glacial erratics just north of the terminal moraine in north-central New Jersey; as such, our ages represent a minimum limit on the timing of ice recession from the moraine. The data set includes field and laboratory replicates, as well as replication of the entire data set five years after initial measurement. We find that recession of the Laurentide Ice Sheet from the terminal moraine in New Jersey began before 25.2±2.1 ka (10Be, n=16, average, 1 standard deviation). This cosmogenic nuclide exposure age is consistent with existing limiting radiocarbon ages in the study area and cosmogenic nuclide exposure ages from the terminal moraine on Martha’s Vineyard ~300 km to the northeast. The age we propose for Laurentide Ice Sheet retreat from the New Jersey terminal position is broadly consistent with regional and global climate records of the last glacial maximum termination and records of fluvial incision.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

Science.gov (United States)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

Geomorphologically effective floods from moraine-dammed lakes in the Cordillera Blanca, Peru

Czech Academy of Sciences Publication Activity Database

Emmer, Adam

2017-01-01

Roč. 177, DEC (2017), s. 220-234 ISSN 0277-3791 R&D Projects: GA MŠk(CZ) LO1415 Institutional support: RVO:86652079 Keywords : Andes * Documentary data * Geomorphology * glof * Lichenometry * Little Ice Age * Moraine-dammed lake * Outburst flood * South America Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 4.797, year: 2016

A subaquatic moraine complex in overdeepened Lake Thun (Switzerland) unravelling the deglaciation history of the Aare Glacier

Science.gov (United States)

Fabbri, S. C.; Buechi, M. W.; Horstmeyer, H.; Hilbe, M.; Hübscher, C.; Schmelzbach, C.; Weiss, B.; Anselmetti, F. S.

2018-05-01

To investigate the history of the Aare Glacier and its overdeepened valley, a high-resolution multibeam bathymetric dataset and a 2D multi-channel reflection seismic dataset were acquired on perialpine Lake Thun (Switzerland). The overdeepened basin was formed by a combination of tectonically predefined weak zones and glacial erosion during several glacial cycles. In the deepest region of the basin, top of bedrock lies at ∼200 m below sea level, implying more than 750 m of overdeepening with respect to the current fluvial base level (i.e. lake level). Seismic stratigraphic analysis reveals the evolution of the basin and indicates a subaquatic moraine complex marked by high-amplitude reflections below the outermost edge of a morphologically distinct platform in the southeastern part of the lake. This stack of seven subaquatic terminal moraine crests was created by a fluctuating, "quasi-stagnant" grounded Aare Glacier during its overall recessional phase. Single packages of overridden moraine crests are seismically distuinguishable, which show a transition downstream into prograding clinoforms with foresets at the ice-distal slope. The succession of subaquatic glacial sequences (foresets and adjacent bottomsets) represent one fifth of the entire sedimentary thickness. Exact time constraints concerning the deglacial history of the Aare Glacier are very sparse. However, existing 10Be exposure ages from the accumulation area of the Aare Glacier and radiocarbon ages from a Late-Glacial lake close to the outlet of Lake Thun indicate that the formation of the subaquatic moraine complex and the associated sedimentary infill must have occurred in less than 1000 years, implying high sedimentation rates and rapid disintegration of the glacier. These new data improve our comprehension of the landforms associated with the ice-contact zone in water, the facies architecture of the sub- to proglacial units, the related depositional processes, and thus the retreat mechanisms of

Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

Energy Technology Data Exchange (ETDEWEB)

Jing, Yaqi; Meng, Qinghao, E-mail: qh-meng@tju.edu.cn; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen [Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

2014-05-15

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.

Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

International Nuclear Information System (INIS)

Jing, Yaqi; Meng, Qinghao; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen

2014-01-01

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively

The linear attenuation coefficients as features of multiple energy CT image classification

International Nuclear Information System (INIS)

Homem, M.R.P.; Mascarenhas, N.D.A.; Cruvinel, P.E.

2000-01-01

We present in this paper an analysis of the linear attenuation coefficients as useful features of single and multiple energy CT images with the use of statistical pattern classification tools. We analyzed four CT images through two pointwise classifiers (the first classifier is based on the maximum-likelihood criterion and the second classifier is based on the k-means clustering algorithm) and one contextual Bayesian classifier (ICM algorithm - Iterated Conditional Modes) using an a priori Potts-Strauss model. A feature extraction procedure using the Jeffries-Matusita (J-M) distance and the Karhunen-Loeve transformation was also performed. Both the classification and the feature selection procedures were found to be in agreement with the predicted discrimination given by the separation of the linear attenuation coefficient curves for different materials

An approach for estimating the breach probabilities of moraine-dammed lakes in the Chinese Himalayas using remote-sensing data

Directory of Open Access Journals (Sweden)

X. Wang

2012-10-01

Full Text Available To make first-order estimates of the probability of moraine-dammed lake outburst flood (MDLOF and prioritize the probabilities of breaching posed by potentially dangerous moraine-dammed lakes (PDMDLs in the Chinese Himalayas, an objective approach is presented. We first select five indicators to identify PDMDLs according to four predesigned criteria. The climatic background was regarded as the climatic precondition of the moraine-dam failure, and under different climatic preconditions, we distinguish the trigger mechanisms of MDLOFs and subdivide them into 17 possible breach modes, with each mode having three or four components; we combined the precondition, modes and components to construct a decision-making tree of moraine-dam failure. Conversion guidelines were established so as to quantify the probabilities of components of a breach mode employing the historic performance method combined with expert knowledge and experience. The region of the Chinese Himalayas was chosen as a study area where there have been frequent MDLOFs in recent decades. The results show that the breaching probabilities (P of 142 PDMDLs range from 0.037 to 0.345, and they can be further categorized as 43 lakes with very high breach probabilities (P ≥ 0.24, 47 lakes with high breach probabilities (0.18 ≤ P < 0.24, 24 lakes with mid-level breach probabilities (0.12 ≤ P < 0.18, 24 lakes with low breach probabilities (0.06 ≤ P < 0.12, and four lakes with very low breach probabilities (p < 0.06.

Feature-space-based FMRI analysis using the optimal linear transformation.

Science.gov (United States)

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Borax in the supraglacial moraine of the Lewis Cliff, Buckley Island quadrangle--first Antarctic occurrence

Science.gov (United States)

Fitzpatrick, J.J.; Muhs, D.R.

1989-01-01

During the 1987-1988 austral summer field season, membersof the south party of the antarctic search for meteorites south-ern team* working in the Lewis Cliff/Colbert Hills region dis-covered several areas of unusual mineralization within theLewis Cliff ice tongue and its associated moraine field (figure1). The Lewis Cliff ice tongue (84°15'S 161°25'E) is a meteorite-stranding surface of ablating blue ice, about 2.3 by 7.0 kilo-meters, bounded on the west by the Lewis Cliff, on the northand northeast by a large supraglacial moraine, and on the eastby the Colbert Hills. To the south it opens to the Walcott Névé.Because it is a meteorite-stranding surface, the major component of ice motion in the area is believed to be vertical(Whillans and Cassidy 1983). The presence of Thule-Baffinmoraines at the northern terminus of the blue ice tends tosupport the hypothesis that the area underlying the moraineis essentially stagnant and that ice arriving from the south ispiling up against it. Areas containing mineral deposits werefound within the moraine field to the north and east of theblue ice margin and also along the east margins of the blue iceitself. Subsequent X-ray diffraction analyses of these depositshave shown that they are composed predominantly of nah-colite (NaHCO3), trona [Na3(CO3)(HCO3) · 2H20], borax[Na2B405(OH)4 · 8H20], and a new hexagonal hydrous sulfatespecies. This paper reports the details of the borax occurrence,because it is the first known on the continent.

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

Science.gov (United States)

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

The linear trend of headache prevalence and some headache features in school children.

Science.gov (United States)

Ozge, Aynur; Buğdayci, Resul; Saşmaz, Tayyar; Kaleağasi, Hakan; Kurt, Oner; Karakelle, Ali; Siva, Aksel

2007-04-01

The objectives of this study were to determine the age and sex dependent linear trend of recurrent headache prevalence in schoolchildren in Mersin. A stratified sample composed of 5562 children; detailed characteristics were previously published. In this study the prevalence distribution of headache by age and sex showed a peak in the female population at the age of 11 (27.2%) with a plateau in the following years. The great stratified random sample results suggested that, in addition to socio-demographic features, detailed linear trend analysis showed headache features of children with headache have some specific characteristics dependent on age, gender and headache type. This study results can constitute a basis for the future epidemiological based studies.

The present flora and vegetation of the moraines of the Klutlan Glacier, Yukon Territory, Canada: A study in plant succession*1

Science.gov (United States)

Birks, H. J. B.

1980-07-01

The flora and vegetation of six ice-cored moraines of the Klutlan Glacier were analyzed in 65 plots by European plant-sociological techniques. The age of each plot was estimated from annual growth rings of shrubs or trees in the plots. Nine major vegetation types are distinguished: Crepis nana, Dryas drummondii, Hedysarum mackenzii, Hedysarum-Salix, Salix-Shepherdia canadensis, Picea-Salix, Picea-Arctostaphylos, Picea-Ledum, and Picea-Rhytidium. These contain plants aged 2-6, 9-23, 10-20, 24-30, 32-58, 58-80, 96-178, 177-240, and >163- >339 yr, respectively. Six other vegetation types are described from windthrow areas, drainage channels, volcanic tephra slopes, lake margins, fens, and drained lakes. The major vegetation types reflect a vegetational succession related to moraine age and stability, with the Crepis nana type as the pioneer vegetation developing through the other vegetation types to the Picea-Rhytidium type on the oldest moraines. Changes in species diversity and soil development, particularly humus accumulation, parallel the vegetational succession. This succession differs from patterns of revegetation of deglaciated landscapes in Alaska and British Columbia today and in Minnesota in late-Wisconsin times because of differences in climate, plant migration, and local ecology.

Linear microstructural features in R5(Si,Ge)4-type alloys: Difficulties in identification

International Nuclear Information System (INIS)

Chumbley, L.S.; Ugurlu, O.; McCallum, R.W.; Dennis, K.W.; Mudryk, Y.; Gschneidner, K.A.; Pecharsky, V.K.

2008-01-01

A brief review of the current literature concerning compounds based upon the R 5 (Si x Ge 1-x ) 4 structure reveals that essentially all examined alloys contain 'linear features' similar to those first observed by Szade et al. on the surface of Gd 5 Si 4 , Gd 5 Si 2 Ge 2 and Gd 5 Ge 4 samples. Attempts to characterize these features, using a variety of techniques, have proven to be a difficult task. Rather than becoming clearer and better understood, discrepancies in the reported data have resulted in much confusion. A series of comprehensive experiments involving optical, scanning and transmission electron microscopy, X-ray diffractometry, magnetization, and heat capacity measurements have been performed in an attempt to clarify the situation. These experiments, coupled with a critical examination of published data, allow certain misconceptions and apparent contradictions to be understood and explained. Of major importance is the discovery that the volume fraction of the linear feature present is far lower than what one may estimate on the basis of etched samples. The results of this study support previous data that show the linear features are a second phase of composition R 5 (Si x Ge 1-x ) 3 , and reveal the various difficulties associated with proper identification of this phase due to its small size scale and low volume percentage

Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals.

Science.gov (United States)

Elhaj, Fatin A; Salim, Naomie; Harris, Arief R; Swee, Tan Tian; Ahmed, Taqwa

2016-04-01

Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, and an electrocardiogram (ECG) is the non-invasive method used to detect arrhythmias or heart abnormalities. Due to the presence of noise, the non-stationary nature of the ECG signal (i.e. the changing morphology of the ECG signal with respect to time) and the irregularity of the heartbeat, physicians face difficulties in the diagnosis of arrhythmias. The computer-aided analysis of ECG results assists physicians to detect cardiovascular diseases. The development of many existing arrhythmia systems has depended on the findings from linear experiments on ECG data which achieve high performance on noise-free data. However, nonlinear experiments characterize the ECG signal more effectively sense, extract hidden information in the ECG signal, and achieve good performance under noisy conditions. This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data. In this study, five types of beat classes of arrhythmia as recommended by the Association for Advancement of Medical Instrumentation are analyzed: non-ectopic beats (N), supra-ventricular ectopic beats (S), ventricular ectopic beats (V), fusion beats (F) and unclassifiable and paced beats (U). The characterization ability of nonlinear features such as high order statistics and cumulants and nonlinear feature reduction methods such as independent component analysis are combined with linear features, namely, the principal component analysis of discrete wavelet transform coefficients. The features are tested for their ability to differentiate different classes of data using different classifiers, namely, the support vector machine and neural network methods with tenfold cross-validation. Our proposed method is able to classify the N, S, V, F and U arrhythmia classes with high accuracy (98.91%) using a combined support

Use of {sup 10}Be exposure ages and Schmidt hammer data for correlation of moraines in the Krkonose Mountains, Poland/Czech Republic

Energy Technology Data Exchange (ETDEWEB)

Engel, Zbynek; Krizek, Marek [Charles Univ., Prague (Czech Republic). Dept. of Physical Geography and Geoecology; Traczyk, Andrzej [Wroclaw Univ. (Poland). Dept. of Geomorphology; Braucher, Regis [CEREGE, Aix-en-Provence (France); Woronko, Barbara [Warsaw Univ. (Poland). Dept. of Geography and Regional Development

2011-06-15

Exposure ages and relative-age data are presented from eight sites in the Lomnica and Lomniczka valleys to provide essential information for reconstructing local glaciation chronology. A combination of {sup 10}Be exposure ages and Schmidt hammer data obtained for moraines indicate relatively short period of glacier accumulation lasting from 17.0{+-}0.4 ka to 13.6{+-}0.9 ka. Exposure age of 8.4{+-}0.3 ka measured on the lowermost section of the Lomnica cirque headwall further confirms the view of glacier preservation in favourable sites until the beginning of the Holocene. A comparison of the obtained chronological data with timing of mountain glaciation in the nearby Upa Valley is used to propose the first correlative model of Late Quaternary glaciation in the eastern part of the Krkonose Mountains. The correlation implies that the lowermost preserved moraines originated during the local maximum of the last glaciation whereas recessional moraines were deposited until the Lateglacial period. A subsequent melting of glaciers terminated at the beginning of the Holocene. The implications of the model are discussed and further investigations are suggested to extend its validity to the whole mountain area. (orig.)

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression.

Science.gov (United States)

Yu, Xu; Lin, Jun-Yu; Jiang, Feng; Du, Jun-Wei; Han, Ji-Zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Linear and Nonlinear Gait Features in Older Adults Walking on Inclined Surfaces at Different Speeds.

Science.gov (United States)

Vieira, Marcus Fraga; Rodrigues, Fábio Barbosa; de Sá E Souza, Gustavo Souto; Magnani, Rina Márcia; Lehnen, Georgia Cristina; Andrade, Adriano O

2017-06-01

This study evaluated linear and nonlinear gait features in healthy older adults walking on inclined surfaces at different speeds. Thirty-seven active older adults (experimental group) and fifty young adults (control group) walked on a treadmill at 100% and ±20% of their preferred walking speed for 4 min under horizontal (0%), upward (UP) (+8%), and downward (DOWN) (-8%) conditions. Linear gait variability was assessed using the average standard deviation of trunk acceleration between strides (VAR). Gait stability was assessed using the margin of stability (MoS). Nonlinear gait features were assessed by using the maximum Lyapunov exponent, as a measure of local dynamic stability (LDS), and sample entropy (SEn), as a measure of regularity. VAR increased for all conditions, but the interaction effects between treadmill inclination and age, and speed and age were higher for young adults. DOWN conditions showed the lowest stability in the medial-lateral MoS, but not in LDS. LDS was smaller in UP conditions. However, there were no effects of age for either MoS or LDS. The values of SEn decreased almost linearly from the DOWN to the UP conditions, with significant interaction effects of age for anterior-posterior SEn. The overall results supported the hypothesis that inclined surfaces modulate nonlinear gait features and alter linear gait variability, particularly in UP conditions, but there were no significant effects of age for active older adults.

Developing a visual moraine classification scheme to support investigations into the Holocene glacier chronology of the Southern Alps, New Zealand

Science.gov (United States)

Kaufung, Eva; Winkler, Stefan

2014-05-01

The Southern Alps of New Zealand have provided one of only a few suitable study sites for investigating Holocene glacier chronologies in the mid-latitudinal Southern Hemisphere. Although a considerable number of studies have been conducted during the past few decades, these generally focus on a very limited number of glacier forelands. Additionally, those glaciers studied have often been selected because of their accessibility rather than their representativeness for the whole region. A common drawback of many regional studies is the lack of attention to glacial geomorphology and the mode of moraine formation with the dating of such landforms in chronological context. With the Southern Alps characterized by very dynamic geomorphological process-systems and a high seismic activity, this seems unfortunate as it causes a relatively high potential "geomorphological uncertainty" with any published glacier chronology and its subsequent palaeoclimatological interpretation. Future investigations into the Holocene glacier chronology in the Southern Alps need to address those existing shortcomings and, consequently, should achieve a representative spatial distribution of study sites in order to overcome the current strong data bias towards few, albeit relatively well-studied glacier forelands. The specific regional geomorphological environment of the Southern Alps requires, furthermore, a thorough assessment of any moraine selected for the subsequent dating in consideration of its "reliability" if it is considered as evidence of specific former glacier variations. With more than 3000 potential glacier forelands in the entire mountain range, careful selection of future targets for successful chronological field work is essential. We present the preliminary results of an ongoing, time-efficient study to apply different remote sensing sources (aerial photography, Google Earth, satellite images) to evaluate the potential of certain glacier forelands for detailed ground

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression

Directory of Open Access Journals (Sweden)

Xu Yu

2018-01-01

Full Text Available Cross-domain collaborative filtering (CDCF solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR. We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Aging linear viscoelasticity of matrix-inclusion composite materials featuring ellipsoidal inclusions

OpenAIRE

LAVERGNE, Francis; SAB, Karam; SANAHUJA, Julien; BORNERT, Michel; TOULEMONDE, Charles

2016-01-01

A multi-scale homogenization scheme is proposed to estimate the time-dependent strains of fiber-reinforced concrete. This material is modeled as an aging linear viscoelastic composite material featuring ellipsoidal inclusions embedded in a viscoelastic cementitious matrix characterized by a time-dependent Poisson's ratio. To this end, the homogenization scheme proposed in Lavergne et al. [1] is adapted to the case of a time-dependent Poisson's ratio and it is successfully validated on a non-a...

Landslides in moraines as triggers of glacial lake outburst floods: example from Palcacocha Lake (Cordillera Blanca, Peru)

Czech Academy of Sciences Publication Activity Database

Klimeš, Jan; Novotný, J.; Novotná, I.; Urries de, B.J.; Vilímek, V.; Emmer, Adam; Strozzi, T.; Kusák, Michal; Rapre, A.C.; Hartvich, Filip; Frey, H.

2016-01-01

Roč. 13, č. 6 (2016), s. 1461-1477 ISSN 1612-510X R&D Projects: GA ČR(CZ) GAP209/11/1000 Institutional support: RVO:67985891 ; RVO:67179843 Keywords : landslides * moraines * glacial lakes * slope stability calculation * glacial lake outburst floods * impact wave models * Cordillera Blanca Subject RIV: DE - Earth Magnetism, Geodesy, Geography; DE - Earth Magnetism, Geodesy, Geography (UEK-B) Impact factor: 3.657, year: 2016

Geodiversity characterization and assessment of the Morainic Amphitheatre of Rivoli -Avigliana (NW-Italy)

Science.gov (United States)

Giordano, Enrico; Lucchesi, Stefania; Perotti, Luigi; Giardino, Marco

2014-05-01

The concept of Geodiversity in its wide sense refers specifically to particular geosystems that are in themselves complex (e.g diverse) assemblages of bedrock, landform, and soil features. Therefore, geodiversity assessment is strictly related to landscape structure, whose studies are in the field of complex Physical Geography. Moreover, Geodiversity studies provide a fundamental base for geoconservation and environmental management in a holistic way. This is particularly true within complex geomorphological environments, where many intrinsic and extrinsic factors are interconnected. Various procedures has been already applied for the creation of geodiversity maps in different geomorphological context, but especially in wide areas with a large geodiversity of landforms. Pleistocene morainic amphitheatres of the Alpine piedmont regions are indeed particular and complex environments: not only for the geological and geomorphological points of view, but also for their relationships with biotic components and human life. The aim of this study is to carry out a geodiversity characterization of the Rivoli-Avigliana Morainic Amphitheatre (AMRA; NW Italy). The AMRA separates the lower Susa Valley from the middle course of the Sangone River; it is a set of low hills and depressions related to glacial pulsations aged between 750,000 and 12,000 years ago. Earth Sciences knowledge of the area has been compared to detailed field geomorphological and territorial data in order to determine qualitative and quantitative landscape parameters and to evaluate their validity for geodiversity assessment. A first qualitative characterization of the AMRA and an estimation of its geodiversity have been performed by means of geomorphological mapping and stratigraphic studies, including geomorphosites assessment for the same area. Then, geodiversity characterization and evaluation have been performed through the definition and application of quantitative parameters (landform energy, slope

Linear microstructural features in R{sub 5}(Si,Ge){sub 4}-type alloys: Difficulties in identification

Energy Technology Data Exchange (ETDEWEB)

Chumbley, L.S. [Iowa State University, 214 Wilhelm, Ames, IA 50011 (United States); Ames Laboratory, 126 Metals Development, Ames, IA 50011 (United States)], E-mail: chumbley@iastate.edu; Ugurlu, O. [Los Alamos National Laboratory, Mail stop G755, Los Alamos, NM 87544 (United States); McCallum, R.W.; Dennis, K.W.; Mudryk, Y. [Ames Laboratory, 126 Metals Development, Ames, IA 50011 (United States); Gschneidner, K.A.; Pecharsky, V.K. [Iowa State University, 214 Wilhelm, Ames, IA 50011 (United States); Ames Laboratory, 126 Metals Development, Ames, IA 50011 (United States)

2008-02-15

A brief review of the current literature concerning compounds based upon the R{sub 5}(Si{sub x}Ge{sub 1-x}){sub 4} structure reveals that essentially all examined alloys contain 'linear features' similar to those first observed by Szade et al. on the surface of Gd{sub 5}Si{sub 4}, Gd{sub 5}Si{sub 2}Ge{sub 2} and Gd{sub 5}Ge{sub 4} samples. Attempts to characterize these features, using a variety of techniques, have proven to be a difficult task. Rather than becoming clearer and better understood, discrepancies in the reported data have resulted in much confusion. A series of comprehensive experiments involving optical, scanning and transmission electron microscopy, X-ray diffractometry, magnetization, and heat capacity measurements have been performed in an attempt to clarify the situation. These experiments, coupled with a critical examination of published data, allow certain misconceptions and apparent contradictions to be understood and explained. Of major importance is the discovery that the volume fraction of the linear feature present is far lower than what one may estimate on the basis of etched samples. The results of this study support previous data that show the linear features are a second phase of composition R{sub 5}(Si{sub x}Ge{sub 1-x}){sub 3}, and reveal the various difficulties associated with proper identification of this phase due to its small size scale and low volume percentage.

Fungal colonization and decomposition of leaves and stems of Salix arctica on deglaciated moraines in high-Arctic Canada

Science.gov (United States)

Osono, Takashi; Matsuoka, Shunsuke; Hirose, Dai; Uchida, Masaki; Kanda, Hiroshi

2014-06-01

Fungal colonization, succession, and decomposition of leaves and stems of Salix arctica were studied to estimate the roles of fungi in the decomposition processes in the high Arctic. The samples were collected from five moraines with different periods of development since deglaciation to investigate the effects of ecosystem development on the decomposition processes during the primary succession. The total hyphal lengths and the length of darkly pigmented hyphae increased during decomposition of leaves and stems and were not varied with the moraines. Four fungal morphotaxa were frequently isolated from both leaves and stems. The frequencies of occurrence of two morphotaxa varied with the decay class of leaves and/or stems. The hyphal lengths and the frequencies of occurrence of fungal morphotaxa were positively or negatively correlated with the contents of organic chemical components and nutrients in leaves and stems, suggesting the roles of fungi in chemical changes in the field. Pure culture decomposition tests demonstrated that the fungal morphotaxa were cellulose decomposers. Our results suggest that fungi took part in the chemical changes in decomposing leaves and stems even under the harsh environment of the high Arctic.

Moraine preservation and boulder erosion in the tropical Andes: interpreting old surface exposure ages in glaciated valleys

Science.gov (United States)

Smith, Jacqueline A.; Finkel, Robert C.; Farber, Daniel L.; Rodbell, Donald T.; Seltzer, Geoffrey O.

2005-10-01

Cosmogenic dating provides a long-awaited means of directly dating glacial deposits that pre-date the last glacial cycle. Although the potential benefits of longer chronologies are obvious, the greater uncertainty associated with older cosmogenic ages may be less readily apparent. We illustrate the challenges of developing and interpreting a long chronology using our data from the Peruvian Andes. We used surface exposure dating with cosmogenic radionuclides (CRNs; 10Be and 26Al) to date 140 boulders on moraines in valleys bordering the Junin Plain (11° S, 76° W) in central Peru. Our chronology spans multiple glacial cycles and includes exposure ages greater than 1 million years, which indicate that long-term rates of boulder erosion have been very low. Interpreting the chronology of moraines for glaciations that predate the last glacial cycle is complicated by the need to consider boulder erosion and exhumation, surface uplift, and inheritance of CRNs from previous exposure intervals. As an example, we recalculate exposure ages using our boulder erosion rates (0.3-0.5 metres per million years) and estimated surface uplift rates to emphasise both the challenges involved in interpreting old surface exposure ages and the value of chronological data, even with large uncertainties, when reconstructing the palaeoclimate of a region.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites

Science.gov (United States)

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-01-01

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. PMID:29518062

Spin fluctuations and low temperature features of thermal coefficient of linear expansion of iron monosilicide

International Nuclear Information System (INIS)

Volkov, A.G.; Kortov, S.V.; Povzner, A.A.

1996-01-01

The low temperature measurements of thermal coefficient of linear expansion of strong paramagnet FeSi are carried out. The results obtained are discussed with in the framework of spin-fluctuation theory. It is shown that electronic part of the thermal coefficient of linear expansion is negative in the range of temperatures lower that of the semiconductor-metal phase transition. In metal phase it becomes positive. This specific features of the thermal coefficient is explained by the spin-fluctuation renormalization of d-electronic states density

Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification.

Science.gov (United States)

Hariharan, M; Sindhu, R; Vijean, Vikneswaran; Yazid, Haniza; Nadarajaw, Thiyagar; Yaacob, Sazali; Polat, Kemal

2018-03-01

Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. The experimental

Linear sign in cystic brain lesions ≥5 mm: A suggestive feature of perivascular space.

Science.gov (United States)

Sung, Jinkyeong; Jang, Jinhee; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-Soo

2017-11-01

To determine the prevalence of a linear sign within enlarged perivascular space (EPVS) and chronic lacunar infarction (CLI) ≥ 5 mm on T2-weighted imaging (T2WI) and time-of-flight (TOF) magnetic resonance angiography (MRA), and to evaluate the diagnostic value of the linear signs for EPVS over CLI. This study included 101 patients with cystic lesions ≥ 5 mm on brain MRI including TOF MRA. After classification of cystic lesions into EPVS or CLI, two readers assessed linear signs on T2WI and TOF MRA. We compared the prevalence and the diagnostic performance of linear signs. Among 46 EPVS and 51 CLI, 84 lesions (86.6%) were in basal ganglia. The prevalence of T2 and TOF linear signs was significantly higher in the EPVS than in the CLI (P linear signs showed high sensitivity (> 80%). TOF linear sign showed significantly higher specificity (100%) and accuracy (92.8% and 90.7%) than T2 linear sign (P linear signs were more frequently observed in EPVS than CLI. They showed high sensitivity in differentiation of them, especially for basal ganglia. TOF sign showed higher specificity and accuracy than T2 sign. • Linear sign is a suggestive feature of EPVS. • Time-of-flight magnetic resonance angiography can reveal the lenticulostriate artery within perivascular spaces. • Linear sign helps differentiation of EPVS and CLI, especially in basal ganglia.

Debris flow from 2012 failure of moraine-dammed lake, Three Fingered Jack volcano, Mount Jefferson Wilderness, Oregon

Science.gov (United States)

Sherrod, David R.; Wills, Barton B.

2014-01-01

In the late spring or early summer of 2012, a flood emanated from a small moraine-dammed lake on the northeast flank of Three Fingered Jack in the Mount Jefferson Wilderness. Channel erosion or slope collapse breached the natural dam of the lake, leading to a sudden lowering of lake level by 2.8 m and discharge of 12,700 cubic meters (m3) of water. The resulting debris flow formed a bouldery deposit extending about 0.35 km downslope.

Comparisons of Circular Transmit and Linear Receive Compact Polarimetric SAR Features for Oil Slicks Discrimination

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Yu Li

2015-01-01

Full Text Available Compact polarimetric (CP synthetic aperture radar (SAR has proven its potential in distinguishing oil slicks and look-alikes. Polarimetric information can be retrieved directly from scattering vector or from reconstructed pseudo-Quad-Pol covariance matrix of CP SAR data. In this paper, we analysed features from Circular Transmit and Linear Receive (CTLR CP SAR data that are derived by taking both of these two methods. K-means clustering followed by accuracy assessment was also implemented for performance evaluation. Through experiments that were conducted based on L-band UAVSAR fully polarimetric data, it was found that optimum extraction methods varied for different features. The histogram analysis and segmentation results also demonstrated the comparable performance of CP SAR features in distinguishing different damping properties within oil slicks. This study proposed a framework of statistically analyzing polarimetric SAR (Pol-SAR features and provided guidelines for determining optimum feature extraction methods from CP SAR data and for marine oil-spills detection and classification.

The Effect of Creative Tasks on Electrocardiogram: Using Linear and Nonlinear Features in Combination with Classification Approaches

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Sahar Zakeri

2017-02-01

Full Text Available Objective: Interest in the subject of creativity and its impacts on human life is growing extensively. However, only a few surveys pay attention to the relation between creativity and physiological changes. This paper presents a novel approach to distinguish between creativity states from electrocardiogram signals. Nineteen linear and nonlinear features of the cardiac signal were extracted to detect creativity states. Method: ECG signals of 52 participants were recorded while doing three tasks of Torrance Tests of Creative Thinking (TTCT/ figural B. To remove artifacts, notch filter 50 Hz and Chebyshev II were applied. According to TTCT scores, participants were categorized into the high and low creativity groups: Participants with scores higher than 70 were assigned into the high creativity group and those with scores less than 30 were considered as low creativity group. Some linear and nonlinear features were extracted from the ECGs. Then, Support Vector Machine (SVM and Adaptive Neuro-Fuzzy Inference System (ANFIS were used to classify the groups.Results: Applying the Wilcoxon test, significant differences were observed between rest and each three tasks of creativity. However, better discrimination was performed between rest and the first task. In addition, there were no statistical differences between the second and third task of the test. The results indicated that the SVM effectively detects all the three tasks from the rest, particularly the task 1 and reached the maximum accuracy of 99.63% in the linear analysis. In addition, the high creative group was separated from the low creative group with the accuracy of 98.41%.Conclusion: the combination of SVM classifier with linear features can be useful to show the relation between creativity and physiological changes.

Recent changes in Imja Glacial Lake and its damming moraine in the Nepal Himalaya revealed by in situ surveys and multi-temporal ASTER imagery

International Nuclear Information System (INIS)

Fujita, Koji; Sakai, Akiko; Nuimura, Takayuki; Yamaguchi, Satoru; Sharma, Rishi R

2009-01-01

Changes in the area and bathymetry of Imja Glacial Lake and in the elevation of its damming moraine, Khumbu region, Nepal Himalaya are investigated. Previously reported changes in the lake area have been updated by multi-temporal ASTER images, which revealed a decreased expansion rate after 2000. A provisional expansion of the lake observed in 2004, from which some studies concluded an accelerated lake expansion due to global warming, has, from 2005, subsided to the glacier surface. Bathymetric changes for the period 1992-2002 that were first obtained for Himalayan glacial lakes suggest that the melting of debris-covered ice beneath the lake is insignificant in terms of the increase in lake volume, and that the retreat of a glacier in contact with the lake by calving is essential for the lake's expansion. Changes in the height of a damming moraine for the period 2001-2007 suggest a continuous surface lowering near the lake, though the lowering rates are smaller than those for the period 1989-1994.

Linear feature extraction from radar imagery: SBIR (Small Business Innovative Research), phase 2, option 2

Science.gov (United States)

Milgram, David L.; Kahn, Philip; Conner, Gary D.; Lawton, Daryl T.

1988-12-01

The goal of this effort is to develop and demonstrate prototype processing capabilities for a knowledge-based system to automatically extract and analyze features from Synthetic Aperture Radar (SAR) imagery. This effort constitutes Phase 2 funding through the Defense Small Business Innovative Research (SBIR) Program. Previous work examined the feasibility of and technology issues involved in the development of an automated linear feature extraction system. This final report documents this examination and the technologies involved in automating this image understanding task. In particular, it reports on a major software delivery containing an image processing algorithmic base, a perceptual structures manipulation package, a preliminary hypothesis management framework and an enhanced user interface.

1.60 Ga felsic volcanic blocks in the moraines of the Terre Adelie Craton, Antarctica: comparisons with the Gawler Range Volcanics, South Australia

International Nuclear Information System (INIS)

Peucat, J.J.; Capdevila, R.; Pecora, L.; Fanning, C.M.; Testut, L.

2002-01-01

Rhyodacite and rhyolite blocks found in numerous moraines on the Terre Adelie Craton in Antarctica are samples of a high-temperature high-K calc-alkaline to alkali-calcic igneous suite emplaced at ca 1.60Ga. They comprise lavas and pyroclastic rocks, including ignimbritic varieties, chemically representative of anorogenic and post-orogenic igneous suites. The eruptive centres are probably close to the coast according to radar satellite images that show the trace of the ice streams. The volcanic suite is similar in age, petrography and chemical composition (major and trace elements as well as Nd isotopes) to the Gawler Range Volcanics from the Gawler Craton of South Australia. These similarities strengthen correlations previously established between the Gawler Craton and the Terre Adelie Craton (Mawson Continent). Moreover, the present petrological, geochemical and geochronological data give a new insight into the last major thermal event affecting the Mawson Continent. The results also highlight the useful contribution of moraines to our knowledge of Antarctic geology. Copyright (2002) Geological Society of Australia

On Feature Extraction from Large Scale Linear LiDAR Data

Science.gov (United States)

Acharjee, Partha Pratim

Airborne light detection and ranging (LiDAR) can generate co-registered elevation and intensity map over large terrain. The co-registered 3D map and intensity information can be used efficiently for different feature extraction application. In this dissertation, we developed two algorithms for feature extraction, and usages of features for practical applications. One of the developed algorithms can map still and flowing waterbody features, and another one can extract building feature and estimate solar potential on rooftops and facades. Remote sensing capabilities, distinguishing characteristics of laser returns from water surface and specific data collection procedures provide LiDAR data an edge in this application domain. Furthermore, water surface mapping solutions must work on extremely large datasets, from a thousand square miles, to hundreds of thousands of square miles. National and state-wide map generation/upgradation and hydro-flattening of LiDAR data for many other applications are two leading needs of water surface mapping. These call for as much automation as possible. Researchers have developed many semi-automated algorithms using multiple semi-automated tools and human interventions. This reported work describes a consolidated algorithm and toolbox developed for large scale, automated water surface mapping. Geometric features such as flatness of water surface, higher elevation change in water-land interface and, optical properties such as dropouts caused by specular reflection, bimodal intensity distributions were some of the linear LiDAR features exploited for water surface mapping. Large-scale data handling capabilities are incorporated by automated and intelligent windowing, by resolving boundary issues and integrating all results to a single output. This whole algorithm is developed as an ArcGIS toolbox using Python libraries. Testing and validation are performed on a large datasets to determine the effectiveness of the toolbox and results are

Linear feature extraction from radar imagery: SBIR (Small Business Innovative Research) phase 2, option 1

Science.gov (United States)

Conner, Gary D.; Milgram, David L.; Lawton, Daryl T.; McConnell, Christopher C.

1988-04-01

The goal of this effort is to develop and demonstrate prototype processing capabilities for a knowledge-based system to automatically extract and analyze linear features from synthetic aperture radar (SAR) imagery. This effort constitutes Phase 2 funding through the Defense Small Business Innovative Research (SBIR) Program. Previous work examined the feasibility of the technology issues involved in the development of an automatedlinear feature extraction system. This Option 1 Final Report documents this examination and the technologies involved in automating this image understanding task. In particular, it reports on a major software delivery containing an image processing algorithmic base, a perceptual structures manipulation package, a preliminary hypothesis management framework and an enhanced user interface.

Recent changes in Imja Glacial Lake and its damming moraine in the Nepal Himalaya revealed by in situ surveys and multi-temporal ASTER imagery

Energy Technology Data Exchange (ETDEWEB)

Fujita, Koji; Sakai, Akiko; Nuimura, Takayuki [Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601 (Japan); Yamaguchi, Satoru [Snow and Ice Research Center, National Research Institute for Earth Science and Disaster Prevention, Nagaoka 940-0821 (Japan); Sharma, Rishi R [Department of Hydrology and Meteorology, Ministry of Environment, Science and Technology, Babar Mahal, Kathmandu (Nepal)

2009-10-15

Changes in the area and bathymetry of Imja Glacial Lake and in the elevation of its damming moraine, Khumbu region, Nepal Himalaya are investigated. Previously reported changes in the lake area have been updated by multi-temporal ASTER images, which revealed a decreased expansion rate after 2000. A provisional expansion of the lake observed in 2004, from which some studies concluded an accelerated lake expansion due to global warming, has, from 2005, subsided to the glacier surface. Bathymetric changes for the period 1992-2002 that were first obtained for Himalayan glacial lakes suggest that the melting of debris-covered ice beneath the lake is insignificant in terms of the increase in lake volume, and that the retreat of a glacier in contact with the lake by calving is essential for the lake's expansion. Changes in the height of a damming moraine for the period 2001-2007 suggest a continuous surface lowering near the lake, though the lowering rates are smaller than those for the period 1989-1994.

Odor valence linearly modulates attractiveness, but not age assessment, of invariant facial features in a memory-based rating task.

Science.gov (United States)

Seubert, Janina; Gregory, Kristen M; Chamberland, Jessica; Dessirier, Jean-Marc; Lundström, Johan N

2014-01-01

Scented cosmetic products are used across cultures as a way to favorably influence one's appearance. While crossmodal effects of odor valence on perceived attractiveness of facial features have been demonstrated experimentally, it is unknown whether they represent a phenomenon specific to affective processing. In this experiment, we presented odors in the context of a face battery with systematic feature manipulations during a speeded response task. Modulatory effects of linear increases of odor valence were investigated by juxtaposing subsequent memory-based ratings tasks--one predominantly affective (attractiveness) and a second, cognitive (age). The linear modulation pattern observed for attractiveness was consistent with additive effects of face and odor appraisal. Effects of odor valence on age perception were not linearly modulated and may be the result of cognitive interference. Affective and cognitive processing of faces thus appear to differ in their susceptibility to modulation by odors, likely as a result of privileged access of olfactory stimuli to affective brain networks. These results are critically discussed with respect to potential biases introduced by the preceding speeded response task.

A Feature-Free 30-Disease Pathological Brain Detection System by Linear Regression Classifier.

Science.gov (United States)

Chen, Yi; Shao, Ying; Yan, Jie; Yuan, Ti-Fei; Qu, Yanwen; Lee, Elizabeth; Wang, Shuihua

2017-01-01

Alzheimer's disease patients are increasing rapidly every year. Scholars tend to use computer vision methods to develop automatic diagnosis system. (Background) In 2015, Gorji et al. proposed a novel method using pseudo Zernike moment. They tested four classifiers: learning vector quantization neural network, pattern recognition neural network trained by Levenberg-Marquardt, by resilient backpropagation, and by scaled conjugate gradient. This study presents an improved method by introducing a relatively new classifier-linear regression classification. Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. Our method performs better than Gorji's approach and five other state-of-the-art approaches. Therefore, it can be used to detect Alzheimer's disease. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Little Ice Age glacial geomorphology and sedimentology of Portage Glacier, South-Central Alaska

Directory of Open Access Journals (Sweden)

Carlos Córdova

2009-06-01

Full Text Available The study of glacial landforms and deposits is important, as it isdifficult to observe processes under modern glaciers and ice-sheets. Thus landscapes and sediments that are the product of present glaciation can give insight into processes that occurred during Pleistocene times. This study investigates the genesis of little ice age glacial landforms present in Portage Glacier, South-Central Alaska. The present day moraine morphology and sedimentology in Portage Glacier valley reveals the presence of two types of till and moraines. The clast-rich sandy diamicton present on the 1852 moraine is interpreted to be a basal till indicating this feature is a pushmoraine representing an advance or a standstill position of Portage Glacier in 1852. The moderately sorted gray sandy boulder gravel present on the 1900 and 1922 moraines is interpreted to be an ice-marginal deposit (ablation till with a mixture of supraglacial and glaciofluvial sediments deposited by slumping and stream sortingprocesses. All of these features are interpreted to be ablation moraines representing glacier retreat and moraine building in 1900 and1922.

Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features.

Science.gov (United States)

Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara

2017-01-01

In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.

Review Article: Lake and breach hazard assessment for moraine-dammed lakes: an example from the Cordillera Blanca (Peru

Directory of Open Access Journals (Sweden)

A. Emmer

2013-06-01

Full Text Available Glacial lake outburst floods (GLOFs and related debris flows represent a significant threat in high mountainous areas across the globe. It is necessary to quantify this threat so as to mitigate their catastrophic effects. Complete GLOF hazard assessment incorporates two phases: the probability of water release from a given glacial lake is estimated through lake and breach hazard assessment while the endangered areas are identified during downstream hazard assessment. This paper outlines a number of methods of lake and breach hazard assessment, which can be grouped into three categories: qualitative, of which we outline eight; semi-quantitative, of which we outline two; and quantitative, of which we outline three. It is considered that five groups of critical parameters are essential for an accurate regionally focused hazard assessment method for moraine-dammed lakes in the Cordillera Blanca. These comprise the possibility of dynamic slope movements into the lake, the possibility of a flood wave from a lake situated upstream, the possibility of dam rupture following a large earthquake, the size of the dam freeboard (or ratio of dam freeboard, and a distinction between natural dams and those with remedial work. It is shown that none of the summarised methods uses all these criteria with, at most, three of the five considered by the outlined methods. A number of these methods were used on six selected moraine-dammed lakes in the Cordillera Blanca: lakes Quitacocha, Checquiacocha, Palcacocha, Llaca, Rajucolta, and Tararhua. The results have been compared and show that each method has certain advantages and disadvantages when used in this region. These methods demonstrate that the most hazardous lake is Lake Palcacocha.

