WorldWideScience

Sample records for deep n-well maps

  1. Status and perspectives of deep N-well 130 nm CMOS MAPS

    International Nuclear Information System (INIS)

    Re, Valerio

    2009-01-01

    Deep N-Well (DNW) MAPS were developed in two different flavors to approach the specifications of vertex detectors in dissimilar experimental environments such as the Super B-Factory and the ILC. The first generation of MAPS with on-pixel data sparsification and time stamping capabilities is now available and was tested in a beam for the first time in September 2008. These devices are fabricated in a commercial 130 nm CMOS process, and the triple well structure available in such an ultra-deep submicron technology is exploited by using the deep N-well as the charge-collecting electrode. Because of the high integration density of such a technology, complex digital functions can be included in each pixel, implementing a sparsified readout architecture of the pixel matrix with time stamping. This paper reviews the features of the ''ILC class'' and ''SuperB class'' MAPS devices, discussing their different design in terms of pixel pitch, analog signal processing, and digital readout architecture. For SuperB, a data-driven, continuously operating readout scheme was adopted along with a macropixel matrix arrangement, whereas for the ILC the matrix is read out in the long intertrain period. In both versions, the address of hit pixels is transmitted off-chip along with the time stamp. The experimental performance of the chips provides an assessment of the Deep N-Well MAPS potential in view of future applications. The paper also discusses the way forward in the development of these devices, outlining the issues that have to be tackled to design full size Deep N-Well MAPS for actual experiments. These sensors could take advantage from technological advances in microelectronic industry, such as vertical integration. The impact of these new technologies on the design and performance of DNW pixel sensors could be large, with potential benefit for various device features, from the charge collection properties to the digital readout architecture.

  2. Recent progress in the development of 3D deep n-well CMOS MAPS

    International Nuclear Information System (INIS)

    Traversi, G; Manghisoni, M; Re, V; Gaioni, L; Manazza, A; Ratti, L; Zucca, S

    2012-01-01

    In the deep n-well (DNW) monolithic active pixel sensor (MAPS) a full in-pixel signal processing chain is integrated by exploiting the triple well option of a deep submicron CMOS process. This work is concerned with the design and characterization of DNW MAPS fabricated in a vertical integration (3D) CMOS technology. 3D processes can be very effective in overcoming typical limitations of monolithic active pixel sensors. This paper discusses the main features of a new analog processor for DNW MAPS (ApselVI) in view of applications to the SVT Layer0 of the SuperB Factory. It also presents the first experimental results from the test of a DNW MAPS prototype in the GlobalFoundries 130 nm CMOS technology.

  3. A 3D deep n-well CMOS MAPS for the ILC vertex detector

    Energy Technology Data Exchange (ETDEWEB)

    Gaioni, L., E-mail: luigi.gaioni@unipv.i [Universita di Pavia, I-27100 Pavia (Italy); INFN, Sezione di Pavia, I-27100 Pavia (Italy); Manghisoni, M. [Universita di Bergamo, I-24044 Dalmine (Bulgaria) (Italy); INFN, Sezione di Pavia, I-27100 Pavia (Italy); Ratti, L. [Universita di Pavia, I-27100 Pavia (Italy); INFN, Sezione di Pavia, I-27100 Pavia (Italy); Re, V.; Traversi, G. [Universita di Bergamo, I-24044 Dalmine (Bulgaria) (Italy); INFN, Sezione di Pavia, I-27100 Pavia (Italy)

    2010-05-21

    This work presents the features of a new kind of deep n-well monolithic active pixel sensor (DNW-MAPS), called SDR1 (Sparsified Data Readout), which exploits the capabilities of vertical integration (3D) processing in view of the design of a high granularity detector for vertexing applications at the International Linear Collider (ILC). SDR1 inherits and extends the functional capabilities of DNW-MAPS fabricated in planar (2D) CMOS technology and is expected to show better collection efficiency with respect to 2D versions. The aim of the paper is to outline the features of analog and digital architecture of the SDR1 chip, together with circuit simulations data. Also some device simulation results concerning detection efficiency will be discussed.

  4. Deep n-well MAPS in a 130 nm CMOS technology: Beam test results

    International Nuclear Information System (INIS)

    Neri, N.; Avanzini, C.; Batignani, G.; Bettarini, S.; Bosi, F.; Ceccanti, M.; Cenci, R.; Cervelli, A.; Crescioli, F.; Dell'Orso, M.; Forti, F.; Giannetti, P.; Giorgi, M.A.; Gregucci, S.; Mammini, P.; Marchiori, G.; Massa, M.; Morsani, F.; Paoloni, E.; Piendibene, M.

    2010-01-01

    We report on recent beam test results for the APSEL4D chip, a new deep n-well MAPS prototype with a full in-pixel signal processing chain obtained by exploiting the triple well option of the CMOS 0.13μm process. The APSEL4D chip consists of a 4096 pixel matrix (32 rows and 128 columns) with 50x50μm 2 pixel cell area, with custom readout architecture capable of performing data sparsification at pixel level. APSEL4D has been characterized in terms of charge collection efficiency and intrinsic spatial resolution under different conditions of discriminator threshold settings using a 12 GeV/c proton beam in the T9 area of the CERN PS. We observe a maximum hit efficiency of 92% and we estimate an intrinsic resolution of about 14μm. The data driven approach of the tracking detector readout chips has been successfully used to demonstrate the possibility to build a Level 1 trigger system based on associative memories. The analysis of the beam test data is critically reviewed along with the characterization of the device under test.

  5. A 3D Vertically Integrated Deep N-Well CMOS MAPS for the SuperB Layer0

    International Nuclear Information System (INIS)

    Traversi, G; Manghisoni, M; Re, V; Gaioni, L; Ratti, L

    2011-01-01

    Deep N-Well (DNW) Monolithic Active Pixel Sensors (MAPS) have been developed in the last few years with the aim of building monolithic sensors with similar functionalities as hybrid pixels systems. In these devices the triple well option, available in deep submicron processes, is exploited to implement analog and digital signal processing at the pixel level. Many prototypes have been fabricated in a planar (2D) 130nm CMOS technology. A new kind of DNW-MAPS, namely Apsel5 3 D, which exploits the capabilities of vertical integration (3D) processes, is presented and discussed in this paper. The impact of 3D processes on the design and performance of DNW pixel sensors could be large, with significant advantages in terms of detection efficiency, pixel cell size and immunity to cross-talk, therefore complying with the severe constraints set by future HEP experiments.

  6. A 3D Vertically Integrated Deep N-Well CMOS MAPS for the SuperB Layer0

    Energy Technology Data Exchange (ETDEWEB)

    Traversi, G; Manghisoni, M; Re, V [University of Bergamo, Via Marconi 5, 24044 Dalmine (Italy); Gaioni, L; Ratti, L, E-mail: gianluca.traversi@unibg.it [INFN Pavia, Via Bassi 6, 27100 Pavia (Italy)

    2011-01-15

    Deep N-Well (DNW) Monolithic Active Pixel Sensors (MAPS) have been developed in the last few years with the aim of building monolithic sensors with similar functionalities as hybrid pixels systems. In these devices the triple well option, available in deep submicron processes, is exploited to implement analog and digital signal processing at the pixel level. Many prototypes have been fabricated in a planar (2D) 130nm CMOS technology. A new kind of DNW-MAPS, namely Apsel5{sub 3}D, which exploits the capabilities of vertical integration (3D) processes, is presented and discussed in this paper. The impact of 3D processes on the design and performance of DNW pixel sensors could be large, with significant advantages in terms of detection efficiency, pixel cell size and immunity to cross-talk, therefore complying with the severe constraints set by future HEP experiments.