Photogeologic study of small-scale linear features near a potential nuclear-waste repository site at Yucca Mountain, southern Nye County, Nevada

International Nuclear Information System (INIS)

Throckmorton, C.K.

1987-01-01

Linear features were mapped from 1:2400-scale aerial photographs of the northern half of the potential underground nuclear-waste repository site at Yucca Mountain by means of a Kern PG 2 stereoplotter. These features were thought to be the expression of fractures at the ground surface (fracture traces), and were mapped in the caprock, upper lithophysal, undifferentiated lower lithophysal and hackly units of the Tiva Canyon Member of the Miocene Paintbrush Tuff. To determine if the linear features corresponded to fracture traces observed in the field, stations (areas) were selected on the map where the traces were both abundant and located solely within one unit. These areas were visited in the field, where fracture-trace bearings and fracture-trace lengths were recorded. Additional data on fracture-trace length and fracture abundance, obtained from ground-based studies of cleared pavements located within the study area were used to help evaluate data collected for this study. 16 refs., 4 figs., 2 tabs

GLACIER DEGRADATION AND CATASTROPHIC MUDFLOWS ORIGIN FROM THE MODERN GLACIAL-MORAINE BODIES IN THE ELBRUS REGION

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E. A. Zolotarev

2012-01-01

Full Text Available Mechanism of formation of the catastrophic mudflows in different glacial valleys of Elbrus region at the present stage of glacial degradation is described. The important role of the buried ice in the formation of catastrophic mudflows that affected Tyrnyauz in the XX century was revealed as a result of remote monitoring of changes in glacial-moraine complex of Kayarta river. The dynamics of glacial lakes in the Adyl-Su valley in the Bashkara Glacier region was described and probability of their breakthrough was estimated. The quantitative indicators of the dynamics of the landslide in the Kubasanty valley were obtained as a result of remote monitoring, and its influence on the formation of catastrophic mudflows is discovered. Various possible methods of catastrophic mudflows prevention not requiring expensive protective constructions are discussed.

To evaluate ERTS-1 data for usefulness as a geological sensor in the diverse geological terraines of New York State

Science.gov (United States)

Isachsen, Y. W. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Linear anomalies dominate the new geological information derived from ERTS-1 imagery, total lengths now exceeding 6000 kms. Experimentation with a variety of viewing techniques suggests that conventional photogeologic analyses of band 7 results in the location of more than 97 percent of all linears found. Bedrock lithologic types are distinguishable only where they are topographically expressed or govern land use signatures. The maxima on rose diagrams for ERTS-1 anomalies correspond well with those for mapped faults and topographic lineaments, despite a difference in relative magnitudes of maxima thought due to solar illumination direction. A multiscale analysis of linears showed that single topographic linears at 1:2,500,000 became dashed jugate linears at 1:500,000, and shorter linears lacking any conspicuous zonal alignment at 1:250,000. Most circular features found were explained away by U-2 airphoto analysis but several remain as anomalies. Visible glacial features include individual drumlins, best seen in winter imagery, drumlinoids, eskers, ice-marginal drainage channels, glacial lake shorelines and sand plains, and end moraines.

Linear Colliders

International Nuclear Information System (INIS)

Alcaraz, J.

2001-01-01

After several years of study e''+ e''- linear colliders in the TeV range have emerged as the major and optimal high-energy physics projects for the post-LHC era. These notes summarize the present status form the main accelerator and detector features to their physics potential. The LHC era. These notes summarize the present status, from the main accelerator and detector features to their physics potential. The LHC is expected to provide first discoveries in the new energy domain, whereas an e''+ e''- linear collider in the 500 GeV-1 TeV will be able to complement it to an unprecedented level of precision in any possible areas: Higgs, signals beyond the SM and electroweak measurements. It is evident that the Linear Collider program will constitute a major step in the understanding of the nature of the new physics beyond the Standard Model. (Author) 22 refs

Simulating groundwater flow and runoff for the Oro Moraine aquifer system. Part II. Automated calibration and mass balance calculations

Science.gov (United States)

Beckers, J.; Frind, E. O.

2001-03-01

A steady-state groundwater model of the Oro Moraine aquifer system in Central Ontario, Canada, is developed. The model is used to identify the role of baseflow in the water balance of the Minesing Swamp, a 70 km 2 wetland of international significance. Lithologic descriptions are used to develop a hydrostratigraphic conceptual model of the aquifer system. The numerical model uses long-term averages to represent temporal variations of the flow regime and includes a mechanism to redistribute recharge in response to near-surface geologic heterogeneity. The model is calibrated to water level and streamflow measurements through inverse modeling. Observed baseflow and runoff quantities validate the water mass balance of the numerical model and provide information on the fraction of the water surplus that contributes to groundwater flow. The inverse algorithm is used to compare alternative model zonation scenarios, illustrating the power of non-linear regression in calibrating complex aquifer systems. The adjoint method is used to identify sensitive recharge areas for groundwater discharge to the Minesing Swamp. Model results suggest that nearby urban development will have a significant impact on baseflow to the swamp. Although the direct baseflow contribution makes up only a small fraction of the total inflow to the swamp, it provides an important steady influx of water over relatively large portions of the wetland. Urban development will also impact baseflow to the headwaters of local streams. The model provides valuable insight into crucial characteristics of the aquifer system although definite conclusions regarding details of its water budget are difficult to draw given current data limitations. The model therefore also serves to guide future data collection and studies of sub-areas within the basin.

Non linear system become linear system

Directory of Open Access Journals (Sweden)

Petre Bucur

2007-01-01

Full Text Available The present paper refers to the theory and the practice of the systems regarding non-linear systems and their applications. We aimed the integration of these systems to elaborate their response as well as to highlight some outstanding features.

Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection.

Science.gov (United States)

Wang, Yong; Wu, Qiao-Feng; Chen, Chen; Wu, Ling-Yun; Yan, Xian-Zhong; Yu, Shu-Guang; Zhang, Xiang-Sun; Liang, Fan-Rong

2012-01-01

Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use. In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints. Our result demonstrates that metabolic profiling might be a promising method to

Linear Accelerators

International Nuclear Information System (INIS)

Vretenar, M

2014-01-01

The main features of radio-frequency linear accelerators are introduced, reviewing the different types of accelerating structures and presenting the main characteristics aspects of linac beam dynamics

Linear and nonlinear resonance features of an erbium-doped fibre ...

Indian Academy of Sciences (India)

2014-07-01

Jul 1, 2014 ... Abstract. The continuous-wave output of a single-mode erbium-doped fibre ring laser when sub- jected to cavity-loss modulation is found to exhibit linear as well as nonlinear resonances. At sufficiently low driving amplitude, the system resembles a linear damped oscillator. At higher amplitudes, the ...

Contextual Multi-armed Bandits under Feature Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nam, Jun Hyun [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Mo, Sangwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Shin, Jinwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of)

2017-03-03

We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined NLinRel, having O(T⁷/₈(log(dT)+K√d)) regret bound for T rounds, K actions, and d-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including NLinRel are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has O(T²/₃√log d)regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case, we also design a practical variant of NLinRel, coined Universal-NLinRel, for arbitrary feature distributions. It first runs NLinRel for finding the ‘true’ coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of Universal-NLinRel on both synthetic and real-world datasets.

Linear Models

CERN Document Server

Searle, Shayle R

2012-01-01

This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.

Extended Linear Models with Gaussian Priors

DEFF Research Database (Denmark)

Quinonero, Joaquin

2002-01-01

In extended linear models the input space is projected onto a feature space by means of an arbitrary non-linear transformation. A linear model is then applied to the feature space to construct the model output. The dimension of the feature space can be very large, or even infinite, giving the model...... a very big flexibility. Support Vector Machines (SVM's) and Gaussian processes are two examples of such models. In this technical report I present a model in which the dimension of the feature space remains finite, and where a Bayesian approach is used to train the model with Gaussian priors...... on the parameters. The Relevance Vector Machine, introduced by Tipping, is a particular case of such a model. I give the detailed derivations of the expectation-maximisation (EM) algorithm used in the training. These derivations are not found in the literature, and might be helpful for newcomers....

Classification of line features from remote sensing data

OpenAIRE

Kolankiewiczová, Soňa

2009-01-01

This work deals with object-based classification of high resolution data. The aim of the thesis (paper, work) is to develope an acceptable classification process of linear features (roads and railways) from high-resolution satellite images. The first part shows different approaches of the linear feature classification and compares theoretic differences between an object-oriented and a pixel-based classification. Linear feature classification was created in the second part. The high-resolution...

An application of locally linear model tree algorithm with combination of feature selection in credit scoring

Science.gov (United States)

Siami, Mohammad; Gholamian, Mohammad Reza; Basiri, Javad

2014-10-01

Nowadays, credit scoring is one of the most important topics in the banking sector. Credit scoring models have been widely used to facilitate the process of credit assessing. In this paper, an application of the locally linear model tree algorithm (LOLIMOT) was experimented to evaluate the superiority of its performance to predict the customer's credit status. The algorithm is improved with an aim of adjustment by credit scoring domain by means of data fusion and feature selection techniques. Two real world credit data sets - Australian and German - from UCI machine learning database were selected to demonstrate the performance of our new classifier. The analytical results indicate that the improved LOLIMOT significantly increase the prediction accuracy.

Estimation of the groundwater resources of the bedrock aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin

Science.gov (United States)

Dunning, Charles; Feinstein, Daniel T.; Buchwald, Cheryl A.; Hunt, Randall J.; Haserodt, Megan J.

2017-10-12

Groundwater resources information was needed to understand regional aquifer systems and water available to wells and springs for rearing important Lake Michigan fish species at the Kettle Moraine Springs State Fish Hatchery in Sheboygan County, Wisconsin. As a basis for estimating the groundwater resources available, an existing groundwater-flow model was refined, and new groundwater-flow models were developed for the Kettle Moraine Springs State Fish Hatchery area using the U.S. Geological Survey (USGS) finite-difference code MODFLOW. This report describes the origin and construction of these groundwater-flow models and their use in testing conceptual models and simulating the hydrogeologic system.The study area is in the Eastern Ridges and Lowlands geographical province of Wisconsin, and the hatchery property is situated on the southeastern edge of the Kettle Moraine, a north-south trending topographic high of glacial origin. The bedrock units underlying the study area consist of Cambrian, Ordovician, and Silurian units of carbonate and siliciclastic lithology. In the Sheboygan County area, the sedimentary bedrock sequence reaches a thickness of as much as about 1,600 feet (ft).Two aquifer systems are present at the Kettle Moraine Springs State Fish Hatchery. A shallow system is made up of Silurian bedrock, consisting chiefly of dolomite, overlain by unconsolidated Quaternary-age glacial deposits. The glacial deposits of this aquifer system are the typical source of water to local springs, including the springs that have historically supplied the hatchery. The shallow aquifer system, therefore, consists of the unconsolidated glacial aquifer and the underlying bedrock Silurian aquifer. Most residential wells in the area draw from the Silurian aquifer. A deeper confined aquifer system is made up of Cambrian- and Ordovician-age bedrock units including sandstone formations. Because of its depth, very few wells are completed in the Cambrian-Ordovician aquifer system

Fault tolerant linear actuator

Science.gov (United States)

Tesar, Delbert

2004-09-14

In varying embodiments, the fault tolerant linear actuator of the present invention is a new and improved linear actuator with fault tolerance and positional control that may incorporate velocity summing, force summing, or a combination of the two. In one embodiment, the invention offers a velocity summing arrangement with a differential gear between two prime movers driving a cage, which then drives a linear spindle screw transmission. Other embodiments feature two prime movers driving separate linear spindle screw transmissions, one internal and one external, in a totally concentric and compact integrated module.

Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network

Directory of Open Access Journals (Sweden)

Jie Wang

2017-03-01

Full Text Available Deep convolutional neural networks (CNNs have been widely used to obtain high-level representation in various computer vision tasks. However, in the field of remote sensing, there are not sufficient images to train a useful deep CNN. Instead, we tend to transfer successful pre-trained deep CNNs to remote sensing tasks. In the transferring process, generalization power of features in pre-trained deep CNNs plays the key role. In this paper, we propose two promising architectures to extract general features from pre-trained deep CNNs for remote scene classification. These two architectures suggest two directions for improvement. First, before the pre-trained deep CNNs, we design a linear PCA network (LPCANet to synthesize spatial information of remote sensing images in each spectral channel. This design shortens the spatial “distance” of target and source datasets for pre-trained deep CNNs. Second, we introduce quaternion algebra to LPCANet, which further shortens the spectral “distance” between remote sensing images and images used to pre-train deep CNNs. With five well-known pre-trained deep CNNs, experimental results on three independent remote sensing datasets demonstrate that our proposed framework obtains state-of-the-art results without fine-tuning and feature fusing. This paper also provides baseline for transferring fresh pretrained deep CNNs to other remote sensing tasks.

Linear and Nonlinear Electrostatic Waves in Unmagnetized Dusty Plasmas

International Nuclear Information System (INIS)

Mamun, A. A.; Shukla, P. K.

2010-01-01

A rigorous and systematic theoretical study has been made of linear and nonlinear electrostatic waves propagating in unmagnetized dusty plasmas. The basic features of linear and nonlinear electrostatic waves (particularly, dust-ion-acoustic and dust-acoustic waves) for different space and laboratory dusty plasma conditions are described. The experimental observations of such linear and nonlinear features of dust-ion-acoustic and dust-acoustic waves are briefly discussed.

Basic linear algebra

CERN Document Server

Blyth, T S

2002-01-01

Basic Linear Algebra is a text for first year students leading from concrete examples to abstract theorems, via tutorial-type exercises. More exercises (of the kind a student may expect in examination papers) are grouped at the end of each section. The book covers the most important basics of any first course on linear algebra, explaining the algebra of matrices with applications to analytic geometry, systems of linear equations, difference equations and complex numbers. Linear equations are treated via Hermite normal forms which provides a successful and concrete explanation of the notion of linear independence. Another important highlight is the connection between linear mappings and matrices leading to the change of basis theorem which opens the door to the notion of similarity. This new and revised edition features additional exercises and coverage of Cramer's rule (omitted from the first edition). However, it is the new, extra chapter on computer assistance that will be of particular interest to readers:...

Geochronology of Quaternary glaciations from the tropical Cordillera Huayhuash, Peru

Science.gov (United States)

Hall, Sarah R.; Farber, Daniel L.; Ramage, Joan M.; Rodbell, Donald T.; Finkel, Robert C.; Smith, Jacqueline A.; Mark, Bryan G.; Kassel, Christopher

2009-12-01

The Cordillera Huayhuash in the central Peruvian Andes (10.3°S, 76.9°W) is an ideal mountain range in which to study regional climate through variations in paleoglacier extents. The range trends nearly north-south with modern glaciers confined to peaks >4800 m a.s.l. Geomorphology and geochronology in the nearby Cordillera Blanca and Junin Plain reveal that the Peruvian Andes preserve a detailed record of tropical glaciation. Here, we use ASTER imagery, aerial photographs, and GPS to map and date glacial features in both the western and eastern drainages of the Cordillera Huayhuash. We have used in situ produced cosmogenic 10Be concentrations in quartz bearing erratics on moraine crests and ice-polished bedrock surfaces to develop an exposure age chronology for Pleistocene glaciation within the range. We have also collected sediment cores from moraine-dammed lakes and bogs to provide limiting 14C ages for glacial deposits. In contrast to the ranges to the north and south, most glacial features within the Cordillera Huayhuash are Lateglacial in age, however we have identified features with ages that span ˜0.2 to ˜38 ka with moraine sets marking the onset of glacier retreat at ˜0.3 ka, ˜9-10 ka, ˜13-14 ka, ˜20-22 ka, and >26 ka. The range displays a pronounced east-west variation in maximum down-valley distance from the headwall of moraine crests with considerably longer paleoglaciers in the eastern drainages. Importantly, Lateglacial paleoglaciers reached a terminal elevation of ˜4000 m a.s.l. on both sides of the Cordillera Huayhuash; suggesting that temperature may have been a dominant factor in controlling the maximum glacier extent. We suggest that valley morphology, specifically valley slope, strongly influences down-valley distance to the maximum glacier extent and potential for moraine preservation. While regionally there is an extensive record of older (>50 ka) advances to the north (Cordillera Blanca) and to the south (Junin region), the apparent

Introduction to RF linear accelerators

International Nuclear Information System (INIS)

Weiss, M.

1994-01-01

The basic features of RF linear accelerators are described. The concept of the 'loaded cavity', essential for the synchronism wave-particle, is introduced, and formulae describing the action of electromagnetic fields on the beam are given. The treatment of intense beams is mentioned, and various existing linear accelerators are presented as examples. (orig.)

Topics in computational linear optimization

DEFF Research Database (Denmark)

Hultberg, Tim Helge

2000-01-01

Linear optimization has been an active area of research ever since the pioneering work of G. Dantzig more than 50 years ago. This research has produced a long sequence of practical as well as theoretical improvements of the solution techniques avilable for solving linear optimization problems...... of high quality solvers and the use of algebraic modelling systems to handle the communication between the modeller and the solver. This dissertation features four topics in computational linear optimization: A) automatic reformulation of mixed 0/1 linear programs, B) direct solution of sparse unsymmetric...... systems of linear equations, C) reduction of linear programs and D) integration of algebraic modelling of linear optimization problems in C++. Each of these topics is treated in a separate paper included in this dissertation. The efficiency of solving mixed 0-1 linear programs by linear programming based...

Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

Science.gov (United States)

Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

2015-01-01

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

Language identification using excitation source features

CERN Document Server

Rao, K Sreenivasa

2015-01-01

This book discusses the contribution of excitation source information in discriminating language. The authors focus on the excitation source component of speech for enhancement of language identification (LID) performance. Language specific features are extracted using two different modes: (i) Implicit processing of linear prediction (LP) residual and (ii) Explicit parameterization of linear prediction residual. The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual; and in explicit parameterization approach, LP residual signal is processed in spectral domain to extract the relevant language specific features. The authors further extract source features from these modes, which are combined for enhancing the performance of LID systems. The proposed excitation source features are also investigated for LID in background noisy environments. Each chapter of this book provides the motivatio...

GEOMORPHOLOGY AND SEDIMENTOLOGY OF UNION GLACIER AREA, ELLSWORTH MOUNTAINS, OCCIDENTAL ANTARCTICA

Directory of Open Access Journals (Sweden)

Vanessa do Couto Silva Costa

2017-08-01

Full Text Available The work aims to investigate the geomorphological and sedimentological aspects of Union Glacier area (79°45’00’’S; 82°30’00’’W, southern sector of Ellsworth Mountains. Geomorphological cartography based on 15 m ASTER (2010 satellite imagery and field works were carried out during the Brazilian expedition (2011/2012 enabled the identification of morainic formations: ice-cored hummock moraines, supraglacial moraines, and recession moraines in the interior of the valleys. With the exception of the latter one, all types of moraines have been developed on the blue-ice areas. The evidence for paleo wet-based glacial conditions is reconstructed from a range of geomorphological record, including exposed abrasion marks, striations and glaciotectonic deformation. This type of deformation is represented by lee sides of oversteepening bedrock promontories which follow the tributaries of glaciers ice flow. Glacial sediments were collected from the moraines for granulometric and morphometric analyses. They show the prevalence of sandy gravel and sand texture, low quantity of fine fractions, and absence of attributes such as striated and faceted clasts, which indicate, on the other side, low-sediment transport capacity from the ice sheet bottom. It is inferred that the moraine debris are originated from local sources. Weathering action and constant katabatic winds are possibly the major agents of transport and alteration of the exposed sediments. The geomorphological features reveal an ancient thicker ice sheet, and sedimentary characteristics of the morainic formations reveal a latter thinner ice sheet in this sector of Ellsworth Mountains.

Linear feature selection in texture analysis - A PLS based method

DEFF Research Database (Denmark)

Marques, Joselene; Igel, Christian; Lillholm, Martin

2013-01-01

We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

SEEDLING DISCRIMINATION USING SHAPE FEATURES DERIVED FROM A DISTANCE TRANSFORM

DEFF Research Database (Denmark)

Mosgaard Giselsson, Thomas; Jørgensen, Rasmus Nyholm; Midtiby, Henrik

NN, Naive-Bayes, Linear SVM, Non-linear SVM). A set of well known features is used for comparison. This feature set will be referred to as Standard Feature Set (SFS). The used dataset consisted of 139 samples of Corn Flower (Centaura cyanus L.) and 63 samples of Night Shade (Solanum nigrum L.). The highest...

Integrated Phoneme Subspace Method for Speech Feature Extraction

Directory of Open Access Journals (Sweden)

Park Hyunsin

2009-01-01

Full Text Available Speech feature extraction has been a key focus in robust speech recognition research. In this work, we discuss data-driven linear feature transformations applied to feature vectors in the logarithmic mel-frequency filter bank domain. Transformations are based on principal component analysis (PCA, independent component analysis (ICA, and linear discriminant analysis (LDA. Furthermore, this paper introduces a new feature extraction technique that collects the correlation information among phoneme subspaces and reconstructs feature space for representing phonemic information efficiently. The proposed speech feature vector is generated by projecting an observed vector onto an integrated phoneme subspace (IPS based on PCA or ICA. The performance of the new feature was evaluated for isolated word speech recognition. The proposed method provided higher recognition accuracy than conventional methods in clean and reverberant environments.

Menu-Driven Solver Of Linear-Programming Problems

Science.gov (United States)

Viterna, L. A.; Ferencz, D.

1992-01-01

Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).

Directional filtering for linear feature enhancement in geophysical maps

NARCIS (Netherlands)

Sykes, M.P.; Das, U.C.

2000-01-01

Geophysical maps of data acquired in ground and airborne surveys are extensively used for mineral, groundwater, and petroleum exploration. Lineaments in these maps are often indicative of contacts, basement faulting, and other tectonic features of interest. To aid the interpretation of these maps, a

Classification of acute stress using linear and non-linear heart rate variability analysis derived from sternal ECG

DEFF Research Database (Denmark)

Tanev, George; Saadi, Dorthe Bodholt; Hoppe, Karsten

2014-01-01

Chronic stress detection is an important factor in predicting and reducing the risk of cardiovascular disease. This work is a pilot study with a focus on developing a method for detecting short-term psychophysiological changes through heart rate variability (HRV) features. The purpose of this pilot...... study is to establish and to gain insight on a set of features that could be used to detect psychophysiological changes that occur during chronic stress. This study elicited four different types of arousal by images, sounds, mental tasks and rest, and classified them using linear and non-linear HRV...

Microwave Radiometer Linearity Measured by Simple Means

DEFF Research Database (Denmark)

Skou, Niels

2002-01-01

Modern spaceborne radiometer systems feature an almost perfect on-board calibration, hence the primary calibration task to be carried out before launch is a check of radiometer linearity. This paper describes two ways of measuring linearity of microwave radiometers only requiring relatively simple...

A linear-time algorithm for Euclidean feature transform sets

NARCIS (Netherlands)

Hesselink, Wim H.

2007-01-01

The Euclidean distance transform of a binary image is the function that assigns to every pixel the Euclidean distance to the background. The Euclidean feature transform is the function that assigns to every pixel the set of background pixels with this distance. We present an algorithm to compute the

Non-linear effects in the Boltzmann equation

International Nuclear Information System (INIS)

Barrachina, R.O.

1985-01-01

The Boltzmann equation is studied by defining an integral transformation of the energy distribution function for an isotropic and homogeneous gas. This transformation may be interpreted as a linear superposition of equilibrium states with variable temperatures. It is shown that the temporal evolution features of the distribution function are determined by the singularities of said transformation. This method is applied to Maxwell and Very Hard Particle interaction models. For the latter, the solution of the Boltzmann equation with the solution of its linearized version is compared, finding out many basic discrepancies and non-linear effects. This gives a hint to propose a new rational approximation method with a clear physical meaning. Applying this technique, the relaxation features of the BKW (Bobylev, Krook anf Wu) mode is analyzed, finding a conclusive counter-example for the Krook and Wu conjecture. The anisotropic Boltzmann equation for Maxwell models is solved as an expansion in terms of the eigenfunctions of the corresponding linearized collision operator, finding interesting transient overpopulation and underpopulation effects at thermal energies as well as a new preferential spreading effect. By analyzing the initial collision, a criterion is established to deduce the general features of the final approach to equilibrium. Finally, it is shown how to improve the convergence of the eigenfunction expansion for high energy underpopulated distribution functions. As an application of this theory, the linear cascade model for sputtering is analyzed, thus finding out that many differences experimentally observed are due to non-linear effects. (M.E.L.) [es

Geostatistical mapping of leakance in a regional aquitard, Oak Ridges Moraine area, Ontario, Canada

Science.gov (United States)

Desbarats, A. J.; Hinton, M. J.; Logan, C. E.; Sharpe, D. R.

2001-01-01

The Newmarket Till forms a regionally extensive aquitard separating two major aquifer systems in the Greater Toronto area, Canada. The till is incised, and sometimes eroded entirely, by a network of sand- and gravel-filled channels forming productive aquifers and, locally, high-conductivity windows between aquifer systems. Leakage through the till may also be substantial in places. This study investigates the spatial variability of aquitard leakance in order to assess the relative importance of recharge processes to the lower aquifers. With a large database derived from water-well records and containing both hard and soft information, the Sequential Indicator Simulation method is used to generate maps of aquitard thickness and window probability. These can be used for targeting channel aquifers and for identifying potential areas of recharge to the lower aquifers. Conductivities are modeled from sparse data assuming that their correlation range is much smaller than the grid spacing. Block-scale leakances are obtained by upscaling nodal values based on simulated conductivity and thickness fields. Under the "aquifer-flow'' assumption, upscaling is performed by arithmetic spatial averaging. Histograms and maps of upscaled leakances show that heterogeneities associated with aquitard windows have the largest effect on regional groundwater flow patterns. Résumé. La moraine glaciaire de Newmarket constitue un imperméable d'extension régionale séparant deux systèmes aquifères dans la région du Grand Toronto (Canada). La moraine est entaillée, et parfois entièrement érodée, par un réseau de chenaux comblés de sables et de graviers formant des aquifères productifs et, localement, des «fenêtres», zones à forte conductivité hydraulique reliant les systèmes aquifères. Une drainance au travers de la moraine peut également être significative par endroits. Cette étude s'intéresse à la variabilité spatiale de la drainance au travers de l

KASHKATASH GLACIER FLUCTUATIONS IN THE XVII–XXI CENTURIES FROM CARTOGRAPHIC, DENDROCHRONOLOGICAL AND LICHENOMETRIC DATA

Directory of Open Access Journals (Sweden)

I. S. Bushueva

2012-01-01

Full Text Available We focused our study on the retreat of a typical valley glacier Kashkatash, located in the Elbrus Area. We compared the old photographs of the glacier forefields (H. Burmester, 1911; H. Altberg, 1927; E.N. Lukasheva, 1932; unknown author, 1939 with the aerial photograph of 1957, 1965, 1987, maps of scale 1:100 000 (1890 and 1:25 000 (1950s, satellite images (CORONA of 1971, ASTER of 2005, EROS of 2006, oblique photographs taken in 1980s–2000s and plans, created by different researches. Using cartographic material and old photographs we reconstructed 14 positions of glacier tongue over the last 120 years. We estimated the linear glacier retreat and the age of numerous stadial moraines basing on geomorphic, tree-ring and lichenometric data and correlated our results with previous sparse glacier fluctuation reconstructions in this region. We identified at least 13 end moraines within the distance of 900 meters from the up-to-date glacier front position. The minimum age of the outer moraine is 450 years according to the tree-ring data. One tree growing on this moraine was damaged by a boulder falling down from a younger moraine under formation in the period from autumn 1839 to spring 1840. Three moraines were deposited in 1870s–1890s. In 20th century the glacier advanced in 1910-s, 1920-s, and 1970–1980-s.

Geochronology of Tropical Alpine Glaciations From the Cordillera Huayhuash, Peru

Science.gov (United States)

Hall, S. R.; Farber, D. L.; Rodbell, D. T.; Finkel, R. C.; Ramage, J. M.; Smith, J. A.; Mark, B. G.; Seltzer, G. O.

2004-12-01

The Cordillera Huayhuash of the Central Peruvian Andes (10.3° S, 76.9° W) is an ideal range to study regional climate signals and variations in paleo-ice volumes. Located between the Cordillera Blanca to the north and the Junin region to the south, the range trends nearly north-south with modern glaciers confined to the high peaks (>4800 m). Cross-cutting relationships, geomorphology, and correlation with surface exposure dated moraines in the nearby Cordillera Blanca suggest the region preserves a rich record of tropical glaciation. In order to determine the glacial chronology we mapped and dated glacial features of the Jahuacocha valley (which drains the western side of the range) and two eastern drainages, the Mitococha valley, and the Carhuacocha valley. At each locality we used ASTER data, aerial photographs, and GPS to map glacial features both within main valleys and tributaries. We sampled quartz-bearing erratics on moraine crests as well as ice-polished bedrock surfaces for exposure age dating using in situ produced cosmogenic 10Be and 26Al. In the Jahuacocha valley, the greatest ice extent reached an elevation of ˜4090m and moraine crest boulders yield and age of ˜11.2 ±0.6 ka suggesting a significant late Glacial ice advance or stillstand. A younger cluster of moraines exists ˜1 km up-valley at an elevation of ˜4100m. These moraines, dated at ˜8.0 ±1.0 ka, suggest an early Holocene advance. In the Mitococha valley, a young moraine and polished bedrock dated at ˜0.2 ka and ˜11.4 ±0.4 ka respectively span the late Glacial through recent. The late Glacial features of this eastern drainage occur at an elevation of ˜4100m while the recent events occur at an elevation of ˜4380m. Our preliminary results suggest that all three valleys experienced a very similar glacial history with minor differences likely due to the variations in valley morphology. Comparing the chronology of glaciation in the Cordillaera Huayhuash with that in regions to the

Linear sign in cystic brain lesions ≥5 mm. A suggestive feature of perivascular space

Energy Technology Data Exchange (ETDEWEB)

Sung, Jinkyeong [The Catholic University of Korea, Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, Seoul (Korea, Republic of); The Catholic University of Korea, Department of Radiology, St. Vincent' s Hospital, College of Medicine, Seoul (Korea, Republic of); Jang, Jinhee; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-soo [The Catholic University of Korea, Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, Seoul (Korea, Republic of)

2017-11-15

To determine the prevalence of a linear sign within enlarged perivascular space (EPVS) and chronic lacunar infarction (CLI) ≥ 5 mm on T2-weighted imaging (T2WI) and time-of-flight (TOF) magnetic resonance angiography (MRA), and to evaluate the diagnostic value of the linear signs for EPVS over CLI. This study included 101 patients with cystic lesions ≥ 5 mm on brain MRI including TOF MRA. After classification of cystic lesions into EPVS or CLI, two readers assessed linear signs on T2WI and TOF MRA. We compared the prevalence and the diagnostic performance of linear signs. Among 46 EPVS and 51 CLI, 84 lesions (86.6%) were in basal ganglia. The prevalence of T2 and TOF linear signs was significantly higher in the EPVS than in the CLI (P <.001). For the diagnosis of EPVS, T2 and TOF linear signs showed high sensitivity (> 80%). TOF linear sign showed significantly higher specificity (100%) and accuracy (92.8% and 90.7%) than T2 linear sign (P <.001). T2 and TOF linear signs were more frequently observed in EPVS than CLI. They showed high sensitivity in differentiation of them, especially for basal ganglia. TOF sign showed higher specificity and accuracy than T2 sign. (orig.)

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

Science.gov (United States)

Harwit, M.

2010-03-01

We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

Selecting protein families for environmental features based on manifold regularization.

Science.gov (United States)

Jiang, Xingpeng; Xu, Weiwei; Park, E K; Li, Guangrong

2014-06-01

Recently, statistics and machine learning have been developed to identify functional or taxonomic features of environmental features or physiological status. Important proteins (or other functional and taxonomic entities) to environmental features can be potentially used as biosensors. A major challenge is how the distribution of protein and gene functions embodies the adaption of microbial communities across environments and host habitats. In this paper, we propose a novel regularization method for linear regression to adapt the challenge. The approach is inspired by local linear embedding (LLE) and we call it a manifold-constrained regularization for linear regression (McRe). The novel regularization procedure also has potential to be used in solving other linear systems. We demonstrate the efficiency and the performance of the approach in both simulation and real data.

Imaging linear and circular polarization features in leaves with complete Mueller matrix polarimetry.

Science.gov (United States)

Patty, C H Lucas; Luo, David A; Snik, Frans; Ariese, Freek; Buma, Wybren Jan; Ten Kate, Inge Loes; van Spanning, Rob J M; Sparks, William B; Germer, Thomas A; Garab, Győző; Kudenov, Michael W

2018-06-01

Spectropolarimetry of intact plant leaves allows to probe the molecular architecture of vegetation photosynthesis in a non-invasive and non-destructive way and, as such, can offer a wealth of physiological information. In addition to the molecular signals due to the photosynthetic machinery, the cell structure and its arrangement within a leaf can create and modify polarization signals. Using Mueller matrix polarimetry with rotating retarder modulation, we have visualized spatial variations in polarization in transmission around the chlorophyll a absorbance band from 650 nm to 710 nm. We show linear and circular polarization measurements of maple leaves and cultivated maize leaves and discuss the corresponding Mueller matrices and the Mueller matrix decompositions, which show distinct features in diattenuation, polarizance, retardance and depolarization. Importantly, while normal leaf tissue shows a typical split signal with both a negative and a positive peak in the induced fractional circular polarization and circular dichroism, the signals close to the veins only display a negative band. The results are similar to the negative band as reported earlier for single macrodomains. We discuss the possible role of the chloroplast orientation around the veins as a cause of this phenomenon. Systematic artefacts are ruled out as three independent measurements by different instruments gave similar results. These results provide better insight into circular polarization measurements on whole leaves and options for vegetation remote sensing using circular polarization. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.

Linear feature detection algorithm for astronomical surveys - II. Defocusing effects on meteor tracks

Science.gov (United States)

Bektešević, Dino; Vinković, Dejan; Rasmussen, Andrew; Ivezić, Željko

2018-03-01

Given the current limited knowledge of meteor plasma micro-physics and its interaction with the surrounding atmosphere and ionosphere, meteors are a highly interesting observational target for high-resolution wide-field astronomical surveys. Such surveys are capable of resolving the physical size of meteor plasma heads, but they produce large volumes of images that need to be automatically inspected for possible existence of long linear features produced by meteors. Here, we show how big aperture sky survey telescopes detect meteors as defocused tracks with a central brightness depression. We derive an analytic expression for a defocused point source meteor track and use it to calculate brightness profiles of meteors modelled as uniform brightness discs. We apply our modelling to meteor images as seen by the Sloan Digital Sky Survey and Large Synoptic Survey Telescope telescopes. The expression is validated by Monte Carlo ray-tracing simulations of photons travelling through the atmosphere and the Large Synoptic Survey Telescope telescope optics. We show that estimates of the meteor distance and size can be extracted from the measured full width at half-maximum and the strength of the central dip in the observed brightness profile. However, this extraction becomes difficult when the defocused meteor track is distorted by the atmospheric seeing or contaminated by a long-lasting glowing meteor trail. The full width at half-maximum of satellite tracks is distinctly narrower than meteor values, which enables removal of a possible confusion between satellites and meteors.

Explorative methods in linear models

DEFF Research Database (Denmark)

Høskuldsson, Agnar

2004-01-01

The author has developed the H-method of mathematical modeling that builds up the model by parts, where each part is optimized with respect to prediction. Besides providing with better predictions than traditional methods, these methods provide with graphic procedures for analyzing different feat...... features in data. These graphic methods extend the well-known methods and results of Principal Component Analysis to any linear model. Here the graphic procedures are applied to linear regression and Ridge Regression....

Linear morphea with secondary mucinosis

Directory of Open Access Journals (Sweden)

Khandpur Sujay

2009-01-01

Full Text Available Secondary mucin deposition in the skin is a common feature of lupus erythematosus and dermatomyositis. In scleroderma, it occurs uncommonly or in small amount. We describe a 7-year-old boy with progressive, linear, bound-down plaques involving the thighs, lower abdomen and back with no systemic involvement. Histopathology showed features of scleroderma with abundant mucin deposition in the reticular dermis. This report highlights excessive mucin deposition in lesions of morphea.

Feature extraction with deep neural networks by a generalized discriminant analysis.

Science.gov (United States)

Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

2012-04-01

We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

Science.gov (United States)

Li, Jing; Hong, Wenxue

2014-12-01

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

WHIZARD 2.2 for linear colliders

International Nuclear Information System (INIS)

Kilian, W.; Ohl, T.

2014-03-01

We review the current status of the WHIZARD event generator. We discuss, in particular, recent improvements and features that are relevant for simulating the physics program at a future Linear Collider.

Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

2017-03-01

In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

Basic linear partial differential equations

CERN Document Server

Treves, Francois

1975-01-01

Focusing on the archetypes of linear partial differential equations, this text for upper-level undergraduates and graduate students features most of the basic classical results. The methods, however, are decidedly nontraditional: in practically every instance, they tend toward a high level of abstraction. This approach recalls classical material to contemporary analysts in a language they can understand, as well as exploiting the field's wealth of examples as an introduction to modern theories.The four-part treatment covers the basic examples of linear partial differential equations and their

Salient Region Detection via Feature Combination and Discriminative Classifier

Directory of Open Access Journals (Sweden)

Deming Kong

2015-01-01

Full Text Available We introduce a novel approach to detect salient regions of an image via feature combination and discriminative classifier. Our method, which is based on hierarchical image abstraction, uses the logistic regression approach to map the regional feature vector to a saliency score. Four saliency cues are used in our approach, including color contrast in a global context, center-boundary priors, spatially compact color distribution, and objectness, which is as an atomic feature of segmented region in the image. By mapping a four-dimensional regional feature to fifteen-dimensional feature vector, we can linearly separate the salient regions from the clustered background by finding an optimal linear combination of feature coefficients in the fifteen-dimensional feature space and finally fuse the saliency maps across multiple levels. Furthermore, we introduce the weighted salient image center into our saliency analysis task. Extensive experiments on two large benchmark datasets show that the proposed approach achieves the best performance over several state-of-the-art approaches.

Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Muhammad Naveed Iqbal Qureshi

2017-09-01

Full Text Available Multimodal features of structural and functional magnetic resonance imaging (MRI of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001 accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

Analysis of Feature Extraction Methods for Speaker Dependent Speech Recognition

Directory of Open Access Journals (Sweden)

Gurpreet Kaur

2017-02-01

Full Text Available Speech recognition is about what is being said, irrespective of who is saying. Speech recognition is a growing field. Major progress is taking place on the technology of automatic speech recognition (ASR. Still, there are lots of barriers in this field in terms of recognition rate, background noise, speaker variability, speaking rate, accent etc. Speech recognition rate mainly depends on the selection of features and feature extraction methods. This paper outlines the feature extraction techniques for speaker dependent speech recognition for isolated words. A brief survey of different feature extraction techniques like Mel-Frequency Cepstral Coefficients (MFCC, Linear Predictive Coding Coefficients (LPCC, Perceptual Linear Prediction (PLP, Relative Spectra Perceptual linear Predictive (RASTA-PLP analysis are presented and evaluation is done. Speech recognition has various applications from daily use to commercial use. We have made a speaker dependent system and this system can be useful in many areas like controlling a patient vehicle using simple commands.

Linear interictal pain in Epicrania Fugax.

Science.gov (United States)

Pareja, Juan A; Bandrés, Pablo

2015-01-01

Epicrania Fugax is a paroxysmal, short-lasting, head pain moving across one hemicranium, describing a linear or zag trajectory, starting and ending in territories of different nerves. Between attacks, patients are usually free of symptoms. We describe an Epicrania Fugax patient complaining of interictal pain. The interictal pain was line-shaped and extended across the usual starting and ending points of the typical Epicrania Fugax paroxysms. Although rarely encountered, persistent linear pain may be a feature of Epicrania Fugax.

Novel features of non-linear Raman instability in a laser plasma

Czech Academy of Sciences Publication Activity Database

Mašek, Martin; Rohlena, Karel

2010-01-01

Roč. 56, č. 1 (2010), s. 79-90 ISSN 1434-6060 R&D Projects: GA MŠk(CZ) 7E08099; GA MŠk(CZ) LC528; GA ČR GA202/05/2475 Institutional research plan: CEZ:AV0Z10100523 Keywords : laser plasma * non-linear Raman instability Subject RIV: BH - Optics, Masers, Lasers Impact factor: 1.513, year: 2010

Non-linear wave packet dynamics of coherent states

Indian Academy of Sciences (India)

In recent years, the non-linear quantum dynamics of these states have revealed some striking features. It was found that under the action of a Hamil- tonian which is a non-linear function of the photon operator(s) only, an initial coherent state loses its coherent structure quickly due to quantum dephasing induced by the non-.

Lines of landscape organisation

DEFF Research Database (Denmark)

Løvschal, Mette

2015-01-01

This paper offers a landscape analysis of the earliest linear landscape boundaries on Skovbjerg Moraine, Denmark, during the first millennium BC. Using Delaunay triangulation as well as classic distribution analyses, it demonstrates that landscape boundaries articulated already established use-pa...

Restoring the missing features of the corrupted speech using linear interpolation methods

Science.gov (United States)

Rassem, Taha H.; Makbol, Nasrin M.; Hasan, Ali Muttaleb; Zaki, Siti Syazni Mohd; Girija, P. N.

2017-10-01

One of the main challenges in the Automatic Speech Recognition (ASR) is the noise. The performance of the ASR system reduces significantly if the speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low Signal to Noise Ratio (SNR) elements, the incomplete spectrogram is obtained. In this case, the speech recognizer should make modifications to the spectrogram in order to restore the missing elements, which is one direction. In another direction, speech recognizer should be able to restore the missing elements due to deleting low SNR elements before performing the recognition. This is can be done using different spectrogram reconstruction methods. In this paper, the geometrical spectrogram reconstruction methods suggested by some researchers are implemented as a toolbox. In these geometrical reconstruction methods, the linear interpolation along time or frequency methods are used to predict the missing elements between adjacent observed elements in the spectrogram. Moreover, a new linear interpolation method using time and frequency together is presented. The CMU Sphinx III software is used in the experiments to test the performance of the linear interpolation reconstruction method. The experiments are done under different conditions such as different lengths of the window and different lengths of utterances. Speech corpus consists of 20 males and 20 females; each one has two different utterances are used in the experiments. As a result, 80% recognition accuracy is achieved with 25% SNR ratio.

Teaching Linear Algebra: Must the Fog Always Roll In?

Science.gov (United States)

Carlson, David

1993-01-01

Proposes methods to teach the more difficult concepts of linear algebra. Examines features of the Linear Algebra Curriculum Study Group Core Syllabus, and presents problems from the core syllabus that utilize the mathematical process skills of making conjectures, proving the results, and communicating the results to colleagues. Presents five…

Crevasse-squeeze ridge corridors: Diagnostic features of late-stage palaeo-ice stream activity

Science.gov (United States)

Evans, David J. A.; Storrar, Robert D.; Rea, Brice R.

2016-04-01

A 200-km-long and 10-km-wide linear assemblage of till-filled geometrical ridges on the bed of the Maskwa palaeo-ice stream of the late Wisconsinan southwest Laurentide Ice Sheet are interpreted as crevasse-squeeze ridges (CSR) developed during internal flow unit reorganization, immediately prior to ice stream shutdown. Ridge orientations are predominantly orientated WNW-ESE, with a subordinate WSW-ENE alignment, both indicative of ice fracture development transverse to former ice stream flow, as indicated by NNE-SSW aligned MSGL. Subglacial till injection into basal and/or full depth, mode I and II crevasses occurred at the approximate centreline of the ice stream, in response to extension and fracturing. Landform preservation indicates that this took place during the final stages of ice streaming, immediately prior to ice stream shutdown. This linear zone of ice fracturing therefore likely represents the narrowing of the fast-flowing trunk, similar to the plug flow identified in some surging valley glaciers. Lateral drag between the final active flow unit and the slower moving ice on either side is likely recorded by the up-ice bending of the CSR limbs. The resulting CSR corridor, here related to an individual ice stream flow unit, constitutes a previously unreported style of crevasse infilling and contrasts with two existing CSR patterns: (1) wide arcuate zones of CSRs related to widespread fracturing within glacier surge lobes; and (2) narrow concentric arcs of CSRs and recessional push moraines related to submarginal till deformation at active temperate glacier lobes.

Linear Malignant Melanoma In Situ: Reports and Review of Cutaneous Malignancies Presenting as Linear Skin Cancer.

Science.gov (United States)

Cohen, Philip R

2017-09-18

Melanomas usually present as oval lesions in which the borders may be irregular. Other morphological features of melanoma include clinical asymmetry, variable color, diameter greater than 6 mm and evolving lesions. Two males whose melanoma in situ presented as linear skin lesions are described and cutaneous malignancies that may appear linear in morphology are summarized in this report. A medical literature search engine, PubMed, was used to search the following terms: cancer, cutaneous, in situ, linear, malignant, malignant melanoma, melanoma in situ, neoplasm, and skin. The 25 papers that were generated by the search and their references, were reviewed; 10 papers were selected for inclusion. The cancer of the skin typically presents as round lesions. However, basal cell carcinoma and squamous cell carcinoma may arise from primary skin conditions or benign skin neoplasms such as linear epidermal nevus and linear porokeratosis. In addition, linear tumors such as basal cell carcinoma can occur. The development of linear cutaneous neoplasms may occur secondary to skin tension line or embryonal growth patterns (as reflected by the lines of Langer and lines of Blaschko) or exogenous factors such as prior radiation therapy. Cutaneous neoplasms and specifically melanoma in situ can be added to the list of linear skin lesions.

Embedded Incremental Feature Selection for Reinforcement Learning

Science.gov (United States)

2012-05-01

Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature

Linear and non-linear interdependence of EEG and HRV frequency bands in human sleep.

Science.gov (United States)

Chaparro-Vargas, Ramiro; Dissanayaka, P Chamila; Patti, Chanakya Reddy; Schilling, Claudia; Schredl, Michael; Cvetkovic, Dean

2014-01-01

The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests upon 10 overnight polysomnographic (PSG) recordings, allowed the computation of wavelet coherence and phase locking values, in order to identify discerning features amongst the clinical healthy subjects. Our findings showed that neuronal oscillations θ, α and σ interact with cardiac power bands at mid-to-high rank of coherence and phase locking, particularly during NREM sleep stages.

Analysis of separation test for automatic brake adjuster based on linear radon transformation

Science.gov (United States)

Luo, Zai; Jiang, Wensong; Guo, Bin; Fan, Weijun; Lu, Yi

2015-01-01

The linear Radon transformation is applied to extract inflection points for online test system under the noise conditions. The linear Radon transformation has a strong ability of anti-noise and anti-interference by fitting the online test curve in several parts, which makes it easy to handle consecutive inflection points. We applied the linear Radon transformation to the separation test system to solve the separating clearance of automatic brake adjuster. The experimental results show that the feature point extraction error of the gradient maximum optimal method is approximately equal to ±0.100, while the feature point extraction error of linear Radon transformation method can reach to ±0.010, which has a lower error than the former one. In addition, the linear Radon transformation is robust.

Geomorphic features as indicators of climatic fluctuations in a periglacial environment, northern Sweden

Energy Technology Data Exchange (ETDEWEB)

Nyberg, R; Lindh, L [Lund Univ. (SE). Dept. of Physical Geography

1990-01-01

Goemorphic responses to climatic fluctuations in the periglacial mountain environment of northern Sweden, especially the Abisko mountains, are discussed. Although the frequency and magnitude of rapid mass movements are related to climatic conditions, the depositional patterns of the processes and the variable availability of source material complicate their use as climatic indicators. Possibly, debris flows and slushflows were frequent during the Little Ice Age, according to lichenometric dating of old deposits. Field observations suggest a fairly high frequency also during the last few decades. Boulder pavements, moraine-like ridges and glacial striae in front of major snowfields indicate these were previously larger and in some cases active as small glaciers perhaps in the cold beginning of the 1900's. During the warm 1920-30's snowpatches and glaciers, as well as permafrost mounds were affected by a general degeneration. Climatic inferences made from the mentioned features are still very crude. Tentatively, it is suggested that they are presently beginning to respond to the cooling trend affecting northern Scandinavia since about 1940. The anticipated impact of a greenhouse warming of the atmosphere has thus so far not been noticeable in this high latitude area. (authors).

ALPS: A Linear Program Solver

Science.gov (United States)

Ferencz, Donald C.; Viterna, Larry A.

1991-01-01

ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.

Linear Polarization Properties of Parsec-Scale AGN Jets

Directory of Open Access Journals (Sweden)

Alexander B. Pushkarev

2017-12-01

Full Text Available We used 15 GHz multi-epoch Very Long Baseline Array (VLBA polarization sensitive observations of 484 sources within a time interval 1996–2016 from the MOJAVE program, and also from the NRAO data archive. We have analyzed the linear polarization characteristics of the compact core features and regions downstream, and their changes along and across the parsec-scale active galactic nuclei (AGN jets. We detected a significant increase of fractional polarization with distance from the radio core along the jet as well as towards the jet edges. Compared to quasars, BL Lacs have a higher degree of polarization and exhibit more stable electric vector position angles (EVPAs in their core features and a better alignment of the EVPAs with the local jet direction. The latter is accompanied by a higher degree of linear polarization, suggesting that compact bright jet features might be strong transverse shocks, which enhance magnetic field regularity by compression.

Linear scleroderma following Blaschko′s lines

Directory of Open Access Journals (Sweden)

Mukhopadhyay Amiya

2005-01-01

Full Text Available Blaschko′s lines form a pattern, which many diseases are found to follow, but linear scleroderma following Blaschko′s lines is a controversial entity rarely reported in the literature. A 24-year-old man presented with multiple linear, atrophic, hyperpigmented lesions punctuated by areas of depigmentations on the left half of the trunk distributed on the anterior, lateral and posterior aspects. The lesions were distributed in a typical S-shaped line. Antinuclear antibody and antihistone antibody tests were negative. Histopathological examination of the skin from the affected area showed features suggestive of scleroderma. Here, we present a case of linear scleroderma following Blaschko′s lines in a male patient - an entity reported only three times so far.

Universal features of multiplicity distributions

International Nuclear Information System (INIS)

Balantekin, A.B.; Washington Univ., Seattle, WA

1994-01-01

Universal features of multiplicity distributions are studied and combinants, certain linear combinations of ratios of probabilities, are introduced. It is argued that they can be a useful tool in analyzing multiplicity distributions of hadrons emitted in high energy collisions and large scale structure of galaxy distributions

Acoustic features of objects matched by an echolocating bottlenose dolphin.

Science.gov (United States)

Delong, Caroline M; Au, Whitlow W L; Lemonds, David W; Harley, Heidi E; Roitblat, Herbert L

2006-03-01

The focus of this study was to investigate how dolphins use acoustic features in returning echolocation signals to discriminate among objects. An echolocating dolphin performed a match-to-sample task with objects that varied in size, shape, material, and texture. After the task was completed, the features of the object echoes were measured (e.g., target strength, peak frequency). The dolphin's error patterns were examined in conjunction with the between-object variation in acoustic features to identify the acoustic features that the dolphin used to discriminate among the objects. The present study explored two hypotheses regarding the way dolphins use acoustic information in echoes: (1) use of a single feature, or (2) use of a linear combination of multiple features. The results suggested that dolphins do not use a single feature across all object sets or a linear combination of six echo features. Five features appeared to be important to the dolphin on four or more sets: the echo spectrum shape, the pattern of changes in target strength and number of highlights as a function of object orientation, and peak and center frequency. These data suggest that dolphins use multiple features and integrate information across echoes from a range of object orientations.

Linear latent variable models: the lava-package

DEFF Research Database (Denmark)

Holst, Klaus Kähler; Budtz-Jørgensen, Esben

2013-01-01

are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...

Linear Basal Cell Carcinoma: A Case Report

Directory of Open Access Journals (Sweden)

Yuko Ichinokawa

2011-07-01

Full Text Available Basal cell carcinoma (BCC presents with diverse clinical features, and several morphologic and histologic variants of BCC have been reported [Sexton et al.: J Am Acad Dermatol 1990;23:1118–1126]. Linear BCC was first described as a new clinical subtype in 1985 by Lewis [Int J Dematol 1985;24:124–125]. Here, we present a case of linear BCC that we recently encountered in an elderly Japanese patient, and review other cases reported in Japan.

Topics in quaternion linear algebra

CERN Document Server

Rodman, Leiba

2014-01-01

Quaternions are a number system that has become increasingly useful for representing the rotations of objects in three-dimensional space and has important applications in theoretical and applied mathematics, physics, computer science, and engineering. This is the first book to provide a systematic, accessible, and self-contained exposition of quaternion linear algebra. It features previously unpublished research results with complete proofs and many open problems at various levels, as well as more than 200 exercises to facilitate use by students and instructors. Applications presented in the book include numerical ranges, invariant semidefinite subspaces, differential equations with symmetries, and matrix equations. Designed for researchers and students across a variety of disciplines, the book can be read by anyone with a background in linear algebra, rudimentary complex analysis, and some multivariable calculus. Instructors will find it useful as a complementary text for undergraduate linear algebra courses...

Asymptotic stability of linearly evolving non-stationary modes in a ...

Indian Academy of Sciences (India)

attention and it is believed to shed important light on the unresolved .... number assumption and is termed as the triple-deck theory. Having ... to analyse asymptotically the linear and weakly non-linear stability features of the station- ..... A numerical integration of equations (7–9) was implemented first to obtain the basic flow.

Linear programming mathematics, theory and algorithms

CERN Document Server

1996-01-01

Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.

Analysis of blood pressure signal in patients with different ventricular ejection fraction using linear and non-linear methods.

Science.gov (United States)

Arcentales, Andres; Rivera, Patricio; Caminal, Pere; Voss, Andreas; Bayes-Genis, Antonio; Giraldo, Beatriz F

2016-08-01

Changes in the left ventricle function produce alternans in the hemodynamic and electric behavior of the cardiovascular system. A total of 49 cardiomyopathy patients have been studied based on the blood pressure signal (BP), and were classified according to the left ventricular ejection fraction (LVEF) in low risk (LR: LVEF>35%, 17 patients) and high risk (HR: LVEF≤35, 32 patients) groups. We propose to characterize these patients using a linear and a nonlinear methods, based on the spectral estimation and the recurrence plot, respectively. From BP signal, we extracted each systolic time interval (STI), upward systolic slope (BPsl), and the difference between systolic and diastolic BP, defined as pulse pressure (PP). After, the best subset of parameters were obtained through the sequential feature selection (SFS) method. According to the results, the best classification was obtained using a combination of linear and nonlinear features from STI and PP parameters. For STI, the best combination was obtained considering the frequency peak and the diagonal structures of RP, with an area under the curve (AUC) of 79%. The same results were obtained when comparing PP values. Consequently, the use of combined linear and nonlinear parameters could improve the risk stratification of cardiomyopathy patients.

Fault diagnosis of rotating machine by isometric feature mapping

International Nuclear Information System (INIS)

Zhang, Yun; Li, Benwei; Wang, Lin; Wang, Wen; Wang, Zibin

2013-01-01

Principal component analysis (PCA) and linear discriminate analysis (LDA) are well-known linear dimensionality reductions for fault classification. However, since they are linear methods, they perform not well for high-dimensional data that has the nonlinear geometric structure. As kernel extension of PCA, Kernel PCA is used for nonlinear fault classification. However, the performance of Kernel PCA largely depends on its kernel function which can only be empirically selected from finite candidates. Thus, a novel rotating machine fault diagnosis approach based on geometrically motivated nonlinear dimensionality reduction named isometric feature mapping (Isomap) is proposed. The approach can effectively extract the intrinsic nonlinear manifold features embedded in high-dimensional fault data sets. Experimental results with rotor and rolling bearing data show that the proposed approach overcomes the flaw of conventional fault pattern recognition approaches and obviously improves the fault classification performance.

Linear gate with prescaled window

Energy Technology Data Exchange (ETDEWEB)

Koch, J; Bissem, H H; Krause, H; Scobel, W [Hamburg Univ. (Germany, F.R.). 1. Inst. fuer Experimentalphysik

1978-07-15

An electronic circuit is described that combines the features of a linear gate, a single channel analyzer and a prescaler. It allows selection of a pulse height region between two adjustable thresholds and scales the intensity of the spectrum within this window down by a factor 2sup(N) (0<=N<=9), whereas the complementary part of the spectrum is transmitted without being affected.

Breaking of ensembles of linear and nonlinear oscillators

International Nuclear Information System (INIS)

Buts, V.A.

2016-01-01

Some results concerning the study of the dynamics of ensembles of linear and nonlinear oscillators are stated. It is shown that, in general, a stable ensemble of linear oscillator has a limited number of oscillators. This number has been defined for some simple models. It is shown that the features of the dynamics of linear oscillators can be used for conversion of the low-frequency energy oscillations into high frequency oscillations. The dynamics of coupled nonlinear oscillators in most cases is chaotic. For such a case, it is shown that the statistical characteristics (moments) of chaotic motion can significantly reduce potential barriers that keep the particles in the capture region

International Conference on Trends and Perspectives in Linear Statistical Inference

CERN Document Server

Rosen, Dietrich

2018-01-01

This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference. .

A kernel-based multivariate feature selection method for microarray data classification.

Directory of Open Access Journals (Sweden)

Shiquan Sun

Full Text Available High dimensionality and small sample sizes, and their inherent risk of overfitting, pose great challenges for constructing efficient classifiers in microarray data classification. Therefore a feature selection technique should be conducted prior to data classification to enhance prediction performance. In general, filter methods can be considered as principal or auxiliary selection mechanism because of their simplicity, scalability, and low computational complexity. However, a series of trivial examples show that filter methods result in less accurate performance because they ignore the dependencies of features. Although few publications have devoted their attention to reveal the relationship of features by multivariate-based methods, these methods describe relationships among features only by linear methods. While simple linear combination relationship restrict the improvement in performance. In this paper, we used kernel method to discover inherent nonlinear correlations among features as well as between feature and target. Moreover, the number of orthogonal components was determined by kernel Fishers linear discriminant analysis (FLDA in a self-adaptive manner rather than by manual parameter settings. In order to reveal the effectiveness of our method we performed several experiments and compared the results between our method and other competitive multivariate-based features selectors. In our comparison, we used two classifiers (support vector machine, [Formula: see text]-nearest neighbor on two group datasets, namely two-class and multi-class datasets. Experimental results demonstrate that the performance of our method is better than others, especially on three hard-classify datasets, namely Wang's Breast Cancer, Gordon's Lung Adenocarcinoma and Pomeroy's Medulloblastoma.

Fall Detection Using Smartphone Audio Features.

Science.gov (United States)

Cheffena, Michael

2016-07-01

An automated fall detection system based on smartphone audio features is developed. The spectrogram, mel frequency cepstral coefficents (MFCCs), linear predictive coding (LPC), and matching pursuit (MP) features of different fall and no-fall sound events are extracted from experimental data. Based on the extracted audio features, four different machine learning classifiers: k-nearest neighbor classifier (k-NN), support vector machine (SVM), least squares method (LSM), and artificial neural network (ANN) are investigated for distinguishing between fall and no-fall events. For each audio feature, the performance of each classifier in terms of sensitivity, specificity, accuracy, and computational complexity is evaluated. The best performance is achieved using spectrogram features with ANN classifier with sensitivity, specificity, and accuracy all above 98%. The classifier also has acceptable computational requirement for training and testing. The system is applicable in home environments where the phone is placed in the vicinity of the user.

Features of the non-collinear one-phonon anomalous light scattering controlled by elastic waves with elevated linear losses: potentials for multi-frequency parallel spectrum analysis of radio-wave signals.

Science.gov (United States)

Shcherbakov, Alexandre S; Arellanes, Adan Omar

2017-12-01

During subsequent development of the recently proposed multi-frequency parallel spectrometer for precise spectrum analysis of wideband radio-wave signals, we study potentials of new acousto-optical cells exploiting selected crystalline materials at the limits of their capabilities. Characterizing these wide-aperture cells is non-trivial due to new features inherent in the chosen regime of an advanced non-collinear one-phonon anomalous light scattering by elastic waves with significantly elevated acoustic losses. These features can be observed simpler in uniaxial, tetragonal, and trigonal crystals possessing linear acoustic attenuation. We demonstrate that formerly studied additional degree of freedom, revealed initially for multi-phonon regimes of acousto-optical interaction, can be identified within the one-phonon geometry as well and exploited for designing new cells. We clarify the role of varying the central acoustic frequency and acoustic attenuation using the identified degree of freedom. Therewith, we are strongly restricted by a linear regime of acousto-optical interaction to avoid the origin of multi-phonon processes within carrying out a multi-frequency parallel spectrum analysis of radio-wave signals. Proof-of-principle experiments confirm the developed approaches and illustrate their applicability to innovative technique for an advanced spectrum analysis of wideband radio-wave signals with the improved resolution in an extended frequency range.

Feature Selection via Chaotic Antlion Optimization.

Directory of Open Access Journals (Sweden)

Hossam M Zawbaa

Full Text Available Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting while minimizing the number of features used.We propose an optimization approach for the feature selection problem that considers a "chaotic" version of the antlion optimizer method, a nature-inspired algorithm that mimics the hunting mechanism of antlions in nature. The balance between exploration of the search space and exploitation of the best solutions is a challenge in multi-objective optimization. The exploration/exploitation rate is controlled by the parameter I that limits the random walk range of the ants/prey. This variable is increased iteratively in a quasi-linear manner to decrease the exploration rate as the optimization progresses. The quasi-linear decrease in the variable I may lead to immature convergence in some cases and trapping in local minima in other cases. The chaotic system proposed here attempts to improve the tradeoff between exploration and exploitation. The methodology is evaluated using different chaotic maps on a number of feature selection datasets. To ensure generality, we used ten biological datasets, but we also used other types of data from various sources. The results are compared with the particle swarm optimizer and with genetic algorithm variants for feature selection using a set of quality metrics.

Breast image feature learning with adaptive deconvolutional networks

Science.gov (United States)

Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

2012-03-01

Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

Development of non-linear vibration analysis code for CANDU fuelling machine

International Nuclear Information System (INIS)

Murakami, Hajime; Hirai, Takeshi; Horikoshi, Kiyomi; Mizukoshi, Kaoru; Takenaka, Yasuo; Suzuki, Norio.

1988-01-01

This paper describes the development of a non-linear, dynamic analysis code for the CANDU 600 fuelling machine (F-M), which includes a number of non-linearities such as gap with or without Coulomb friction, special multi-linear spring connections, etc. The capabilities and features of the code and the mathematical treatment for the non-linearities are explained. The modeling and numerical methodology for the non-linearities employed in the code are verified experimentally. Finally, the simulation analyses for the full-scale F-M vibration testing are carried out, and the applicability of the code to such multi-degree of freedom systems as F-M is demonstrated. (author)

Evaluating EMG Feature and Classifier Selection for Application to Partial-Hand Prosthesis Control

Directory of Open Access Journals (Sweden)

Adenike A. Adewuyi

2016-10-01

Full Text Available Pattern recognition-based myoelectric control of upper limb prostheses has the potential to restore control of multiple degrees of freedom. Though this control method has been extensively studied in individuals with higher-level amputations, few studies have investigated its effectiveness for individuals with partial-hand amputations. Most partial-hand amputees retain a functional wrist and the ability of pattern recognition-based methods to correctly classify hand motions from different wrist positions is not well studied. In this study, focusing on partial-hand amputees, we evaluate (1 the performance of non-linear and linear pattern recognition algorithms and (2 the performance of optimal EMG feature subsets for classification of four hand motion classes in different wrist positions for 16 non-amputees and 4 amputees. Our results show that linear discriminant analysis and linear and non-linear artificial neural networks perform significantly better than the quadratic discriminant analysis for both non-amputees and partial-hand amputees. For amputees, including information from multiple wrist positions significantly decreased error (p<0.001 but no further significant decrease in error occurred when more than 4, 2, or 3 positions were included for the extrinsic (p=0.07, intrinsic (p=0.06, or combined extrinsic and intrinsic muscle EMG (p=0.08, respectively. Finally, we found that a feature set determined by selecting optimal features from each channel outperformed the commonly used time domain (p<0.001 and time domain/autoregressive feature sets (p<0.01. This method can be used as a screening filter to select the features from each channel that provide the best classification of hand postures across different wrist positions.

Linear mixed models for longitudinal data

CERN Document Server

Molenberghs, Geert

2000-01-01

This paperback edition is a reprint of the 2000 edition. This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commerc...

Synoptic evaluation of scale-dependent metrics for hydrographic line feature geometry

Science.gov (United States)

Stanislawski, Larry V.; Buttenfield, Barbara P.; Raposo, Paulo; Cameron, Madeline; Falgout, Jeff T.

2015-01-01

Methods of acquisition and feature simplification for vector feature data impact cartographic representations and scientific investigations of these data, and are therefore important considerations for geographic information science (Haunert and Sester 2008). After initial collection, linear features may be simplified to reduce excessive detail or to furnish a reduced-scale version of the features through cartographic generalization (Regnauld and McMaster 2008, Stanislawski et al. 2014). A variety of algorithms exist to simplify linear cartographic features, and all of the methods affect the positional accuracy of the features (Shahriari and Tao 2002, Regnauld and McMaster 2008, Stanislawski et al. 2012). In general, simplification operations are controlled by one or more tolerance parameters that limit the amount of positional change the operation can make to features. Using a single tolerance value can have varying levels of positional change on features; depending on local shape, texture, or geometric characteristics of the original features (McMaster and Shea 1992, Shahriari and Tao 2002, Buttenfield et al. 2010). Consequently, numerous researchers have advocated calibration of simplification parameters to control quantifiable properties of resulting changes to the features (Li and Openshaw 1990, Raposo 2013, Tobler 1988, Veregin 2000, and Buttenfield, 1986, 1989).This research identifies relations between local topographic conditions and geometric characteristics of linear features that are available in the National Hydrography Dataset (NHD). The NHD is a comprehensive vector dataset of surface 18 th ICA Workshop on Generalisation and Multiple Representation, Rio de Janiero, Brazil 2015 2 water features within the United States that is maintained by the U.S. Geological Survey (USGS). In this paper, geometric characteristics of cartographic representations for natural stream and river features are summarized for subbasin watersheds within entire regions of the

LINEAR2007, Linear-Linear Interpolation of ENDF Format Cross-Sections

International Nuclear Information System (INIS)

2007-01-01

1 - Description of program or function: LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form. Codes used subsequently need thus to consider only linear-linear data. IAEA1311/15: This version include the updates up to January 30, 2007. Changes in ENDF/B-VII Format and procedures, as well as the evaluations themselves, make it impossible for versions of the ENDF/B pre-processing codes earlier than PREPRO 2007 (2007 Version) to accurately process current ENDF/B-VII evaluations. The present code can handle all existing ENDF/B-VI evaluations through release 8, which will be the last release of ENDF/B-VI. Modifications from previous versions: - Linear VERS. 2007-1 (JAN. 2007): checked against all ENDF/B-VII; increased page size from 60,000 to 600,000 points 2 - Method of solution: Each section of data is considered separately. Each section of File 3, 23, and 27 data consists of a table of cross section versus energy with any of five interpolation laws. LINEAR will replace each section with a new table of energy versus cross section data in which the interpolation law is always linear in energy and cross section. The histogram (constant cross section between two energies) interpolation law is converted to linear-linear by substituting two points for each initial point. The linear-linear is not altered. For the log-linear, linear-log and log- log laws, the cross section data are converted to linear by an interval halving algorithm. Each interval is divided in half until the value at the middle of the interval can be approximated by linear-linear interpolation to within a given accuracy. The LINEAR program uses a multipoint fractional error thinning algorithm to minimize the size of each cross section table

Hybrid logic on linear structures: expressivity and complexity

NARCIS (Netherlands)

Franceschet, M.; de Rijke, M.; Schlingoff, B.-H.

2003-01-01

We investigate expressivity and complexity of hybrid logics on linear structures. Hybrid logics are an enrichment of modal logics with certain first-order features which are algorithmically well behaved. Therefore, they are well suited for the specification of certain properties of computational

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

Science.gov (United States)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

Feedback Systems for Linear Colliders

International Nuclear Information System (INIS)

1999-01-01

Feedback systems are essential for stable operation of a linear collider, providing a cost-effective method for relaxing tight tolerances. In the Stanford Linear Collider (SLC), feedback controls beam parameters such as trajectory, energy, and intensity throughout the accelerator. A novel dithering optimization system which adjusts final focus parameters to maximize luminosity contributed to achieving record performance in the 1997-98 run. Performance limitations of the steering feedback have been investigated, and improvements have been made. For the Next Linear Collider (NLC), extensive feedback systems are planned as an integral part of the design. Feedback requirements for JLC (the Japanese Linear Collider) are essentially identical to NLC; some of the TESLA requirements are similar but there are significant differences. For NLC, algorithms which incorporate improvements upon the SLC implementation are being prototyped. Specialized systems for the damping rings, rf and interaction point will operate at high bandwidth and fast response. To correct for the motion of individual bunches within a train, both feedforward and feedback systems are planned. SLC experience has shown that feedback systems are an invaluable operational tool for decoupling systems, allowing precision tuning, and providing pulse-to-pulse diagnostics. Feedback systems for the NLC will incorporate the key SLC features and the benefits of advancing technologies

Linear collider systems and costs

International Nuclear Information System (INIS)

Loew, G.A.

1993-05-01

The purpose of this paper is to examine some of the systems and sub-systems involved in so-called ''conventional'' e + e - linear colliders and to study how their design affects the overall cost of these machines. There are presently a total of at least six 500 GeV c. of m. linear collider projects under study in the world. Aside from TESLA (superconducting linac at 1.3 GHz) and CLIC (two-beam accelerator with main linac at 30GHz), the other four proposed e + e - linear colliders can be considered ''conventional'' in that their main linacs use the proven technique of driving room temperature accelerator sections with pulsed klystrons and modulators. The centrally distinguishing feature between these projects is their main linac rf frequency: 3 GHz for the DESY machine, 11.424 GHz for the SLAC and JLC machines, and 14 GHz for the VLEPP machine. The other systems, namely the electron and positron sources, preaccelerators, compressors, damping rings and final foci, are fairly similar from project to project. Probably more than 80% of the cost of these linear colliders will be incurred in the two main linacs facing each other and it is therefore in their design and construction that major savings or extra costs may be found

Orthogonal sparse linear discriminant analysis

Science.gov (United States)

Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

2018-03-01

Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.

The morphing of geographical features by Fourier transformation.

Science.gov (United States)

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

Evidence for Multiple Late Quaternary Glaciations in the Southernmost Cordillera Blanca, Peru

Science.gov (United States)

Smith, J. A.; Rodbell, D. T.; Ramage, J. M.

2007-12-01

Surface-exposure dating with in-situ-produced cosmogenic isotopes has provided the basis for a growing framework of glacial chronologies in the tropical Andes. In the Peruvian Andes, long chronologies (>400 ka) with relatively small local last glacial maximum (LLGM) advances have been reported for the central Cordillera Blanca (ca. 9°30'S) and Junin Plain (11°00'S), whereas preliminary data suggest a shorter record (<40 ka) in the intervening Cordillera Huayhuash (10°15'S). These seemingly contradictory findings raise several questions: Was the LLGM a relatively minor event in the Peruvian Andes, far exceeded by bigger, older advances? Which combination of geographic and geomorphic factors increases the likelihood that evidence of older advances will be preserved? With these questions in mind, we sought a site with both high peaks and a high-altitude plateau. The glaciated Nevado Jeulla Rajo massif (10°00'S, 77°16'W, peaks ca. 5600 masl) marks the southern end of the Cordillera Blanca and the Callejon de Huaylas valley in the central Peruvian Andes. The Conococha Plain (ca. 4050 masl) borders the western side of the massif. Large lateral moraines extend onto the Conococha Plain from the west-facing valleys and multiple moraine loops lie upvalley, closer to active ice margins. Surface-exposure dating (10Be) indicates that the largest lateral moraines from Jeullesh Valley are compound features deposited during the LLGM (ca. 30 ka) and a late-glacial readvance (ca. 16 ka). The LLGM/late-glacial moraines cross-cut an older pair of lateral moraines (ca. 70 ka) that may provide evidence for a smaller advance during marine isotope stage 4. Although the LLGM/late-glacial moraines are impressively large (ca. 150 m high), they do not represent the maximum ice extent in the region. Fluvial outwash deposits beyond the termini of the moraines on the Conococha Plain are underlain by lodgement till that is up to 20 m thick and extends ca. 6 km across the width of the Plain

Inflammatory linear verrucous epidermal naevus: Report of three ...

African Journals Online (AJOL)

Background: Epidermal naevi are congenital harmatomas that arise from embryonal ectodermal cells. The inflammatory linear verrucous variant is rare and presents with disturbing symptoms. In blacks the classical erythema is not common but pruritus and discharge are the commonest features. Methods and results: We ...

Distributed Monitoring of the R2 Statistic for Linear Regression

Data.gov (United States)

National Aeronautics and Space Administration — The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and...

Linearized motion estimation for articulated planes.

Science.gov (United States)

Datta, Ankur; Sheikh, Yaser; Kanade, Takeo

2011-04-01

In this paper, we describe the explicit application of articulation constraints for estimating the motion of a system of articulated planes. We relate articulations to the relative homography between planes and show that these articulations translate into linearized equality constraints on a linear least-squares system, which can be solved efficiently using a Karush-Kuhn-Tucker system. The articulation constraints can be applied for both gradient-based and feature-based motion estimation algorithms and to illustrate this, we describe a gradient-based motion estimation algorithm for an affine camera and a feature-based motion estimation algorithm for a projective camera that explicitly enforces articulation constraints. We show that explicit application of articulation constraints leads to numerically stable estimates of motion. The simultaneous computation of motion estimates for all of the articulated planes in a scene allows us to handle scene areas where there is limited texture information and areas that leave the field of view. Our results demonstrate the wide applicability of the algorithm in a variety of challenging real-world cases such as human body tracking, motion estimation of rigid, piecewise planar scenes, and motion estimation of triangulated meshes.

Linearization Method and Linear Complexity

Science.gov (United States)

Tanaka, Hidema

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N(≅2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

Approximate Method for Solving the Linear Fuzzy Delay Differential Equations

Directory of Open Access Journals (Sweden)

S. Narayanamoorthy

2015-01-01

Full Text Available We propose an algorithm of the approximate method to solve linear fuzzy delay differential equations using Adomian decomposition method. The detailed algorithm of the approach is provided. The approximate solution is compared with the exact solution to confirm the validity and efficiency of the method to handle linear fuzzy delay differential equation. To show this proper features of this proposed method, numerical example is illustrated.

Sparse non-linear denoising: Generalization performance and pattern reproducibility in functional MRI

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2011-01-01

We investigate sparse non-linear denoising of functional brain images by kernel Principal Component Analysis (kernel PCA). The main challenge is the mapping of denoised feature space points back into input space, also referred to as ”the pre-image problem”. Since the feature space mapping is typi...

Ice stream behaviour and deglaciation of the Scandinavian Ice Sheet in the Kuittijärvi area, Russian Karelia

Directory of Open Access Journals (Sweden)

Juha-Pekka Lunkka

2008-01-01

Full Text Available Glacial landforms of the Lake Kuittijärvi area, Russian Karelia, which covers an area of more than 7000 km^2, were studied in detail using aerial photography and satellite imagery methods and on-site field observations. This was done to reconstruct a detailed historyof Scandinavian ice sheet behaviour in the Lake Kuittijärvi area. The results indicate that the Lake Tuoppajärvi sub-ice stream (TIS that formed the northern part of the Kuusamo-White Sea ice stream and the Lake Kuittijärvi sub-ice stream (KIS, which was part of theNorthern Karelian ice stream, operated in the area during the last deglaciation. Subglacially formed lineation patterns associated with other indicative landforms such as end moraines and esker ridges indicate a clear age relationship between the ice streams’ activity and that the KIS was active after the linear landforms were created by the TIS. It is estimated that deglaciation of the TIS from the Kalevala end moraine to the Lake Pääjärvi end moraine took place between ca. 11 300 – 10 900 calendar years ago. It seems that the terminus of the KIS marker by the Kalevala end moraine was also formed around 11 300 calendar years ago but the KIS remained active longer than the TIS. Both of these sub-ice streams terminated into a glacial lake that was part of a larger White Sea Basin ice lake.

Use of probabilistic weights to enhance linear regression myoelectric control

Science.gov (United States)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-12-01

Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

The Stanford Linear Collider

International Nuclear Information System (INIS)

Emma, P.

1995-01-01

The Stanford Linear Collider (SLC) is the first and only high-energy e + e - linear collider in the world. Its most remarkable features are high intensity, submicron sized, polarized (e - ) beams at a single interaction point. The main challenges posed by these unique characteristics include machine-wide emittance preservation, consistent high intensity operation, polarized electron production and transport, and the achievement of a high degree of beam stability on all time scales. In addition to serving as an important machine for the study of Z 0 boson production and decay using polarized beams, the SLC is also an indispensable source of hands-on experience for future linear colliders. Each new year of operation has been highlighted with a marked improvement in performance. The most significant improvements for the 1994-95 run include new low impedance vacuum chambers for the damping rings, an upgrade to the optics and diagnostics of the final focus systems, and a higher degree of polarization from the electron source. As a result, the average luminosity has nearly doubled over the previous year with peaks approaching 10 30 cm -2 s -1 and an 80% electron polarization at the interaction point. These developments as well as the remaining identifiable performance limitations will be discussed

Present SLAC accelerator computer control system features

International Nuclear Information System (INIS)

Davidson, V.; Johnson, R.

1981-02-01

The current functional organization and state of software development of the computer control system of the Stanford Linear Accelerator is described. Included is a discussion of the distribution of functions throughout the system, the local controller features, and currently implemented features of the touch panel portion of the system. The functional use of our triplex of PDP11-34 computers sharing common memory is described. Also included is a description of the use of pseudopanel tables as data tables for closed loop control functions

EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.

Science.gov (United States)

Jarvis, John J.; And Others

Designed for student use in solving linear programming problems, the interactive computer program described (EZLP) permits the student to input the linear programming model in exactly the same manner in which it would be written on paper. This report includes a brief review of the development of EZLP; narrative descriptions of program features,…

Global numerical modeling of magnetized plasma in a linear device

DEFF Research Database (Denmark)

Magnussen, Michael Løiten

Understanding the turbulent transport in the plasma-edge in fusion devices is of utmost importance in order to make precise predictions for future fusion devices. The plasma turbulence observed in linear devices shares many important features with the turbulence observed in the edge of fusion dev...... with simulations performed at different ionization levels, using a simple model for plasma interaction with neutrals. It is found that the steady state and the saturated state of the system bifurcates when the neutral interaction dominates the electron-ion collisions.......Understanding the turbulent transport in the plasma-edge in fusion devices is of utmost importance in order to make precise predictions for future fusion devices. The plasma turbulence observed in linear devices shares many important features with the turbulence observed in the edge of fusion...... devices, and are easier to diagnose due to lower temperatures and a better access to the plasma. In order to gain greater insight into this complex turbulent behavior, numerical simulations of plasma in a linear device are performed in this thesis. Here, a three-dimensional drift-fluid model is derived...

A Type System for the Vectorial Aspect of the Linear-Algebraic Lambda-Calculus

Directory of Open Access Journals (Sweden)

Pablo Arrighi

2012-07-01

Full Text Available We describe a type system for the linear-algebraic lambda-calculus. The type system accounts for the part of the language emulating linear operators and vectors, i.e. it is able to statically describe the linear combinations of terms resulting from the reduction of programs. This gives rise to an original type theory where types, in the same way as terms, can be superposed into linear combinations. We show that the resulting typed lambda-calculus is strongly normalizing and features a weak subject-reduction.

How linear features alter predator movement and the functional response.

KAUST Repository

McKenzie, Hannah W

2012-01-18

In areas of oil and gas exploration, seismic lines have been reported to alter the movement patterns of wolves (Canis lupus). We developed a mechanistic first passage time model, based on an anisotropic elliptic partial differential equation, and used this to explore how wolf movement responses to seismic lines influence the encounter rate of the wolves with their prey. The model was parametrized using 5 min GPS location data. These data showed that wolves travelled faster on seismic lines and had a higher probability of staying on a seismic line once they were on it. We simulated wolf movement on a range of seismic line densities and drew implications for the rate of predator-prey interactions as described by the functional response. The functional response exhibited a more than linear increase with respect to prey density (type III) as well as interactions with seismic line density. Encounter rates were significantly higher in landscapes with high seismic line density and were most pronounced at low prey densities. This suggests that prey at low population densities are at higher risk in environments with a high seismic line density unless they learn to avoid them.

How linear features alter predator movement and the functional response.

KAUST Repository

McKenzie, Hannah W; Merrill, Evelyn H; Spiteri, Raymond J; Lewis, Mark A

2012-01-01

In areas of oil and gas exploration, seismic lines have been reported to alter the movement patterns of wolves (Canis lupus). We developed a mechanistic first passage time model, based on an anisotropic elliptic partial differential equation, and used this to explore how wolf movement responses to seismic lines influence the encounter rate of the wolves with their prey. The model was parametrized using 5 min GPS location data. These data showed that wolves travelled faster on seismic lines and had a higher probability of staying on a seismic line once they were on it. We simulated wolf movement on a range of seismic line densities and drew implications for the rate of predator-prey interactions as described by the functional response. The functional response exhibited a more than linear increase with respect to prey density (type III) as well as interactions with seismic line density. Encounter rates were significantly higher in landscapes with high seismic line density and were most pronounced at low prey densities. This suggests that prey at low population densities are at higher risk in environments with a high seismic line density unless they learn to avoid them.

High-order quantum algorithm for solving linear differential equations

International Nuclear Information System (INIS)

Berry, Dominic W

2014-01-01

Linear differential equations are ubiquitous in science and engineering. Quantum computers can simulate quantum systems, which are described by a restricted type of linear differential equations. Here we extend quantum simulation algorithms to general inhomogeneous sparse linear differential equations, which describe many classical physical systems. We examine the use of high-order methods (where the error over a time step is a high power of the size of the time step) to improve the efficiency. These provide scaling close to Δt 2 in the evolution time Δt. As with other algorithms of this type, the solution is encoded in amplitudes of the quantum state, and it is possible to extract global features of the solution. (paper)

Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

Science.gov (United States)

Ying, Xiaoguo; Lin, Han; Hui, Guohua

2015-01-01

Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

Gait recognition using kinect and locally linear embedding ...

African Journals Online (AJOL)

This paper presents the use of locally linear embedding (LLE) as feature extraction technique for classifying a person's identity based on their walking gait patterns. Skeleton data acquired from Microsoft Kinect camera were used as an input for (1). Multilayer Perceptron (MLP) and (2). LLE with MLP. The MLP classification ...

Grammar-based feature generation for time-series prediction

CERN Document Server

De Silva, Anthony Mihirana

2015-01-01

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...

Stormwater Infrastructure and other features - Linear Features

Data.gov (United States)

Vermont Center for Geographic Information — This data was collected and compiled for various towns in watersheds (currently including the Missisquoi Basin, Winooski Basin, Connecticut River Basin, Lamoille...

Linear and non-linear dose-response functions reveal a hormetic relationship between stress and learning.