  7. First results from the characterization of a three-dimensional deep N-well MAPS prototype for vertexing applications

    International Nuclear Information System (INIS)

    Ratti, L.; Gaioni, L.; Manazza, A.; Manghisoni, M.; Re, V.; Traversi, G.

    2013-01-01

    The prototype of a three-dimensional (3D) monolithic active pixel sensor (MAPS) has been characterized. The device, featuring a 20μm pitch, was designed based on the same approach that was adopted in developing the so-called deep N-well (DNW) MAPS in planar CMOS process. The new 3D design relies upon stacking two homogeneous tiers fabricated in a 130 nm CMOS technology. Different kinds of test structures, including single pixels, 3×3 arrays and 8×8 and 16×16 matrices were tested. Functionality of the collecting deep N-well electrode, the analog front-end and the digital readout electronics has been demonstrated. Inter-tier communication was found to work properly in the case of redundant interconnection and could be exploited for the test of the analog pixel section. On the other hand, inter-tier interconnections based on individual bond pads were proven ineffective likely due to wafer misalignment. -- Highlights: ► First results on the characterization of 3D DNW monolithic sensor. ► Functionality of the analog and digital sections is demonstrated. ► DNW collecting electrode is tested by means of a laser source. ► A non-linear model for charge preamplifier response is discussed. ► Redundant vertical interconnection is shown to work properly.

  8. First results from the characterization of a three-dimensional deep N-well MAPS prototype for vertexing applications

    Energy Technology Data Exchange (ETDEWEB)

    Ratti, L., E-mail: lodovico.ratti@unipv.it [Università di Pavia, Dipartimento di Elettronica, Via Ferrata 1, I-27100 Pavia (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Gaioni, L. [INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Manazza, A. [Università di Pavia, Dipartimento di Elettronica, Via Ferrata 1, I-27100 Pavia (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Manghisoni, M.; Re, V.; Traversi, G. [Università di Bergamo, Dipartimento di Ingegneria Industriale, Via Marconi 5, I-24044 Dalmine (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy)

    2013-01-21

    The prototype of a three-dimensional (3D) monolithic active pixel sensor (MAPS) has been characterized. The device, featuring a 20μm pitch, was designed based on the same approach that was adopted in developing the so-called deep N-well (DNW) MAPS in planar CMOS process. The new 3D design relies upon stacking two homogeneous tiers fabricated in a 130 nm CMOS technology. Different kinds of test structures, including single pixels, 3×3 arrays and 8×8 and 16×16 matrices were tested. Functionality of the collecting deep N-well electrode, the analog front-end and the digital readout electronics has been demonstrated. Inter-tier communication was found to work properly in the case of redundant interconnection and could be exploited for the test of the analog pixel section. On the other hand, inter-tier interconnections based on individual bond pads were proven ineffective likely due to wafer misalignment. -- Highlights: ► First results on the characterization of 3D DNW monolithic sensor. ► Functionality of the analog and digital sections is demonstrated. ► DNW collecting electrode is tested by means of a laser source. ► A non-linear model for charge preamplifier response is discussed. ► Redundant vertical interconnection is shown to work properly.

  9. Towards a high performance vertex detector based on 3D integration of deep N-well MAPS

    International Nuclear Information System (INIS)

    Re, V

    2010-01-01

    The development of deep N-Well (DNW) CMOS active pixel sensors was driven by the ambitious goal of designing a monolithic device with similar functionalities as in hybrid pixel readout chips, such as pixel-level sparsification and time stamping. The implementation of the DNW MAPS concept in a 3D vertical integration process naturally leads the designer towards putting more intelligence in the chip and in the pixels themselves, achieving novel device structures based on the interconnection of two or more layers fabricated in the same technology. These devices are read out with a data-push scheme that makes it possible to use pixel data for the generation of a flexible level 1 track trigger, based on associative memories, with short latency and high efficiency. This paper gives an update of the present status of DNW MAPS design in both 2D and 3D versions, and presents a discussion of the architectures that are being devised for the Layer 0 of the SuperB Silicon Vertex Tracker.

  10. Vertically integrated deep N-well CMOS MAPS with sparsification and time stamping capabilities for thin charged particle trackers

    International Nuclear Information System (INIS)

    Ratti, L.; Gaioni, L.; Manghisoni, M.; Re, V.; Traversi, G.

    2010-01-01

    A fine pitch, deep N-well CMOS monolithic active pixel sensor (DNW CMOS MAPS) with sparsified readout architecture and time stamping capabilities has been designed in a vertical integration (3D) technology. In this process, two 130 nm CMOS wafers are face-to-face bonded by means of thermo-compression techniques ensuring both the mechanical stability of the structure and the electrical interconnection between circuits belonging to different layers. This 3D design represents the evolution of a DNW monolithic sensor already fabricated in a planar 130 nm CMOS technology in view of applications to the vertex detector of the International Linear Collider (ILC). The paper is devoted to discussing the main design features and expected performance of the 3D DNW MAPS. Besides describing the front-end circuits and the general architecture of the detector, the work also provides some results from calculations and Monte Carlo device simulations comparing the old 2D solution with the new 3D one and illustrating the attainable detection efficiency improvements.

  11. Vertically integrated deep N-well CMOS MAPS with sparsification and time stamping capabilities for thin charged particle trackers

    Energy Technology Data Exchange (ETDEWEB)

    Ratti, L., E-mail: lodovico.ratti@unipv.i [Universita di Pavia, Dipartimento di Elettronica, Via Ferrata 1, I-27100 Pavia (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Gaioni, L. [Universita di Pavia, Dipartimento di Elettronica, Via Ferrata 1, I-27100 Pavia (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Manghisoni, M.; Re, V.; Traversi, G. [Universita di Bergamo, Dipartimento di Ingegneria Industriale, Via Marconi 5, I-24044 Dalmine (Bulgaria) (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy)

    2010-12-11

    A fine pitch, deep N-well CMOS monolithic active pixel sensor (DNW CMOS MAPS) with sparsified readout architecture and time stamping capabilities has been designed in a vertical integration (3D) technology. In this process, two 130 nm CMOS wafers are face-to-face bonded by means of thermo-compression techniques ensuring both the mechanical stability of the structure and the electrical interconnection between circuits belonging to different layers. This 3D design represents the evolution of a DNW monolithic sensor already fabricated in a planar 130 nm CMOS technology in view of applications to the vertex detector of the International Linear Collider (ILC). The paper is devoted to discussing the main design features and expected performance of the 3D DNW MAPS. Besides describing the front-end circuits and the general architecture of the detector, the work also provides some results from calculations and Monte Carlo device simulations comparing the old 2D solution with the new 3D one and illustrating the attainable detection efficiency improvements.

  12. Towards a high performance vertex detector based on 3D integration of deep N-well MAPS

    Energy Technology Data Exchange (ETDEWEB)

    Re, V, E-mail: valerio.re@unibg.i [University of Bergamo, Department of Industrial Engineering, Viale Marconi 5, 24044 Dalmine (Italy)

    2010-06-15

    The development of deep N-Well (DNW) CMOS active pixel sensors was driven by the ambitious goal of designing a monolithic device with similar functionalities as in hybrid pixel readout chips, such as pixel-level sparsification and time stamping. The implementation of the DNW MAPS concept in a 3D vertical integration process naturally leads the designer towards putting more intelligence in the chip and in the pixels themselves, achieving novel device structures based on the interconnection of two or more layers fabricated in the same technology. These devices are read out with a data-push scheme that makes it possible to use pixel data for the generation of a flexible level 1 track trigger, based on associative memories, with short latency and high efficiency. This paper gives an update of the present status of DNW MAPS design in both 2D and 3D versions, and presents a discussion of the architectures that are being devised for the Layer 0 of the SuperB Silicon Vertex Tracker.

  13. First generation of deep n-well CMOS MAPS with in-pixel sparsification for the ILC vertex detector

    International Nuclear Information System (INIS)

    Traversi, Gianluca; Bulgheroni, Antonio; Caccia, Massimo; Jastrzab, Marcin; Manghisoni, Massimo; Pozzati, Enrico; Ratti, Lodovico; Re, Valerio

    2009-01-01

    In this paper we present the characterization results relevant to a deep n-well (DNW) CMOS active pixel sensor chip designed for vertexing applications at the International Linear Collider. In this chip, named sparsified digital readout (SDR0), for the first time we implemented a sparsification logic at the pixel level. The DNW available in deep submicron CMOS processes is used to collect the charge released in the substrate, and signal processing is performed by a classical optimum amplifying stage for capacitive detectors. In this work, the experimental characterization of the SDR0 chip, including data from radioactive source ( 55 Fe) tests, will be presented.

  14. Effect of body biasing on single-event induced charge collection in deep N-well technology

    International Nuclear Information System (INIS)

    Ding Yi; Hu Jian-Guo; Tan Hong-Zhou; Qin Jun-Rui

    2015-01-01

    As the device size decreases, the soft error induced by space ions is becoming a great concern for the reliability of integrated circuits (ICs). At present, the body biasing technique is widely used in highly scaled technologies. In the paper, using the three-dimensional technology computer-aided design (TCAD) simulation, we analyze the effect of the body biasing on the single-event charge collection in deep N-well technology. Our simulation results show that the body biasing mainly affects the behavior of the source, and the effect of body biasing on the charge collection for the nMOSFET and pMOSFET is quite different. For the nMOSFET, the RBB will increase the charge collection, while the FBB will reduce the charge collection. For the pMOSFET, the effect of RBB on the SET pulse width is small, while the FBB has an adverse effect. Moreover, the differenceof the effect of body biasing on the charge collection is compared in deep N-well and twin well. (paper)

  15. The first fully functional 3D CMOS chip with Deep N-well active pixel sensors for the ILC vertex detector

    International Nuclear Information System (INIS)

    Traversi, G.; Gaioni, L.; Manazza, A.; Manghisoni, M.; Ratti, L.; Re, V.

    2013-01-01

    This work presents the characterization of Deep N-well (DNW) active pixel sensors fabricated in a vertically integrated technology. The DNW approach takes advantage of the triple well structure to lay out a sensor with relatively large charge collecting area (as compared to standard three transistor MAPS), while the readout is performed by a classical signal processing chain for capacitive detectors. This new 3D design relies upon stacking two homogeneous tiers fabricated in a 130 nm CMOS process where the top tier is thinned down to about 12μm to expose through silicon vias (TSV), therefore making connection to the buried circuits possible. This technology has been used to design a fine pitch 3D CMOS sensor with sparsification capabilities, in view of vertexing applications to the International Linear Collider (ILC) experiments. Results from the characterization of different kind of test structures, including single pixels, 3×3 and 8×8 matrices, are presented

  16. Deep Mapping and Spatial Anthropology

    Directory of Open Access Journals (Sweden)

    Les Roberts

    2016-01-01

    Full Text Available This paper provides an introduction to the Humanities Special Issue on “Deep Mapping”. It sets out the rationale for the collection and explores the broad-ranging nature of perspectives and practices that fall within the “undisciplined” interdisciplinary domain of spatial humanities. Sketching a cross-current of ideas that have begun to coalesce around the concept of “deep mapping”, the paper argues that rather than attempting to outline a set of defining characteristics and “deep” cartographic features, a more instructive approach is to pay closer attention to the multivalent ways deep mapping is performatively put to work. Casting a critical and reflexive gaze over the developing discourse of deep mapping, it is argued that what deep mapping “is” cannot be reduced to the otherwise a-spatial and a-temporal fixity of the “deep map”. In this respect, as an undisciplined survey of this increasing expansive field of study and practice, the paper explores the ways in which deep mapping can engage broader discussion around questions of spatial anthropology.

  17. Mapping the deep sea floor

    DEFF Research Database (Denmark)

    Nielsen, Kristian Hvidtfelt

    's attempt to "wave the Danish flag". The expedition was the first scientific expedition to have on board a separate press section communicating its scientific results as well as Danish nationality to the wider public. In this poster, the Galathea maps of the Philippine Trench are placed within this context...... of combined national "flag-waving", publicity, and scientific exploration....

  18. Deep neural mapping support vector machines.

    Science.gov (United States)

    Li, Yujian; Zhang, Ting

    2017-09-01

    The choice of kernel has an important effect on the performance of a support vector machine (SVM). The effect could be reduced by NEUROSVM, an architecture using multilayer perceptron for feature extraction and SVM for classification. In binary classification, a general linear kernel NEUROSVM can be theoretically simplified as an input layer, many hidden layers, and an SVM output layer. As a feature extractor, the sub-network composed of the input and hidden layers is first trained together with a virtual ordinary output layer by backpropagation, then with the output of its last hidden layer taken as input of the SVM classifier for further training separately. By taking the sub-network as a kernel mapping from the original input space into a feature space, we present a novel model, called deep neural mapping support vector machine (DNMSVM), from the viewpoint of deep learning. This model is also a new and general kernel learning method, where the kernel mapping is indeed an explicit function expressed as a sub-network, different from an implicit function induced by a kernel function traditionally. Moreover, we exploit a two-stage procedure of contrastive divergence learning and gradient descent for DNMSVM to jointly training an adaptive kernel mapping instead of a kernel function, without requirement of kernel tricks. As a whole of the sub-network and the SVM classifier, the joint training of DNMSVM is done by using gradient descent to optimize the objective function with the sub-network layer-wise pre-trained via contrastive divergence learning of restricted Boltzmann machines. Compared to the separate training of NEUROSVM, the joint training is a new algorithm for DNMSVM to have advantages over NEUROSVM. Experimental results show that DNMSVM can outperform NEUROSVM and RBFSVM (i.e., SVM with the kernel of radial basis function), demonstrating its effectiveness. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Clustered deep shadow maps for integrated polyhedral and volume rendering