Science.gov (United States)

Zoladz, Phillip R; Diamond, David M

2008-10-16

Over a century of behavioral research has shown that stress can enhance or impair learning and memory. In the present review, we have explored the complex effects of stress on cognition and propose that they are characterized by linear and non-linear dose-response functions, which together reveal a hormetic relationship between stress and learning. We suggest that stress initially enhances hippocampal function, resulting from amygdala-induced excitation of hippocampal synaptic plasticity, as well as the excitatory effects of several neuromodulators, including corticosteroids, norepinephrine, corticotropin-releasing hormone, acetylcholine and dopamine. We propose that this rapid activation of the amygdala-hippocampus brain memory system results in a linear dose-response relation between emotional strength and memory formation. More prolonged stress, however, leads to an inhibition of hippocampal function, which can be attributed to compensatory cellular responses that protect hippocampal neurons from excitotoxicity. This inhibition of hippocampal functioning in response to prolonged stress is potentially relevant to the well-described curvilinear dose-response relationship between arousal and memory. Our emphasis on the temporal features of stress-brain interactions addresses how stress can activate, as well as impair, hippocampal functioning to produce a hormetic relationship between stress and learning.

Partially Flipped Linear Algebra: A Team-Based Approach

Science.gov (United States)

Carney, Debra; Ormes, Nicholas; Swanson, Rebecca

2015-01-01

In this article we describe a partially flipped Introductory Linear Algebra course developed by three faculty members at two different universities. We give motivation for our partially flipped design and describe our implementation in detail. Two main features of our course design are team-developed preview videos and related in-class activities.…

Feature-based Alignment of Volumetric Multi-modal Images

Science.gov (United States)

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Measurements of Rayleigh-Taylor-Induced Magnetic Fields in the Linear and Non-linear Regimes

Science.gov (United States)

Manuel, Mario

2012-10-01

Magnetic fields are generated in plasmas by the Biermann-battery, or thermoelectric, source driven by non-collinear temperature and density gradients. The ablation front in laser-irradiated targets is susceptible to Rayleigh-Taylor (RT) growth that produces gradients capable of generating magnetic fields. Measurements of these RT-induced magnetic fields in planar foils have been made using a combination of x-ray and monoenergetic-proton radiography techniques. At a perturbation wavelength of 120 μm, proton radiographs indicate an increase of the magnetic-field strength from ˜1 to ˜10 Tesla during the linear growth phase. A characteristic change in field structure was observed later in time for irradiated foils of different initial surface perturbations. Proton radiographs show a regular cellular configuration initiated at the same time during the drive, independent of the initial foil conditions. This non-linear behavior has been experimentally investigated and the source of these characteristic features will be discussed.

Decision time horizon for music genre classification using short time features

DEFF Research Database (Denmark)

Ahrendt, Peter; Meng, Anders; Larsen, Jan

2004-01-01

In this paper music genre classification has been explored with special emphasis on the decision time horizon and ranking of tapped-delay-line short-time features. Late information fusion as e.g. majority voting is compared with techniques of early information fusion such as dynamic PCA (DPCA......). The most frequently suggested features in the literature were employed including mel-frequency cepstral coefficients (MFCC), linear prediction coefficients (LPC), zero-crossing rate (ZCR), and MPEG-7 features. To rank the importance of the short time features consensus sensitivity analysis is applied...

Boosting Discriminant Learners for Gait Recognition Using MPCA Features

Directory of Open Access Journals (Sweden)

Haiping Lu

2009-01-01

Full Text Available This paper proposes a boosted linear discriminant analysis (LDA solution on features extracted by the multilinear principal component analysis (MPCA to enhance gait recognition performance. Three-dimensional gait objects are projected in the MPCA space first to obtain low-dimensional tensorial features. Then, lower-dimensional vectorial features are obtained through discriminative feature selection. These feature vectors are then fed into an LDA-style booster, where several regularized and weakened LDA learners work together to produce a strong learner through a novel feature weighting and sampling process. The LDA learner employs a simple nearest-neighbor classifier with a weighted angle distance measure for classification. The experimental results on the NIST/USF “Gait Challenge” data-sets show that the proposed solution has successfully improved the gait recognition performance and outperformed several state-of-the-art gait recognition algorithms.

A consistency-based feature selection method allied with linear SVMs for HIV-1 protease cleavage site prediction.

Directory of Open Access Journals (Sweden)

Orkun Oztürk

Full Text Available BACKGROUND: Predicting type-1 Human Immunodeficiency Virus (HIV-1 protease cleavage site in protein molecules and determining its specificity is an important task which has attracted considerable attention in the research community. Achievements in this area are expected to result in effective drug design (especially for HIV-1 protease inhibitors against this life-threatening virus. However, some drawbacks (like the shortage of the available training data and the high dimensionality of the feature space turn this task into a difficult classification problem. Thus, various machine learning techniques, and specifically several classification methods have been proposed in order to increase the accuracy of the classification model. In addition, for several classification problems, which are characterized by having few samples and many features, selecting the most relevant features is a major factor for increasing classification accuracy. RESULTS: We propose for HIV-1 data a consistency-based feature selection approach in conjunction with recursive feature elimination of support vector machines (SVMs. We used various classifiers for evaluating the results obtained from the feature selection process. We further demonstrated the effectiveness of our proposed method by comparing it with a state-of-the-art feature selection method applied on HIV-1 data, and we evaluated the reported results based on attributes which have been selected from different combinations. CONCLUSION: Applying feature selection on training data before realizing the classification task seems to be a reasonable data-mining process when working with types of data similar to HIV-1. On HIV-1 data, some feature selection or extraction operations in conjunction with different classifiers have been tested and noteworthy outcomes have been reported. These facts motivate for the work presented in this paper. SOFTWARE AVAILABILITY: The software is available at http

Linear Algebra and Smarandache Linear Algebra

OpenAIRE

Vasantha, Kandasamy

2003-01-01

The present book, on Smarandache linear algebra, not only studies the Smarandache analogues of linear algebra and its applications, it also aims to bridge the need for new research topics pertaining to linear algebra, purely in the algebraic sense. We have introduced Smarandache semilinear algebra, Smarandache bilinear algebra and Smarandache anti-linear algebra and their fuzzy equivalents. Moreover, in this book, we have brought out the study of linear algebra and vector spaces over finite p...

Lakes near the glacier Maliy Azau on the Elbrus (Central Caucasus: dynamics and outbursts

Directory of Open Access Journals (Sweden)

M. D. Dokukin

2016-01-01

Full Text Available The lake dynamics and the current state of them were analyzed on the basis of interpretation of aerial and satellite images of different years together with results of field surveys. Areas of six lakes existing in different years near the Maliy Azau Glacier had been determined. On August 22, 2011, the maximum area of one of the lakes was equal to 25.5 thousand m2. The first outburst was caused by the landslide deformations of the moraine massif forming a part of the lake basin, while the second one was a result of degradation of the lake ice dam and the water overflow on top of it. The present‑day lake dams (terminal‑moraine ramparts and medial moraine ridges are the result of the Maliy Azau Glacier advance in 1990s. The revealed feature of the lake dynamics on the mountain Elbrus was a drop of the water level and corresponding decrease of the lake areas in winter that was related to existence of the groundwater runoff into fractured volcanic rocks. At present, moraine dams of lakes and areas of the surface water runoff from the lakes are in stable condition due to which there is no threat of a lake outburst. However, the potential threat of outburst still remains because of high seismicity and possible volcanic activity in this region.

Robust Features Of Surface Electromyography Signal

Science.gov (United States)

Sabri, M. I.; Miskon, M. F.; Yaacob, M. R.

2013-12-01

Nowadays, application of robotics in human life has been explored widely. Robotics exoskeleton system are one of drastically areas in recent robotic research that shows mimic impact in human life. These system have been developed significantly to be used for human power augmentation, robotics rehabilitation, human power assist, and haptic interaction in virtual reality. This paper focus on solving challenges in problem using neural signals and extracting human intent. Commonly, surface electromyography signal (sEMG) are used in order to control human intent for application exoskeleton robot. But the problem lies on difficulty of pattern recognition of the sEMG features due to high noises which are electrode and cable motion artifact, electrode noise, dermic noise, alternating current power line interface, and other noise came from electronic instrument. The main objective in this paper is to study the best features of electromyography in term of time domain (statistical analysis) and frequency domain (Fast Fourier Transform).The secondary objectives is to map the relationship between torque and best features of muscle unit activation potential (MaxPS and RMS) of biceps brachii. This project scope use primary data of 2 male sample subject which using same dominant hand (right handed), age between 20-27 years old, muscle diameter 32cm to 35cm and using single channel muscle (biceps brachii muscle). The experiment conduct 2 times repeated task of contraction and relaxation of biceps brachii when lifting different load from no load to 3kg with ascending 1kg The result shows that Fast Fourier Transform maximum power spectrum (MaxPS) has less error than mean value of reading compare to root mean square (RMS) value. Thus, Fast Fourier Transform maximum power spectrum (MaxPS) show the linear relationship against torque experience by elbow joint to lift different load. As the conclusion, the best features is MaxPS because it has the lowest error than other features and show

Robust Features Of Surface Electromyography Signal

International Nuclear Information System (INIS)

Sabri, M I; Miskon, M F; Yaacob, M R

2013-01-01

Nowadays, application of robotics in human life has been explored widely. Robotics exoskeleton system are one of drastically areas in recent robotic research that shows mimic impact in human life. These system have been developed significantly to be used for human power augmentation, robotics rehabilitation, human power assist, and haptic interaction in virtual reality. This paper focus on solving challenges in problem using neural signals and extracting human intent. Commonly, surface electromyography signal (sEMG) are used in order to control human intent for application exoskeleton robot. But the problem lies on difficulty of pattern recognition of the sEMG features due to high noises which are electrode and cable motion artifact, electrode noise, dermic noise, alternating current power line interface, and other noise came from electronic instrument. The main objective in this paper is to study the best features of electromyography in term of time domain (statistical analysis) and frequency domain (Fast Fourier Transform).The secondary objectives is to map the relationship between torque and best features of muscle unit activation potential (MaxPS and RMS) of biceps brachii. This project scope use primary data of 2 male sample subject which using same dominant hand (right handed), age between 20–27 years old, muscle diameter 32cm to 35cm and using single channel muscle (biceps brachii muscle). The experiment conduct 2 times repeated task of contraction and relaxation of biceps brachii when lifting different load from no load to 3kg with ascending 1kg The result shows that Fast Fourier Transform maximum power spectrum (MaxPS) has less error than mean value of reading compare to root mean square (RMS) value. Thus, Fast Fourier Transform maximum power spectrum (MaxPS) show the linear relationship against torque experience by elbow joint to lift different load. As the conclusion, the best features is MaxPS because it has the lowest error than other features and

An efficient approach for differentiating Alzheimer's disease from normal elderly based on multicenter MRI using gray-level invariant features.

Directory of Open Access Journals (Sweden)

Muwei Li

Full Text Available Machine learning techniques, along with imaging markers extracted from structural magnetic resonance images, have been shown to increase the accuracy to differentiate patients with Alzheimer's disease (AD from normal elderly controls. Several forms of anatomical features, such as cortical volume, shape, and thickness, have demonstrated discriminative capability. These approaches rely on accurate non-linear image transformation, which could invite several nuisance factors, such as dependency on transformation parameters and the degree of anatomical abnormality, and an unpredictable influence of residual registration errors. In this study, we tested a simple method to extract disease-related anatomical features, which is suitable for initial stratification of the heterogeneous patient populations often encountered in clinical data. The method employed gray-level invariant features, which were extracted from linearly transformed images, to characterize AD-specific anatomical features. The intensity information from a disease-specific spatial masking, which was linearly registered to each patient, was used to capture the anatomical features. We implemented a two-step feature selection for anatomic recognition. First, a statistic-based feature selection was implemented to extract AD-related anatomical features while excluding non-significant features. Then, seven knowledge-based ROIs were used to capture the local discriminative powers of selected voxels within areas that were sensitive to AD or mild cognitive impairment (MCI. The discriminative capability of the proposed feature was measured by its performance in differentiating AD or MCI from normal elderly controls (NC using a support vector machine. The statistic-based feature selection, together with the knowledge-based masks, provided a promising solution for capturing anatomical features of the brain efficiently. For the analysis of clinical populations, which are inherently heterogeneous

On the Convergence of Piecewise Linear Strategic Interaction Dynamics on Networks

KAUST Repository

Gharesifard, Bahman; Touri, Behrouz; Basar, Tamer; Shamma, Jeff S.

2015-01-01

We prove that the piecewise linear best-response dynamical systems of strategic interactions are asymptotically convergent to their set of equilibria on any weighted undirected graph. We study various features of these dynamical systems, including

The Computer Program LIAR for Beam Dynamics Calculations in Linear Accelerators

International Nuclear Information System (INIS)

Assmann, R.W.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.H.; Thompson, K.

2011-01-01

Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. We present a new program LIAR ('LInear Accelerator Research code') that includes wakefield effects, a 6D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. The program is available for UNIX workstations and Windows PC's. It can be applied to a broad range of accelerators. We present examples of simulations for SLC and NLC.

Nowhere to hide: Effects of linear features on predator-prey dynamics in a large mammal system.

Science.gov (United States)

DeMars, Craig A; Boutin, Stan

2018-01-01

Rapid landscape alteration associated with human activity is currently challenging the evolved dynamical stability of many predator-prey systems by forcing species to behaviourally respond to novel environmental stimuli. In many forested systems, linear features (LFs) such as roads, pipelines and resource exploration lines (i.e. seismic lines) are a ubiquitous form of landscape alteration that have been implicated in altering predator-prey dynamics. One hypothesized effect is that LFs facilitate predator movement into and within prey refugia, thereby increasing predator-prey spatial overlap. We evaluated this hypothesis in a large mammal system, focusing on the interactions between boreal woodland caribou (Rangifer tarandus caribou) and their two main predators, wolves (Canis lupus) and black bears (Ursus americanus), during the calving season of caribou. In this system, LFs extend into and occur within peatlands (i.e. bogs and nutrient-poor fens), a habitat type highly used by caribou due to its refugia effects. Using resource selection analyses, we found that LFs increased predator selection of peatlands. Female caribou appeared to respond by avoiding LFs and areas with high LF density. However, in our study area, most caribou cannot completely avoid exposure to LFs and variation in female response had demographic effects. In particular, increasing proportional use of LFs by females negatively impacted survival of their neonate calves. Collectively, these results demonstrate how LFs can reduce the efficacy of prey refugia. Mitigating such effects will require limiting or restoring LFs within prey refugia, although the effectiveness of mitigation efforts will depend upon spatial scale, which in turn will be influenced by the life-history traits of predator and prey. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Unification of three linear models for the transient visual system

NARCIS (Netherlands)

Brinker, den A.C.

1989-01-01

Three different linear filters are considered as a model describing the experimentally determined triphasic impulse responses of discs. These impulse responses arc associated with the transient visual system. Each model reveals a different feature of the system. Unification of the models is

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

Science.gov (United States)

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

Laboratory beam-plasma interactions linear and nonlinear

International Nuclear Information System (INIS)

Christiansen, P.J.; Bond, J.W.; Jain, V.K.

1982-01-01

This chapter attempts to demonstrate that despite unavoidable scaling limitations, laboratory experiments can uncover details of beam plasma interaction processes which could never be revealed through space plasma physics. Topics covered include linear theory, low frequency couplings, indirect effects, nonlinear effects, quasi-linear effects, trapping effects, nonlinear wave-wave interactions, and self modulation and cavitation. Unstable electrostatic waves arising from an exchange of energy with the ''free energy'' beam features are considered as kinetic and as hydrodynamic, or fluid, instabilities. The consequences of such instabilities (e.g. when the waves have grown to a finite level) are examined and some studies are reviewed which have attempted to understand how the free energy originally available in the beam is redistributed to produce a final state of equilibrium turbulence

Low-Dimensional Feature Representation for Instrument Identification

Science.gov (United States)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

The use of multibeam backscatter intensity data as a tool for mapping glacial deposits in the Central North Sea, UK

Science.gov (United States)

Stewart, Heather; Bradwell, Tom

2014-05-01

gravelly sands and sandy gravels compared to the surrounding sandy and muddy sediments. Moraines are indicated as areas of high backscatter intensity and comprise coarse grained sediments. A range of moraine sizes have been identified from large scale moraines reflecting both frontal still stands or re-advances of the ice-sheet margin, de geer moraines and smaller moraines that may represent annual variations. Meltwater channels and tunnel valleys are revealed as areas of low backscatter intensity reflecting post-glacial soft sediment infill of the depressions incised into coarser grained and higher strength glacial deposits by these features.

Linear algebra and matrices topics for a second course

CERN Document Server

Shapiro, Helene

2015-01-01

Linear algebra and matrix theory are fundamental tools for almost every area of mathematics, both pure and applied. This book combines coverage of core topics with an introduction to some areas in which linear algebra plays a key role, for example, block designs, directed graphs, error correcting codes, and linear dynamical systems. Notable features include a discussion of the Weyr characteristic and Weyr canonical forms, and their relationship to the better-known Jordan canonical form; the use of block cyclic matrices and directed graphs to prove Frobenius's theorem on the structure of the eigenvalues of a nonnegative, irreducible matrix; and the inclusion of such combinatorial topics as BIBDs, Hadamard matrices, and strongly regular graphs. Also included are McCoy's theorem about matrices with property P, the Bruck-Ryser-Chowla theorem on the existence of block designs, and an introduction to Markov chains. This book is intended for those who are familiar with the linear algebra covered in a typical first c...

Essential linear algebra with applications a problem-solving approach

CERN Document Server

Andreescu, Titu

2014-01-01

This textbook provides a rigorous introduction to linear algebra in addition to material suitable for a more advanced course while emphasizing the subject’s interactions with other topics in mathematics such as calculus and geometry. A problem-based approach is used to develop the theoretical foundations of vector spaces, linear equations, matrix algebra, eigenvectors, and orthogonality. Key features include: • a thorough presentation of the main results in linear algebra along with numerous examples to illustrate the theory;  • over 500 problems (half with complete solutions) carefully selected for their elegance and theoretical significance; • an interleaved discussion of geometry and linear algebra, giving readers a solid understanding of both topics and the relationship between them.   Numerous exercises and well-chosen examples make this text suitable for advanced courses at the junior or senior levels. It can also serve as a source of supplementary problems for a sophomore-level course.    ...

Neighbors Based Discriminative Feature Difference Learning for Kinship Verification

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a discriminative feature difference learning method for facial image based kinship verification. To transform feature difference of an image pair to be discriminative for kinship verification, a linear transformation matrix for feature difference between an image pair...... than the commonly used feature concatenation, leading to a low complexity. Furthermore, there is no positive semi-definitive constrain on the transformation matrix while there is in metric learning methods, leading to an easy solution for the transformation matrix. Experimental results on two public...... databases show that the proposed method combined with a SVM classification method outperforms or is comparable to state-of-the-art kinship verification methods. © Springer International Publishing AG, Part of Springer Science+Business Media...

Feature curve extraction from point clouds via developable strip intersection

Directory of Open Access Journals (Sweden)

Kai Wah Lee

2016-04-01

Full Text Available In this paper, we study the problem of computing smooth feature curves from CAD type point clouds models. The proposed method reconstructs feature curves from the intersections of developable strip pairs which approximate the regions along both sides of the features. The generation of developable surfaces is based on a linear approximation of the given point cloud through a variational shape approximation approach. A line segment sequencing algorithm is proposed for collecting feature line segments into different feature sequences as well as sequential groups of data points. A developable surface approximation procedure is employed to refine incident approximation planes of data points into developable strips. Some experimental results are included to demonstrate the performance of the proposed method.

Linear Power-Flow Models in Multiphase Distribution Networks: Preprint

Energy Technology Data Exchange (ETDEWEB)

Bernstein, Andrey; Dall' Anese, Emiliano

2017-05-26

This paper considers multiphase unbalanced distribution systems and develops approximate power-flow models where bus-voltages, line-currents, and powers at the point of common coupling are linearly related to the nodal net power injections. The linearization approach is grounded on a fixed-point interpretation of the AC power-flow equations, and it is applicable to distribution systems featuring (i) wye connections; (ii) ungrounded delta connections; (iii) a combination of wye-connected and delta-connected sources/loads; and, (iv) a combination of line-to-line and line-to-grounded-neutral devices at the secondary of distribution transformers. The proposed linear models can facilitate the development of computationally-affordable optimization and control applications -- from advanced distribution management systems settings to online and distributed optimization routines. Performance of the proposed models is evaluated on different test feeders.

Kernel-based discriminant feature extraction using a representative dataset

Science.gov (United States)

Li, Honglin; Sancho Gomez, Jose-Luis; Ahalt, Stanley C.

2002-07-01

Discriminant Feature Extraction (DFE) is widely recognized as an important pre-processing step in classification applications. Most DFE algorithms are linear and thus can only explore the linear discriminant information among the different classes. Recently, there has been several promising attempts to develop nonlinear DFE algorithms, among which is Kernel-based Feature Extraction (KFE). The efficacy of KFE has been experimentally verified by both synthetic data and real problems. However, KFE has some known limitations. First, KFE does not work well for strongly overlapped data. Second, KFE employs all of the training set samples during the feature extraction phase, which can result in significant computation when applied to very large datasets. Finally, KFE can result in overfitting. In this paper, we propose a substantial improvement to KFE that overcomes the above limitations by using a representative dataset, which consists of critical points that are generated from data-editing techniques and centroid points that are determined by using the Frequency Sensitive Competitive Learning (FSCL) algorithm. Experiments show that this new KFE algorithm performs well on significantly overlapped datasets, and it also reduces computational complexity. Further, by controlling the number of centroids, the overfitting problem can be effectively alleviated.

Venus - Volcanic features in Atla Region

Science.gov (United States)

1991-01-01

This Magellan image from the Atla region of Venus shows several types of volcanic features and superimposed surface fractures. The area in the image is approximately 350 kilometers (217 miles) across, centered at 9 degrees south latitude, 199 degrees east longitude. Lava flows emanating from circular pits or linear fissures form flower-shaped patterns in several areas. A collapse depression approximately 20 kilometers by 10 kilometers (12 by 6 miles) near the center of the image is drained by a lava channel approximately 40 kilometers (25 miles) long. Numerous surface fractures and graben (linear valleys) criss-cross the volcanic deposits in north to northeast trends. The fractures are not buried by the lavas, indicating that the tectonic activity post-dates most of the volcanic activity.

High-Order Sparse Linear Predictors for Audio Processing

DEFF Research Database (Denmark)

Giacobello, Daniele; van Waterschoot, Toon; Christensen, Mads Græsbøll

2010-01-01

Linear prediction has generally failed to make a breakthrough in audio processing, as it has done in speech processing. This is mostly due to its poor modeling performance, since an audio signal is usually an ensemble of different sources. Nevertheless, linear prediction comes with a whole set...... of interesting features that make the idea of using it in audio processing not far fetched, e.g., the strong ability of modeling the spectral peaks that play a dominant role in perception. In this paper, we provide some preliminary conjectures and experiments on the use of high-order sparse linear predictors...... in audio processing. These predictors, successfully implemented in modeling the short-term and long-term redundancies present in speech signals, will be used to model tonal audio signals, both monophonic and polyphonic. We will show how the sparse predictors are able to model efficiently the different...

Development of high gradient superconducting radio frequency cavities for international linear collider and energy recovery linear accelerator

International Nuclear Information System (INIS)

Saito, Kenji; Furuta, Fumio; Saeki, Takayuki

2009-01-01

Superconducting radio frequency (SRF) cavities were used for storage rings like TRISTAN at KEK, HERA at DESY and LEP-II at CERN in 1990-2000. This technology has been accepted as a common accelerator technology. In August 2004, ITPR recommended an electron/positron linear collider based on SRF technology for the future high energy physics. ICFA accepted the recommendation and named it ILC (International Linear Collider). SRF cavities have a very unique feature due to its very small surface resistance. Energy recovery is another very exciting application. Many laboratories are proposing ERL (Energy Recovery LINAC) as a next bright photon source. In these accelerators, production of SRF cavities with reliably high performance is the most important issue. In this paper the activities of ILC high gradient cavities will be introduced. ERL activity will be briefly presented. (author)

Development of High Gradient Superconducting Radio Frequency Cavities for International Linear Collider and Energy Recovery Linear Accelerator

Science.gov (United States)

Saito, Kenji; Furuta, Fumio; Saeki, Takayuki

Superconducting radio frequency (SRF) cavities were used for storage rings like TRISTAN at KEK, HERA at DESY and LEP-II at CERN in 1990-2000. This technology has been accepted as a common accelerator technology. In August 2004, ITPR recommended an electron/positron linear collider based on SRF technology for the future high energy physics. ICFA accepted the recommendation and named it ILC (International Linear Collider). SRF cavities have a very unique feature due to its very small surface resistance. Energy recovery is another very exciting application. Many laboratories are proposing ERL (Energy Recovery LINAC) as a next bright photon source. In these accelerators, production of SRF cavities with reliably high performance is the most important issue. In this paper the activities of ILC high gradient cavities will be introduced. ERL activity will be briefly presented.

Reduction of Linear Programming to Linear Approximation

OpenAIRE

Vaserstein, Leonid N.

2006-01-01

It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

Science.gov (United States)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

Science.gov (United States)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods. PMID:28120883

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding.

Science.gov (United States)

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-07-06

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches.

Communication: Finding destructive interference features in molecular transport junctions

Energy Technology Data Exchange (ETDEWEB)

Reuter, Matthew G., E-mail: mgreuter@u.northwestern.edu [Department of Chemistry, Northwestern University, Evanston, Illinois 60208 (United States); Hansen, Thorsten [Department of Chemistry, H. C. Ørsted Institute, University of Copenhagen, DK 2100 Copenhagen (Denmark)

2014-11-14

Associating molecular structure with quantum interference features in electrode-molecule-electrode transport junctions has been difficult because existing guidelines for understanding interferences only apply to conjugated hydrocarbons. Herein we use linear algebra and the Landauer-Büttiker theory for electron transport to derive a general rule for predicting the existence and locations of interference features. Our analysis illustrates that interferences can be directly determined from the molecular Hamiltonian and the molecule–electrode couplings, and we demonstrate its utility with several examples.

Last Glacial Maximum Dated by Means of 10Be in the Maritime Alps (Italy)

Science.gov (United States)

Granger, D. E.; Spagnolo, M.; Federici, P.; Pappalardo, M.; Ribolini, A.; Cyr, A. J.

2006-12-01

Relatively few exposure dates of LGM moraines boulders are available for the European Alps, and none on the southern flank. Ponte Murato (PM) is a frontal moraine at 860 m asl in the Gesso Basin (Maritime Alps, SW European Alps). The PM moraine dams the 157 km2 Gesso della Barra Valley and it represents the lowermost frontal moraine of the entire Gesso Valley, near the outlet of the valley in the Po Plain. Its ELA, determined from the paleo- shape of the supposed Gesso della Barra glacier, is 1746 m asl. Tetti Bandito (TB) is a small and badly preserved glacial deposit, tentatively attributed to a lateral-frontal moraine, that is positioned 5 km downvalley from the PM deposit at 800 m asl. There are no other glacial deposits downvalley from the TB moraine in the Gesso Basin or farther NE in the piedmont region of the upper Po Plain. Boulders sampled on the PM and on the TB moraine crests gave a 10Be cosmogenic age of respectively 16300 ± 880 ka (average value) and 18798 ± 973 ka. This result constrains the PM frontal moraine within the LGM interval but also suggests that the maximum expansion of the Gesso Basin glacier was more downvalley at some point during the last glaciation. If the TB is a lateral-frontal moraine as supposed, the two TB and PM moraines would represent the outer and inner moraine crests of the same LGM stadial, with the outer moraine much less pronounced than the inner moraine, similarly to the maximalstand and the hochstand described in the Eastern Alps (Van Husen, 1997). Within this perspective, the PM and TB dates are consistent with a European Alps LGM corresponding to MIS 2 (Ivy-Ochs et al., 2004). This study of the Maritime Alps moraines is also in agreement with the Upper Würm climatic theory (Florineth and Schlüchter, 2000) of a stronger influence of the W and SW incoming humid airflows in the European Alps, differently from the nearby Vosges and Pyrenees mountain chains where more dry conditions were probably responsible for a very

Net ecosystem production in a Little Ice Age moraine: the role of plant functional traits

Science.gov (United States)

Varolo, E.; Zanotelli, D.; Tagliavini, M.; Zerbe, S.; Montagnani, L.

2015-07-01

Current glacier retreat allows vast mountain ranges available for vegetation establishment and growth. Little is known about the effective carbon (C) budget of these new ecosystems and how the presence of different vegetation communities, characterized by their specific physiology and life forms influences C fluxes. In this study, using a comparative analysis of the C fluxes of two contrasting vegetation types, we intend to evaluate if the different physiologies of the main species have an effect on Ecosystem Respiration (Reco), Gross Primary Production (GPP), annual cumulated Net Ecosystem Exchange (NEE), and long-term carbon accumulation in soil. The NEE of two plant communities present on a Little Ice Age moraine in the Matsch glacier forefield (Alps, Italy) was measured over two growing seasons. They are a typical C3 grassland, dominated by Festuca halleri All. and a community dominated by CAM rosettes Sempervivum montanum L. on rocky soils. Using transparent and opaque chambers, we extrapolated the ecophysiological responses to the main environmental drivers and performed the partition of NEE into Reco and GPP. Soil samples were collected from the same site to measure long-term C accumulation in the ecosystem. The two communities showed contrasting GPP but similar Reco patterns and as a result significantly different in NEE. The grassland acted mainly as a carbon sink with a total cumulated value of -46.4 ± 35.5 g C m-2 NEE while the plots dominated by the CAM rosettes acted as a source with 31.9 ± 22.4 g C m-2. In spite of the NEE being different in the two plant communities, soil analysis did not reveal significant differences in carbon accumulation. Grasslands showed 1.76 ± 0.12 kg C m-2, while CAM rosettes showed 2.06 ± 0.23 kg C m-2. This study demonstrates that carbon dynamics of two vegetation communities can be distinct even though the growing environment is similar. The physiological traits of the dominant species determine large differences in

Non-linear dynamics in Parkinsonism

Directory of Open Access Journals (Sweden)

Olivier eDarbin

2013-12-01

Full Text Available Over the last 30 years, the functions (and dysfunctions of the sensory-motor circuitry have been mostly conceptualized using linear modelizations which have resulted in two main models: the "rate hypothesis" and the "oscillatory hypothesis". In these two models, the basal ganglia data stream is envisaged as a random temporal combination of independent simple patterns issued from its probability distribution of interval interspikes or its spectrum of frequencies respectively.More recently, non-linear analyses have been introduced in the modelization of motor circuitry activities, and they have provided evidences that complex temporal organizations exist in basal ganglia neuronal activities. Regarding movement disorders, these complex temporal organizations in the basal ganglia data stream differ between conditions (i.e. parkinsonism, dyskinesia, healthy control and are responsive to treatments (i.e. L-DOPA,DBS. A body of evidence has reported that basal ganglia neuronal entropy (a marker for complexity/irregularity in time series is higher in hypokinetic state. In line with these findings, an entropy-based model has been recently formulated to introduce basal ganglia entropy as a marker for the alteration of motor processing and a factor of motor inhibition. Importantly, non-linear features have also been identified as a marker of condition and/or treatment effects in brain global signals (EEG, muscular activities (EMG or kinetic of motor symptoms (tremor, gait of patients with movement disorders. It is therefore warranted that the non-linear dynamics of motor circuitry will contribute to a better understanding of the neuronal dysfunctions underlying the spectrum of parkinsonian motor symptoms including tremor, rigidity and hypokinesia.

Subdivision of Glacial Deposits in Southeastern Peru Based on Pedogenic Development and Radiometric Ages

Science.gov (United States)

Goodman, Adam Y.; Rodbell, Donald T.; Seltzer, Geoffrey O.; Mark, Bryan G.

2001-07-01

The Cordillera Vilcanota and Quelccaya Ice Cap region of southern Peru (13°30‧-14°00‧S; 70°40‧-71°25‧W) contains a detailed record of late Quaternary glaciation in the tropical Andes. Quantification of soil development on 19 moraine crests and radiocarbon ages are used to reconstruct the glacial history. Secondary iron and clay increase linearly in Quelccaya soils and clay accumulates at a linear rate in Vilcanota soils, which may reflect the semicontinuous addition of eolian dust enriched in secondary iron to all soils. In contrast, logarithmic rates of iron buildup in soils in the Cordillera Vilcanota reflect chemical weathering; high concentrations of secondary iron in Vilcanota tills may mask the role of eolian input to these soils. Soil-age estimates from extrapolation of field and laboratory data suggest that the most extensive late Quaternary glaciation occurred >70,000 yr B.P. This provides one of the first semiquantitative age estimates for maximum ice extent in southern Peru and is supported by a minimum-limiting age of ∼41,520 14C yr B.P. A late glacial readvance culminated ∼16,650 cal yr B.P. in the Cordillera Vilcanota. Following rapid deglaciation of unknown extent, an advance of the Quelccaya Ice Cap occurred between ∼13,090 and 12,800 cal yr B.P., which coincides approximately with the onset of the Younger Dryas cooling in the North Atlantic region. Moraines deposited <394 cal yr B.P. in the Cordillera Vilcanota and <300 cal yr B.P. on the west side of the Quelccaya Ice Cap correlate with Little Ice Age moraines of other regions.

Local Environment Sensitivity of the Cu K-Edge XANES Features in Cu-SSZ-13: Analysis from First-Principles.

Science.gov (United States)

Zhang, Renqin; McEwen, Jean-Sabin

2018-05-22

Cu K-edge X-ray absorption near-edge spectra (XANES) have been widely used to study the properties of Cu-SSZ-13. In this Letter, the sensitivity of the XANES features to the local environment for a Cu + cation with a linear configuration and a Cu 2+ cation with a square-linear configuration in Cu-SSZ-13 is reported. When a Cu + cation is bonded to H 2 O or NH 3 in a linear configuration, the XANES has a strong peak at around 8983 eV. The intensity of this peak decreases as the linear configuration is broken. As for the Cu 2+ cations in a square-planar configuration with a coordination number of 4, two peaks at around 8986 and 8993 eV are found. An intensity decrease for both peaks at around 8986 and 8993 eV is found in an NH 3 _4_Z 2 Cu model as the N-Cu-N angle changes from 180 to 100°. We correlate these features to the variation of the 4p state by PDOS analysis. In addition, the feature peaks for both the Cu + cation and Cu 2+ cation do not show a dependence on the Cu-N bond length. We further show that the feature peaks also change when the coordination number of the Cu cation is varied, while these feature peaks are independent of the zeolite topology. These findings help elucidate the experimental XANES features at an atomic and an electronic level.

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

Science.gov (United States)

Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.

Science.gov (United States)

Zhang, Qingtian; Hu, Xiaolin; Zhang, Bo

2015-08-01

Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Sparse coding (SC) is a technique widely used in many areas and a number of efficient algorithms are available. Both l1-norm SVR and SC can be used for linear regression. In this brief, the close connection between the l1-norm SVR and SC is revealed and some typical algorithms are compared for linear regression. The results show that the SC algorithms outperform the Newton linear programming algorithm, an efficient l1-norm SVR algorithm, in efficiency. The algorithms are then used to design the radial basis function (RBF) neural networks. Experiments on some benchmark data sets demonstrate the high efficiency of the SC algorithms. In particular, one of the SC algorithms, the orthogonal matching pursuit is two orders of magnitude faster than a well-known RBF network designing algorithm, the orthogonal least squares algorithm.

Relevance of echo-structure and texture features

DEFF Research Database (Denmark)

Karemore, Gopal; Mullick, Jhinuk Basu; KV, Dr. Rajagopal

2010-01-01

Aim: Echostructure is an essential parameter for the evaluation of circumscribed lesions and can be described as a texture feature on ultrasound images. Present study evaluates the possibility of distinguishing between benign and malignant breast tumors using various texture features. Materials...... and Methods: 58 cases of breast tumor (29 each from benign and malignant) were documented under standardized conditions using a linear array machine and 7.5 MHz transducer. In each sonographic image, ROI of tumor was marked and then subjected to the evaluation of tumor status using five parameters of second...... performance ROC= 0.78(pbenign and malignant tumors. It also reveals that when evaluating images of a breast tumor...

Advanced Thomson scattering system for high-flux linear plasma generator

NARCIS (Netherlands)

Meiden, van der H.J.; Lof, A.R.; Berg, van den M.A.; Brons, S.; Donné, A.J.H.; Eck, van H.J.N.; Koelman, Peter; Koppers, W.R.; Kruijt, O.G.; Naumenko, N.N.; Oyevaar, T.; Prins, P.R.; Rapp, J.; Scholten, J.; Schram, D.C.; Smeets, P.H.M.; Star, van der G.; Tugarinov, S.N.; Zeijlmans van Emmichoven, P.A.

2012-01-01

An advanced Thomson scattering system has been built for a linear plasma generator for plasma surface interaction studies. The Thomson scattering system is based on a Nd:YAG laser operating at the second harmonic and a detection branch featuring a high etendue (f /3) transmission grating

Higher-Order Blind Signal Feature Separation: An Enabling Technology for Battlefield Awareness

National Research Council Canada - National Science Library

Su, Wei; Kosinski, John A

2006-01-01

Higher-order transform blind signal feature classification is discussed for separating bar-shaped, circular, squared, circular-squared, and offset-diamonded constellation patterns of digital linear signals...

The sense of balance in humans: Structural features of otoconia and their response to linear acceleration.

Directory of Open Access Journals (Sweden)

Rüdiger Kniep

Full Text Available We explored the functional role of individual otoconia within the otolith system of mammalians responsible for the detection of linear accelerations and head tilts in relation to the gravity vector. Details of the inner structure and the shape of intact human and artificial otoconia were studied using environmental scanning electron microscopy (ESEM, including decalcification by ethylenediaminetetraacetic acid (EDTA to discriminate local calcium carbonate density. Considerable differences between the rhombohedral faces of human and artificial otoconia already indicate that the inner architecture of otoconia is not consistent with the point group -3m. This is clearly confirmed by decalcified otoconia specimen which are characterized by a non-centrosymmetric volume distribution of the compact 3+3 branches. This structural evidence for asymmetric mass distribution was further supported by light microscopy in combination with a high speed camera showing the movement of single otoconia specimen (artificial specimen under gravitational influence within a viscous medium (artificial endolymph. Moreover, the response of otoconia to linear acceleration forces was investigated by particle dynamics simulations. Both, time-resolved microscopy and computer simulations of otoconia acceleration show that the dislocation of otoconia include significant rotational movement stemming from density asymmetry. Based on these findings, we suggest an otolith membrane expansion/stiffening mechanism for enhanced response to linear acceleration transmitted to the vestibular hair cells.

On application of kernel PCA for generating stimulus features for fMRI during continuous music listening.

Science.gov (United States)

Tsatsishvili, Valeri; Burunat, Iballa; Cong, Fengyu; Toiviainen, Petri; Alluri, Vinoo; Ristaniemi, Tapani

2018-06-01

There has been growing interest towards naturalistic neuroimaging experiments, which deepen our understanding of how human brain processes and integrates incoming streams of multifaceted sensory information, as commonly occurs in real world. Music is a good example of such complex continuous phenomenon. In a few recent fMRI studies examining neural correlates of music in continuous listening settings, multiple perceptual attributes of music stimulus were represented by a set of high-level features, produced as the linear combination of the acoustic descriptors computationally extracted from the stimulus audio. NEW METHOD: fMRI data from naturalistic music listening experiment were employed here. Kernel principal component analysis (KPCA) was applied to acoustic descriptors extracted from the stimulus audio to generate a set of nonlinear stimulus features. Subsequently, perceptual and neural correlates of the generated high-level features were examined. The generated features captured musical percepts that were hidden from the linear PCA features, namely Rhythmic Complexity and Event Synchronicity. Neural correlates of the new features revealed activations associated to processing of complex rhythms, including auditory, motor, and frontal areas. Results were compared with the findings in the previously published study, which analyzed the same fMRI data but applied linear PCA for generating stimulus features. To enable comparison of the results, methodology for finding stimulus-driven functional maps was adopted from the previous study. Exploiting nonlinear relationships among acoustic descriptors can lead to the novel high-level stimulus features, which can in turn reveal new brain structures involved in music processing. Copyright © 2018 Elsevier B.V. All rights reserved.

Interstitial Features at Chest CT Enhance the Deleterious Effects of Emphysema in the COPDGene Cohort.

Science.gov (United States)

Ash, Samuel Y; Harmouche, Rola; Ross, James C; Diaz, Alejandro A; Rahaghi, Farbod N; Sanchez-Ferrero, Gonzalo Vegas; Putman, Rachel K; Hunninghake, Gary M; Onieva, Jorge Onieva; Martinez, Fernando J; Choi, Augustine M; Bowler, Russell P; Lynch, David A; Hatabu, Hiroto; Bhatt, Surya P; Dransfield, Mark T; Wells, J Michael; Rosas, Ivan O; San Jose Estepar, Raul; Washko, George R

2018-06-05

Purpose To determine if interstitial features at chest CT enhance the effect of emphysema on clinical disease severity in smokers without clinical pulmonary fibrosis. Materials and Methods In this retrospective cohort study, an objective CT analysis tool was used to measure interstitial features (reticular changes, honeycombing, centrilobular nodules, linear scar, nodular changes, subpleural lines, and ground-glass opacities) and emphysema in 8266 participants in a study of chronic obstructive pulmonary disease (COPD) called COPDGene (recruited between October 2006 and January 2011). Additive differences in patients with emphysema with interstitial features and in those without interstitial features were analyzed by using t tests, multivariable linear regression, and Kaplan-Meier analysis. Multivariable linear and Cox regression were used to determine if interstitial features modified the effect of continuously measured emphysema on clinical measures of disease severity and mortality. Results Compared with individuals with emphysema alone, those with emphysema and interstitial features had a higher percentage predicted forced expiratory volume in 1 second (absolute difference, 6.4%; P < .001), a lower percentage predicted diffusing capacity of lung for carbon monoxide (DLCO) (absolute difference, 7.4%; P = .034), a 0.019 higher right ventricular-to-left ventricular (RVLV) volume ratio (P = .029), a 43.2-m shorter 6-minute walk distance (6MWD) (P < .001), a 5.9-point higher St George's Respiratory Questionnaire (SGRQ) score (P < .001), and 82% higher mortality (P < .001). In addition, interstitial features modified the effect of emphysema on percentage predicted DLCO, RVLV volume ratio, 6WMD, SGRQ score, and mortality (P for interaction < .05 for all). Conclusion In smokers, the combined presence of interstitial features and emphysema was associated with worse clinical disease severity and higher mortality than was emphysema alone. In addition, interstitial features

Principle and analysis of a linear motor driving system for HTS levitation applications

International Nuclear Information System (INIS)

Jin, Jian X.; Guo, You G.; Zhu, Jian G.