    KAUST Repository

    Bornik, Alexander; Knecht, Wolfgang; Hadwiger, Markus; Schmalstieg, Dieter

    2012-01-01

    This paper presents a hardware-accelerated approach for shadow computation in scenes containing both complex volumetric objects and polyhedral models. Our system is the first hardware accelerated complete implementation of deep shadow maps, which

  20. Anticipating Deep Mapping: Tracing the Spatial Practice of Tim Robinson

    Directory of Open Access Journals (Sweden)

    Jos Smith

    2015-07-01

    Full Text Available There has been little academic research published on the work of Tim Robinson despite an illustrious career, first as an artist of the London avant-garde, then as a map-maker in the west of Ireland, and finally as an author of place. In part, this dearth is due to the difficulty of approaching these three diverse strands collectively. However, recent developments in the field of deep mapping encourage us to look back at the continuity of Robinson’s achievements in full and offer a suitable framework for doing so. Socially engaged with living communities and a depth of historical knowledge about place, but at the same time keen to contribute artistically to the ongoing contemporary culture of place, the parameters of deep mapping are broad enough to encompass the range of Robinson’s whole practice and suggest unique ways to illuminate his very unusual career. But Robinson’s achievements also encourage a reflection on the historical context of deep mapping itself, as well as on the nature of its spatial practice (especially where space comes to connote a medium to be worked rather than an area/volume. With this in mind the following article both explores Robinson’s work through deep mapping and deep mapping through the work of this unusual artist.

  1. Clustered deep shadow maps for integrated polyhedral and volume rendering

    KAUST Repository

    Bornik, Alexander

    2012-01-01

    This paper presents a hardware-accelerated approach for shadow computation in scenes containing both complex volumetric objects and polyhedral models. Our system is the first hardware accelerated complete implementation of deep shadow maps, which unifies the computation of volumetric and geometric shadows. Up to now such unified computation was limited to software-only rendering . Previous hardware accelerated techniques can handle only geometric or only volumetric scenes - both resulting in the loss of important properties of the original concept. Our approach supports interactive rendering of polyhedrally bounded volumetric objects on the GPU based on ray casting. The ray casting can be conveniently used for both the shadow map computation and the rendering. We show how anti-aliased high-quality shadows are feasible in scenes composed of multiple overlapping translucent objects, and how sparse scenes can be handled efficiently using clustered deep shadow maps. © 2012 Springer-Verlag.

  2. Archaeological Excavation and Deep Mapping in Historic Rural Communities

    Directory of Open Access Journals (Sweden)

    Carenza Lewis

    2015-09-01

    Full Text Available This paper reviews the results of more than a hundred small archaeological “test pit” excavations carried out in 2013 within four rural communities in eastern England. Each excavation used standardized protocols in a different location within the host village, with the finds dated and mapped to create a series of maps spanning more than 3500 years, in order to advance understanding of the spatial development of settlements and landscapes over time. The excavations were all carried out by local volunteers working physically within their own communities, supported and advised by professional archaeologists, with most test pits sited in volunteers’ own gardens or those of their friends, family or neighbors. Site-by-site, the results provided glimpses of the use made by humans of each of the excavated sites spanning prehistory to the present day; while in aggregate the mapped data show how settlement and land-use developed and changed over time. Feedback from participants also demonstrates the diverse positive impacts the project had on individuals and communities. The results are presented and reviewed here in order to highlight the contribution archaeological test pit excavation can make to deep mapping, and the contribution that deep mapping can make to rural communities.

  3. Deep Neural Architectures for Mapping Scalp to Intracranial EEG.

    Science.gov (United States)

    Antoniades, Andreas; Spyrou, Loukianos; Martin-Lopez, David; Valentin, Antonio; Alarcon, Gonzalo; Sanei, Saeid; Took, Clive Cheong

    2018-03-19

    Data is often plagued by noise which encumbers machine learning of clinically useful biomarkers and electroencephalogram (EEG) data is no exemption. Intracranial EEG (iEEG) data enhances the training of deep learning models of the human brain, yet is often prohibitive due to the invasive recording process. A more convenient alternative is to record brain activity using scalp electrodes. However, the inherent noise associated with scalp EEG data often impedes the learning process of neural models, achieving substandard performance. Here, an ensemble deep learning architecture for nonlinearly mapping scalp to iEEG data is proposed. The proposed architecture exploits the information from a limited number of joint scalp-intracranial recording to establish a novel methodology for detecting the epileptic discharges from the sEEG of a general population of subjects. Statistical tests and qualitative analysis have revealed that the generated pseudo-intracranial data are highly correlated with the true intracranial data. This facilitated the detection of IEDs from the scalp recordings where such waveforms are not often visible. As a real-world clinical application, these pseudo-iEEGs are then used by a convolutional neural network for the automated classification of intracranial epileptic discharges (IEDs) and non-IED of trials in the context of epilepsy analysis. Although the aim of this work was to circumvent the unavailability of iEEG and the limitations of sEEG, we have achieved a classification accuracy of 68% an increase of 6% over the previously proposed linear regression mapping.

  4. MBARI Mapping AUV: A High-Resolution Deep Ocean Seafloor Mapping Capability

    Science.gov (United States)

    Caress, D. W.; Kirkwood, W. J.; Thomas, H.; McEwen, R.; Henthorn, R.; McGill, P.; Thompson, D.; Sibenac, M.; Jensen, S.; Shane, F.; Hamilton, A.

    2005-05-01

    The Monterey Bay Aquarium Research Institute (MBARI) is developing an autonomous seafloor mapping capability for deep ocean science applications. The MBARI Mapping AUV is a 0.53 m (21 in) diameter, 5.1 m (16.7 ft) long, Dorado-class vehicle designed to carry four mapping sonars. The primary sensor is a 200 kHz multibeam sonar producing swath bathymetry and sidescan. In addition, the vehicle carries 100 kHz and 410 kHz chirp sidescan sonars, and a 2-16 kHz sweep chirp subbottom profiler. Navigation and attitude data are obtained from an inertial navigation system (INS) incorporating a ring laser gyro and a 300 kHz Doppler velocity log (DVL). The vehicle also includes acoustic modem, ultra-short baseline navigation, and long-baseline navigation systems. The Mapping AUV is powered by 6 kWhr of Li-polymer batteries, providing expected mission duration of 12 hours at a typical speed of 1.5 m/s. All components of the vehicle are rated to 6000 m depth, allowing MBARI to conduct high-resolution mapping of the deep-ocean seafloor. The sonar package is also be mountable on ROV Ventana, allowing surveys at altitudes less than 20 m at topographically challenging sites. The vehicle was assembled and extensively tested during 2004; this year we are commencing operations for MBARI science projects while continuing the process of testing and integrating the complete suite of sensors and systems. MBARI is beginning to use this capability to observe the changing morphology of dynamic systems such as submarine canyons and active slumps, to map deep-water benthic habitats at resolutions comparable to ROV and submersible observations, to provide basemaps for ROV dives, and to provide high resolution bathymetry and subbottom profiles as part of a variety of projects requiring knowledge of the seafloor. We will present initial results from surveys in and around Monterey Canyon, including high resolution repeat surveys of four sites along the canyon axis.

  5. Deep Mapping the Biome: The Biology of Place in Don Gayton's "The Wheatgrass Mechanism" and John Janovy Jr.'s "Dunwoody Pond"

    Science.gov (United States)

    Maher, Susan Naramore

    2005-01-01

    The term "deep map" is the invention of writer William Least Heat-Moon, whose extended essay "PrairyErth (a deep map)" has given definition to this form. Deep-map writing is marked by its intertextual, interdisciplinary, and multivocal nature. It is also self-consciously cartographic, presenting maps, following maps, and redrawing maps. Deep…

  6. Putting the Deep Biosphere and Gas Hydrates on the Map

    Science.gov (United States)

    Sikorski, Janelle J.; Briggs, Brandon R.

    2016-01-01

    Microbial processes in the deep biosphere affect marine sediments, such as the formation of gas hydrate deposits. Gas hydrate deposits offer a large source of natural gas with the potential to augment energy reserves and affect climate and seafloor stability. Despite the significant interdependence between life and geology in the ocean, coverage…

  7. Uniform, optimal signal processing of mapped deep-sequencing data.

    Science.gov (United States)

    Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

    2013-07-01

    Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

  8. Reduced deep regional cerebral venous oxygen saturation in hemodialysis patients using quantitative susceptibility mapping.

    Science.gov (United States)

    Chai, Chao; Liu, Saifeng; Fan, Linlin; Liu, Lei; Li, Jinping; Zuo, Chao; Qian, Tianyi; Haacke, E Mark; Shen, Wen; Xia, Shuang

    2018-02-01

    Cerebral venous oxygen saturation (SvO 2 ) is an important indicator of brain function. There was debate about lower cerebral oxygen metabolism in hemodialysis patients and there were no reports about the changes of deep regional cerebral SvO 2 in hemodialysis patients. In this study, we aim to explore the deep regional cerebral SvO 2 from straight sinus using quantitative susceptibility mapping (QSM) and the correlation with clinical risk factors and neuropsychiatric testing . 52 hemodialysis patients and 54 age-and gender-matched healthy controls were enrolled. QSM reconstructed from original phase data of 3.0 T susceptibility-weighted imaging was used to measure the susceptibility of straight sinus. The susceptibility was used to calculate the deep regional cerebral SvO 2 and compare with healthy individuals. Correlation analysis was performed to investigate the correlation between deep regional cerebral SvO 2 , clinical risk factors and neuropsychiatric testing. The deep regional cerebral SvO 2 of hemodialysis patients (72.5 ± 3.7%) was significantly lower than healthy controls (76.0 ± 2.1%) (P deep regional cerebral SvO 2 in patients. The Mini-Mental State Examination (MMSE) scores of hemodialysis patients were significantly lower than healthy controls (P deep regional cerebral SvO 2 did not correlate with MMSE scores (P = 0.630). In summary, the decreased deep regional cerebral SvO 2 occurred in hemodialysis patients and dialysis duration, parathyroid hormone, hematocrit, hemoglobin and red blood cell may be clinical risk factors.

  9. Going Deeper or Flatter: Connecting Deep Mapping, Flat Ontologies and the Democratizing of Knowledge

    Directory of Open Access Journals (Sweden)

    Selina Springett

    2015-10-01

    Full Text Available The concept of “deep mapping”, as an approach to place, has been deployed as both a descriptor of a specific suite of creative works and as a set of aesthetic practices. While its definition has been amorphous and adaptive, a number of distinct, yet related, manifestations identify as, or have been identified by, the term. In recent times, it has garnered attention beyond literary discourse, particularly within the “spatial” turn of representation in the humanities and as a result of expanded platforms of data presentation. This paper takes a brief look at the practice of “deep mapping”, considering it as a consciously performative act and tracing a number of its various manifestations. It explores how deep mapping is a reflection of epistemological trends in ontological practices of connectivity and the “flattening” of knowledge systems. In particular those put forward by post structural and cultural theorists, such as Bruno Latour, Gilles Deleuze, and Felix Guattari, as well as by theorists who associate with speculative realism. The concept of deep mapping as an aesthetic, methodological, and ideological tool, enables an approach to place that democratizes knowledge by crossing temporal, spatial, and disciplinary boundaries.

  10. Quantitative trait locus mapping of deep rooting by linkage and association analysis in rice.

    Science.gov (United States)

    Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Wei, Haibin; Feng, Fangjun; Wang, Pei; Xia, Hui; Li, Tiemei; Luo, Lijun

    2015-08-01

    Deep rooting is a very important trait for plants' drought avoidance, and it is usually represented by the ratio of deep rooting (RDR). Three sets of rice populations were used to determine the genetic base for RDR. A linkage mapping population with 180 recombinant inbred lines and an association mapping population containing 237 rice varieties were used to identify genes linked to RDR. Six quantitative trait loci (QTLs) of RDR were identified as being located on chromosomes 1, 2, 4, 7, and 10. Using 1 019 883 single-nucleotide polymorphisms (SNPs), a genome-wide association study of the RDR was performed. Forty-eight significant SNPs of the RDR were identified and formed a clear peak on the short arm of chromosome 1 in a Manhattan plot. Compared with the shallow-rooting group and the whole collection, the deep-rooting group had selective sweep regions on chromosomes 1 and 2, especially in the major QTL region on chromosome 2. Seven of the nine candidate SNPs identified by association mapping were verified in two RDR extreme groups. The findings from this study will be beneficial to rice drought-resistance research and breeding. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  11. Improving the pseudo-randomness properties of chaotic maps using deep-zoom

    Science.gov (United States)

    Machicao, Jeaneth; Bruno, Odemir M.

    2017-05-01

    A generalized method is proposed to compose new orbits from a given chaotic map. The method provides an approach to examine discrete-time chaotic maps in a "deep-zoom" manner by using k-digits to the right from the decimal separator of a given point from the underlying chaotic map. Interesting phenomena have been identified. Rapid randomization was observed, i.e., chaotic patterns tend to become indistinguishable when compared to the original orbits of the underlying chaotic map. Our results were presented using different graphical analyses (i.e., time-evolution, bifurcation diagram, Lyapunov exponent, Poincaré diagram, and frequency distribution). Moreover, taking advantage of this randomization improvement, we propose a Pseudo-Random Number Generator (PRNG) based on the k-logistic map. The pseudo-random qualities of the proposed PRNG passed both tests successfully, i.e., DIEHARD and NIST, and were comparable with other traditional PRNGs such as the Mersenne Twister. The results suggest that simple maps such as the logistic map can be considered as good PRNG methods.