2007-01-01

High temperature superconductor (HTS) high levitation force density with passive and self-stabilizing features allows a number of special applications to be developed. Linear motor driving systems are commonly required for those applications such as levitated transport systems. In this paper a prototype linear motor driving system with HTS is analyzed with calculation details including its magnetic fields and driving forces presented in the paper

Feature network models for proximity data : statistical inference, model selection, network representations and links with related models

NARCIS (Netherlands)

Frank, Laurence Emmanuelle

2006-01-01

Feature Network Models (FNM) are graphical structures that represent proximity data in a discrete space with the use of features. A statistical inference theory is introduced, based on the additivity properties of networks and the linear regression framework. Considering features as predictor

On combining principal components with Fisher's linear discriminants for supervised learning

NARCIS (Netherlands)

Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.

2006-01-01

"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic increase of computational complexity and classification error in high dimensions. In this paper, principal component analysis (PCA), parametric feature extraction (FE) based on Fisher’s linear

A cross-sectional electromyography assessment in linear scleroderma patients

Science.gov (United States)

2014-01-01

Background Muscle atrophy and asymmetric extremity growth is a common feature of linear scleroderma (LS). Extra-cutaneous features are also common and primary neurologic involvement, with sympathetic dysfunction, may have a pathogenic role in subcutaneous and muscle atrophy. The aim was investigate nerve conduction and muscle involvement by electromyography in pediatric patients with LS. Methods We conducted a retrospective review of LS pediatric patients who had regular follow up at a single pediatric center from 1997–2013. We selected participants if they had consistently good follow up and enrolled consecutive patients in the study. We examined LS photos as well as clinical, serological and imaging findings. Electromyograms (EMG) were performed with bilateral symmetric technique, using surface and needle electrodes, comparing the affected side with the contralateral side. Abnormal muscle activity was categorized as a myopathic or neurogenic pattern. Results Nine LS subjects were selected for EMG, 2 with Parry-Romberg/Hemifacial Atrophy Syndrome, 7 linear scleroderma of an extremity and 2 with mixed forms (linear and morphea). Electromyogram analysis indicated that all but one had asymmetric myopathic pattern in muscles underlying the linear streaks. Motor and sensory nerve conduction was also evaluated in upper and lower limbs and one presented a neurogenic pattern. Masticatory muscle testing showed a myopathic pattern in the atrophic face of 2 cases with head and face involvement. Conclusion In our small series of LS patients, we found a surprising amount of muscle dysfunction by EMG. The muscle involvement may be possibly related to a secondary peripheral nerve involvement due to LS inflammation and fibrosis. Further collaborative studies to confirm these findings are needed. PMID:25053924

Movements and instability in the Swedish bedrock

International Nuclear Information System (INIS)

Moerner, N.A.

1977-01-01

The report gives a geological evaluation of the Swedish bedrock and its movements during the last 20,000 years, which may serve as a base for further evaluations of the possibilities of storing nuclear waste in the bedrock. The Swedish bedrock is by no means stable. Like all other bedrocks it is unstable. The Swedish bedrock has an old and rich tectono-geodynamic inheritance. Irregularities in the uplift in the form of shoreline bends and isobase irregularities have been established with ancient shorelines and geodetic data. They are in general all related to major faultlines and bedrock seams. Bouldery end moraines and bouldery ground in general register paleopseismic activity -(these areas must hence be excluded as alternatives for storage of nuclear waste in the bedrock). The next ice age, is either on its way or it will, under the most favorable circumstances, have begun 20,000years from now (AP). At the next ice age, all the seismic and neotectonic effects from the deglaciation period will be repeated. During an ice age. Nuclear waste cannot bestored in the bedrock. If one succed in finding a Precambrain bedrock unit within an area of smooth uplift, absence of recent earthquakes, the bedrock surface of which shows few fractures and no faultlines, and where the surroundings exhibit normal moraine features and normal till composition, this area must still be evaluated with respect to that which will happen and may happen in connection with the next ice age and in connection with the cyclic gravitational changes in the present linear uplift. (author)

Use of probabilistic weights to enhance linear regression myoelectric control.

Science.gov (United States)

Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

2015-12-01

Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts' law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

Modeling Forest Succession among Ecological Land Units in Northern Minnesota

Directory of Open Access Journals (Sweden)

George Host

1998-12-01

Full Text Available Field and modeling studies were used to quantify potential successional pathways among fine-scale ecological classification units within two geomorphic regions of north-central Minnesota. Soil and overstory data were collected on plots stratified across low-relief ground moraines and undulating sand dunes. Each geomorphic feature was sampled across gradients of topography or soil texture. Overstory conditions were sampled using five variable-radius point samples per plot; soil samples were analyzed for carbon and nitrogen content. Climatic, forest composition, and soil data were used to parameterize the sample plots for use with LINKAGES, a forest growth model that simulates changes in composition and soil characteristics over time. Forest composition and soil properties varied within and among geomorphic features. LINKAGES simulations were using "bare ground" and the current overstory as starting conditions. Northern hardwoods or pines dominated the late-successional communities of morainal and dune landforms, respectively. The morainal landforms were dominated by yellow birch and sugar maple; yellow birch reached its maximum abundance in intermediate landscape positions. On the dune sites, pine was most abundant in drier landscape positions, with white spruce increasing in abundance with increasing soil moisture and N content. The differences in measured soil properties and predicted late-successional composition indicate that ecological land units incorporate some of the key variables that govern forest composition and structure. They further show the value of ecological classification and modeling for developing forest management strategies that incorporate the spatial and temporal dynamics of forest ecosystems.

Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression

Directory of Open Access Journals (Sweden)

Shahrbanoo Goli

2016-01-01

Full Text Available The Support Vector Regression (SVR model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model.

An efficient linear approach in the reservoirs operation for electric power generation; Uma eficiente abordagem linear na operacao de reservatorios para geracao de energia eletrica

Energy Technology Data Exchange (ETDEWEB)

Zambon, Katia Livia

1997-07-01

A new approach for the Scheduling of Hydrothermal Systems, with a formulation that allows the solution of the problem through the linear programming techniques, otherwise the original form, which is complex and difficult is presented. The models were developed through a linear form for the generation function of hydroelectric plants, successive of the linearization of the cost function of the problem. The linear techniques used were the Simplex Method, with some modification that is is efficient, fast and simple. The important physical aspects of the system were preserved, like the individual representation of the hydroelectric plant, the features of cost function with the exponential increase and the head effect. Besides, this formulation can lead to stochastic approaches. All the optimization methods were implemented for the solution of the problem. The performance obtained were compared with each other and with that obtained through the non linear techniques. The algorithms showed to be efficient, with good results and very near to the optimal behavior of the reservoir operation planning obtained by traditional methods. (author)

Image segmentation-based robust feature extraction for color image watermarking

Science.gov (United States)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Motion characteristic of a free piston linear engine

Energy Technology Data Exchange (ETDEWEB)

Xiao, Jin; Li, Qingfeng; Huang, Zhen [Key Laboratory for Power Machinery and Engineering of Ministry of Education, Shanghai Jiao Tong University, Shanghai, 200240 (China)

2010-04-15

A mathematical model of a free piston linear engine is established. The motion characteristics as well as the natural frequency map of the free piston are established. Then, its motion characteristics are successfully explained from the oscillation point. The full simulation model is built up in Matlab/Simulink for a better understanding of its motion features. The results show that the free piston system is a forced vibration system with variable damping coefficient and stiffness. Its steady-state response of periodical excitation is convergent which means that the system is stable under the periodical combustion. Furthermore, it has some unique features which are different from those of traditional Internal Combustion (IC) engines. (author)

Linear infrastructure impacts on landscape hydrology.

Science.gov (United States)

Raiter, Keren G; Prober, Suzanne M; Possingham, Hugh P; Westcott, Fiona; Hobbs, Richard J

2018-01-15

The extent of roads and other forms of linear infrastructure is burgeoning worldwide, but their impacts are inadequately understood and thus poorly mitigated. Previous studies have identified many potential impacts, including alterations to the hydrological functions and soil processes upon which ecosystems depend. However, these impacts have seldom been quantified at a regional level, particularly in arid and semi-arid systems where the gap in knowledge is the greatest, and impacts potentially the most severe. To explore the effects of extensive track, road, and rail networks on surface hydrology at a regional level we assessed over 1000 km of linear infrastructure, including approx. 300 locations where ephemeral streams crossed linear infrastructure, in the largely intact landscapes of Australia's Great Western Woodlands. We found a high level of association between linear infrastructure and altered surface hydrology, with erosion and pooling 5 and 6 times as likely to occur on-road than off-road on average (1.06 erosional and 0.69 pooling features km -1 on vehicle tracks, compared with 0.22 and 0.12 km -1 , off-road, respectively). Erosion severity was greater in the presence of tracks, and 98% of crossings of ephemeral streamlines showed some evidence of impact on water movement (flow impedance (62%); diversion of flows (73%); flow concentration (76%); and/or channel initiation (31%)). Infrastructure type, pastoral land use, culvert presence, soil clay content and erodibility, mean annual rainfall, rainfall erosivity, topography and bare soil cover influenced the frequency and severity of these impacts. We conclude that linear infrastructure frequently affects ephemeral stream flows and intercepts natural overland and near-surface flows, artificially changing site-scale moisture regimes, with some parts of the landscape becoming abnormally wet and other parts becoming water-starved. In addition, linear infrastructure frequently triggers or exacerbates erosion

Application of alternating decision trees in selecting sparse linear solvers

KAUST Repository

Bhowmick, Sanjukta; Eijkhout, Victor; Freund, Yoav; Fuentes, Erika; Keyes, David E.

2010-01-01

The solution of sparse linear systems, a fundamental and resource-intensive task in scientific computing, can be approached through multiple algorithms. Using an algorithm well adapted to characteristics of the task can significantly enhance the performance, such as reducing the time required for the operation, without compromising the quality of the result. However, the best solution method can vary even across linear systems generated in course of the same PDE-based simulation, thereby making solver selection a very challenging problem. In this paper, we use a machine learning technique, Alternating Decision Trees (ADT), to select efficient solvers based on the properties of sparse linear systems and runtime-dependent features, such as the stages of simulation. We demonstrate the effectiveness of this method through empirical results over linear systems drawn from computational fluid dynamics and magnetohydrodynamics applications. The results also demonstrate that using ADT can resolve the problem of over-fitting, which occurs when limited amount of data is available. © 2010 Springer Science+Business Media LLC.

Superpixel-Based Feature for Aerial Image Scene Recognition

Directory of Open Access Journals (Sweden)

Hongguang Li

2018-01-01

Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

Linear nanometric tunnel junction sensors with exchange pinned sensing layer

International Nuclear Information System (INIS)

Leitao, D. C.; Silva, A. V.; Cardoso, S.; Ferreira, R.; Paz, E.; Deepack, F. L.; Freitas, P. P.

2014-01-01

Highly sensitive nanosensors with high spatial resolution provide the necessary features for high accuracy imaging of isolated magnetic nanoparticles. In this work, we report the fabrication and characterization of MgO-barrier magnetic tunnel junction nanosensors, with two exchange-pinned electrodes. The perpendicular magnetization configuration for field sensing is set using a two-step annealing process, where the second annealing temperature was optimized to yield patterned sensors responses with improved linearity. The optimized circular nanosensors show sensitivities up to 0.1%/Oe, larger than previously reported for nanometric sensors and comparable to micrometric spin-valves. Our strategy avoids the use of external permanent biasing or demagnetizing fields (large for smaller structures) to achieve a linear response, enabling the control of the linear operation range using only the stack and thus providing a small footprint device

Linear nanometric tunnel junction sensors with exchange pinned sensing layer

Energy Technology Data Exchange (ETDEWEB)

Leitao, D. C., E-mail: dleitao@inesc-mn.pt; Silva, A. V.; Cardoso, S. [INESC-MN and IN, Rua Alves Redol 9, 1000-029 Lisboa (Portugal); Instituto Superior Técnico (IST), Universidade de Lisboa, Av. Rovisco Pais, 1000-029 Lisboa (Portugal); Ferreira, R.; Paz, E.; Deepack, F. L. [INL, Av. Mestre Jose Veiga, 4715-31 Braga (Portugal); Freitas, P. P. [INESC-MN and IN, Rua Alves Redol 9, 1000-029 Lisboa (Portugal); INL, Av. Mestre Jose Veiga, 4715-31 Braga (Portugal)

2014-05-07

Highly sensitive nanosensors with high spatial resolution provide the necessary features for high accuracy imaging of isolated magnetic nanoparticles. In this work, we report the fabrication and characterization of MgO-barrier magnetic tunnel junction nanosensors, with two exchange-pinned electrodes. The perpendicular magnetization configuration for field sensing is set using a two-step annealing process, where the second annealing temperature was optimized to yield patterned sensors responses with improved linearity. The optimized circular nanosensors show sensitivities up to 0.1%/Oe, larger than previously reported for nanometric sensors and comparable to micrometric spin-valves. Our strategy avoids the use of external permanent biasing or demagnetizing fields (large for smaller structures) to achieve a linear response, enabling the control of the linear operation range using only the stack and thus providing a small footprint device.

Unique features in the ARIES glovebox line

International Nuclear Information System (INIS)

Martinez, H.E.; Brown, W.G.; Flamm, B.; James, C.A.; Laskie, R.; Nelson, T.O.; Wedman, D.E.

1998-01-01

A series of unique features have been incorporated into the Advanced Recovery and Integrated Extraction System (ARIES) at the Los Alamos National Laboratory, TA-55 Plutonium Facility. The features enhance the material handling in the process of the dismantlement of nuclear weapon primaries in the glovebox line. Incorporated into these features are the various plutonium process module's different ventilation zone requirements that the material handling systems must meet. These features include a conveyor system that consists of a remotely controlled cart that transverses the length of the conveyor glovebox, can be operated from a remote location and can deliver process components to the entrance of any selected module glovebox. Within the modules there exists linear motion material handling systems with lifting hoist, which are controlled via an Allen Bradley control panel or local control panels. To remove the packaged products from the hot process line, the package is processed through an air lock/electrolytic decontamination process that removes the radioactive contamination from the outside of the package container and allows the package to be removed from the process line

INTEGRATION OF IMAGE-DERIVED AND POS-DERIVED FEATURES FOR IMAGE BLUR DETECTION

Directory of Open Access Journals (Sweden)

T.-A. Teo

2016-06-01

Full Text Available The image quality plays an important role for Unmanned Aerial Vehicle (UAV’s applications. The small fixed wings UAV is suffering from the image blur due to the crosswind and the turbulence. Position and Orientation System (POS, which provides the position and orientation information, is installed onto an UAV to enable acquisition of UAV trajectory. It can be used to calculate the positional and angular velocities when the camera shutter is open. This study proposes a POS-assisted method to detect the blur image. The major steps include feature extraction, blur image detection and verification. In feature extraction, this study extracts different features from images and POS. The image-derived features include mean and standard deviation of image gradient. For POS-derived features, we modify the traditional degree-of-linear-blur (blinear method to degree-of-motion-blur (bmotion based on the collinear condition equations and POS parameters. Besides, POS parameters such as positional and angular velocities are also adopted as POS-derived features. In blur detection, this study uses Support Vector Machines (SVM classifier and extracted features (i.e. image information, POS data, blinear and bmotion to separate blur and sharp UAV images. The experiment utilizes SenseFly eBee UAV system. The number of image is 129. In blur image detection, we use the proposed degree-of-motion-blur and other image features to classify the blur image and sharp images. The classification result shows that the overall accuracy using image features is only 56%. The integration of image-derived and POS-derived features have improved the overall accuracy from 56% to 76% in blur detection. Besides, this study indicates that the performance of the proposed degree-of-motion-blur is better than the traditional degree-of-linear-blur.

Electron Model of Linear-Field FFAG

CERN Document Server

Koscielniak, Shane R

2005-01-01

A fixed-field alternating-gradient accelerator (FFAG) that employs only linear-field elements ushers in a new regime in accelerator design and dynamics. The linear-field machine has the ability to compact an unprecedented range in momenta within a small component aperture. With a tune variation which results from the natural chromaticity, the beam crosses many strong, uncorrec-table, betatron resonances during acceleration. Further, relativistic particles in this machine exhibit a quasi-parabolic time-of-flight that cannot be addressed with a fixed-frequency rf system. This leads to a new concept of bucketless acceleration within a rotation manifold. With a large energy jump per cell, there is possibly strong synchro-betatron coupling. A few-MeV electron model has been proposed to demonstrate the feasibility of these untested acceleration features and to investigate them at length under a wide range of operating conditions. This paper presents a lattice optimized for a 1.3 GHz rf, initial technology choices f...

Linear step drive

International Nuclear Information System (INIS)

Haniger, L.; Elger, R.; Kocandrle, L.; Zdebor, J.

1986-01-01

A linear step drive is described developed in Czechoslovak-Soviet cooperation and intended for driving WWER-1000 control rods. The functional principle is explained of the motor and the mechanical and electrical parts of the drive, power control, and the indicator of position are described. The motor has latches situated in the reactor at a distance of 3 m from magnetic armatures, it has a low structural height above the reactor cover, which suggests its suitability for seismic localities. Its magnetic circuits use counterpoles; the mechanical shocks at the completion of each step are damped using special design features. The position indicator is of a special design and evaluates motor position within ±1% of total travel. A drive diagram and the flow chart of both the control electronics and the position indicator are presented. (author) 4 figs

Linear verrucous hemangioma-a rare case and dermoscopic clues to diagnosis.

Science.gov (United States)

Dhanta, Aditi; Chauhan, Payal; Meena, Dilip; Hazarika, Neirita

2018-01-01

Verrucous hemangioma (VH) is a rare, congenital and localized vascular malformation, which usually presents as warty, bluish, vascular papules, plaques, or nodules, mainly on the lower extremities. Linear presentation of the disease is rare. A deep biopsy is necessary to confirm the clinical diagnosis by histopathological examination, with dermoscopy acting as a useful tool for evaluating the precise vascular structure. Here, we report on a 13-year-old female child with linear VH presenting over her foot since infancy and dermoscopic findings of VH along with the clinical-pathologic features.

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

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.

Linear versus non-linear supersymmetry, in general

Energy Technology Data Exchange (ETDEWEB)

Ferrara, Sergio [Theoretical Physics Department, CERN,CH-1211 Geneva 23 (Switzerland); INFN - Laboratori Nazionali di Frascati,Via Enrico Fermi 40, I-00044 Frascati (Italy); Department of Physics and Astronomy, UniversityC.L.A.,Los Angeles, CA 90095-1547 (United States); Kallosh, Renata [SITP and Department of Physics, Stanford University,Stanford, California 94305 (United States); Proeyen, Antoine Van [Institute for Theoretical Physics, Katholieke Universiteit Leuven,Celestijnenlaan 200D, B-3001 Leuven (Belgium); Wrase, Timm [Institute for Theoretical Physics, Technische Universität Wien,Wiedner Hauptstr. 8-10, A-1040 Vienna (Austria)

2016-04-12

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Linear versus non-linear supersymmetry, in general

International Nuclear Information System (INIS)

Ferrara, Sergio; Kallosh, Renata; Proeyen, Antoine Van; Wrase, Timm

2016-01-01

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

The design of a small linear-resonant, split Stirling cryogenic refrigerator compressor

Science.gov (United States)

Ackermann, R. A.

1985-01-01

The development of a small linear-resonant compressor for use in a 1/4-watt, 78K, split Stirling cryogenic refrigerator is discussed. The compressor contains the following special features: (1) a permanent-magnet linear motor; (2) resonant dynamics; (3) dynamic balancing; and (4) a close-clearance seal between the compressor piston and cylinder. This paper describes the design of the compressor, and presents component test data and system test data for the compressor driving a 1/4-watt expander.

Painlevйe analysis and integrability of two-coupled non-linear ...

Indian Academy of Sciences (India)

the Painlevйe property. In this case the system is expected to be integrable. In recent years more attention is paid to the study of coupled non-linear oscilla- ... Painlevйe analysis. To be self-contained, in §2 we briefly outline the salient features.

Aspect-object alignment with Integer Linear Programming in opinion mining.

Directory of Open Access Journals (Sweden)

Yanyan Zhao

Full Text Available Target extraction is an important task in opinion mining. In this task, a complete target consists of an aspect and its corresponding object. However, previous work has always simply regarded the aspect as the target itself and has ignored the important "object" element. Thus, these studies have addressed incomplete targets, which are of limited use for practical applications. This paper proposes a novel and important sentiment analysis task, termed aspect-object alignment, to solve the "object neglect" problem. The objective of this task is to obtain the correct corresponding object for each aspect. We design a two-step framework for this task. We first provide an aspect-object alignment classifier that incorporates three sets of features, namely, the basic, relational, and special target features. However, the objects that are assigned to aspects in a sentence often contradict each other and possess many complicated features that are difficult to incorporate into a classifier. To resolve these conflicts, we impose two types of constraints in the second step: intra-sentence constraints and inter-sentence constraints. These constraints are encoded as linear formulations, and Integer Linear Programming (ILP is used as an inference procedure to obtain a final global decision that is consistent with the constraints. Experiments on a corpus in the camera domain demonstrate that the three feature sets used in the aspect-object alignment classifier are effective in improving its performance. Moreover, the classifier with ILP inference performs better than the classifier without it, thereby illustrating that the two types of constraints that we impose are beneficial.

Aspect-object alignment with Integer Linear Programming in opinion mining.

Science.gov (United States)

Zhao, Yanyan; Qin, Bing; Liu, Ting; Yang, Wei

2015-01-01

Target extraction is an important task in opinion mining. In this task, a complete target consists of an aspect and its corresponding object. However, previous work has always simply regarded the aspect as the target itself and has ignored the important "object" element. Thus, these studies have addressed incomplete targets, which are of limited use for practical applications. This paper proposes a novel and important sentiment analysis task, termed aspect-object alignment, to solve the "object neglect" problem. The objective of this task is to obtain the correct corresponding object for each aspect. We design a two-step framework for this task. We first provide an aspect-object alignment classifier that incorporates three sets of features, namely, the basic, relational, and special target features. However, the objects that are assigned to aspects in a sentence often contradict each other and possess many complicated features that are difficult to incorporate into a classifier. To resolve these conflicts, we impose two types of constraints in the second step: intra-sentence constraints and inter-sentence constraints. These constraints are encoded as linear formulations, and Integer Linear Programming (ILP) is used as an inference procedure to obtain a final global decision that is consistent with the constraints. Experiments on a corpus in the camera domain demonstrate that the three feature sets used in the aspect-object alignment classifier are effective in improving its performance. Moreover, the classifier with ILP inference performs better than the classifier without it, thereby illustrating that the two types of constraints that we impose are beneficial.

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

Science.gov (United States)

Irshad, Humayun; Jalali, Sepehr; Roux, Ludovic; Racoceanu, Daniel; Hwee, Lim Joo; Naour, Gilles Le; Capron, Frédérique

2013-01-01

According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. The aim is to investigate the various texture features and Hierarchical Model and X (HMAX) biologically inspired approach for mitosis detection using machine-learning techniques. We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT) features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM), and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for an International Conference on Pattern Recognition (ICPR) 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and classification rate.

Positive Quasi Linear Operator Formulation

International Nuclear Information System (INIS)

Berry, L.A.; Jaeger, E.F.

2005-01-01

Expressions for the RF quasi-linear operator are biquadratic sums over the Fourier modes (or FLR equivalent) that describe the RF electric field with a kernel that is a function of the two wave vectors, k-vector L and k-vector R , in the sum. As a result of either an implicit or explicit average over field lines or flux surfaces, this kernel only depends on one parallel wave vector, conventionally k R -vector. When k-vector is an independent component of the representation for E, the sums are demonstrably positive. However, except for closed field line systems, k-vector is dependent on the local direction of the equilibrium magnetic field, and, empirically, the absorbed energy and quasi-linear diffusion coefficients are observed to have negative features. We have formally introduced an independent k-vector sum by Fourier transforming the RF electric field (assuming straight field lines) using a field-line-length coordinate. The resulting expression is positive. We have modeled this approach by calculating the quasi linear operator for 'modes' with fixed k-vector. We form these modes by discretizing k-vector and then assigning all of the Fourier components with k-vectorthat fall within a given k-vector bin to that k-vector mode. Results will be shown as a function of the number of bins. Future work will involve implementing the expressions derived from the Fourier transform and evaluating the dependence on field line length

A Linear Active Disturbance Rejection Control for a Ball and Rigid Triangle System

Directory of Open Access Journals (Sweden)

Carlos Aguilar-Ibanez

2016-01-01

Full Text Available This paper proposes an application of linear flatness control along with active disturbance rejection control (ADRC for the local stabilization and trajectory tracking problems in the underactuated ball and rigid triangle system. To this end, an observer-based linear controller of the ADRC type is designed based on the flat tangent linearization of the system around its corresponding unstable equilibrium rest position. It was accomplished through two decoupled linear extended observers and a single linear output feedback controller, with disturbance cancelation features. The controller guarantees locally exponentially asymptotic stability for the stabilization problem and practical local stability in the solution of the tracking error. An advantage of combining the flatness and the ADRC methods is that it possible to perform online estimates and cancels the undesirable effects of the higher-order nonlinearities discarded by the linearization approximation. Simulation indicates that the proposed controller behaves remarkably well, having an acceptable domain of attraction.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Research on geometric rectification of the Large FOV Linear Array Whiskbroom Image

Science.gov (United States)

Liu, Dia; Liu, Hui-tong; Dong, Hao; Liu, Xiao-bo

2015-08-01

To solve the geometric distortion problem of large FOV linear array whiskbroom image, a model of multi center central projection collinearity equation was founded considering its whiskbroom and linear CCD imaging feature, and the principle of distortion was analyzed. Based on the rectification method with POS, we introduced the angular position sensor data of the servo system, and restored the geometric imaging process exactly. An indirect rectification scheme aiming at linear array imaging with best scanline searching method was adopted, matrixes for calculating the exterior orientation elements was redesigned. We improved two iterative algorithms for this device, and did comparison and analysis. The rectification for the images of airborne imaging experiment showed ideal effect.

Multiscale wavelet representations for mammographic feature analysis

Science.gov (United States)

Laine, Andrew F.; Song, Shuwu

1992-12-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

An Improved EMD-Based Dissimilarity Metric for Unsupervised Linear Subspace Learning

Directory of Open Access Journals (Sweden)

Xiangchun Yu

2018-01-01

Full Text Available We investigate a novel way of robust face image feature extraction by adopting the methods based on Unsupervised Linear Subspace Learning to extract a small number of good features. Firstly, the face image is divided into blocks with the specified size, and then we propose and extract pooled Histogram of Oriented Gradient (pHOG over each block. Secondly, an improved Earth Mover’s Distance (EMD metric is adopted to measure the dissimilarity between blocks of one face image and the corresponding blocks from the rest of face images. Thirdly, considering the limitations of the original Locality Preserving Projections (LPP, we proposed the Block Structure LPP (BSLPP, which effectively preserves the structural information of face images. Finally, an adjacency graph is constructed and a small number of good features of a face image are obtained by methods based on Unsupervised Linear Subspace Learning. A series of experiments have been conducted on several well-known face databases to evaluate the effectiveness of the proposed algorithm. In addition, we construct the noise, geometric distortion, slight translation, slight rotation AR, and Extended Yale B face databases, and we verify the robustness of the proposed algorithm when faced with a certain degree of these disturbances.

Diagnosis and prognosis of Ostheoarthritis by texture analysis using sparse linear models

DEFF Research Database (Denmark)

Marques, Joselene; Clemmensen, Line Katrine Harder; Dam, Erik

We present a texture analysis methodology that combines uncommitted machine-learning techniques and sparse feature transformation methods in a fully automatic framework. We compare the performances of a partial least squares (PLS) forward feature selection strategy to a hard threshold sparse PLS...... algorithm and a sparse linear discriminant model. The texture analysis framework was applied to diagnosis of knee osteoarthritis (OA) and prognosis of cartilage loss. For this investigation, a generic texture feature bank was extracted from magnetic resonance images of tibial knee bone. The features were...... used as input to the sparse algorithms, which dened the best features to retain in the model. To cope with the limited number of samples, the data was evaluated using 10 fold cross validation (CV). The diagnosis evaluation using sparse PLS reached a generalization area-under-the-ROC curve (AUC) of 0...

Estimating epidemic arrival times using linear spreading theory

Science.gov (United States)

Chen, Lawrence M.; Holzer, Matt; Shapiro, Anne

2018-01-01

We study the dynamics of a spatially structured model of worldwide epidemics and formulate predictions for arrival times of the disease at any city in the network. The model is composed of a system of ordinary differential equations describing a meta-population susceptible-infected-recovered compartmental model defined on a network where each node represents a city and the edges represent the flight paths connecting cities. Making use of the linear determinacy of the system, we consider spreading speeds and arrival times in the system linearized about the unstable disease free state and compare these to arrival times in the nonlinear system. Two predictions are presented. The first is based upon expansion of the heat kernel for the linearized system. The second assumes that the dominant transmission pathway between any two cities can be approximated by a one dimensional lattice or a homogeneous tree and gives a uniform prediction for arrival times independent of the specific network features. We test these predictions on a real network describing worldwide airline traffic.

Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

Science.gov (United States)

Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo

2016-01-01

The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.

Improved harmonic balance approach to periodic solutions of non-linear jerk equations

International Nuclear Information System (INIS)

Wu, B.S.; Lim, C.W.; Sun, W.P.

2006-01-01

An analytical approximate approach for determining periodic solutions of non-linear jerk equations involving third-order time-derivative is presented. This approach incorporates salient features of both Newton's method and the method of harmonic balance. By appropriately imposing the method of harmonic balance to the linearized equation, the approach requires only one or two iterations to predict very accurate analytical approximate solutions for a large range of initial velocity amplitude. One typical example is used to verify and illustrate the usefulness and effectiveness of the proposed approach

Development of pre-critical excore detector linear subchannel calibration method

International Nuclear Information System (INIS)

Choi, Yoo Sun; Goo, Bon Seung; Cha, Kyun Ho; Lee, Chang Seop; Kim, Yong Hee; Ahn, Chul Soo; Kim, Man Soo

2001-01-01

The improved pre-critical excore detector linear subchannel calibration method has been developed to improve the applicability of pre-critical calibration method. The existing calibration method does not always guarantee the accuracy of pre-critical calibration because the calibration results of the previous cycle are not reflected into the current cycle calibration. The developed method has a desirable feature that calibration error would not be propagated in the following cycles since the calibration data determined in previous cycle is incorporated in the current cycle calibration. The pre-critical excore detector linear calibration is tested for YGN unit 3 and UCN unit 3 to evaluate its characteristics and accuracy

Foundations of linear and generalized linear models

CERN Document Server

Agresti, Alan

2015-01-01

A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,

Textural features for image classification

Science.gov (United States)

Haralick, R. M.; Dinstein, I.; Shanmugam, K.

1973-01-01

Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

Optical linear algebra processors - Architectures and algorithms

Science.gov (United States)

Casasent, David

1986-01-01

Attention is given to the component design and optical configuration features of a generic optical linear algebra processor (OLAP) architecture, as well as the large number of OLAP architectures, number representations, algorithms and applications encountered in current literature. Number-representation issues associated with bipolar and complex-valued data representations, high-accuracy (including floating point) performance, and the base or radix to be employed, are discussed, together with case studies on a space-integrating frequency-multiplexed architecture and a hybrid space-integrating and time-integrating multichannel architecture.

Non-linear and signal energy optimal asymptotic filter design

Directory of Open Access Journals (Sweden)

Josef Hrusak

2003-10-01

Full Text Available The paper studies some connections between the main results of the well known Wiener-Kalman-Bucy stochastic approach to filtering problems based mainly on the linear stochastic estimation theory and emphasizing the optimality aspects of the achieved results and the classical deterministic frequency domain linear filters such as Chebyshev, Butterworth, Bessel, etc. A new non-stochastic but not necessarily deterministic (possibly non-linear alternative approach called asymptotic filtering based mainly on the concepts of signal power, signal energy and a system equivalence relation plays an important role in the presentation. Filtering error invariance and convergence aspects are emphasized in the approach. It is shown that introducing the signal power as the quantitative measure of energy dissipation makes it possible to achieve reasonable results from the optimality point of view as well. The property of structural energy dissipativeness is one of the most important and fundamental features of resulting filters. Therefore, it is natural to call them asymptotic filters. The notion of the asymptotic filter is carried in the paper as a proper tool in order to unify stochastic and non-stochastic, linear and nonlinear approaches to signal filtering.

Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease

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Xiaoli Liu

2018-01-01

Full Text Available Alzheimer’s disease (AD has been not only the substantial financial burden to the health care system but also the emotional burden to patients and their families. Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer’s disease. Recently, the multitask learning (MTL methods with sparsity-inducing norm (e.g., l2,1-norm have been widely studied to select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures. However, these previous works formulate the prediction tasks as a linear regression problem. The major limitation is that they assumed a linear relationship between the MRI features and the cognitive outcomes. Some multikernel-based MTL methods have been proposed and shown better generalization ability due to the nonlinear advantage. We quantify the power of existing linear and nonlinear MTL methods by evaluating their performance on cognitive score prediction of Alzheimer’s disease. Moreover, we extend the traditional l2,1-norm to a more general lql1-norm (q≥1. Experiments on the Alzheimer’s Disease Neuroimaging Initiative database showed that the nonlinear l2,1lq-MKMTL method not only achieved better prediction performance than the state-of-the-art competitive methods but also effectively fused the multimodality data.

Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data

International Nuclear Information System (INIS)

Balabin, Roman M.; Smirnov, Sergey V.

2011-01-01

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm -1 ) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic

On the linear programming bound for linear Lee codes.

Science.gov (United States)

Astola, Helena; Tabus, Ioan

2016-01-01

Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.

Surficial geologic map of Berrien County, Michigan, and the adjacent offshore area of Lake Michigan

Science.gov (United States)

Stone, Byron D.; Kincare, Kevin A.; O'Leary, Dennis W.; Newell, Wayne L.; Taylor, Emily M.; Williams, Van S.; Lundstrom, Scott C.; Abraham, Jared E.; Powers, Michael H.

2017-12-13

The surficial geologic map of Berrien County, southwestern Michigan (sheet 1), shows the distribution of glacial and postglacial deposits at the land surface and in the adjacent offshore area of Lake Michigan. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics, stratigraphic relationships, and age. Drill-hole information correlated in cross sections provides details of typical stratigraphic sequences that compose one or more penetrated geologic map units. A new bedrock geologic map (on sheet 2) includes contours of the altitude of the eroded top of bedrock and shows the distribution of middle Paleozoic shale and carbonate units in the subcrop. A sediment thickness map (also on sheet 2) portrays the extent of as much as 150 meters of surficial materials that overlie the bedrock surface.The major physical features of the county are related principally to deposits of the last Laurentide ice sheet that advanced and then retreated back through the region from about 19,000 to 14,000 radiocarbon years before present. Glacial and postglacial deposits underlie the entire county; shale bedrock crops out only in the adjacent offshore area on the bottom of Lake Michigan. All glacial deposits and glacial meltwater deposits in Berrien County are related to the late Wisconsinan glacial advances of the Lake Michigan ice lobe and its three regional recessional moraines, which cross the county as three north-northeast-trending belts.From east to west (oldest to youngest), the three moraine belts are known as the Kalamazoo, Valparaiso, and Lake Border morainic systems. The till-ridge morainic systems (Lake Border and local Valparaiso morainic systems) consist of multiple, elongate moraine ridges separated by till plains and lake-bottom plains. Tills in ground and end moraines in Berrien County are distinguished as informal units, and are correlated with three proposed regional till units in southwestern Michigan

Oversampling the Minority Class in the Feature Space.

Science.gov (United States)

Perez-Ortiz, Maria; Gutierrez, Pedro Antonio; Tino, Peter; Hervas-Martinez, Cesar

2016-09-01

The imbalanced nature of some real-world data is one of the current challenges for machine learning researchers. One common approach oversamples the minority class through convex combination of its patterns. We explore the general idea of synthetic oversampling in the feature space induced by a kernel function (as opposed to input space). If the kernel function matches the underlying problem, the classes will be linearly separable and synthetically generated patterns will lie on the minority class region. Since the feature space is not directly accessible, we use the empirical feature space (EFS) (a Euclidean space isomorphic to the feature space) for oversampling purposes. The proposed method is framed in the context of support vector machines, where the imbalanced data sets can pose a serious hindrance. The idea is investigated in three scenarios: 1) oversampling in the full and reduced-rank EFSs; 2) a kernel learning technique maximizing the data class separation to study the influence of the feature space structure (implicitly defined by the kernel function); and 3) a unified framework for preferential oversampling that spans some of the previous approaches in the literature. We support our investigation with extensive experiments over 50 imbalanced data sets.

Solitary waves under the competition of linear and nonlinear periodic potentials

International Nuclear Information System (INIS)

Rapti, Z; Kevrekidis, P G; Konotop, V V; Jones, C K R T

2007-01-01

In this paper, we study the competition of the linear and nonlinear lattices and its effects on the stability and dynamics of bright solitary waves. We consider both lattices in a perturbative framework, whereby the technique of Hamiltonian perturbation theory can be used to obtain information about the existence of solutions, and the same approach, as well as eigenvalue count considerations, can be used to obtain detailed conditions about their linear stability. We find that the analytical results are in very good agreement with our numerical findings and can also be used to predict features of the dynamical evolution of such solutions. A particularly interesting result of these considerations is the existence of a tunable cancellation effect between the linear and nonlinear lattices that allows for increased mobility of the solitary wave

A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features

Directory of Open Access Journals (Sweden)

LEI Xiaoqi

2016-02-01

Full Text Available Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds(semi-automatic extraction,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features,is proposed in this paper.Firstly,the image is segmented,and then the linear and curve roads are obtained by using several object shape features,so the method that just only extract linear roads are rectified.Secondly,the step of road extraction is carried out based on the region growth,the road seeds are automatic selected and the road network is extracted.Finally,the extracted roads are regulated by combining the edge information.In experiments,the images that including the better gray uniform of road and the worse illuminated of road surface were chosen,and the results prove that the method of this study is promising.

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach

Directory of Open Access Journals (Sweden)

Humayun Irshad

2013-01-01

Full Text Available Context: According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Aims: The aim is to investigate the various texture features and Hierarchical Model and X (HMAX biologically inspired approach for mitosis detection using machine-learning techniques. Materials and Methods: We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM, and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. Results: The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS dataset provided for an International Conference on Pattern Recognition (ICPR 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Conclusions: Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and

Characterizing Hypervelocity Impact (HVI-Induced Pitting Damage Using Active Guided Ultrasonic Waves: From Linear to Nonlinear

Directory of Open Access Journals (Sweden)

Menglong Liu

2017-05-01

Full Text Available Hypervelocity impact (HVI, ubiquitous in low Earth orbit with an impacting velocity in excess of 1 km/s, poses an immense threat to the safety of orbiting spacecraft. Upon penetration of the outer shielding layer of a typical two-layer shielding system, the shattered projectile, together with the jetted materials of the outer shielding material, subsequently impinge the inner shielding layer, to which pitting damage is introduced. The pitting damage includes numerous craters and cracks disorderedly scattered over a wide region. Targeting the quantitative evaluation of this sort of damage (multitudinous damage within a singular inspection region, a characterization strategy, associating linear with nonlinear features of guided ultrasonic waves, is developed. Linear-wise, changes in the signal features in the time domain (e.g., time-of-flight and energy dissipation are extracted, for detecting gross damage whose characteristic dimensions are comparable to the wavelength of the probing wave; nonlinear-wise, changes in the signal features in the frequency domain (e.g., second harmonic generation, which are proven to be more sensitive than their linear counterparts to small-scale damage, are explored to characterize HVI-induced pitting damage scattered in the inner layer. A numerical simulation, supplemented with experimental validation, quantitatively reveals the accumulation of nonlinearity of the guided waves when the waves traverse the pitting damage, based on which linear and nonlinear damage indices are proposed. A path-based rapid imaging algorithm, in conjunction with the use of the developed linear and nonlinear indices, is developed, whereby the HVI-induced pitting damage is characterized in images in terms of the probability of occurrence.

On the preference of cold RF technology for the international linear collider

Energy Technology Data Exchange (ETDEWEB)

Gamp, A.

2005-07-01

On August 20th 2004 the International Technology Recommendation Panel (ITRP) released its recommendation that the Linear Collider be based on Superconducting RF Technology. Following a request of the organizers of this conference we summarise in this article the arguments worked out and presented by the ITRP, which led to this recommendation. The main features of both RF-technologies, the favoured L-band RF system of the superconducting version of the Linear Collider and the X-band-technology anticipated for the normal-conducting alternative are briefly described. (orig.)

Linear rotary optical delay lines

Science.gov (United States)

Guerboukha, Hichem; Qu, Hang; Skorobogatiy, Maksim

2016-03-01

We present a semi-analytical solution for the design of a high-speed rotary optical delay line that use a combination of two rotating curvilinear reflectors. We demonstrate that it is possible to design an infinite variety of the optical delay lines featuring linear dependence of the optical delay on the rotation angle. This is achieved via shape optimization of the rotating reflector surfaces. Moreover, a convenient spatial separation of the incoming and outgoing beams is possible. For the sake of example, we present blades that fit into a circle of 10cm diameter. Finally, a prototype of a rotary delay line is fabricated using CNC machining, and its optical properties are characterized.

Analysis of photo linear elements, Laramie Mountains, Wyoming

Science.gov (United States)

Blackstone, D. L., Jr.