  12. Generating Importance Map for Geometry Splitting using Discrete Ordinates Code in Deep Shielding Problem

    International Nuclear Information System (INIS)

    Kim, Jong Woon; Lee, Young Ouk

    2016-01-01

    When we use MCNP code for a deep shielding problem, we prefer to use variance reduction technique such as geometry splitting, or weight window, or source biasing to have relative error within reliable confidence interval. To generate importance map for geometry splitting in MCNP calculation, we should know the track entering number and previous importance on each cells since a new importance is calculated based on these information. If a problem is deep shielding problem such that we have zero tracks entering on a cell, we cannot generate new importance map. In this case, discrete ordinates code can provide information to generate importance map easily. In this paper, we use AETIUS code as a discrete ordinates code. Importance map for MCNP is generated based on a zone average flux of AETIUS calculation. The discretization of space, angle, and energy is not necessary for MCNP calculation. This is the big merit of MCNP code compared to the deterministic code. However, deterministic code (i.e., AETIUS) can provide a rough estimate of the flux throughout a problem relatively quickly. This can help MCNP by providing variance reduction parameters. Recently, ADVANTG code is released. This is an automated tool for generating variance reduction parameters for fixed-source continuous-energy Monte Carlo simulations with MCNP5 v1.60

  13. Improving accuracy of simultaneously reconstructed activity and attenuation maps using deep learning.

    Science.gov (United States)

    Hwang, Donghwi; Kim, Kyeong Yun; Kang, Seung Kwan; Seo, Seongho; Paeng, Jin Chul; Lee, Dong Soo; Lee, Jae Sung

    2018-02-15

    Simultaneous reconstruction of activity and attenuation using the maximum likelihood reconstruction of activity and attenuation (MLAA) augmented by time-of-flight (TOF) information is a promising method for positron emission tomography (PET) attenuation correction. However, it still suffers from several problems, including crosstalk artifacts, slow convergence speed, and noisy attenuation maps (μ-maps). In this work, we developed deep convolutional neural networks (CNNs) to overcome these MLAA limitations, and we verified their feasibility using a clinical brain PET data set. Methods: We applied the proposed method to one of the most challenging PET cases for simultaneous image reconstruction ( 18 F-FP-CIT PET scans with highly specific binding to striatum of the brain). Three different CNN architectures (convolutional autoencoder (CAE), U-net, hybrid of CAE and U-net) were designed and trained to learn x-ray computed tomography (CT) derived μ-map (μ-CT) from the MLAA-generated activity distribution and μ-map (μ-MLAA). PET/CT data of 40 patients with suspected Parkinson's disease were employed for five-fold cross-validation. For the training of CNNs, 800,000 transverse PET slices and CTs augmented from 32 patient data sets were used. The similarity to μ-CT of the CNN-generated μ-maps (μ-CAE, μ-Unet, and μ-Hybrid) and μ-MLAA was compared using Dice similarity coefficients. In addition, we compared the activity concentration of specific (striatum) and non-specific binding regions (cerebellum and occipital cortex) and the binding ratios in the striatum in the PET activity images reconstructed using those μ-maps. Results: The CNNs generated less noisy and more uniform μ-maps than original μ-MLAA. Moreover, the air cavities and bones were better resolved in the proposed CNN outputs. In addition, the proposed deep learning approach was useful for mitigating the crosstalk problem in the MLAA reconstruction. The hybrid network of CAE and U-net yielded the

  14. Beyond the usual mapping functions in GPS, VLBI and Deep Space tracking.

    Science.gov (United States)

    Barriot, Jean-Pierre; Serafini, Jonathan; Sichoix, Lydie

    2014-05-01

    We describe here a new algorithm to model the water contents of the atmosphere (including ZWD) from GPS slant wet delays relative to a single receiver. We first make the assumption that the water vapor contents are mainly governed by a scale height (exponential law), and secondly that the departures from this decaying exponential can be mapped as a set of low degree 3D Zernike functions (w.r.t. space) and Tchebyshev polynomials (w.r.t. time.) We compare this new algorithm with previous algorithms known as mapping functions in GPS, VLBI and Deep Space tracking and give an example with data acquired over a one day time span at the Geodesy Observatory of Tahiti.

  15. DEEP NEAR-INFRARED SURVEY OF THE PIPE NEBULA. II. DATA, METHODS, AND DUST EXTINCTION MAPS

    International Nuclear Information System (INIS)

    Roman-Zuniga, Carlos G.; Alves, Joao F.; Lada, Charles J.; Lombardi, Marco

    2010-01-01

    We present a new set of high-resolution dust extinction maps of the nearby and essentially starless Pipe Nebula molecular cloud. The maps were constructed from a concerted deep near-infrared imaging survey with the ESO-VLT, ESO-NTT, CAHA 3.5 m telescopes, and 2MASS data. The new maps have a resolution three times higher than the previous extinction map of this cloud by Lombardi et al. and are able to resolve structures down to 2600 AU. We detect 244 significant extinction peaks across the cloud. These peaks have masses between 0.1 and 18.4 M sun , diameters between 1.2 and 5.7 x 10 4 AU (0.06 and 0.28 pc), and mean densities of about 10 4 cm -3 , all in good agreement with previous results. From the analysis of the mean surface density of companions we find a well-defined scale near 1.4 x 10 4 AU below which we detect a significant decrease in structure of the cloud. This scale is smaller than the Jeans length calculated from the mean density of the peaks. The surface density of peaks is not uniform but instead it displays clustering. Extinction peaks in the Pipe Nebula appear to have a spatial distribution similar to the stars in Taurus, suggesting that the spatial distribution of stars evolves directly from the primordial spatial distribution of high-density material.

  16. Deep-sea benthic habitats modeling and mapping in a NE Atlantic seamount (Galicia Bank)

    Science.gov (United States)

    Serrano, A.; González-Irusta, J. M.; Punzón, A.; García-Alegre, A.; Lourido, A.; Ríos, P.; Blanco, M.; Gómez-Ballesteros, M.; Druet, M.; Cristobo, J.; Cartes, J. E.

    2017-08-01

    This study presents the results of seafloor habitat identification and mapping of a NE Atlantic deep seamount. An ;assemble first, predict later; approach has been followed to identify and map the benthic habitats of the Galicia Bank (NW Iberian). Biotic patterns inferred from the survey data have been used to drive the definition of benthic assemblages using multivariate tools. Eight assemblages, four hard substrates and four sedimentary ones, have been described from a matrix of structural species. Distribution of these assemblages was correlated with environmental factors (multibeam and backscatter data) using binomial GAMs. Finally, the distribution model of each assemblage was applied to produce continuous maps and pooled in a final map with the distribution of the main benthic habitats. Depth and substrate type are key factors when determining soft bottom communities, whereas rocky habitat distribution is mainly explained by rock slope and orientation. Enrichment by northern water masses (LSW) arriving to GB and possible zooplankton biomass increase at vertical-steep walls by ;bottom trapping; can explain the higher diversity of habitat providing filter-feeders at slope rocky breaks. These results concerning vulnerable species and habitats, such as Lophelia and Madrepora communities and black and bamboo coral aggregations were the basis of the Spanish proposal of inclusion within the Natura 2000 network. The aim of the present study was to establish the scientific criteria needed for managing and protecting those environmental values.