1973-01-01

The author has identified the following significant results. Photo linear features in the Precambrian rocks of the Laramie Mountains are delineated, and the azimuths plotted on rose diagrams. Three strike directions are dominant, two of which are in the northeast quadrant. Laramide folds in the Laramie basin to the west of the mountains appear to have the same trend, and apparently have been controlled by response of the basement along fractures such as have been measured from the imagery.

Coastal glaciers advanced onto Jameson Land, East Greenland during the late glacial–early Holocene Milne Land Stade

Directory of Open Access Journals (Sweden)

Helena Alexanderson

2014-01-01

Full Text Available We report on 10Be and optically stimulated luminescence ages from moraines and glaciolacustrine sediments on eastern Jameson Land, East Greenland. Sampled landforms and sediment are associated with advances of outlet glaciers from the local Liverpool Land ice cap situated in the coastal Scoresby Sund region. Previous studies have tentatively correlated these advances with the Milne Land Stade moraines, which are prominent moraine sets deposited by mountain glaciers in the inner Scoresby Sund region. Recent constraints on the formation of the outer and inner of these moraines have suggested two advances of local glaciers, one prior to or during the Younger Dryas and another during the Preboreal. In this paper, we test the correlation of the Liverpool Land glacial advance with the Milne Land Stade. Our results show that outlet glaciers from the Liverpool Land ice cap reached ice-marginal positions marked by moraines in east-facing valleys on Jameson Land sometime during late glacial–early Holocene time (ca. 13–11 Kya. This confirms the correlation of these moraines with the Milne Land Stade moraines described elsewhere in the Scoresby Sund region.

Three caveats for linear stability theory: Rayleigh-Benard convection

International Nuclear Information System (INIS)

Greenside, H.S.

1984-06-01

Recent theories and experiments challenge the applicability of linear stability theory near the onset of buoyancy-driven (Rayleigh-Benard) convection. This stability theory, based on small perturbations of infinite parallel rolls, is found to miss several important features of the convective flow. The reason is that the lateral boundaries have a profound influence on the possible wave numbers and flow patterns even for the largest cells studied. Also, the nonlinear growth of incoherent unstable modes distorts the rolls, leading to a spatially disordered and sometimes temporally nonperiodic flow. Finally, the relation of the skewed varicose instability to the onset of turbulence (nonperiodic time dependence) is examined. Linear stability theory may not suffice to predict the onset of time dependence in large cells close to threshold

One-step deterministic multipartite entanglement purification with linear optics

Energy Technology Data Exchange (ETDEWEB)

Sheng, Yu-Bo [Department of Physics, Tsinghua University, Beijing 100084 (China); Long, Gui Lu, E-mail: gllong@tsinghua.edu.cn [Department of Physics, Tsinghua University, Beijing 100084 (China); Center for Atomic and Molecular NanoSciences, Tsinghua University, Beijing 100084 (China); Key Laboratory for Quantum Information and Measurements, Beijing 100084 (China); Deng, Fu-Guo [Department of Physics, Applied Optics Beijing Area Major Laboratory, Beijing Normal University, Beijing 100875 (China)

2012-01-09

We present a one-step deterministic multipartite entanglement purification scheme for an N-photon system in a Greenberger–Horne–Zeilinger state with linear optical elements. The parties in quantum communication can in principle obtain a maximally entangled state from each N-photon system with a success probability of 100%. That is, it does not consume the less-entangled photon systems largely, which is far different from other multipartite entanglement purification schemes. This feature maybe make this scheme more feasible in practical applications. -- Highlights: ► We proposed a deterministic entanglement purification scheme for GHZ states. ► The scheme uses only linear optical elements and has a success probability of 100%. ► The scheme gives a purified GHZ state in just one-step.

Linear algebra

CERN Document Server

Shilov, Georgi E

1977-01-01

Covers determinants, linear spaces, systems of linear equations, linear functions of a vector argument, coordinate transformations, the canonical form of the matrix of a linear operator, bilinear and quadratic forms, Euclidean spaces, unitary spaces, quadratic forms in Euclidean and unitary spaces, finite-dimensional space. Problems with hints and answers.

Sodium flow rate measurement method of annular linear induction pump

International Nuclear Information System (INIS)

Araseki, Hideo

2011-01-01

This report describes a method for measuring sodium flow rate of annular linear induction pumps arranged in parallel and its verification result obtained through an experiment and a numerical analysis. In the method, the leaked magnetic field is measured with measuring coils at the stator end on the outlet side and is correlated with the sodium flow rate. The experimental data and the numerical result indicate that the leaked magnetic field at the stator edge keeps almost constant when the sodium flow rate changes and that the leaked magnetic field change arising from the flow rate change is small compared with the overall leaked magnetic field. It is shown that the correlation between the leaked magnetic field and the sodium flow rate is almost linear due to this feature of the leaked magnetic field, which indicates the applicability of the method to small-scale annular linear induction pumps. (author)

Characteristic Lifetime Of A Polarized Feature In The V=0, J=1-0 Sio Maser VY Canis Majoris

Science.gov (United States)

Rislow, Benjamin; McIntosh, G. C.

2008-05-01

A time series cross correlation analysis has been developed for calculating the characteristic lifetime of linearly polarized features in the spectrum of silicon monoxide masers. Our observations of VY CMa in the v=0, J=1→0; transition from June 2003 to March 2006 revealed a highly linearly polarized feature at Vlsr=18.5 km s-1. Applying the cross correlation to this feature gave a characteristic lifetime of 2800 days. This time is much longer than the v=1, J=2→1; transition's lifetime of 645 days and indicates that the two transitions occur under different physical conditions. This research was supported by the University of Minnesota and the University of Minnesota, Morris.

Search asymmetry: a diagnostic for preattentive processing of separable features.

Science.gov (United States)

Treisman, A; Souther, J

1985-09-01

The search rate for a target among distractors may vary dramatically depending on which stimulus plays the role of target and which that of distractors. For example, the time required to find a circle distinguished by an intersecting line is independent of the number of regular circles in the display, whereas the time to find a regular circle among circles with lines increases linearly with the number of distractors. The pattern of performance suggests parallel processing when the target has a unique distinguishing feature and serial self-terminating search when the target is distinguished only by the absence of a feature that is present in all the distractors. The results are consistent with feature-integration theory (Treisman & Gelade, 1980), which predicts that a single feature should be detected by the mere presence of activity in the relevant feature map, whereas tasks that require subjects to locate multiple instances of a feature demand focused attention. Search asymmetries may therefore offer a new diagnostic to identify the primitive features of early vision. Several candidate features are examined in this article: Colors, line ends or terminators, and closure (in the sense of a partly or wholly enclosed area) appear to be functional features; connectedness, intactness (absence of an intersecting line), and acute angles do not.

Linear and non-linear optics of condensed matter

International Nuclear Information System (INIS)

McLean, T.P.

1977-01-01

Part I - Linear optics: 1. General introduction. 2. Frequency dependence of epsilon(ω, k vector). 3. Wave-vector dependence of epsilon(ω, k vector). 4. Tensor character of epsilon(ω, k vector). Part II - Non-linear optics: 5. Introduction. 6. A classical theory of non-linear response in one dimension. 7. The generalization to three dimensions. 8. General properties of the polarizability tensors. 9. The phase-matching condition. 10. Propagation in a non-linear dielectric. 11. Second harmonic generation. 12. Coupling of three waves. 13. Materials and their non-linearities. 14. Processes involving energy exchange with the medium. 15. Two-photon absorption. 16. Stimulated Raman effect. 17. Electro-optic effects. 18. Limitations of the approach presented here. (author)

Hyperbolicity and constrained evolution in linearized gravity

International Nuclear Information System (INIS)

Matzner, Richard A.

2005-01-01

Solving the 4-d Einstein equations as evolution in time requires solving equations of two types: the four elliptic initial data (constraint) equations, followed by the six second order evolution equations. Analytically the constraint equations remain solved under the action of the evolution, and one approach is to simply monitor them (unconstrained evolution). Since computational solution of differential equations introduces almost inevitable errors, it is clearly 'more correct' to introduce a scheme which actively maintains the constraints by solution (constrained evolution). This has shown promise in computational settings, but the analysis of the resulting mixed elliptic hyperbolic method has not been completely carried out. We present such an analysis for one method of constrained evolution, applied to a simple vacuum system, linearized gravitational waves. We begin with a study of the hyperbolicity of the unconstrained Einstein equations. (Because the study of hyperbolicity deals only with the highest derivative order in the equations, linearization loses no essential details.) We then give explicit analytical construction of the effect of initial data setting and constrained evolution for linearized gravitational waves. While this is clearly a toy model with regard to constrained evolution, certain interesting features are found which have relevance to the full nonlinear Einstein equations

(2,0)-Super-Yang-Mills coupled to non-linear {sigma}-model

Energy Technology Data Exchange (ETDEWEB)

Goes-Negrao, M.S.; Penna-Firme, A.B. [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil); Negrao, M.R. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Inst. de Fisica

1999-07-01

Considering a class of (2,0)-super yang-Mills multiplets that accommodate a pair of independent gauge potentials in connection with a single symmetry group, we present here their coupling to ordinary matter to non-linear {sigma}-models in (2,0)-superspace. The dynamics and the coupling of the gauge potentials are discussed and the interesting feature that comes out is a sort of chirality for one of the gauge potentials are discussed and the interesting feature that comes out is a sort of chirality for one of the gauge potentials once light-cone coordinates are chosen. (author)

(2,0)-Super-Yang-Mills coupled to non-linear σ-model

International Nuclear Information System (INIS)

Goes-Negrao, M.S.; Penna-Firme, A.B.; Negrao, M.R.

1999-07-01

Considering a class of (2,0)-super yang-Mills multiplets that accommodate a pair of independent gauge potentials in connection with a single symmetry group, we present here their coupling to ordinary matter to non-linear σ-models in (2,0)-superspace. The dynamics and the coupling of the gauge potentials are discussed and the interesting feature that comes out is a sort of chirality for one of the gauge potentials are discussed and the interesting feature that comes out is a sort of chirality for one of the gauge potentials once light-cone coordinates are chosen. (author)

Neurons in the thalamic reticular nucleus are selective for diverse and complex visual features

Science.gov (United States)

Vaingankar, Vishal; Soto-Sanchez, Cristina; Wang, Xin; Sommer, Friedrich T.; Hirsch, Judith A.

2012-01-01

All visual signals the cortex receives are influenced by the perigeniculate sector (PGN) of the thalamic reticular nucleus, which receives input from relay cells in the lateral geniculate and provides feedback inhibition in return. Relay cells have been studied in quantitative depth; they behave in a roughly linear fashion and have receptive fields with a stereotyped center-surround structure. We know far less about reticular neurons. Qualitative studies indicate they simply pool ascending input to generate non-selective gain control. Yet the perigeniculate is complicated; local cells are densely interconnected and fire lengthy bursts. Thus, we employed quantitative methods to explore the perigeniculate using relay cells as controls. By adapting methods of spike-triggered averaging and covariance analysis for bursts, we identified both first and second order features that build reticular receptive fields. The shapes of these spatiotemporal subunits varied widely; no stereotyped pattern emerged. Companion experiments showed that the shape of the first but not second order features could be explained by the overlap of On and Off inputs to a given cell. Moreover, we assessed the predictive power of the receptive field and how much information each component subunit conveyed. Linear-non-linear (LN) models including multiple subunits performed better than those made with just one; further each subunit encoded different visual information. Model performance for reticular cells was always lesser than for relay cells, however, indicating that reticular cells process inputs non-linearly. All told, our results suggest that the perigeniculate encodes diverse visual features to selectively modulate activity transmitted downstream. PMID:23269915

Facial expression recognition in the wild based on multimodal texture features

Science.gov (United States)

Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

2016-11-01

Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

Face Alignment via Regressing Local Binary Features.

Science.gov (United States)

Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian

2016-03-01

This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.

A study on linear and nonlinear Schrodinger equations by the variational iteration method

International Nuclear Information System (INIS)

Wazwaz, Abdul-Majid

2008-01-01

In this work, we introduce a framework to obtain exact solutions to linear and nonlinear Schrodinger equations. The He's variational iteration method (VIM) is used for analytic treatment of these equations. Numerical examples are tested to show the pertinent features of this method

Non-linear nuclear engineering models as genetic programming application; Modelos nao-lineares de engenharia nuclear como aplicacao de programacao genetica

Energy Technology Data Exchange (ETDEWEB)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

1997-12-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.

Stacked Denoise Autoencoder Based Feature Extraction and Classification for Hyperspectral Images

Directory of Open Access Journals (Sweden)

Chen Xing

2016-01-01

Full Text Available Deep learning methods have been successfully applied to learn feature representations for high-dimensional data, where the learned features are able to reveal the nonlinear properties exhibited in the data. In this paper, deep learning method is exploited for feature extraction of hyperspectral data, and the extracted features can provide good discriminability for classification task. Training a deep network for feature extraction and classification includes unsupervised pretraining and supervised fine-tuning. We utilized stacked denoise autoencoder (SDAE method to pretrain the network, which is robust to noise. In the top layer of the network, logistic regression (LR approach is utilized to perform supervised fine-tuning and classification. Since sparsity of features might improve the separation capability, we utilized rectified linear unit (ReLU as activation function in SDAE to extract high level and sparse features. Experimental results using Hyperion, AVIRIS, and ROSIS hyperspectral data demonstrated that the SDAE pretraining in conjunction with the LR fine-tuning and classification (SDAE_LR can achieve higher accuracies than the popular support vector machine (SVM classifier.

Non-linear spin transport in magnetic semiconductor superlattices

International Nuclear Information System (INIS)

Bejar, Manuel; Sanchez, David; Platero, Gloria; MacDonald, A.H.

2004-01-01

The electronic spin dynamics in DC-biased n-doped II-VI semiconductor multiquantum wells doped with magnetic impurities is presented. Under certain range of electronic doping, conventional semiconductor superlattices present self-sustained oscillations. Magnetically doped wells (Mn) present large spin splittings due to the exchange interaction. The interplay between non-linear interwell transport, the electron-electron interaction and the exchange between electrons and the magnetic impurities produces interesting time-dependent features in the spin polarization current tuned by an external magnetic field

Linearity and Non-linearity of Photorefractive effect in Materials ...

African Journals Online (AJOL)

In this paper we have studied the Linearity and Non-linearity of Photorefractive effect in materials using the band transport model. For low light beam intensities the change in the refractive index is proportional to the electric field for linear optics while for non- linear optics the change in refractive index is directly proportional ...

Non-linear neutron star oscillations viewed as deviations from an equilibrium state

International Nuclear Information System (INIS)

Sperhake, U

2002-01-01

A numerical technique is presented which facilitates the evolution of non-linear neutron star oscillations with a high accuracy essentially independent of the oscillation amplitude. We apply this technique to radial neutron star oscillations in a Lagrangian formulation and demonstrate the superior performance of the new scheme compared with 'conventional' techniques. The key feature of our approach is to describe the evolution in terms of deviations from an equilibrium configuration. In contrast to standard perturbation analysis we keep all higher order terms in the evolution equations and thus obtain a fully non-linear description. The advantage of our scheme lies in the elimination of background terms from the equations and the associated numerical errors. The improvements thus achieved will be particularly significant in the study of mildly non-linear effects where the amplitude of the dynamic signal is small compared with the equilibrium values but large enough to warrant non-linear effects. We apply the new technique to the study of non-linear coupling of Eigenmodes and non-linear effects in the oscillations of marginally stable neutron stars. We find non-linear effects in low amplitude oscillations to be particularly pronounced in the range of modes with vanishing frequency which typically mark the onset of instability. (author)

Quantum features of natural cellular automata

International Nuclear Information System (INIS)

Elze, Hans-Thomas

2016-01-01

Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schrödinger equation. This includes corresponding conservation laws. The class of “natural” Hamiltonian cellular automata is based exclusively on integer-valued variables and couplings and their dynamics derives from an Action Principle. They can be mapped reversibly to continuum models by applying Sampling Theory. Thus, “deformed” quantum mechanical models with a finite discreteness scale l are obtained, which for l → 0 reproduce familiar continuum results. We have recently demonstrated that such automata can form “multipartite” systems consistently with the tensor product structures of nonrelativistic many-body quantum mechanics, while interacting and maintaining the linear evolution. Consequently, the Superposition Principle fully applies for such primitive discrete deterministic automata and their composites and can produce the essential quantum effects of interference and entanglement. (paper)

General mirror pairs for gauged linear sigma models

Energy Technology Data Exchange (ETDEWEB)

Aspinwall, Paul S.; Plesser, M. Ronen [Departments of Mathematics and Physics, Duke University,Box 90320, Durham, NC 27708-0320 (United States)

2015-11-05

We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

General mirror pairs for gauged linear sigma models

International Nuclear Information System (INIS)

Aspinwall, Paul S.; Plesser, M. Ronen

2015-01-01

We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

Sustainable agriculture and soil conservation

DEFF Research Database (Denmark)

Olsen, Preben; Dubgaard, Alex

, sandy soils in the West, (that had not been covered by ice) from more fertile soils being mostly sandy loams and finer textured soils covering the Eastern part of the study area. Several geological features such as pitting due to dead ice formation, smaller, terminal moraines in association with melt......, separate the moraine plateau. From the plateau several, minor erosion valleys, formed at the end of the glaciation some 10,000 years ago, feed into the two valleys. Very accurate soil type information is available for the area as intensive measurements within the area has formed the basis for a new...... methodology for soil classification in Denmark. The soil survey included a detailed mapping at field level, using the electromagnetic sensor, EM38. A high-resolution digital elevation model, obtained by use of laser scanning, is available for the study area. The original scanning has a horizontal resolution...

Alzheimer's Disease Detection by Pseudo Zernike Moment and Linear Regression Classification.

Science.gov (United States)

Wang, Shui-Hua; Du, Sidan; Zhang, Yin; Phillips, Preetha; Wu, Le-Nan; Chen, Xian-Qing; Zhang, Yu-Dong

2017-01-01

This study presents an improved method based on "Gorji et al. Neuroscience. 2015" by introducing a relatively new classifier-linear regression classification. Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. Our method performs better than Gorji's approach and five other state-of-the-art approaches. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Late Pleistocene glaciations of the arid subtropical Andes and new results from the Chajnantor Plateau, northern Chile

Science.gov (United States)

Ward, Dylan J.; Cesta, Jason M.; Galewsky, Joseph; Sagredo, Esteban

2015-11-01

The spatiotemporal pattern of glaciation along the Andes Mountains is an important proxy record reflecting the varying influence of global and regional circulation features on South American climate. However, the timing and extent of glaciation in key parts of the orogen, particularly the deglaciated arid Andes, are poorly constrained. We present new cosmogenic 10Be and 36Cl exposure ages for glacial features on and near the Chajnantor Plateau (23 °S). The new dates, although scattered due to cosmogenic inheritance, imply that the most recent extensive glacial occupation ended before or during the global Last Glacial Maximum (LGM). We discuss this new record in the context of published glacial chronologies from glacial features in Peru, Bolivia, and northern Chile rescaled using the latest cosmogenic 10Be production rate calibration for the tropical Andes. The results imply regionally synchronous moraine stabilization ca. 25-40 ka, 15-17 ka, and 12-14 ka, with the youngest of these moraines absent in records south of ∼20 °S, including in our new Chajnantor area chronology. This spatial pattern implicates easterly moisture in generating sufficient snowfall to glaciate the driest parts of the Andes, while allowing a role for westerly moisture, possibly modulated by the migration of the Southern Westerly Wind belt, in the regions near and south of the Atacama Desert.

Electronic structure of graphene beyond the linear dispersion regime

OpenAIRE

POWER, STEPHEN; FERREIRA, MAURO

2011-01-01

PUBLISHED Among the many interesting features displayed by graphene, one of the most attractive is the simplicity with which its electronic structure can be described. The study of its physical properties is significantly simplified by the linear dispersion relation of electrons in a narrow range around the Fermi level. Unfortunately, the mathematical simplicity of graphene electrons is limited only to this narrow energy region and is not very practical when dealing with problems that invo...

An improved feature extraction algorithm based on KAZE for multi-spectral image

Science.gov (United States)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Improving the Separability of Deep Features with Discriminative Convolution Filters for RSI Classification

Directory of Open Access Journals (Sweden)

Na Liu

2018-03-01

Full Text Available The extraction of activation vectors (or deep features from the fully connected layers of a convolutional neural network (CNN model is widely used for remote sensing image (RSI representation. In this study, we propose to learn discriminative convolution filter (DCF based on class-specific separability criteria for linear transformation of deep features. In particular, two types of pretrained CNN called CaffeNet and VGG-VD16 are introduced to illustrate the generality of the proposed DCF. The activation vectors extracted from the fully connected layers of a CNN are rearranged into the form of an image matrix, from which a spatial arrangement of local patches is extracted using sliding window strategy. DCF learning is then performed on each local patch individually to obtain the corresponding discriminative convolution kernel through generalized eigenvalue decomposition. The proposed DCF learning characterizes that a convolutional kernel with small size (e.g., 3 × 3 pixels can be effectively learned on a small-size local patch (e.g., 8 × 8 pixels, thereby ensuring that the linear transformation of deep features can maintain low computational complexity. Experiments on two RSI datasets demonstrate the effectiveness of DCF in improving the classification performances of deep features without increasing dimensionality.

Quantifying the contribution of the root system of alpine vegetation in the soil aggregate stability of moraine

Directory of Open Access Journals (Sweden)

Csilla Hudek

2017-03-01

Full Text Available One fifth of the world's population is living in mountains or in their surrounding areas. This anthropogenic pressure continues to grow with the increasing number of settlements, especially in areas connected to touristic activities, such as the Italian Alps. The process of soil formation on high mountains is particularly slow and these soils are particularly vulnerable to soil degradation. In alpine regions, extreme meteorological events are increasingly frequent due to climate change, speeding up the process of soil degradation and increasing the number of severe erosion processes, shallow landslides and debris flows. Vegetation cover plays a crucial role in the stabilization of mountain soils thereby reducing the risk of natural hazards effecting downslope areas. Soil aggregate stability is one of the main soil properties that can be linked to soil loss processes. Soils developed on moraines in recently deglaciated areas typically have low levels of soil aggregation, and a limited or discontinuous vegetation cover making them more susceptible to degradation. However, soil structure can be influenced by the root system of the vegetation. Roots are actively involved in the formation of water-stable soil aggregation, increasing the stability of the soil and its nutrient content. In the present study, we aim to quantify the effect of the root system of alpine vegetation on the soil aggregate stability of the forefield of the Lys glacier, in the Aosta Valley (NW-Italy. This proglacial area provides the opportunity to study how the root system of ten pioneer alpine species from different successional stages can contribute to soil development and soil stabilization. To quantify the aggregate stability of root permeated soils, a modified wet sieving method was employed. The root length per soil volume of the different species was also determined and later correlated with the aggregate stability results. The results showed that soil aggregate

Urolinin: The First Linear Peptidic Urotensin-II Receptor Agonist.

Science.gov (United States)

Bandholtz, Sebastian; Erdmann, Sarah; von Hacht, Jan Lennart; Exner, Samantha; Krause, Gerd; Kleinau, Gunnar; Grötzinger, Carsten

2016-11-23

This study investigated the role of individual U-II amino acid positions and side chain characteristics important for U-IIR activation. A complete permutation library of 209 U-II variants was studied in an activity screen that contained single substitution variants of each position with one of the other 19 proteinogenic amino acids. Receptor activation was measured using a cell-based high-throughput fluorescence calcium mobilization assay. We generated the first complete U-II substitution map for U-II receptor activation, resulting in a detailed view into the structural features required for receptor activation, accompanied by complementary information from receptor modeling and ligand docking studies. On the basis of the systematic SAR study of U-II, we created 33 further short and linear U-II variants from eight to three amino acids in length, including d- and other non-natural amino acids. We identified the first high-potency linear U-II analogues. Urolinin, a linear U-II agonist (nWWK-Tyr(3-NO 2 )-Abu), shows low nanomolar potency as well as improved metabolic stability.

Beam dynamics in the final focus section of the future linear collider

CERN Document Server

AUTHOR|(SzGeCERN)739431; TOMAS, Rogelio

The exploration of new physics in the ``Tera electron-Volt''~(TeV) scale with precision measurements requires lepton colliders providing high luminosities to obtain enough statistics for the particle interaction analysis. In order to achieve design luminosity values, linear colliders feature nanometer beam spot sizes at the Interaction~Point~(IP).\\par In addition to several effects affecting the luminosity, three main issues to achieve the beam size demagnification in the Final Focus Section (FFS) of the accelerator are the chromaticity correction, the synchrotron radiation effects and the correction of the lattice errors.\\par This thesis considers two important aspects for linear colliders: push the limits of linear colliders design, in particular the chromaticity correction and the radiation effects at 3~TeV, and the instrumentation and experimental work on beam stabilization in a test facility.\\par The current linear collider projects, CLIC~\\cite{CLICdes} and ILC~\\cite{ILCdes}, have lattices designed using...

Tracking Electroencephalographic Changes Using Distributions of Linear Models: Application to Propofol-Based Depth of Anesthesia Monitoring.

Science.gov (United States)

Kuhlmann, Levin; Manton, Jonathan H; Heyse, Bjorn; Vereecke, Hugo E M; Lipping, Tarmo; Struys, Michel M R F; Liley, David T J

2017-04-01

Tracking brain states with electrophysiological measurements often relies on short-term averages of extracted features and this may not adequately capture the variability of brain dynamics. The objective is to assess the hypotheses that this can be overcome by tracking distributions of linear models using anesthesia data, and that anesthetic brain state tracking performance of linear models is comparable to that of a high performing depth of anesthesia monitoring feature. Individuals' brain states are classified by comparing the distribution of linear (auto-regressive moving average-ARMA) model parameters estimated from electroencephalographic (EEG) data obtained with a sliding window to distributions of linear model parameters for each brain state. The method is applied to frontal EEG data from 15 subjects undergoing propofol anesthesia and classified by the observers assessment of alertness/sedation (OAA/S) scale. Classification of the OAA/S score was performed using distributions of either ARMA parameters or the benchmark feature, Higuchi fractal dimension. The highest average testing sensitivity of 59% (chance sensitivity: 17%) was found for ARMA (2,1) models and Higuchi fractal dimension achieved 52%, however, no statistical difference was observed. For the same ARMA case, there was no statistical difference if medians are used instead of distributions (sensitivity: 56%). The model-based distribution approach is not necessarily more effective than a median/short-term average approach, however, it performs well compared with a distribution approach based on a high performing anesthesia monitoring measure. These techniques hold potential for anesthesia monitoring and may be generally applicable for tracking brain states.

Special set linear algebra and special set fuzzy linear algebra

OpenAIRE

Kandasamy, W. B. Vasantha; Smarandache, Florentin; Ilanthenral, K.

2009-01-01

The authors in this book introduce the notion of special set linear algebra and special set fuzzy Linear algebra, which is an extension of the notion set linear algebra and set fuzzy linear algebra. These concepts are best suited in the application of multi expert models and cryptology. This book has five chapters. In chapter one the basic concepts about set linear algebra is given in order to make this book a self contained one. The notion of special set linear algebra and their fuzzy analog...

High Field Linear Magnetoresistance Sensors with Perpendicular Anisotropy L10-FePt Reference Layer

Directory of Open Access Journals (Sweden)

X. Liu

2016-01-01

Full Text Available High field linear magnetoresistance is an important feature for magnetic sensors applied in magnetic levitating train and high field positioning measurements. Here, we investigate linear magnetoresistance in Pt/FePt/ZnO/Fe/Pt multilayer magnetic sensor, where FePt and Fe ferromagnetic layers exhibit out-of-plane and in-plane magnetic anisotropy, respectively. Perpendicular anisotropy L10-FePt reference layer with large coercivity and high squareness ratio was obtained by in situ substrate heating. Linear magnetoresistance is observed in this sensor in a large range between +5 kOe and −5 kOe with the current parallel to the film plane. This L10-FePt based sensor is significant for the expansion of linear range and the simplification of preparation for future high field magnetic sensors.

Applicability of computer-aided comprehensive tool (LINDA: LINeament Detection and Analysis) and shaded digital elevation model for characterizing and interpreting morphotectonic features from lineaments

Science.gov (United States)

Masoud, Alaa; Koike, Katsuaki

2017-09-01

Detection and analysis of linear features related to surface and subsurface structures have been deemed necessary in natural resource exploration and earth surface instability assessment. Subjectivity in choosing control parameters required in conventional methods of lineament detection may cause unreliable results. To reduce this ambiguity, we developed LINDA (LINeament Detection and Analysis), an integrated tool with graphical user interface in Visual Basic. This tool automates processes of detection and analysis of linear features from grid data of topography (digital elevation model; DEM), gravity and magnetic surfaces, as well as data from remote sensing imagery. A simple interface with five display windows forms a user-friendly interactive environment. The interface facilitates grid data shading, detection and grouping of segments, lineament analyses for calculating strike and dip and estimating fault type, and interactive viewing of lineament geometry. Density maps of the center and intersection points of linear features (segments and lineaments) are also included. A systematic analysis of test DEMs and Landsat 7 ETM+ imagery datasets in the North and South Eastern Deserts of Egypt is implemented to demonstrate the capability of LINDA and correct use of its functions. Linear features from the DEM are superior to those from the imagery in terms of frequency, but both linear features agree with location and direction of V-shaped valleys and dykes and reference fault data. Through the case studies, LINDA applicability is demonstrated to highlight dominant structural trends, which can aid understanding of geodynamic frameworks in any region.

Online feature selection with streaming features.

Science.gov (United States)

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

Radiographic Features of Acute Patellar Tendon Rupture.

Science.gov (United States)

Fazal, Muhammad Ali; Moonot, Pradeep; Haddad, Fares

2015-11-01

The purpose of our study was to assess soft tissue features of acute patellar tendon rupture on lateral knee radiograph that would facilitate early diagnosis. The participants were divided into two groups of 35 patients each. There were 28 men and seven women with a mean age of 46 years in the control group and 26 men and nine women with a mean age of 47 years in the rupture group. The lateral knee radiograph of each patient was evaluated for Insall-Salvati ratio for patella alta, increased density of the infrapatellar fat pad, appearance of the soft tissue margin of the patellar tendon and bony avulsions. In the rupture group there were three consistent soft tissue radiographic features in addition to patellar alta. These were increased density of infrapatellar fat pad; loss of sharp, well-defined linear margins of the patellar tendon and angulated wavy margin of the patellar tendon while in the control group these features were not observed. The soft tissue radiographic features described in the rupture group are consistent and reliable. When coupled with careful clinical assessment, these will aid in early diagnosis and further imaging will be seldom required. © 2015 Chinese Orthopaedic Association and Wiley Publishing Asia Pty Ltd.

The study of interferometer spectrometer based on DSP and linear CCD

Science.gov (United States)

Kang, Hua; Peng, Yuexiang; Xu, Xinchen; Xing, Xiaoqiao

2010-11-01

In this paper, general theory of Fourier-transform spectrometer and polarization interferometer is presented. A new design is proposed for Fourier-transform spectrometer based on polarization interferometer with Wollaston prisms and linear CCD. Firstly, measured light is changed into linear polarization light by polarization plate. And then the light can be split into ordinary and extraordinary lights by going through one Wollaston prism. At last, after going through another Wollaston prism and analyzer, interfering fringes can be formed on linear CCD behind the analyzer. The linear CCD is driven by CPLD to output amplitude of interfering fringes and synchronous signals of frames and pixels respectively. DSP is used to collect interference pattern signals from CCD and the digital data of interfering fringes are processed by using 2048-point-FFT. Finally, optical spectrum of measured light can be display on LCD connected to DSP with RS232. The spectrometer will possess the features of firmness, portability and the ability of real-time analyzing. The work will provide a convenient and significant foundation for application of more high accuracy of Fourier-transform spectrometer.

AGSuite: Software to conduct feature analysis of artificial grammar learning performance.

Science.gov (United States)

Cook, Matthew T; Chubala, Chrissy M; Jamieson, Randall K

2017-10-01

To simplify the problem of studying how people learn natural language, researchers use the artificial grammar learning (AGL) task. In this task, participants study letter strings constructed according to the rules of an artificial grammar and subsequently attempt to discriminate grammatical from ungrammatical test strings. Although the data from these experiments are usually analyzed by comparing the mean discrimination performance between experimental conditions, this practice discards information about the individual items and participants that could otherwise help uncover the particular features of strings associated with grammaticality judgments. However, feature analysis is tedious to compute, often complicated, and ill-defined in the literature. Moreover, the data violate the assumption of independence underlying standard linear regression models, leading to Type I error inflation. To solve these problems, we present AGSuite, a free Shiny application for researchers studying AGL. The suite's intuitive Web-based user interface allows researchers to generate strings from a database of published grammars, compute feature measures (e.g., Levenshtein distance) for each letter string, and conduct a feature analysis on the strings using linear mixed effects (LME) analyses. The LME analysis solves the inflation of Type I errors that afflicts more common methods of repeated measures regression analysis. Finally, the software can generate a number of graphical representations of the data to support an accurate interpretation of results. We hope the ease and availability of these tools will encourage researchers to take full advantage of item-level variance in their datasets in the study of AGL. We moreover discuss the broader applicability of the tools for researchers looking to conduct feature analysis in any field.

Optimizing methods for linking cinematic features to fMRI data.

Science.gov (United States)

Kauttonen, Janne; Hlushchuk, Yevhen; Tikka, Pia

2015-04-15

One of the challenges of naturalistic neurosciences using movie-viewing experiments is how to interpret observed brain activations in relation to the multiplicity of time-locked stimulus features. As previous studies have shown less inter-subject synchronization across viewers of random video footage than story-driven films, new methods need to be developed for analysis of less story-driven contents. To optimize the linkage between our fMRI data collected during viewing of a deliberately non-narrative silent film 'At Land' by Maya Deren (1944) and its annotated content, we combined the method of elastic-net regularization with the model-driven linear regression and the well-established data-driven independent component analysis (ICA) and inter-subject correlation (ISC) methods. In the linear regression analysis, both IC and region-of-interest (ROI) time-series were fitted with time-series of a total of 36 binary-valued and one real-valued tactile annotation of film features. The elastic-net regularization and cross-validation were applied in the ordinary least-squares linear regression in order to avoid over-fitting due to the multicollinearity of regressors, the results were compared against both the partial least-squares (PLS) regression and the un-regularized full-model regression. Non-parametric permutation testing scheme was applied to evaluate the statistical significance of regression. We found statistically significant correlation between the annotation model and 9 ICs out of 40 ICs. Regression analysis was also repeated for a large set of cubic ROIs covering the grey matter. Both IC- and ROI-based regression analyses revealed activations in parietal and occipital regions, with additional smaller clusters in the frontal lobe. Furthermore, we found elastic-net based regression more sensitive than PLS and un-regularized regression since it detected a larger number of significant ICs and ROIs. Along with the ISC ranking methods, our regression analysis proved

Understanding Legacy Features with Featureous

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...

ALPS - A LINEAR PROGRAM SOLVER

Science.gov (United States)

Viterna, L. A.

1994-01-01

Linear programming is a widely-used engineering and management tool. Scheduling, resource allocation, and production planning are all well-known applications of linear programs (LP's). Most LP's are too large to be solved by hand, so over the decades many computer codes for solving LP's have been developed. ALPS, A Linear Program Solver, is a full-featured LP analysis program. ALPS can solve plain linear programs as well as more complicated mixed integer and pure integer programs. ALPS also contains an efficient solution technique for pure binary (0-1 integer) programs. One of the many weaknesses of LP solvers is the lack of interaction with the user. ALPS is a menu-driven program with no special commands or keywords to learn. In addition, ALPS contains a full-screen editor to enter and maintain the LP formulation. These formulations can be written to and read from plain ASCII files for portability. For those less experienced in LP formulation, ALPS contains a problem "parser" which checks the formulation for errors. ALPS creates fully formatted, readable reports that can be sent to a printer or output file. ALPS is written entirely in IBM's APL2/PC product, Version 1.01. The APL2 workspace containing all the ALPS code can be run on any APL2/PC system (AT or 386). On a 32-bit system, this configuration can take advantage of all extended memory. The user can also examine and modify the ALPS code. The APL2 workspace has also been "packed" to be run on any DOS system (without APL2) as a stand-alone "EXE" file, but has limited memory capacity on a 640K system. A numeric coprocessor (80X87) is optional but recommended. The standard distribution medium for ALPS is a 5.25 inch 360K MS-DOS format diskette. IBM, IBM PC and IBM APL2 are registered trademarks of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation.

A regression-based Kansei engineering system based on form feature lines for product form design

Directory of Open Access Journals (Sweden)

Yan Xiong

2016-06-01

Full Text Available When developing new products, it is important for a designer to understand users’ perceptions and develop product form with the corresponding perceptions. In order to establish the mapping between users’ perceptions and product design features effectively, in this study, we presented a regression-based Kansei engineering system based on form feature lines for product form design. First according to the characteristics of design concept representation, product form features–product form feature lines were defined. Second, Kansei words were chosen to describe image perceptions toward product samples. Then, multiple linear regression and support vector regression were used to construct the models, respectively, that predicted users’ image perceptions. Using mobile phones as experimental samples, Kansei prediction models were established based on the front view form feature lines of the samples. From the experimental results, these two predict models were of good adaptability. But in contrast to multiple linear regression, the predict performance of support vector regression model was better, and support vector regression is more suitable for form regression prediction. The results of the case showed that the proposed method provided an effective means for designers to manipulate product features as a whole, and it can optimize Kansei model and improve practical values.

Nonlinear smooth orthogonal decomposition of kinematic features of sawing reconstructs muscle fatigue evolution as indicated by electromyography.

Science.gov (United States)

Segala, David B; Gates, Deanna H; Dingwell, Jonathan B; Chelidze, David

2011-03-01

Tracking or predicting physiological fatigue is important for developing more robust training protocols and better energy supplements and/or reducing muscle injuries. Current methodologies are usually impractical and/or invasive and may not be realizable outside of laboratory settings. It was recently demonstrated that smooth orthogonal decomposition (SOD) of phase space warping (PSW) features of motion kinematics can identify fatigue in individual muscle groups. We hypothesize that a nonlinear extension of SOD will identify more optimal fatigue coordinates and provide a lower-dimensional reconstruction of local fatigue dynamics than the linear SOD. Both linear and nonlinear SODs were applied to PSW features estimated from measured kinematics to reconstruct muscle fatigue dynamics in subjects performing a sawing motion. Ten healthy young right-handed subjects pushed a weighted handle back and forth until voluntary exhaustion. Three sets of joint kinematic angles were measured from the right upper extremity in addition to surface electromyography (EMG) recordings. The SOD coordinates of kinematic PSW features were compared against independently measured fatigue markers (i.e., mean and median EMG spectrum frequencies of individual muscle groups). This comparison was based on a least-squares linear fit of a fixed number of the dominant SOD coordinates to the appropriate local fatigue markers. Between subject variability showed that at most four to five nonlinear SOD coordinates were needed to reconstruct fatigue in local muscle groups, while on average 15 coordinates were needed for the linear SOD. Thus, the nonlinear coordinates provided a one-order-of-magnitude improvement over the linear ones.

Quasi-linear theory for a tokamak plasma in the presence of cyclotron resonance

International Nuclear Information System (INIS)

Belikov, V.S.; Kolesnichenko, Ya.I.

1993-01-01

Quasi-linear diffusion equations for the distribution function of trapped and circulating particles interacting with waves in a tokamak by means of cyclotron resonance are derived. The resulting equations reveal new features of quasi-linear diffusion and are of two kinds, one which involves bounce resonances overlapping in velocity space and one with well separated bounce resonances. These two cases correspond to situations where the phase of the wave-particle interaction between successive resonances can be considered as random or deterministic, respectively. An analysis of the conditions of applicability of the new equations is carried out and previous well-known forms of the quasi-linear diffusion equations are shown to be recovered in the proper limits. (10 refs., 3 figs.)

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Science.gov (United States)

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Directory of Open Access Journals (Sweden)

Guan Yu

Full Text Available Accurately identifying mild cognitive impairment (MCI individuals who will progress to Alzheimer's disease (AD is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI and fluorodeoxyglucose positron emission tomography (FDG-PET. However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI subjects and 226 stable MCI (sMCI subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images and also the single-task classification method (using only MRI or only subjects with both MRI and

Analysis of a cryolava flow-like feature on Titan

Science.gov (United States)

Le, Corre L.; Le, Mouelic S.; Sotin, Christophe; Combe, J.-P.; Rodriguez, S.; Barnes, J.W.; Brown, R.H.; Buratti, B.J.; Jaumann, R.; Soderblom, J.; Soderblom, L.A.; Clark, R.; Baines, K.H.; Nicholson, P.D.

2009-01-01

This paper reports on the analysis of the highest spatial resolution hyperspectral images acquired by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini spacecraft during its prime mission. A bright area matches a flow-like feature coming out of a caldera-like feature observed in Synthetic Aperture Radar (SAR) data recorded by the Cassini radar experiment [Lopes et al., 2007. Cryovolcanic features on Titan's surface as revealed by the Cassini Titan Radar Mapper. Icarus 186, 395-412, doi:10.1016/j.icarus.2006.09.006]. In this SAR image, the flow extends about 160 km east of the caldera. The contrast in brightness between the flow and the surroundings progressively vanishes, suggesting alteration or evolution of the composition of the cryolava during the lifetime of the eruptions. Dunes seem to cover part of this flow on its eastern end. We analyze the different terrains using the Spectral Mixing Analysis (SMA) approach of the Multiple-Endmember Linear Unmixing Model (MELSUM, Combe et al., 2008). The study area can be fully modeled by using only two types of terrains. Then, the VIMS spectra are compared with laboratory spectra of known materials in the relevant atmospheric windows (from 1 to 2.78 ??m). We considered simple molecules that could be produced during cryovolcanic events, including H2O, CO2 (using two different grain sizes), CH4 and NH3. We find that the mean spectrum of the cryoflow-like feature is not consistent with pure water ice. It can be best fitted by linear combinations of spectra of the candidate materials, showing that its composition is compatible with a mixture of H2O, CH4 and CO2.. ?? 2009 Elsevier Ltd.

Issues relating to classification of colluvial soils in young morainic areas (Chełmno and Brodnica Lake District, northern Poland

Directory of Open Access Journals (Sweden)

Świtoniak Marcin

2015-06-01

Full Text Available Colluvial soils (in Polish: gleby deluwialne are an important part of the soil cover in young morainic landscapes of northern Poland. They evolved as a result of the accumulation of eroded material at the foot of the slopes and bottoms of closed depressions. The aim of this study was to determine the systematic position of colluvial soils commonly found in the Chełmno and Brodnica Lake District, northern Poland. Ten soil pits located in different types of landscapes were selected for testing soil properties. The colluvial material is characterized by diversified properties: thickness, particle-size distribution, organic carbon content, color, pH, and base saturation. As a result, the investigated soils represent broad spectrum of typological units according to Polish Soil Classification (2011. Some of them contain epipedons mollic and meet the criteria of colluvial chernozemic soils. They were found mainly on buried black earths in areas with small slope inclinations. Many pedons contain pale colored acidic colluvial material with low base saturation and low organic carbon content and must be classified as other types: arenosols (in Polish: arenosole or rusty soils (in Polish: gleby rdzawe. These soils occur mostly in areas with intensive relief and overlay the different soil types, including rusty soil and organic soils. They are formed as a result of soils lessivés and rusty soils truncation. An introduction of the additional units of “proper colluvial soils” which have epipedon ochric, and “rusty-colluvial soils” with endopedon sideric to the next edition of Polish Soil Classification would enable a more precise expression of the genesis of these soils in the type rank. Moreover, the definition of chernozemic colluvial soils could be extended to colluvial soils with umbric horizon. Classifying soils derived from colluvial material as soils of other types leads to the disappearance of this units on maps and underestimation of the

Modality prediction of biomedical literature images using multimodal feature representation

Directory of Open Access Journals (Sweden)

Pelka, Obioma

2016-08-01

Full Text Available This paper presents the modelling approaches performed to automatically predict the modality of images found in biomedical literature. Various state-of-the-art visual features such as Bag-of-Keypoints computed with dense SIFT descriptors, texture features and Joint Composite Descriptors were used for visual image representation. Text representation was obtained by vector quantisation on a Bag-of-Words dictionary generated using attribute importance derived from a χ-test. Computing the principal components separately on each feature, dimension reduction as well as computational load reduction was achieved. Various multiple feature fusions were adopted to supplement visual image information with corresponding text information. The improvement obtained when using multimodal features vs. visual or text features was detected, analysed and evaluated. Random Forest models with 100 to 500 deep trees grown by resampling, a multi class linear kernel SVM with C=0.05 and a late fusion of the two classifiers were used for modality prediction. A Random Forest classifier achieved a higher accuracy and computed Bag-of-Keypoints with dense SIFT descriptors proved to be a better approach than with Lowe SIFT.

Visual scan-path analysis with feature space transient fixation moments

Science.gov (United States)

Dempere-Marco, Laura; Hu, Xiao-Peng; Yang, Guang-Zhong

2003-05-01

The study of eye movements provides useful insight into the cognitive processes underlying visual search tasks. The analysis of the dynamics of eye movements has often been approached from a purely spatial perspective. In many cases, however, it may not be possible to define meaningful or consistent dynamics without considering the features underlying the scan paths. In this paper, the definition of the feature space has been attempted through the concept of visual similarity and non-linear low dimensional embedding, which defines a mapping from the image space into a low dimensional feature manifold that preserves the intrinsic similarity of image patterns. This has enabled the definition of perceptually meaningful features without the use of domain specific knowledge. Based on this, this paper introduces a new concept called Feature Space Transient Fixation Moments (TFM). The approach presented tackles the problem of feature space representation of visual search through the use of TFM. We demonstrate the practical values of this concept for characterizing the dynamics of eye movements in goal directed visual search tasks. We also illustrate how this model can be used to elucidate the fundamental steps involved in skilled search tasks through the evolution of transient fixation moments.

Locally linear approximation for Kernel methods : the Railway Kernel

OpenAIRE

Muñoz, Alberto; González, Javier

2008-01-01

In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capab...

LIAR -- A new program for the modeling and simulation of linear accelerators with high gradients and small emittances

International Nuclear Information System (INIS)

Assmann, R.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.; Thompson, K.

1996-09-01

Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. The authors present a new program LIAR (LInear Accelerator Research code) that includes wakefield effects, a 4D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. They present examples of simulations for SLC and NLC

Linear Algebraic Method for Non-Linear Map Analysis

International Nuclear Information System (INIS)

Yu, L.; Nash, B.

2009-01-01

We present a newly developed method to analyze some non-linear dynamics problems such as the Henon map using a matrix analysis method from linear algebra. Choosing the Henon map as an example, we analyze the spectral structure, the tune-amplitude dependence, the variation of tune and amplitude during the particle motion, etc., using the method of Jordan decomposition which is widely used in conventional linear algebra.

Feature and Region Selection for Visual Learning.

Science.gov (United States)

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

PySSM: A Python Module for Bayesian Inference of Linear Gaussian State Space Models

Directory of Open Access Journals (Sweden)

Christopher Strickland

2014-04-01

Full Text Available PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models. PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries NumPy and SciPy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimized and parallelized Fortran routines. These Fortran routines heavily utilize basic linear algebra and linear algebra Package functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

Ceramic coatings: A phenomenological modeling for damping behavior related to microstructural features

International Nuclear Information System (INIS)

Tassini, N.; Patsias, S.; Lambrinou, K.

2006-01-01

Recent research has shown that both stiffness and damping of ceramic coatings exhibit different non-linearities. These properties strongly depend on the microstructure, which is characterized by heterogeneous sets of elastic elements with mesoscopic sizes and shapes, as in non-linear mesoscopic elastic materials. To predict the damping properties of this class of materials, we have implemented a phenomenological model that characterizes their elastic properties. The model is capable of reproducing the basic features of the observed damping behavior for zirconia coatings prepared by air plasma spraying and electron-beam physical-vapor-deposition

Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case study.

Science.gov (United States)

Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J

2014-08-27

State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the years, classical scoring functions have reached a plateau in their predictive performance. These assume a predetermined additive functional form for some sophisticated numerical features, and use standard multivariate linear regression (MLR) on experimental data to derive the coefficients. In this study we show that such a simple functional form is detrimental for the prediction performance of a scoring function, and replacing linear regression by machine learning techniques like random forest (RF) can improve prediction performance. We investigate the conditions of applying RF under various contexts and find that given sufficient training samples RF manages to comprehensively capture the non-linearity between structural features and measured binding affinities. Incorporating more structural features and training with more samples can both boost RF performance. In addition, we analyze the importance of structural features to binding affinity prediction using the RF variable importance tool. Lastly, we use Cyscore, a top performing empirical scoring function, as a baseline for comparison study. Machine-learning scoring functions are fundamentally different from classical scoring functions because the former circumvents the fixed functional form relating structural features with binding affinities. RF, but not MLR, can effectively exploit more structural features and more training samples, leading to higher prediction performance. The future availability of more X-ray crystal structures will further widen the performance gap between RF-based and MLR-based scoring functions. This further stresses the importance of substituting RF for MLR in scoring function development.

Prediction of human protein function from post-translational modifications and localization features

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Gupta, Ramneek; Blom, Nikolaj

2002-01-01

a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects......We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from...

Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

Directory of Open Access Journals (Sweden)

Eman Magdy

2015-01-01

Full Text Available Computer-aided diagnostic (CAD systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients’ lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR for classification step. Finally, K-nearest neighbour (KNN, support vector machine (SVM, naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

A linear-flow interpretation of the H-3 multiwell pumping test conducted at the Waste Isolation Pilot Plant (WIPP) site

International Nuclear Information System (INIS)

Tomasko, D.; Jensen, A.L.

1987-07-01

Unlike previous interpretations of this test that used a double-porosity radial-flow model, this interpretation is based on a linear-flow process. Drawdowns in pumped well H-3b2 responded as if the Culebra Dolomite Member of the Rustler Formation were pumped from an elongated feature with a significantly higher permeability than the surrounding porous medium. Drawdowns in observation wells DOE-1 and H-11 exhibited nearly classic linear-flow behavior in specialty plots of drawdowns had excellent type-curve matches with a linear-flow type curve. The orientation of the linear feature using data from a multiwell interference test was found by minimizing the squared differences between field observations and linear flow calculations. A second technique was used to calculate the transmissivity and width of the feature. To calculate consistent system parameters, this technique required developing a least-squares fitting procedure to minimize the effects of noise in the drawdown measurements. While the underlying assumptions of the linear-flow model differ from those of a double-porosity radial-flow model, the properties calculated for the Culebra are similar to those previously presented and indicate a basic insensitivity to the system flow model. In addition to yielding hydrologic values that are approximately the same, the two models are complementary and provide unique information for characterizing the aquifer - double-porosity parameters from one model, and the orientation and width of a high-permeability elongated strip from the other. The two interpretations also provide a consistent picture of an extensively fractured porous medium in the vicinity of the H-3 hydropad. 24 refs., 27 figs., 3 tabs

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing

2011-01-01

We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.

Development of a linear motion antenna for the JT-60SA ECRF system

International Nuclear Information System (INIS)

Moriyama, Shinichi; Kobayashi, Takayuki; Isayama, Akihiko; Hoshino, Katsumichi; Suzuki, Sadaaki; Hiranai, Shinichi; Yokokura, Kenji; Sawahata, Masayuki; Terakado, Masayuki; Hinata, Jun; Wada, Kenji; Sato, Yoshikatsu

2013-01-01

Highlights: ► Development of an antenna featuring linear motion (LM) concept for long pulse electron cyclotron range of frequency (ECRF) heating and current drive in JT-60SA is in progress. ► A mock-up using a metallic sliding bearing with solid lubricant was fabricated. ► A vacuum pumping test with mass analyzer showed evidence of some hydrocarbons during shaft motion. ► Injection beam profile in toroidal beam scan was checked by low power measurement with mock-up. ► Current drive characteristics with the LM antenna for typical experimental scenarios of JT-60SA have been investigated by calculation. -- Abstract: Development of an antenna that features the linear motion (LM) concept for long-pulse electron-cyclotron range of frequency heating and current drive for the JT-60SA is in progress. Combining a linearly movable first mirror and a fixed curved second mirror allows the injection-beam angle to be controlled. Cooling water is fed through the drive shaft for the first mirror and through the fixed support for the second mirror. The shaft support structure uses a metallic sliding bearing with a solid lubricant. The sliding bearing supports combined linear and rotational motion, whereas a conventional ball bearing supports either linear or rotational motion. Therefore, the sliding bearing offers the advantage of reducing the support-structure volume, which is important in the design of the relatively narrow port duct of the JT-60SA. Recently, the sliding bearing has been installed into the mockup. Results of a vacuum test with a mass analyzer indicate the presence of hydrocarbons during shaft motion. The injection-beam profile obtained from a toroidal beam scan is checked against low-power measurements taken on the mockup. Finally, for typical JT-60SA experimental scenarios, heating- and current-drive characteristics of the LM antenna are investigated theoretically

Predicting musically induced emotions from physiological inputs: linear and neural network models.

Science.gov (United States)

Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M

2013-01-01

Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of "felt" emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants-heart rate (HR), respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA) dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a non-linear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The non-linear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.

A Study on the Design of PM Exited Transverse Flux Linear Motor for Ropeless Elevator

Energy Technology Data Exchange (ETDEWEB)

Kang, Do Hyun; Bang, Deok Je; Kim, Jong Moo; Jeong, Yeon Ho [Korea Electrotechnology Research Institute (Korea); Kim, Moon Hwan [Silla University (Korea)

2000-03-01

The topological investigations regarding magnetic circuit geometry and winding form of the transverse flux machine have brought up a variety of constructable arrangements with different features for several types of application[1, 2]. Here with, a novel PM-exited linear motor with inner mover, based on the transverse flux configuration leads to a considerable increase in power density for moving part. In this study we designed PM-exited transverse flux linear motor for ropeless elevator, whose output power density is higher and weight is lighter than conventional linear synchronous motors, When the designed motor in this study is applied to ropeless elevator, it is possible to increase power density more than 400% comparing with PM exited linear synchronous motor. The result of this study can be utilized for ropeless elevator or gearless direct linear moving system with high output[3]. (author). 8 refs., 9 figs., 4 tabs.

Nonabelian Gauged Linear Sigma Model

Institute of Scientific and Technical Information of China (English)

Yongbin RUAN

2017-01-01

The gauged linear sigma model (GLSM for short) is a 2d quantum field theory introduced by Witten twenty years ago.Since then,it has been investigated extensively in physics by Hori and others.Recently,an algebro-geometric theory (for both abelian and nonabelian GLSMs) was developed by the author and his collaborators so that he can start to rigorously compute its invariants and check against physical predications.The abelian GLSM was relatively better understood and is the focus of current mathematical investigation.In this article,the author would like to look over the horizon and consider the nonabelian GLSM.The nonabelian case possesses some new features unavailable to the abelian GLSM.To aid the future mathematical development,the author surveys some of the key problems inspired by physics in the nonabelian GLSM.

A Research on Fast Face Feature Points Detection on Smart Mobile Devices

Directory of Open Access Journals (Sweden)

Xiaohe Li

2018-01-01

Full Text Available We explore how to leverage the performance of face feature points detection on mobile terminals from 3 aspects. First, we optimize the models used in SDM algorithms via PCA and Spectrum Clustering. Second, we propose an evaluation criterion using Linear Discriminative Analysis to choose the best local feature descriptions which plays a critical role in feature points detection. Third, we take advantage of multicore architecture of mobile terminal and parallelize the optimized SDM algorithm to improve the efficiency further. The experiment observations show that our final accomplished GPC-SDM (improved Supervised Descent Method using spectrum clustering, PCA, and GPU acceleration suppresses the memory usage, which is beneficial and efficient to meet the real-time requirements.

A unified frame of predicting side effects of drugs by using linear neighborhood similarity.

Science.gov (United States)

Zhang, Wen; Yue, Xiang; Liu, Feng; Chen, Yanlin; Tu, Shikui; Zhang, Xining

2017-12-14

Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. The assumption that similar drugs may induce same side effects is usually employed for modeling, and how to calculate the drug-drug similarity is critical in the side effect predictions. In this paper, we present a novel measure of drug-drug similarity named "linear neighborhood similarity", which is calculated in a drug feature space by exploring linear neighborhood relationship. Then, we transfer the similarity from the feature space into the side effect space, and predict drug side effects by propagating known side effect information through a similarity-based graph. Under a unified frame based on the linear neighborhood similarity, we propose method "LNSM" and its extension "LNSM-SMI" to predict side effects of new drugs, and propose the method "LNSM-MSE" to predict unobserved side effect of approved drugs. We evaluate the performances of LNSM and LNSM-SMI in predicting side effects of new drugs, and evaluate the performances of LNSM-MSE in predicting missing side effects of approved drugs. The results demonstrate that the linear neighborhood similarity can improve the performances of side effect prediction, and the linear neighborhood similarity-based methods can outperform existing side effect prediction methods. More importantly, the proposed methods can predict side effects of new drugs as well as unobserved side effects of approved drugs under a unified frame.

LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

Science.gov (United States)

Zhang, Tao; Chen, Wanzhong

2017-08-01

Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs and raw EEG are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.

ONETEP: linear-scaling density-functional theory with plane-waves

International Nuclear Information System (INIS)

Haynes, P D; Mostof, A A; Skylaris, C-K; Payne, M C

2006-01-01

This paper provides a general overview of the methodology implemented in onetep (Order-N Electronic Total Energy Package), a parallel density-functional theory code for largescale first-principles quantum-mechanical calculations. The distinctive features of onetep are linear-scaling in both computational effort and resources, obtained by making well-controlled approximations which enable simulations to be performed with plane-wave accuracy. Titanium dioxide clusters of increasing size designed to mimic surfaces are studied to demonstrate the accuracy and scaling of onetep

Ion acoustic waves in pair-ion plasma: Linear and nonlinear analyses

International Nuclear Information System (INIS)

Saeed, R.; Mushtaq, A.

2009-01-01

Linear and nonlinear properties of low frequency ion acoustic wave (IAW) in pair-ion plasma in the presence of electrons are investigated. The dispersion relation and Kadomtsev-Petviashvili equation for linear/nonlinear IAW are derived from sets of hydrodynamic equations where the ion pairs are inertial while electrons are Boltzmannian. The dispersion curves for various concentrations of electrons are discussed and compared with experimental results. The predicted linear IAW propagates at the same frequencies as those of the experimentally observed IAW if n e0 ∼10 4 cm -3 . It is found that nonlinear profile of the ion acoustic solitary waves is significantly affected by the percentage ratio of electron number density and temperature. It is also determined that rarefactive solitary waves can propagate in this system. It is hoped that the results presented in this study would be helpful in understanding the salient features of the finite amplitude localized ion acoustic solitary pulses in a laboratory fullerene plasma.

Linear and nonlinear schemes applied to pitch control of wind turbines.

Science.gov (United States)

Geng, Hua; Yang, Geng

2014-01-01

Linear controllers have been employed in industrial applications for many years, but sometimes they are noneffective on the system with nonlinear characteristics. This paper discusses the structure, performance, implementation cost, advantages, and disadvantages of different linear and nonlinear schemes applied to the pitch control of the wind energy conversion systems (WECSs). The linear controller has the simplest structure and is easily understood by the engineers and thus is widely accepted by the industry. In contrast, nonlinear schemes are more complicated, but they can provide better performance. Although nonlinear algorithms can be implemented in a powerful digital processor nowadays, they need time to be accepted by the industry and their reliability needs to be verified in the commercial products. More information about the system nonlinear feature is helpful to simplify the controller design. However, nonlinear schemes independent of the system model are more robust to the uncertainties or deviations of the system parameters.

Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

Energy Technology Data Exchange (ETDEWEB)

Baak, M., E-mail: max.baak@cern.ch [CERN, CH-1211 Geneva 23 (Switzerland); Gadatsch, S., E-mail: stefan.gadatsch@nikhef.nl [Nikhef, PO Box 41882, 1009 DB Amsterdam (Netherlands); Harrington, R. [School of Physics and Astronomy, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JZ, Scotland (United Kingdom); Verkerke, W. [Nikhef, PO Box 41882, 1009 DB Amsterdam (Netherlands)

2015-01-21

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates are often required to model the impact of systematic uncertainties.

Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

International Nuclear Information System (INIS)

Baak, M.; Gadatsch, S.; Harrington, R.; Verkerke, W.

2015-01-01

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates are often required to model the impact of systematic uncertainties

Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

CERN Document Server

Baak, Max; Harrington, Robert; Verkerke, Wouter

2014-01-01

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates is often required to model the impact of systematic uncertainties.

Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

CERN Document Server

Baak, Max; Harrington, Robert; Verkerke, Wouter

2015-01-01

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates is often required to model the impact of systematic uncertainties.

Photon Shielding Features of Quarry Tuff

Directory of Open Access Journals (Sweden)

Vega-Carrillo Hector Rene

2017-01-01

Full Text Available Cantera is a quarry tuff widely used in the building industry; in this work the shielding features of cantera were determined. The shielding characteristics were calculated using XCOM and MCNP5 codes for 0.03, 0.07, 0.1, 0.3, 0.662, 1, 2, and 3 MeV photons. With XCOM the mass interaction coefficients, and the total mass attenuation coefficients, were calculated. With the MCNP5 code a transmission experiment was modelled using a point-like source located 42 cm apart from a point-like detector. Between the source and the detector, cantera pieces with different thickness, ranging from 0 to 40 cm were included. The collided and uncollided photon fluence, the Kerma in air and the Ambient dose equivalent were estimated. With the uncollided fluence the linear attenuation coefficients were determined and compared with those calculated with XCOM. The linear attenuation coefficient for 0.662 MeV photons was compared with the coefficient measured with a NaI(Tl-based γ-ray spectrometer and a 137Cs source.

Advanced statistics: linear regression, part I: simple linear regression.

Science.gov (United States)

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

The role of different linear and non-linear channels of relaxation in scintillator non-proportionality

Energy Technology Data Exchange (ETDEWEB)

Bizarri, G.; Moses, W.W. [Lawrence Berkeley Laboratory, Berkeley, CA 94720-8119 (United States); Singh, J. [Faculty of EHS, B-41, Charles Darwin University, Darwin NT 0909 (Australia); Vasil' ev, A.N., E-mail: anvasiliev@rambler.r [Institute of Nuclear Physics, Moscow State University, Moscow 119991 (Russian Federation); Williams, R.T. [Department of Physics, Wake Forest University, Winston-Salem, NC 27109 (United States)

2009-12-15

The non-proportional dependence of a scintillator's light yield on primary particle energy is believed to be influenced crucially by the interplay of non-linear kinetic terms in the radiative and non-radiative decay of excitations versus locally deposited excitation density. A calculation of energy deposition, -dE/dx, along the electron track for NaI is presented for an energy range from several electron-volt to 1 MeV. Such results can be used to specify an initial excitation distribution, if diffusion is neglected. An exactly solvable two-channel (exciton and hole(electron)) model containing 1st and 2nd order kinetic terms is constructed and used to illustrate important features seen in non-proportional light-yield curves, including a dependence on pulse shaping (detection gate width).

The role of different linear and non-linear channels of relaxation in scintillator non-proportionality

International Nuclear Information System (INIS)

Bizarri, G.; Moses, W.W.; Singh, J.; Vasil'ev, A.N.; Williams, R.T.

2009-01-01

The non-proportional dependence of a scintillator's light yield on primary particle energy is believed to be influenced crucially by the interplay of non-linear kinetic terms in the radiative and non-radiative decay of excitations versus locally deposited excitation density. A calculation of energy deposition, -dE/dx, along the electron track for NaI is presented for an energy range from several electron-volt to 1 MeV. Such results can be used to specify an initial excitation distribution, if diffusion is neglected. An exactly solvable two-channel (exciton and hole(electron)) model containing 1st and 2nd order kinetic terms is constructed and used to illustrate important features seen in non-proportional light-yield curves, including a dependence on pulse shaping (detection gate width).

Privacy-Preserving Distributed Linear Regression on High-Dimensional Data

Directory of Open Access Journals (Sweden)

Gascón Adrià

2017-10-01

Full Text Available We propose privacy-preserving protocols for computing linear regression models, in the setting where the training dataset is vertically distributed among several parties. Our main contribution is a hybrid multi-party computation protocol that combines Yao’s garbled circuits with tailored protocols for computing inner products. Like many machine learning tasks, building a linear regression model involves solving a system of linear equations. We conduct a comprehensive evaluation and comparison of different techniques for securely performing this task, including a new Conjugate Gradient Descent (CGD algorithm. This algorithm is suitable for secure computation because it uses an efficient fixed-point representation of real numbers while maintaining accuracy and convergence rates comparable to what can be obtained with a classical solution using floating point numbers. Our technique improves on Nikolaenko et al.’s method for privacy-preserving ridge regression (S&P 2013, and can be used as a building block in other analyses. We implement a complete system and demonstrate that our approach is highly scalable, solving data analysis problems with one million records and one hundred features in less than one hour of total running time.

Genetic design of interpolated non-linear controllers for linear plants

International Nuclear Information System (INIS)

Ajlouni, N.

2000-01-01

The techniques of genetic algorithms are proposed as a means of designing non-linear PID control systems. It is shown that the use of genetic algorithms for this purpose results in highly effective non-linear PID control systems. These results are illustrated by using genetic algorithms to design a non-linear PID control system and contrasting the results with an optimally tuned linear PID controller. (author)

Sodium flow rate measurement method of annular linear induction pumps

International Nuclear Information System (INIS)

Araseki, Hideo; Kirillov, Igor R.; Preslitsky, Gennady V.

2012-01-01

Highlights: ► We found a new method of flow rate monitoring of electromagnetic pump. ► The method is very simple and does not require a large space. ► The method was verified with an experiment and a numerical analysis. ► The experimental data and the numerical results are in good agreement. - Abstract: The present paper proposes a method for measuring sodium flow rate of annular linear induction pumps. The feature of the method lies in measuring the leaked magnetic field with measuring coils near the stator end on the outlet side and in correlating it with the sodium flow rate. This method is verified through an experiment and a numerical analysis. The data obtained in the experiment reveals that the correlation between the leaked magnetic field and the sodium flow rate is almost linear. The result of the numerical analysis agrees with the experimental data. The present method will be particularly effective to sodium flow rate monitoring of each one of plural annular linear induction pumps arranged in parallel in a vessel which forms a large-scale pump unit.

Glaciers of Avacha group of volcanoes in Neoholocene

Directory of Open Access Journals (Sweden)

T. M. Manevich

2016-01-01

Full Text Available The study of moraines at the Avacha volcano group revealed that glaciers changes at all volcanoes within the group happened almost synchronously. Glacial deposits could be grouped into three generations, corresponding to three periods of glacier fluctuations in Neoholocene. The largest glaciation within the group occurred ~2000 years ago. Fragments of moraine, corresponding to that period were found only in the moraine complex of the Ditmar Glacier which was 15% larger then today at that time. The most of moraines at the Avacha volcano group were formed during the Little Ice Age, which in the studied region continued up to the first decades of XX centuries. The maximal advance of glaciers probably happened in XVII century. The moraine corresponding to that period was found at the Kozelsky Glacier valley. At present time the total area of glaciers which moraines were described and dated approaches 21.46  km2. The area of reconstructed moraines corresponding to the Little Ice Age is estimated to be 2.79 km2, therefore at that period the total glaciation area reaches 24,25 км2 exceeding the present area by 13%. It could be claimed that in general during the time past the Little Ice Age the glaciation nature and glacier types did not change sufficiently. The rate of glacier degradation at various parts of the group is different and depends mainly on exposition. At the valleys of four glaciers we found moraines formed in the middle of XX century. They may appear in 1941–1952 when the unfavorable weather conditions leaded to stable negative anomalies in accumulation have happened.

A feature-based approach to modeling protein-DNA interactions.

Directory of Open Access Journals (Sweden)

Eilon Sharon

Full Text Available Transcription factor (TF binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM, which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs, a novel probabilistic method for modeling TF-DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/.

Victimization and psychopathic features in a population-based sample of Finnish adolescents.

Science.gov (United States)

Saukkonen, Suvi; Aronen, Eeva T; Laajasalo, Taina; Salmi, Venla; Kivivuori, Janne; Jokela, Markus

2016-10-01

We examined different forms of victimization experiences in relation to psychopathic features and whether these associations differed in boys and girls among 4855 Finnish school adolescents aged 15-16 years. Psychopathic features were measured with the Antisocial Process Screening Device- Self Report (APSD-SR). Victimization was assessed with questions about violent and abusive experiences across lifetime and within the last 12 months. Results from linear regression analysis showed that victimization was significantly associated with higher APSD-SR total scores, more strongly in girls than boys. Recent (12-month) victimization showed significance in the relationship between victimization and psychopathic features; especially recent sexual abuse and parental corporal punishment were strong determinants of higher APSD-SR total scores. The present study demonstrates novel findings on how severe victimization experiences relate to psychopathic features in community youth, especially in girls. The findings underscore the need for comprehensive evaluation of victimization experiences when psychopathic features are present in youth. Copyright © 2016 Elsevier Ltd. All rights reserved.

Similarities and Differences Between Warped Linear Prediction and Laguerre Linear Prediction

NARCIS (Netherlands)

Brinker, Albertus C. den; Krishnamoorthi, Harish; Verbitskiy, Evgeny A.

2011-01-01

Linear prediction has been successfully applied in many speech and audio processing systems. This paper presents the similarities and differences between two classes of linear prediction schemes, namely, Warped Linear Prediction (WLP) and Laguerre Linear Prediction (LLP). It is shown that both

Magnetic x-ray linear dichroism in resonant and non-resonant Gd 4f photoemission

Energy Technology Data Exchange (ETDEWEB)

Mishra, S.; Gammon, W.J.; Pappas, D.P. [Virginia Commonwealth Univ., Richmond, VA (United States)] [and others

1997-04-01

The enhancement of the magnetic linear dichroism in resonant 4f photoemission (MLDRPE) is studied from a 50 monolayer film of Gd/Y(0001). The ALS at beamline 7.0.1 provided the source of linearly polarized x-rays used in this study. The polarized light was incident at an angle of 30 degrees relative to the film plane, and the sample magnetization was perpendicular to the photon polarization. The linear dichroism of the 4f core levels is measured as the photon energy is tuned through the 4d-4f resonance. The authors find that the MLDRPE asymmetry is strongest at the resonance. Near the threshold the asymmetry has several features which are out of phase with the fine structure of the total yield.

Magnetic x-ray linear dichroism in resonant and non-resonant Gd 4f photoemission

International Nuclear Information System (INIS)

Mishra, S.; Gammon, W.J.; Pappas, D.P.

1997-01-01

The enhancement of the magnetic linear dichroism in resonant 4f photoemission (MLDRPE) is studied from a 50 monolayer film of Gd/Y(0001). The ALS at beamline 7.0.1 provided the source of linearly polarized x-rays used in this study. The polarized light was incident at an angle of 30 degrees relative to the film plane, and the sample magnetization was perpendicular to the photon polarization. The linear dichroism of the 4f core levels is measured as the photon energy is tuned through the 4d-4f resonance. The authors find that the MLDRPE asymmetry is strongest at the resonance. Near the threshold the asymmetry has several features which are out of phase with the fine structure of the total yield

Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals.

Science.gov (United States)

Ebrahimi, Farideh; Setarehdan, Seyed-Kamaledin; Ayala-Moyeda, Jose; Nazeran, Homer

2013-10-01

The conventional method for sleep staging is to analyze polysomnograms (PSGs) recorded in a sleep lab. The electroencephalogram (EEG) is one of the most important signals in PSGs but recording and analysis of this signal presents a number of technical challenges, especially at home. Instead, electrocardiograms (ECGs) are much easier to record and may offer an attractive alternative for home sleep monitoring. The heart rate variability (HRV) signal proves suitable for automatic sleep staging. Thirty PSGs from the Sleep Heart Health Study (SHHS) database were used. Three feature sets were extracted from 5- and 0.5-min HRV segments: time-domain features, nonlinear-dynamics features and time-frequency features. The latter was achieved by using empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods. Normalized energies in important frequency bands of HRV signals were computed using time-frequency methods. ANOVA and t-test were used for statistical evaluations. Automatic sleep staging was based on HRV signal features. The ANOVA followed by a post hoc Bonferroni was used for individual feature assessment. Most features were beneficial for sleep staging. A t-test was used to compare the means of extracted features in 5- and 0.5-min HRV segments. The results showed that the extracted features means were statistically similar for a small number of features. A separability measure showed that time-frequency features, especially EMD features, had larger separation than others. There was not a sizable difference in separability of linear features between 5- and 0.5-min HRV segments but separability of nonlinear features, especially EMD features, decreased in 0.5-min HRV segments. HRV signal features were classified by linear discriminant (LD) and quadratic discriminant (QD) methods. Classification results based on features from 5-min segments surpassed those obtained from 0.5-min segments. The best result was obtained from features using 5-min HRV

The 20th century retreat of ice caps in Iceland derived from airborne SAR

DEFF Research Database (Denmark)

Magnússon, Eyjólfur; Björnsson, Helgi; Dall, Jørgen

2005-01-01

with the Danish airborne EMISAR radar system. Polarimetric and interferometric SAR data reveal the margins of the present ice caps as well as a series of terminal moraines in the fore field. These moraines date back to the maximum Neoglacial extent at the end of the 19th century and the outermost allow...... of the surges in W-Vatnajokull in the 20th century are observed in the SAR data including the most recent surges in the 1990s. Interestingly no push moraines were observed in front of the surge advance, but the moraines appear when the glaciers start retreating. We estimate that the collective decrease...

AMS of heavy elements with an ECR ion source and the ATLAS linear accelerator

CERN Document Server

Paul, M; Ahmad, I; Borasi, F; Caggiano, J; Davids, C N; Greene, J P; Harss, B; Heinz, A; Henderson, D J; Henning, W F; Jiang, C L; Pardo, R C; Rehm, K E; Rejoub, R; Seweryniak, D; Sonzogni, A; Uusitalo, J; Vondrasek, R C

2000-01-01

Detection of heavy elements by accelerator mass spectrometry with the electron cyclotron resonance ion source, Argonne linear accelerator and fragment mass analyzer (ECRIS-ATLAS-FMA) system has been developed. The use of the ECR-ATLAS system for AMS of heavy elements has two interesting features: (i) the efficient production of high-charge state ions in the ECR source ensures the elimination of molecular ions at the source stage, a highly attractive feature for any mass-spectrometric use not exploited so far; (ii) the linear acceleration based on velocity matching and the beam transport system act as a powerful mass filter for background suppression. We have shown that our system reaches an abundance sensitivity of 1x10 sup - sup 1 sup 4 for Pb isotopes. The sup 2 sup 3 sup 6 U detection sensitivity is sup 2 sup 3 sup 6 U/U > or approx. 1x10 sup - sup 1 sup 2 , limited mainly by the ion source output.

Statistical Feature Extraction and Recognition of Beverages Using Electronic Tongue

Directory of Open Access Journals (Sweden)

P. C. PANCHARIYA

2010-01-01

Full Text Available This paper describes an approach for extraction of features from data generated from an electronic tongue based on large amplitude pulse voltammetry. In this approach statistical features of the meaningful selected variables from current response signals are extracted and used for recognition of beverage samples. The proposed feature extraction approach not only reduces the computational complexity but also reduces the computation time and requirement of storage of data for the development of E-tongue for field applications. With the reduced information, a probabilistic neural network (PNN was trained for qualitative analysis of different beverages. Before the qualitative analysis of the beverages, the methodology has been tested for the basic artificial taste solutions i.e. sweet, sour, salt, bitter, and umami. The proposed procedure was compared with the more conventional and linear feature extraction technique employing principal component analysis combined with PNN. Using the extracted feature vectors, highly correct classification by PNN was achieved for eight types of juices and six types of soft drinks. The results indicated that the electronic tongue based on large amplitude pulse voltammetry with reduced feature was capable of discriminating not only basic artificial taste solutions but also the various sorts of the same type of natural beverages (fruit juices, vegetable juices, soft drinks, etc..

A Discrete-Time Recurrent Neural Network for Solving Rank-Deficient Matrix Equations With an Application to Output Regulation of Linear Systems.

Science.gov (United States)

Liu, Tao; Huang, Jie

2017-04-17

This paper presents a discrete-time recurrent neural network approach to solving systems of linear equations with two features. First, the system of linear equations may not have a unique solution. Second, the system matrix is not known precisely, but a sequence of matrices that converges to the unknown system matrix exponentially is known. The problem is motivated from solving the output regulation problem for linear systems. Thus, an application of our main result leads to an online solution to the output regulation problem for linear systems.

Spatial-temporal features of thermal images for Carpal Tunnel Syndrome detection

Science.gov (United States)

Estupinan Roldan, Kevin; Ortega Piedrahita, Marco A.; Benitez, Hernan D.

2014-02-01

Disorders associated with repeated trauma account for about 60% of all occupational illnesses, Carpal Tunnel Syndrome (CTS) being the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine. IT is non-invasive and detects diseases based on measuring temperature variations. IT represents a possible alternative to prevalent methods for diagnosis of CTS (i.e. nerve conduction studies and electromiography). This work presents a set of spatial-temporal features extracted from thermal images taken in healthy and ill patients. Support Vector Machine (SVM) classifiers test this feature space with Leave One Out (LOO) validation error. The results of the proposed approach show linear separability and lower validation errors when compared to features used in previous works that do not account for temperature spatial variability.

Influencia de los defecaderos de camélidos sobre el desarrollo vegetal y riqueza de especies en morrenas glaciales, Tierra del Fuego Camelid defecation influences vegetation development and species richnesss on glacial moraines, Tierra del Fuego

Directory of Open Access Journals (Sweden)

JUAN M. HENRÍQUEZ

2004-09-01

Full Text Available Los escasos trabajos de interacción planta-herbívoro en ambientes severos han concluido que los herbívoros tienen un rol menor sobre el proceso de colonización en los estados tempranos de la sucesión. Aquí se documentan los efectos de defecaderos de un herbívoro ungulado (Lamma guanicoe sobre los patrones vegetales en una intermorrena glacial reciente. Se evaluó la composición florística, frecuencia y síndrome de dispersión de las especies presentes sobre los defecaderos y sitios control. Parámetros de suelo fueron analizados en ambos substratos. La riqueza y diversidad de especies vasculares fueron significativamente mayores sobre los defecaderos. El síndrome de dispersión dominante es la anemocoría en la vegetación de ambos tipos de substratos. Los defecaderos presentan valores superiores de materia orgánica, nitrógeno y fósforo, indicando condiciones localmente más favorables para el establecimiento de plántulas en este ambiente pobre en nutrientes y materia orgánica. Finalmente, se discute acerca de los posibles mecanismos que originan la mayor riqueza y diversidad de especies sobre los defecaderos de guanaco, concluyendo que constituyen una fuente potencial de propágulos que puede acelerar el proceso de colonización en morrenas glaciaresThe few studies of herbivore-plant interaction in severe environments have concluded that the herbivores have a minor role on the process of colonization in the early states of the succession. This paper describes the effects of camelid (Lamma guanicoe dung heaps on vegetation patterns on a recent glacial moraine. Floristic composition, diversity, abundance and dispersion syndrome spectra of the vegetation growing on dung heaps was compared with that of control sites unaffected by camelid defecation. Soil parameters of both substrates were analyzed. Vascular species riches and diversity were significantly higher on dung heaps. Anemochory was the dominant dispersion syndrome on both

Non-linear nuclear engineering models as genetic programming application

International Nuclear Information System (INIS)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.

1997-01-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs

Timing of Expansions of the Quelccaya Ice Cap, Peru, and Implications for Cosmogenic Nuclide Production Rate Calibration

Science.gov (United States)

Lowell, T. V.; Kelly, M. A.; Applegate, P. J.; Smith, C. A.; Phillips, F. M.; Hudson, A. M.

2010-12-01

We calibrate the production rate of the cosmogenic nuclide beryllium-10 (10Be) at a low-latitude, high-elevation site, using nuclide concentrations measured in moraine boulders and an independent chronology determined with bracketing radiocarbon dates. The measurement of terrestrial cosmogenic nuclide (TCN) concentrations in earth surface materials has been an important development for understanding a host of earth surface processes. Uncertainty in cosmogenic nuclide production rates has hampered application of this method. Here, we contribute to the estimation of 10Be production rates by reporting both preliminary 10Be concentrations and independent radiocarbon dates from a low latitude, high elevation site. Our study site in the southeastern Peruvian Andes (~13.9°S, 70.9°W, 4850 m asl) is centered on a moraine set, known as the Huancané II moraines, that represents a ~4 km expansion of Quelccaya Ice Cap during late glacial time. At this location, organic material situated both stratigraphically below and above moraines in two adjacent valleys provide material for radiocarbon dating. Based on geomorphic arguments, we correlate results from the two valleys. The timing of ice cap margin advance is bracketed by 13 radiocarbon ages on organic material within the outermost Huancané II moraines that range from 13.6 to 12.5 ka. Two stratigraphic sections upvalley from the moraines yield 6 radiocarbon ages from 11.3 to 12.4 ka, indicating the time of retreat . We computed the probability density function that lies between these two sets of dates, and assign an age of 12.4 ka (+/-???) for the formation of the Huancané II moraines. Calculating beryllium-10 exposure dates from the measured concentrations yield exposure dates that significantly underestimate the independently determined age of the moraine (~8-30%), if existing production rate estimates are used. We suggest that the radiocarbon age for the moraines can be used as a robust independent calibration for 10Be

U-Th and 10Be constraints on sediment recycling in proglacial settings, Lago Buenos Aires, Patagonia

Science.gov (United States)

Cogez, Antoine; Herman, Frédéric; Pelt, Éric; Reuschlé, Thierry; Morvan, Gilles; Darvill, Christopher M.; Norton, Kevin P.; Christl, Marcus; Märki, Lena; Chabaux, François

2018-03-01

The estimation of sediment transfer times remains a challenge to our understanding of sediment budgets and the relationships between erosion and climate. Uranium (U) and thorium (Th) isotope disequilibria offer a means of more robustly constraining sediment transfer times. Here, we present new uranium and thorium disequilibrium data for a series of nested moraines around Lago Buenos Aires in Argentine Patagonia. The glacial chronology for the area is constrained using in situ cosmogenic 10Be analysis of glacial outwash. Sediment transfer times within the periglacial domain were estimated by comparing the deposition ages of moraines to the theoretical age of sediment production, i.e., the comminution age inferred from U disequilibrium data and recoil loss factor estimates. Our data show first that the classical comminution age approach must include weathering processes accounted for by measuring Th disequilibrium. Second, our combined data suggest that the pre-deposition history of the moraine sediments is not negligible, as evidenced by the large disequilibrium of the youngest moraines despite the equilibrium of the corresponding glacial flour. Monte Carlo simulations suggest that weathering was more intense before the deposition of the moraines and that the transfer time of the fine sediments to the moraines was on the order of 100-200 kyr. Long transfer times could result from a combination of long sediment residence times in the proglacial lake (recurrence time of a glacial cycle) and the remobilization of sediments from moraines deposited during previous glacial cycles. 10Be data suggest that some glacial cycles are absent from the preserved moraine record (seemingly every second cycle), supporting a model of reworking moraines and/or fluctuations in the extent of glacial advances. The chronological pattern is consistent with the U-Th disequilibrium data and the 100-200 kyr transfer time. This long transfer time raises the question of the proportion of freshly

U–Th and 10Be constraints on sediment recycling in proglacial settings, Lago Buenos Aires, Patagonia

Directory of Open Access Journals (Sweden)

A. Cogez

2018-03-01

Full Text Available The estimation of sediment transfer times remains a challenge to our understanding of sediment budgets and the relationships between erosion and climate. Uranium (U and thorium (Th isotope disequilibria offer a means of more robustly constraining sediment transfer times. Here, we present new uranium and thorium disequilibrium data for a series of nested moraines around Lago Buenos Aires in Argentine Patagonia. The glacial chronology for the area is constrained using in situ cosmogenic 10Be analysis of glacial outwash. Sediment transfer times within the periglacial domain were estimated by comparing the deposition ages of moraines to the theoretical age of sediment production, i.e., the comminution age inferred from U disequilibrium data and recoil loss factor estimates. Our data show first that the classical comminution age approach must include weathering processes accounted for by measuring Th disequilibrium. Second, our combined data suggest that the pre-deposition history of the moraine sediments is not negligible, as evidenced by the large disequilibrium of the youngest moraines despite the equilibrium of the corresponding glacial flour. Monte Carlo simulations suggest that weathering was more intense before the deposition of the moraines and that the transfer time of the fine sediments to the moraines was on the order of 100–200 kyr. Long transfer times could result from a combination of long sediment residence times in the proglacial lake (recurrence time of a glacial cycle and the remobilization of sediments from moraines deposited during previous glacial cycles. 10Be data suggest that some glacial cycles are absent from the preserved moraine record (seemingly every second cycle, supporting a model of reworking moraines and/or fluctuations in the extent of glacial advances. The chronological pattern is consistent with the U–Th disequilibrium data and the 100–200 kyr transfer time. This long transfer time raises the

Finite-dimensional linear algebra

CERN Document Server

Gockenbach, Mark S

2010-01-01

Some Problems Posed on Vector SpacesLinear equationsBest approximationDiagonalizationSummaryFields and Vector SpacesFields Vector spaces Subspaces Linear combinations and spanning sets Linear independence Basis and dimension Properties of bases Polynomial interpolation and the Lagrange basis Continuous piecewise polynomial functionsLinear OperatorsLinear operatorsMore properties of linear operatorsIsomorphic vector spaces Linear operator equations Existence and uniqueness of solutions The fundamental theorem; inverse operatorsGaussian elimination Newton's method Linear ordinary differential eq

Linear algebra

CERN Document Server

Said-Houari, Belkacem

2017-01-01

This self-contained, clearly written textbook on linear algebra is easily accessible for students. It begins with the simple linear equation and generalizes several notions from this equation for the system of linear equations and introduces the main ideas using matrices. It then offers a detailed chapter on determinants and introduces the main ideas with detailed proofs. The third chapter introduces the Euclidean spaces using very simple geometric ideas and discusses various major inequalities and identities. These ideas offer a solid basis for understanding general Hilbert spaces in functional analysis. The following two chapters address general vector spaces, including some rigorous proofs to all the main results, and linear transformation: areas that are ignored or are poorly explained in many textbooks. Chapter 6 introduces the idea of matrices using linear transformation, which is easier to understand than the usual theory of matrices approach. The final two chapters are more advanced, introducing t...