  17. Glas Journal: Deep Mappings of a Harbour or the Charting of Fragments, Traces and Possibilities

    Directory of Open Access Journals (Sweden)

    Silvia Loeffler

    2015-09-01

    Full Text Available With reference to a hybrid ethnographic project entitled Glas Journal (2014–2016, this article invites readers to reflect on the cultural mapping of spaces we intimately inhabit. Developed with the participation of local inhabitants of Dún Laoghaire Harbour, Ireland, Glas Journal seeks to explore the maritime environment as a liminal space, whereby the character of buildings and an area’s economic implications determine our relationship to space as much as our daily spatial rhythms and feelings of safety. Deep mapping provides the methodological blueprint for Glas Journal. In order to create a heteroglossic narrative of place and belonging, I will contextualise the project with references to seminal works in the visual arts, literature, film and geography that emotionally map spaces. Chronotopes of the threshold will be used to elaborate on spatial and cultural phenomena that occur when crossings from public to private and interior to exterior take place. Touching upon questions such as “What is a space of protection?”, “Who am I in it?”, and “Who is the Other?”, this article traces forms of liquid mapping that do not strive to conquer but rather to gain insight into the inner landscapes that are reflected in outer space.

  18. Project CONVERGE: Initial Results From the Mapping of Surface Currents in Palmer Deep

    Science.gov (United States)

    Statscewich, H.; Kohut, J. T.; Winsor, P.; Oliver, M. J.; Bernard, K. S.; Cimino, M. A.; Fraser, W.

    2016-02-01

    The Palmer Deep submarine canyon on the Western Antarctic Peninsula provides a conduit for upwelling of relatively warm, nutrient rich waters which enhance local primary production and support a food web productive enough to sustain a large top predator biomass. In an analysis of ten years of satellite-tagged penguins, Oliver et al. (2013) showed that circulation features associated with tidal flows may be a key driver of nearshore predator distributions. During diurnal tides, the penguins feed close to their breeding colonies and during semi-diurnal tides, the penguins make foraging trips to the more distant regions of Palmer Deep. It is hypothesized that convergent features act to concentrate primary producers and aggregate schools of krill that influence the behavior of predator species. The initial results from a six month deployment of a High Frequency Radar network in Palmer Deep are presented in an attempt to characterize and quantify convergent features. During a three month period from January through March 2015, we conducted in situ sampling consisting of multiple underwater glider deployments, small boat acoustic surveys of Antarctic krill, and penguin ARGOS-linked satellite telemetry and time-depth recorders (TDRs). The combination of real-time surface current maps with adaptive in situ sampling introduces High Frequency Radar to the Antarctic in a way that allows us to rigorously and efficiently test the influence of local tidal processes on top predator foraging ecology.

  19. Deep Mapping and Screen Tourism: The Oxford of Harry Potter and Inspector Morse

    Directory of Open Access Journals (Sweden)

    James Cateridge

    2015-08-01

    Full Text Available This article proposes that the experiences of screen tourists in Oxford help to create a theoretical “deep map” of the city which explores place through narrative. Building on the travel writing of William Least Heat-Moon and other recent work in the spatial humanities, two case studies of major screen tourism drivers are considered and analyzed. The British television drama Inspector Morse (1987–2000 explores the ambiguity of Oxford intellectualism through its central character. Morse’s love of high culture, especially music, provides suggestive additional layers for multimedia mapping, which are realized online through user-adapted Google Maps and geolocated images posted on the Flickr service. Harry Potter fans may not be “pure” or independent screen tourists, but they provide a wealth of data on their interactions with filming locations via social media such as Instagram. This data provides emotional as well as factual evidence, and is accumulating into an ever richer and deeper digital map of human experience.

  20. Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network

    Science.gov (United States)

    Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong

    2016-01-01

    We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods. PMID:26864172

  1. Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

    Directory of Open Access Journals (Sweden)

    Dongyang Hou

    2016-06-01

    Full Text Available Automatic discovery of isolated land cover web map services (LCWMSs can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial web applications, a considerable number of LCWMSs are hidden in JavaScript code, which belongs to the deep web. However, discovering LCWMSs from JavaScript code remains an open challenge. This paper aims to solve this challenge by proposing a focused deep web crawler for finding more LCWMSs from deep web JavaScript code and the surface web. First, the names of a group of JavaScript links are abstracted as initial judgements. Through name matching, these judgements are utilized to judge whether or not the fetched webpages contain predefined JavaScript links that may prompt JavaScript code to invoke WMSs. Secondly, some JavaScript invocation functions and URL formats for WMS are summarized as JavaScript invocation rules from prior knowledge of how WMSs are employed and coded in JavaScript. These invocation rules are used to identify the JavaScript code for extracting candidate WMSs through rule matching. The above two operations are incorporated into a traditional focused crawling strategy situated between the tasks of fetching webpages and parsing webpages. Thirdly, LCWMSs are selected by matching services with a set of land cover keywords. Moreover, a search engine for LCWMSs is implemented that uses the focused deep web crawler to retrieve and integrate the LCWMSs it discovers. In the first experiment, eight online geospatial web applications serve as seed URLs (Uniform Resource Locators and crawling scopes; the proposed crawler addresses only the JavaScript code in these eight applications. All 32 available WMSs hidden in JavaScript code were found using the proposed crawler, while not one WMS was discovered through the focused crawler

  2. Regular Routes: Deep Mapping a Performative Counterpractice for the Daily Commute 1

    Directory of Open Access Journals (Sweden)

    Laura Bissell

    2015-09-01

    Full Text Available This article offers a textual “deep map” of a series of experimental commutes undertaken in the west of Scotland in 2014. Recent developments in the field of transport studies have reconceived travel time as a far richer cultural experience than in previously utilitarian and economic approaches to the “problem” of commuting. Understanding their own commutes in these terms—as spaces of creativity, productivity and transformation—the authors trace the development of a performative “counterpractice” for their daily journeys between home and work. Deep mapping—as a form of “theory-informed story-telling”—is employed as a productive strategy to document this reimagination of ostensibly quotidian and functional travel. Importantly, this particular stage of the project is not presented as an end-point. Striving to develop an ongoing creative engagement with landscape, the authors continue this exploratory mobile research by connecting to other commuters’ journeys, and proposing a series of “strategies” for reimagining the daily commute; a list of prompts for future action within the routines and spaces of commuting. A range of alternative approaches to commuting are offered here to anyone who regularly travels to and from work to employ or develop as they wish, extending the mapping process to other routes and contexts.

  3. Challenges of using an AUV to find and map hydrothermal vent sites in deep and rugged terrains

    OpenAIRE

    McPhail, S.D.; Stevenson, P.; Pebody, M.; Furlong, M.; Perrett, J.; LeBas, T.