Linear gate

International Nuclear Information System (INIS)

Suwono.

1978-01-01

A linear gate providing a variable gate duration from 0,40μsec to 4μsec was developed. The electronic circuity consists of a linear circuit and an enable circuit. The input signal can be either unipolar or bipolar. If the input signal is bipolar, the negative portion will be filtered. The operation of the linear gate is controlled by the application of a positive enable pulse. (author)

Precise chronologies of Holocene glacial culminations in the Cordillera Vilcabamba of southern Peru

Science.gov (United States)

Licciardi, J. M.; Schaefer, J. M.; Schweinsberg, A. D.

2012-12-01

Records of past fluctuations in climatically sensitive tropical mountain glaciers are among the best indicators of regional paleoclimatic trends and controls. The majority of the world's present-day tropical glaciers are found in the Peruvian Andes, but accurate and precise chronologies of past glacial activity in this region remain relatively scarce, particularly during the Holocene. Here we present ~50 new 10Be exposure ages derived from boulders on well-preserved moraine successions in several glaciated drainages in the Cordillera Vilcabamba of southern Peru (13°20'S latitude). The new results suggest that prominent moraines in these valleys are correlative with previously published moraine ages near Nevado Salcantay in this range (Licciardi et al., 2009), but also expand on the initial surface exposure chronologies to reveal additional periods of glacier stabilization not found in previous work. A provisional composite chronology that merges the new and previously obtained moraine ages indicates at least five discrete glacial culminations from the Lateglacial to the late Holocene. Forthcoming 10Be ages from an additional ~50 samples collected from moraine boulders will increase the precision and completeness of the Vilcabamba moraine chronologies. Basal radiocarbon ages are being developed from bog and lake sediments in stratigraphic contact with the 10Be-dated moraines. These new 14C age data will help constrain the local cosmogenic 10Be production rate, thereby increasing the accuracy of the 10Be chronologies.

Broad-band linear polarization and magnetic intensification in rotating magnetic stars

International Nuclear Information System (INIS)

Degl'Innocenti, M.L.; Calamai, G.; Degl'Innocenti, E.L.; Patriarchi, P.

1981-01-01

Magnetic intensification is proposed as a mechanism to explain the general features of the variable broad-band linear polarization emerging from rotating magnetic stars. This mechanism is studied in detail, and some efforts are made to investigate the wide variety of polarization diagrams that can result from it. Theoretical results are compared with direct observations of the variable magnetic star 53 Cam to determine its geometric and magnetic configuration

Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes.

Directory of Open Access Journals (Sweden)

Sharad Shandilya

Full Text Available The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR, rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals.Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA technique.358 defibrillations were evaluated (218 unsuccessful and 140 successful. Non-linear properties (Lyapunov exponent > 0 of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity outperformed AMSA (53.6% sensitivity. At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity.At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations

The linear programming bound for binary linear codes

NARCIS (Netherlands)

Brouwer, A.E.

1993-01-01

Combining Delsarte's (1973) linear programming bound with the information that certain weights cannot occur, new upper bounds for dmin (n,k), the maximum possible minimum distance of a binary linear code with given word length n and dimension k, are derived.

Mathieu's Equation and its Generalizations: Overview of Stability Charts and their Features

DEFF Research Database (Denmark)

Kovacic, Ivana; Rand, Richard H.; Sah, Si Mohamed

2018-01-01

This work is concerned with Mathieu's equation - a classical differential equation, which has the form of a linear second-order ordinary differential equation with Cosine-type periodic forcing of the stiffness coefficient, and its different generalizations/extensions. These extensions include...... and features, and how it differs from that of the classical Mathieu's equation....

Accommodation of practical constraints by a linear programming jet select. [for Space Shuttle

Science.gov (United States)

Bergmann, E.; Weiler, P.

1983-01-01

An experimental spacecraft control system will be incorporated into the Space Shuttle flight software and exercised during a forthcoming mission to evaluate its performance and handling qualities. The control system incorporates a 'phase space' control law to generate rate change requests and a linear programming jet select to compute jet firings. Posed as a linear programming problem, jet selection must represent the rate change request as a linear combination of jet acceleration vectors where the coefficients are the jet firing times, while minimizing the fuel expended in satisfying that request. This problem is solved in real time using a revised Simplex algorithm. In order to implement the jet selection algorithm in the Shuttle flight control computer, it was modified to accommodate certain practical features of the Shuttle such as limited computer throughput, lengthy firing times, and a large number of control jets. To the authors' knowledge, this is the first such application of linear programming. It was made possible by careful consideration of the jet selection problem in terms of the properties of linear programming and the Simplex algorithm. These modifications to the jet select algorithm may by useful for the design of reaction controlled spacecraft.

Glacial and postglacial geology near Lake Tennyson, Clarence River, New Zealand

International Nuclear Information System (INIS)

McCalpin, J.P.

1992-01-01

Otiran valley glaciers extended 15 km down the upper Clarence Valley in central Marlborough, South Island, New Zealand. A massive Otiran terminal moraine complex, composed of moraines of three glacial advances, impounds Lake Tennyson. The moraines are early and middle Otiran, and possibly late Otiran-early Aranuian in age, based on relative position and differences in moraine morphology, weathering rinds, and soils. Radiocarbon ages from a tributary (Serpentine Creek) suggest the latest major episode of aggradation in the Clarence Valley was in progress by 11.3 ka, and had ended by 9.2 ka. Postglacial history was dominated by incision of glacial outwash, deposition of small alluvial fans, and landsliding near the trace of the Awatere Fault. Fault scarps of the Awatere Fault and of unnamed parallel splays displace early Otiran moraines up to 19 m and early Holocene terraces up to 2.6 m. (author). 25 refs., 10 figs., 3 tabs

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

Science.gov (United States)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger

Branched-linear and agglomerate protein polymers as vaccine platforms.

Science.gov (United States)

Wang, Leyi; Xia, Ming; Huang, Pengwei; Fang, Hao; Cao, Dianjun; Meng, Xiang-Jin; McNeal, Monica; Jiang, Xi; Tan, Ming

2014-09-01

Many viral structural proteins and their truncated domains share a common feature of homotypic interaction forming dimers, trimers, and/or oligomers with various valences. We reported previously a simple strategy for construction of linear and network polymers through the dimerization feature of viral proteins for vaccine development. In this study, technologies were developed to produce more sophisticated polyvalent complexes through both the dimerization and oligomerization natures of viral antigens. As proof of concept, branched-linear and agglomerate polymers were made via fusions of the dimeric glutathione-s-transferase (GST) with either a tetrameric hepatitis E virus (HEV) protruding protein or a 24-meric norovirus (NoV) protruding protein. Furthermore, a monomeric antigen, either the M2e epitope of influenza A virus or the VP8* antigen of rotavirus, was inserted and displayed by the polymer platform. All resulting polymers were easily produced in Escherichia coli at high yields. Immunization of mice showed that the polymer vaccines induced significantly higher specific humoral and T cell responses than those induced by the dimeric antigens. Additional evidence in supporting use of polymer vaccines included the significantly higher neutralization activity and protective immunity of the polymer vaccines against the corresponding viruses than those of the dimer vaccines. Thus, our technology for production of polymers containing different viral antigens offers a strategy for vaccine development against infectious pathogens and their associated diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.

Little Ice Age Fluctuations of Quelccaya Ice Cap, Peru

Science.gov (United States)

Stroup, J. S.; Kelly, M. A.; Lowell, T.

2009-12-01

A record of the past extents of Quelccaya Ice Cap (QIC) provides valuable information about tropical climate change from late glacial to recent time. Here, we examine the timing and regional significance of fluctuations of QIC during the Little Ice Age (LIA; ~1300-1850 AD). One prominent set of moraines, known as the Huancane I moraines, is located ~1 km from the present-day western ice cap margin and provides a near-continuous outline of the most recent advance of QIC. This moraine set was radiocarbon dated (~298 ± 134 and 831 ± 87 yr BP) by Mercer and Palacios (1977) and presented as some of the first evidence for cooling in the tropics during the Little Ice Age. Recent field investigations in the QIC region focused on refining the chronology of the Huancane I moraines. In 2008, new stratigraphic sections exposed by local lake-flooding events revealed multiple layers of peat within the Huancane I moraines. In both 2008 and 2009, samples were obtained for 10Be dating of boulders on Huancane I moraines. A combination of radiocarbon and 10Be ages indicate that the Huancane I moraines were deposited by ice cap expansion after ~3800 yr BP and likely by multiple advances at approximately 1000, 600, 400, and 200 yr BP. Radiocarbon and 10Be chronologies of the Huancane I moraines are compared with the Quelccaya ice core records (Thompson et al., 1985; 1986; 2006). Accumulation data from the ice core records are interpreted to indicate a significant wet period at ~1500-1700 AD followed by a significant drought at ~1720-1860 AD. We examine ice marginal fluctuations during these times to determine influence of such events on the ice cap extent.

Application of eigen value expansion to feature extraction from MRI images

International Nuclear Information System (INIS)

Kinosada, Yasutomi; Takeda, Kan; Nakagawa, Tsuyoshi

1991-01-01

The eigen value expansion technique was utilized for feature extraction of magnetic resonance (MR) images. The eigen value expansion is an orthonormal transformation method which decomposes a set of images into some statistically uncorrelated images. The technique was applied to MR images obtained with various imaging parameters at the same anatomical site. It generated one mean image and another set of images called bases for the images. Each basis corresponds to a feature in the images. A basis is, therefore, utilized for the feature extraction from MR images and a weighted sum of bases is also used for the feature enhancement. Furthermore, any MR image with specific feature can be obtained from a linear combination of the mean image and all of the bases. Images of hemorrhaged brain with a spin echo sequence and a series of cinematic cerebro spinal fluid flow images with ECG gated gradient refocused echo sequence were employed to estimate the ability of the feature extraction and the contrast enhancement. Results showed us that proposed application of an eigen value expansion technique to the feature extraction of MR images is good enough to clinical use and superior to other feature extraction methods such as producing a calculated MR image with a given TR and TE or the matched-filter method in processing speed and reproducibility of results. (author)

Landscape history and man-induced landscape changes in the young morainic area of the North European Plain — a case study from the Bäke Valley, Berlin

Science.gov (United States)

Böse, Margot; Brande, Arthur

2010-10-01

The Bäke creek valley is part of the young morainic area in Berlin. Its origin is related to meltwater flow and dead-ice persistence resulting in a valley with a lake-creek system. During the Late Glacial, the slopes of the valley were affected by solifluction. A Holocene brown soil developed in this material, whereas parts of the lakes were filled with limnic-telmatic sediments. The excavation site at Goerzallee revealed Bronze Age and Iron Age burial places at the upper part of the slope, as well as a fireplace further downslope, but the slope itself remained stable. Only German settlements in the 12th and 13th centuries changed the processes in the creek-lake system: the construction of water mills created a retention system with higher ground water levels in the surrounding areas. On the other hand, deforestation on the till plain and on the slope triggered erosion. Therefore, in medieval time interfingering organic sediments and sand layers were deposited in the lower part of the slope on top of the Holocene soil. The new soil which formed on top of these sediments was transformed by ploughing until the 19th century. In 1905/06 the lower part of the slope was reshaped by the construction of the Teltow Canal, following the valley of the former Bäke creek. Finally, the whole area was levelled by infill after World War II.

Handbook on linear motor application

International Nuclear Information System (INIS)

1988-10-01

This book guides the application for Linear motor. It lists classification and speciality of Linear Motor, terms of linear-induction motor, principle of the Motor, types on one-side linear-induction motor, bilateral linear-induction motor, linear-DC Motor on basic of the motor, linear-DC Motor for moving-coil type, linear-DC motor for permanent-magnet moving type, linear-DC motor for electricity non-utility type, linear-pulse motor for variable motor, linear-pulse motor for permanent magneto type, linear-vibration actuator, linear-vibration actuator for moving-coil type, linear synchronous motor, linear electromagnetic motor, linear electromagnetic solenoid, technical organization and magnetic levitation and linear motor and sensor.

Classification of Carotid Plaque Echogenicity by Combining Texture Features and Morphologic Characteristics.

Science.gov (United States)

Huang, Xiaowei; Zhang, Yanling; Qian, Ming; Meng, Long; Xiao, Yang; Niu, Lili; Zheng, Rongqin; Zheng, Hairong

2016-10-01

Anechoic carotid plaques on sonography have been used to predict future cardiovascular or cerebrovascular events. The purpose of this study was to investigate whether carotid plaque echogenicity could be assessed objectively by combining texture features extracted by MaZda software (Institute of Electronics, Technical University of Lodz, Lodz, Poland) and morphologic characteristics, which may provide a promising method for early prediction of acute cardiovascular disease. A total of 268 plaque images were collected from 136 volunteers and classified into 85 hyperechoic, 83 intermediate, and 100 anechoic plaques. About 300 texture features were extracted from histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model, and wavelet transform algorithms by MaZda. The morphologic characteristics, including degree of stenosis, maximum plaque intima-media thickness, and maximum plaque length, were measured by B-mode sonography. Statistically significant features were selected by analysis of covariance. The most discriminative features were obtained from statistically significant features by linear discriminant analysis. The K-nearest neighbor classifier was used to classify plaque echogenicity based on statistically significant and most discriminative features. A total of 30 statistically significant features were selected among the plaques, and 2 most discriminative features were obtained from the statistically significant features. The classification accuracy rates for 3 types of plaques based on statistically significant and most discriminative features were 72.03% (κ= 0.571; P MaZda and morphologic characteristics.

Solving non-linear Horn clauses using a linear Horn clause solver

DEFF Research Database (Denmark)

Kafle, Bishoksan; Gallagher, John Patrick; Ganty, Pierre

2016-01-01

In this paper we show that checking satisfiability of a set of non-linear Horn clauses (also called a non-linear Horn clause program) can be achieved using a solver for linear Horn clauses. We achieve this by interleaving a program transformation with a satisfiability checker for linear Horn...... clauses (also called a solver for linear Horn clauses). The program transformation is based on the notion of tree dimension, which we apply to a set of non-linear clauses, yielding a set whose derivation trees have bounded dimension. Such a set of clauses can be linearised. The main algorithm...... dimension. We constructed a prototype implementation of this approach and performed some experiments on a set of verification problems, which shows some promise....

Generalized Functional Linear Models With Semiparametric Single-Index Interactions

KAUST Repository

Li, Yehua

2010-06-01

We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

Generalized Functional Linear Models With Semiparametric Single-Index Interactions

KAUST Repository

Li, Yehua; Wang, Naisyin; Carroll, Raymond J.

2010-01-01

We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

Locally Linear Embedding of Local Orthogonal Least Squares Images for Face Recognition

Science.gov (United States)

Hafizhelmi Kamaru Zaman, Fadhlan

2018-03-01

Dimensionality reduction is very important in face recognition since it ensures that high-dimensionality data can be mapped to lower dimensional space without losing salient and integral facial information. Locally Linear Embedding (LLE) has been previously used to serve this purpose, however, the process of acquiring LLE features requires high computation and resources. To overcome this limitation, we propose a locally-applied Local Orthogonal Least Squares (LOLS) model can be used as initial feature extraction before the application of LLE. By construction of least squares regression under orthogonal constraints we can preserve more discriminant information in the local subspace of facial features while reducing the overall features into a more compact form that we called LOLS images. LLE can then be applied on the LOLS images to maps its representation into a global coordinate system of much lower dimensionality. Several experiments carried out using publicly available face datasets such as AR, ORL, YaleB, and FERET under Single Sample Per Person (SSPP) constraint demonstrates that our proposed method can reduce the time required to compute LLE features while delivering better accuracy when compared to when either LLE or OLS alone is used. Comparison against several other feature extraction methods and more recent feature-learning method such as state-of-the-art Convolutional Neural Networks (CNN) also reveal the superiority of the proposed method under SSPP constraint.

Linear mixed models a practical guide using statistical software

CERN Document Server

West, Brady T; Galecki, Andrzej T

2014-01-01

Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...

A linear motion machine for soft x-ray interferometry

International Nuclear Information System (INIS)

Duarte, R.; Howells, M.R.; Hussain, Z.; Lauritzen, T.; McGill, R.

1997-07-01

A Fourier Transform X-ray Spectrometer has been designed and built for use at the Advanced light source at Lawrence Berkeley National Laboratory. The design requires a total rectilinear motion of 15 mm with a maximum pitch error of the stage below ±0.4 μradians, to achieve this the authors chose to build the entire machine as a single monolithic flexure. A hydraulic driver with sliding O-ring seals was developed with the intention to provide motion with a stick-slip position error of less than 0.8 nm at a uniform velocity of 20 μm/sec. The machine is comprised of two pairs of nested linear motion flexures, all explained by means of a theory published earlier by Hathaway. Certain manufacturing errors were successfully corrected by an extra weak-link feature in the monolith frame. The engineering details of all the subsystems of the linear motion machine are described and measured performance reported

Linear and non-linear simulation of joints contact surface using ...

African Journals Online (AJOL)

The joint modelling including non-linear effects needs accurate and precise study of their behaviors. When joints are under the dynamic loading, micro, macro- slip happens in contact surface which is non-linear reason of the joint contact surface. The non-linear effects of joint contact surface on total behavior of structure are ...

Linear shaped charge

Energy Technology Data Exchange (ETDEWEB)

Peterson, David; Stofleth, Jerome H.; Saul, Venner W.

2017-07-11

Linear shaped charges are described herein. In a general embodiment, the linear shaped charge has an explosive with an elongated arrowhead-shaped profile. The linear shaped charge also has and an elongated v-shaped liner that is inset into a recess of the explosive. Another linear shaped charge includes an explosive that is shaped as a star-shaped prism. Liners are inset into crevices of the explosive, where the explosive acts as a tamper.

International workshop on emittance preservation in linear colliders

International Nuclear Information System (INIS)

Urakawa, Junji; Oide, Katsunobu

1993-09-01

The extremely low emittances, which are the essential feature for any linear collider, are far beyond those of the present high-energy accelerators. Every part of the linear-collider accelerator complex is liable to blow up them to a fatal degree. Above all, the main linac is the most critical part, since it will have an unprecedented length, through which very highly populated bunches should be accelerated without a faint increase of emittances. A lot of efforts have been paid, mainly theoretically, to settle this problem at all institutes. Any convincing conclusions are not yet reached. Furthermore, there are six approaches of substantially different schemes (Tesla, DLC, JLC, NLC, VLEPP, CLIC), each requiring its own way to tackle the problem. In this workshop, many up-to-date R and D results were presented by each institute. Judging from what were discussed, we may well say that the R and D work has advanced to such a level that the different approaches are rather helping each other to reach more concrete results. (J.P.N.)

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

Science.gov (United States)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Potenciální nebezpečnost vybraných morénami hrazených jezer v pohoří Cordillera Blanca, Peru

OpenAIRE

Emmer, Adam

2013-01-01

Adam Emmer: Potential hazardousness of selected moraine-dammed lakes in the Cordillera Blanca, Peru ABSTRACT: This work is devided into the two parts. Firs part reviews contemporary methods of assessment of potential hazardousness for moraine-dammed lakes (eight qualitative methods and three quantitative methods). Second part has two main aims: 1) Assessment of potential hazardousness of seven selected moraine-dammed lakes in the Cordillera Blanca, and 2) Analysis of suitability of these meth...

Hierarchical Feature Extraction With Local Neural Response for Image Recognition.

Science.gov (United States)

Li, Hong; Wei, Yantao; Li, Luoqing; Chen, C L P

2013-04-01

In this paper, a hierarchical feature extraction method is proposed for image recognition. The key idea of the proposed method is to extract an effective feature, called local neural response (LNR), of the input image with nontrivial discrimination and invariance properties by alternating between local coding and maximum pooling operation. The local coding, which is carried out on the locally linear manifold, can extract the salient feature of image patches and leads to a sparse measure matrix on which maximum pooling is carried out. The maximum pooling operation builds the translation invariance into the model. We also show that other invariant properties, such as rotation and scaling, can be induced by the proposed model. In addition, a template selection algorithm is presented to reduce computational complexity and to improve the discrimination ability of the LNR. Experimental results show that our method is robust to local distortion and clutter compared with state-of-the-art algorithms.

FEAST: a two-dimensional non-linear finite element code for calculating stresses

International Nuclear Information System (INIS)

Tayal, M.

1986-06-01

The computer code FEAST calculates stresses, strains, and displacements. The code is two-dimensional. That is, either plane or axisymmetric calculations can be done. The code models elastic, plastic, creep, and thermal strains and stresses. Cracking can also be simulated. The finite element method is used to solve equations describing the following fundamental laws of mechanics: equilibrium; compatibility; constitutive relations; yield criterion; and flow rule. FEAST combines several unique features that permit large time-steps in even severely non-linear situations. The features include a special formulation for permitting many finite elements to simultaneously cross the boundary from elastic to plastic behaviour; accomodation of large drops in yield-strength due to changes in local temperature and a three-step predictor-corrector method for plastic analyses. These features reduce computing costs. Comparisons against twenty analytical solutions and against experimental measurements show that predictions of FEAST are generally accurate to ± 5%

On the Use of Complementary Spectral Features for Speaker Recognition

Directory of Open Access Journals (Sweden)

Sridhar Krishnan

2007-12-01

Full Text Available The most popular features for speaker recognition are Mel frequency cepstral coefficients (MFCCs and linear prediction cepstral coefficients (LPCCs. These features are used extensively because they characterize the vocal tract configuration which is known to be highly speaker-dependent. In this work, several features are introduced that can characterize the vocal system in order to complement the traditional features and produce better speaker recognition models. The spectral centroid (SC, spectral bandwidth (SBW, spectral band energy (SBE, spectral crest factor (SCF, spectral flatness measure (SFM, Shannon entropy (SE, and Renyi entropy (RE were utilized for this purpose. This work demonstrates that these features are robust in noisy conditions by simulating some common distortions that are found in the speakers' environment and a typical telephone channel. Babble noise, additive white Gaussian noise (AWGN, and a bandpass channel with 1 dB of ripple were used to simulate these noisy conditions. The results show significant improvements in classification performance for all noise conditions when these features were used to complement the MFCC and ΔMFCC features. In particular, the SC and SCF improved performance in almost all noise conditions within the examined SNR range (10–40 dB. For example, in cases where there was only one source of distortion, classification improvements of up to 8% and 10% were achieved under babble noise and AWGN, respectively, using the SCF feature.

Instrument Identification in Polyphonic Music: Feature Weighting to Minimize Influence of Sound Overlaps

Directory of Open Access Journals (Sweden)

Goto Masataka

2007-01-01

Full Text Available We provide a new solution to the problem of feature variations caused by the overlapping of sounds in instrument identification in polyphonic music. When multiple instruments simultaneously play, partials (harmonic components of their sounds overlap and interfere, which makes the acoustic features different from those of monophonic sounds. To cope with this, we weight features based on how much they are affected by overlapping. First, we quantitatively evaluate the influence of overlapping on each feature as the ratio of the within-class variance to the between-class variance in the distribution of training data obtained from polyphonic sounds. Then, we generate feature axes using a weighted mixture that minimizes the influence via linear discriminant analysis. In addition, we improve instrument identification using musical context. Experimental results showed that the recognition rates using both feature weighting and musical context were 84.1 for duo, 77.6 for trio, and 72.3 for quartet; those without using either were 53.4, 49.6, and 46.5 , respectively.

Applying computational geometry techniques for advanced feature analysis in atom probe data

International Nuclear Information System (INIS)

Felfer, Peter; Ceguerra, Anna; Ringer, Simon; Cairney, Julie

2013-01-01

In this paper we present new methods for feature analysis in atom probe tomography data that have useful applications in materials characterisation. The analysis works on the principle of Voronoi subvolumes and piecewise linear approximations, and feature delineation based on the distance to the centre of mass of a subvolume (DCOM). Based on the coordinate systems defined by these approximations, two examples are shown of the new types of analyses that can be performed. The first is the analysis of line-like-objects (i.e. dislocations) using both proxigrams and line-excess plots. The second is interfacial excess mapping of an InGaAs quantum dot. - Highlights: • Computational geometry is used to detect and analyse features within atom probe data. • Limitations of conventional feature detection are overcome by using atomic density gradients. • 0D, 1D, 2D and 3D features can be analysed by using Voronoi tessellation for spatial binning. • New, robust analysis methods are demonstrated, including line and interfacial excess mapping

Nonlinear features of the electron temperature gradient mode and electron thermal transport in tokamaks

International Nuclear Information System (INIS)

Kaw, P.K.; Singh, R.; Weiland, J.G.

2001-01-01

Analytical investigations of several linear and nonlinear features of ETG turbulence are reported. The linear theory includes effects such as finite beta induced electromagnetic shielding, coupling to electron magnetohydrodynamic modes like whistlers etc. It is argued that nonlinearly, turbulence and transport are dominated by radially extended modes called 'streamers'. A nonlinear mechanism generating streamers based on a modulational instability theory of the ETG turbulence is also presented. The saturation levels of the streamers using a Kelvin Helmholtz secondary instability mechanism are calculated and levels of the electron thermal transport due to streamers are estimated. (author)

Frequency-chirped readout of spatial-spectral absorption features

International Nuclear Information System (INIS)

Chang, Tiejun; Mohan, R. Krishna; Harris, Todd L.; Merkel, Kristian D.; Tian Mingzhen; Babbitt, Wm. Randall

2004-01-01

This paper examines the physical mechanisms of reading out spatial-spectral absorption features in an inhomogeneously broadened medium using linear frequency-chirped electric fields. A Maxwell-Bloch model using numerical calculation for angled beams with arbitrary phase modulation is used to simulate the chirped field readout process. The simulation results indicate that any spatial-spectral absorption feature can be read out with a chirped field with the appropriate bandwidth, duration, and intensity. Mapping spectral absorption features into temporal intensity modulations depends on the chirp rate of the field. However, when probing a spatial-spectral grating with a chirped field, a beat signal representing the grating period can be created by interfering the emitted photon echo chirped field with a reference chirped field, regardless of the chirp rate. Comparisons are made between collinear and angled readout configurations. Readout signal strength and spurious signal distortions are investigated as functions of the grating strength and the Rabi frequency of the readout pulse. Using a collinear readout geometry, distortions from optical nutation on the transmitted field and higher-order harmonics are observed, both of which are avoided in an angled beam geometry

Linear algebra

CERN Document Server

Stoll, R R

1968-01-01

Linear Algebra is intended to be used as a text for a one-semester course in linear algebra at the undergraduate level. The treatment of the subject will be both useful to students of mathematics and those interested primarily in applications of the theory. The major prerequisite for mastering the material is the readiness of the student to reason abstractly. Specifically, this calls for an understanding of the fact that axioms are assumptions and that theorems are logical consequences of one or more axioms. Familiarity with calculus and linear differential equations is required for understand

A ROC-based feature selection method for computer-aided detection and diagnosis

Science.gov (United States)

Wang, Songyuan; Zhang, Guopeng; Liao, Qimei; Zhang, Junying; Jiao, Chun; Lu, Hongbing

2014-03-01

Image-based computer-aided detection and diagnosis (CAD) has been a very active research topic aiming to assist physicians to detect lesions and distinguish them from benign to malignant. However, the datasets fed into a classifier usually suffer from small number of samples, as well as significantly less samples available in one class (have a disease) than the other, resulting in the classifier's suboptimal performance. How to identifying the most characterizing features of the observed data for lesion detection is critical to improve the sensitivity and minimize false positives of a CAD system. In this study, we propose a novel feature selection method mR-FAST that combines the minimal-redundancymaximal relevance (mRMR) framework with a selection metric FAST (feature assessment by sliding thresholds) based on the area under a ROC curve (AUC) generated on optimal simple linear discriminants. With three feature datasets extracted from CAD systems for colon polyps and bladder cancer, we show that the space of candidate features selected by mR-FAST is more characterizing for lesion detection with higher AUC, enabling to find a compact subset of superior features at low cost.

Towards real-time detection and tracking of spatio-temporal features: Blob-filaments in fusion plasma

International Nuclear Information System (INIS)

Wu, Lingfei; Wu, Kesheng; Sim, Alex; Churchill, Michael; Choi, Jong Youl

2016-01-01

A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blob-filaments in real time in fusion plasma. Here, on a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.

Combining heterogenous features for 3D hand-held object recognition

Science.gov (United States)

Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

2014-10-01

Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

An integration of minimum local feature representation methods to recognize large variation of foods

Science.gov (United States)

Razali, Mohd Norhisham bin; Manshor, Noridayu; Halin, Alfian Abdul; Mustapha, Norwati; Yaakob, Razali

2017-10-01

Local invariant features have shown to be successful in describing object appearances for image classification tasks. Such features are robust towards occlusion and clutter and are also invariant against scale and orientation changes. This makes them suitable for classification tasks with little inter-class similarity and large intra-class difference. In this paper, we propose an integrated representation of the Speeded-Up Robust Feature (SURF) and Scale Invariant Feature Transform (SIFT) descriptors, using late fusion strategy. The proposed representation is used for food recognition from a dataset of food images with complex appearance variations. The Bag of Features (BOF) approach is employed to enhance the discriminative ability of the local features. Firstly, the individual local features are extracted to construct two kinds of visual vocabularies, representing SURF and SIFT. The visual vocabularies are then concatenated and fed into a Linear Support Vector Machine (SVM) to classify the respective food categories. Experimental results demonstrate impressive overall recognition at 82.38% classification accuracy based on the challenging UEC-Food100 dataset.

Electron Cloud Effect in the Linear Colliders

International Nuclear Information System (INIS)

Pivi, M

2004-01-01

Beam induced multipacting, driven by the electric field of successive positively charged bunches, may arise from a resonant motion of electrons, generated by secondary emission, bouncing back and forth between opposite walls of the vacuum chamber. The electron-cloud effect (ECE) has been observed or is expected at many storage rings [1]. In the beam pipe of the Damping Ring (DR) of a linear collider, an electron cloud is produced initially by ionization of the residual gas and photoelectrons from the synchrotron radiation. The cloud is then sustained by secondary electron emission. This electron cloud can reach equilibrium after the passage of only a few bunches. The electron-cloud effect may be responsible for collective effects as fast coupled-bunch and single-bunch instability, emittance blow-up or incoherent tune shift when the bunch current exceeds a certain threshold, accompanied by a large number of electrons in the vacuum chamber. The ECE was identified as one of the most important R and D topics in the International Linear Collider Report [2]. Systematic studies on the possible electron-cloud effect have been initiated at SLAC for the GLC/NLC and TESLA linear colliders, with particular attention to the effect in the positron main damping ring (MDR) and the positron Low Emittance Transport which includes the bunch compressor system (BCS), the main linac, and the beam delivery system (BDS). We present recent computer simulation results for the main features of the electron cloud generation in both machine designs. Thus, single and coupled-bunch instability thresholds are estimated for the GLC/NLC design

Linear algebra

CERN Document Server

Liesen, Jörg

2015-01-01

This self-contained textbook takes a matrix-oriented approach to linear algebra and presents a complete theory, including all details and proofs, culminating in the Jordan canonical form and its proof. Throughout the development, the applicability of the results is highlighted. Additionally, the book presents special topics from applied linear algebra including matrix functions, the singular value decomposition, the Kronecker product and linear matrix equations. The matrix-oriented approach to linear algebra leads to a better intuition and a deeper understanding of the abstract concepts, and therefore simplifies their use in real world applications. Some of these applications are presented in detailed examples. In several ‘MATLAB-Minutes’ students can comprehend the concepts and results using computational experiments. Necessary basics for the use of MATLAB are presented in a short introduction. Students can also actively work with the material and practice their mathematical skills in more than 300 exerc...

Efficient and robust model-to-image alignment using 3D scale-invariant features.

Science.gov (United States)

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

A Detailed Analytical Study of Non-Linear Semiconductor Device Modelling

Directory of Open Access Journals (Sweden)

Umesh Kumar

1995-01-01

junction diode have been developed. The results of computer simulated examples have been presented in each case. The non-linear lumped model for Gunn is a unified model as it describes the diffusion effects as the-domain traves from cathode to anode. An additional feature of this model is that it describes the domain extinction and nucleation phenomena in Gunn dioder with the help of a simple timing circuit. The non-linear lumped model for SCR is general and is valid under any mode of operation in any circuit environment. The memristive circuit model for p-n junction diodes is capable of simulating realistically the diode’s dynamic behavior under reverse, forward and sinusiodal operating modes. The model uses memristor, the charge-controlled resistor to mimic various second-order effects due to conductivity modulation. It is found that both storage time and fall time of the diode can be accurately predicted.

Linear and Generalized Linear Mixed Models and Their Applications

CERN Document Server

Jiang, Jiming

2007-01-01

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested

Enumeration of virtual libraries of combinatorial modular macrocyclic (bracelet, necklace) architectures and their linear counterparts.

Science.gov (United States)

Taniguchi, Masahiko; Du, Hai; Lindsey, Jonathan S

2013-09-23

A wide variety of cyclic molecular architectures are built of modular subunits and can be formed combinatorially. The mathematics for enumeration of such objects is well-developed yet lacks key features of importance in chemistry, such as specifying (i) the structures of individual members among a set of isomers, (ii) the distribution (i.e., relative amounts) of products, and (iii) the effect of nonequal ratios of reacting monomers on the product distribution. Here, a software program (Cyclaplex) has been developed to determine the number, identity (including isomers), and relative amounts of linear and cyclic architectures from a given number and ratio of reacting monomers. The program includes both mathematical formulas and generative algorithms for enumeration; the latter go beyond the former to provide desired molecular-relevant information and data-mining features. The program is equipped to enumerate four types of architectures: (i) linear architectures with directionality (macroscopic equivalent = electrical extension cords), (ii) linear architectures without directionality (batons), (iii) cyclic architectures with directionality (necklaces), and (iv) cyclic architectures without directionality (bracelets). The program can be applied to cyclic peptides, cycloveratrylenes, cyclens, calixarenes, cyclodextrins, crown ethers, cucurbiturils, annulenes, expanded meso-substituted porphyrin(ogen)s, and diverse supramolecular (e.g., protein) assemblies. The size of accessible architectures encompasses up to 12 modular subunits derived from 12 reacting monomers or larger architectures (e.g. 13-17 subunits) from fewer types of monomers (e.g. 2-4). A particular application concerns understanding the possible heterogeneity of (natural or biohybrid) photosynthetic light-harvesting oligomers (cyclic, linear) formed from distinct peptide subunits.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

Science.gov (United States)

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

Introduction to Special Feature on Catastrophic Thresholds, Perspectives, Definitions, and Applications

Directory of Open Access Journals (Sweden)

Robert A. Washington-Allen

2010-09-01

Full Text Available The contributions to this special feature focus on several conceptual and operational applications for understanding non-linear behavior of complex systems with various ecological criteria at unique levels of organization. The organizing theme of the feature emphasizes alternative stable states or regimes and intervening thresholds that possess great relevance to ecology and natural resource management. The authors within this special feature address the conceptual models of catastrophe theory, self-organization, cross-scale interactions and time-scale calculus; develop operational definitions and procedures for understanding the occurrence of dynamic regimes or multiple stable states and thresholds; suggest diagnostics tools for detection of states and thresholds and contribute to the development of scaling laws; and finally, demonstrate applications that promote both greater ecological understanding and management prescriptions for insect and disease outbreaks, resource island formation, and characterization of ecological resilience. This Special Feature concludes with a synthesis of the commonalities and disparities of concepts and interpretations among the contributed papers to identify issues and approaches that merit further research emphasis.

Statistical distributions of earthquakes and related non-linear features in seismic waves

International Nuclear Information System (INIS)

Apostol, B.-F.

2006-01-01

A few basic facts in the science of the earthquakes are briefly reviewed. An accumulation, or growth, model is put forward for the focal mechanisms and the critical focal zone of the earthquakes, which relates the earthquake average recurrence time to the released seismic energy. The temporal statistical distribution for average recurrence time is introduced for earthquakes, and, on this basis, the Omori-type distribution in energy is derived, as well as the distribution in magnitude, by making use of the semi-empirical Gutenberg-Richter law relating seismic energy to earthquake magnitude. On geometric grounds, the accumulation model suggests the value r = 1/3 for the Omori parameter in the power-law of energy distribution, which leads to β = 1,17 for the coefficient in the Gutenberg-Richter recurrence law, in fair agreement with the statistical analysis of the empirical data. Making use of this value, the empirical Bath's law is discussed for the average magnitude of the aftershocks (which is 1.2 less than the magnitude of the main seismic shock), by assuming that the aftershocks are relaxation events of the seismic zone. The time distribution of the earthquakes with a fixed average recurrence time is also derived, the earthquake occurrence prediction is discussed by means of the average recurrence time and the seismicity rate, and application of this discussion to the seismic region Vrancea, Romania, is outlined. Finally, a special effect of non-linear behaviour of the seismic waves is discussed, by describing an exact solution derived recently for the elastic waves equation with cubic anharmonicities, its relevance, and its connection to the approximate quasi-plane waves picture. The properties of the seismic activity accompanying a main seismic shock, both like foreshocks and aftershocks, are relegated to forthcoming publications. (author)

A Graphical User Interface to Generalized Linear Models in MATLAB

Directory of Open Access Journals (Sweden)

Peter Dunn

1999-07-01

Full Text Available Generalized linear models unite a wide variety of statistical models in a common theoretical framework. This paper discusses GLMLAB-software that enables such models to be fitted in the popular mathematical package MATLAB. It provides a graphical user interface to the powerful MATLAB computational engine to produce a program that is easy to use but with many features, including offsets, prior weights and user-defined distributions and link functions. MATLAB's graphical capacities are also utilized in providing a number of simple residual diagnostic plots.

Linear and non-linear energy barriers in systems of interacting single-domain ferromagnetic particles

International Nuclear Information System (INIS)

Petrila, Iulian; Bodale, Ilie; Rotarescu, Cristian; Stancu, Alexandru

2011-01-01

A comparative analysis between linear and non-linear energy barriers used for modeling statistical thermally-excited ferromagnetic systems is presented. The linear energy barrier is obtained by new symmetry considerations about the anisotropy energy and the link with the non-linear energy barrier is also presented. For a relevant analysis we compare the effects of linear and non-linear energy barriers implemented in two different models: Preisach-Neel and Ising-Metropolis. The differences between energy barriers which are reflected in different coercive field dependence of the temperature are also presented. -- Highlights: → The linear energy barrier is obtained from symmetry considerations. → The linear and non-linear energy barriers are calibrated and implemented in Preisach-Neel and Ising-Metropolis models. → The temperature and time effects of the linear and non-linear energy barriers are analyzed.

Detection of hypertensive retinopathy using vessel measurements and textural features.

Science.gov (United States)

Agurto, Carla; Joshi, Vinayak; Nemeth, Sheila; Soliz, Peter; Barriga, Simon

2014-01-01

Features that indicate hypertensive retinopathy have been well described in the medical literature. This paper presents a new system to automatically classify subjects with hypertensive retinopathy (HR) using digital color fundus images. Our method consists of the following steps: 1) normalization and enhancement of the image; 2) determination of regions of interest based on automatic location of the optic disc; 3) segmentation of the retinal vasculature and measurement of vessel width and tortuosity; 4) extraction of color features; 5) classification of vessel segments as arteries or veins; 6) calculation of artery-vein ratios using the six widest (major) vessels for each category; 7) calculation of mean red intensity and saturation values for all arteries; 8) calculation of amplitude-modulation frequency-modulation (AM-FM) features for entire image; and 9) classification of features into HR and non-HR using linear regression. This approach was tested on 74 digital color fundus photographs taken with TOPCON and CANON retinal cameras using leave-one out cross validation. An area under the ROC curve (AUC) of 0.84 was achieved with sensitivity and specificity of 90% and 67%, respectively.

Linearity and Non-linearity of Photorefractive effect in Materials ...

African Journals Online (AJOL)