    2010-01-01

    In March 2010, the Autosub6000 AUV embarked on a cruise to discover, locate and map hydrothermal vent sites in an active spreading centre, the Cayman trough in the Caribbean sea. The environment provided the challenge of steep and rugged terrain together with deep water (in places greater than 5000 m). Autosub6000 is a flight class, hydrodynamically shaped AUV, with good endurance capability, making it well suited for searching for plume signals and mapping terrain over the required ...

  4. Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

    Science.gov (United States)

    Ganguly, Sangram; Kalia, Subodh; Li, Shuang; Michaelis, Andrew; Nemani, Ramakrishna R.; Saatchi, Sassan A

    2017-01-01

    Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

  5. Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

    Science.gov (United States)

    Ganguly, S.; Kalia, S.; Li, S.; Michaelis, A.; Nemani, R. R.; Saatchi, S.

    2017-12-01

    Uncertainties in input land cover estimates contribute to a significant bias in modeled above gound biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition/ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree/non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial/satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

  6. THE DARKEST SHADOWS: DEEP MID-INFRARED EXTINCTION MAPPING OF A MASSIVE PROTOCLUSTER

    Energy Technology Data Exchange (ETDEWEB)

    Butler, Michael J. [Institute of Theoretical Physics, University of Zürich, CH-8057 Zürich (Switzerland); Tan, Jonathan C. [Departments of Astronomy and Physics, University of Florida, Gainesville, FL 32611 (United States); Kainulainen, Jouni [Max-Planck-Institute for Astronomy, Königstuhl 17, D-69117, Heidelberg (Germany)

    2014-02-20

    We use deep 8 μm Spitzer-IRAC imaging of massive Infrared Dark Cloud (IRDC) G028.37+00.07 to construct a mid-infrared (MIR) extinction map that probes mass surface densities up to Σ ∼ 1 g cm{sup –2} (A{sub V} ∼ 200 mag), amongst the highest values yet probed by extinction mapping. Merging with an NIR extinction map of the region creates a high dynamic range map that reveals structures down to A{sub V} ∼ 1 mag. We utilize the map to: (1) measure a cloud mass ∼7 × 10{sup 4} M {sub ☉} within a radius of ∼8 pc. {sup 13}CO kinematics indicate that the cloud is gravitationally bound. It thus has the potential to form one of the most massive young star clusters known in the Galaxy. (2) Characterize the structures of 16 massive cores within the IRDC, finding they can be fit by singular polytropic spheres with ρ∝r{sup −k{sub ρ}} and k {sub ρ} = 1.3 ± 0.3. They have Σ-bar ≃0.1--0.4 g cm{sup −2}—relatively low values that, along with their measured cold temperatures, suggest that magnetic fields, rather than accretion-powered radiative heating, are important for controlling fragmentation of these cores. (3) Determine the Σ (equivalently column density or A{sub V} ) probability distribution function (PDF) for a region that is nearly complete for A{sub V} > 3 mag. The PDF is well fit by a single log-normal with mean A-bar {sub V}≃9 mag, high compared to other known clouds. It does not exhibit a separate high-end power law tail, which has been claimed to indicate the importance of self-gravity. However, we suggest that the PDF does result from a self-similar, self-gravitating hierarchy of structures present over a wide range of scales in the cloud.

  7. Deep brain stimulation, brain maps and personalized medicine: lessons from the human genome project.

    Science.gov (United States)

    Fins, Joseph J; Shapiro, Zachary E

    2014-01-01

    Although the appellation of personalized medicine is generally attributed to advanced therapeutics in molecular medicine, deep brain stimulation (DBS) can also be so categorized. Like its medical counterpart, DBS is a highly personalized intervention that needs to be tailored to a patient's individual anatomy. And because of this, DBS like more conventional personalized medicine, can be highly specific where the object of care is an N = 1. But that is where the similarities end. Besides their differing medical and surgical provenances, these two varieties of personalized medicine have had strikingly different impacts. The molecular variant, though of a more recent vintage has thrived and is experiencing explosive growth, while DBS still struggles to find a sustainable therapeutic niche. Despite its promise, and success as a vetted treatment for drug resistant Parkinson's Disease, DBS has lagged in broadening its development, often encountering regulatory hurdles and financial barriers necessary to mount an adequate number of quality trials. In this paper we will consider why DBS-or better yet neuromodulation-has encountered these challenges and contrast this experience with the more successful advance of personalized medicine. We will suggest that personalized medicine and DBS's differential performance can be explained as a matter of timing and complexity. We believe that DBS has struggled because it has been a journey of scientific exploration conducted without a map. In contrast to molecular personalized medicine which followed the mapping of the human genome and the Human Genome Project, DBS preceded plans for the mapping of the human brain. We believe that this sequence has given personalized medicine a distinct advantage and that the fullest potential of DBS will be realized both as a cartographical or electrophysiological probe and as a modality of personalized medicine.

  8. Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

    Science.gov (United States)

    Cai, Congbo; Wang, Chao; Zeng, Yiqing; Cai, Shuhui; Liang, Dong; Wu, Yawen; Chen, Zhong; Ding, Xinghao; Zhong, Jianhui

    2018-04-24

    An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T 2 mapping from single-shot overlapping-echo detachment (OLED) planar imaging. The training dataset was obtained from simulations that were carried out on SPROM (Simulation with PRoduct Operator Matrix) software developed by our group. The relationship between the original OLED image containing two echo signals and the corresponding T 2 mapping was learned by ResNet training. After the ResNet was trained, it was applied to reconstruct the T 2 mapping from simulation and in vivo human brain data. Although the ResNet was trained entirely on simulated data, the trained network was generalized well to real human brain data. The results from simulation and in vivo human brain experiments show that the proposed method significantly outperforms the echo-detachment-based method. Reliable T 2 mapping with higher accuracy is achieved within 30 ms after the network has been trained, while the echo-detachment-based OLED reconstruction method took approximately 2 min. The proposed method will facilitate real-time dynamic and quantitative MR imaging via OLED sequence, and deep convolutional neural network has the potential to reconstruct maps from complex MRI sequences efficiently. © 2018 International Society for Magnetic Resonance in Medicine.

  9. Putting the Deep Biosphere on the Map for Oceanography Courses: Gas Hydrates As a Case Study for the Deep Biosphere

    Science.gov (United States)

    Sikorski, J. J.; Briggs, B. R.

    2014-12-01

    The ocean is essential for life on our planet. It covers 71% of the Earth's surface, is the source of the water we drink, the air we breathe, and the food we eat. Yet, the exponential growth in human population is putting the ocean and thus life on our planet at risk. However, based on student evaluations from our introductory oceanography course it is clear that our students have deficiencies in ocean literacy that impact their ability to recognize that the ocean and humans are inextricably connected. Furthermore, life present in deep subsurface marine environments is also interconnected to the study of the ocean, yet the deep biosphere is not typically covered in undergraduate oceanography courses. In an effort to improve student ocean literacy we developed an instructional module on the deep biosphere focused on gas hydrate deposits. Specifically, our module utilizes Google Earth and cutting edge research about microbial life in the ocean to support three inquiry-based activities that each explore different facets of gas hydrates (i.e. environmental controls, biologic controls, and societal implications). The relevant nature of the proposed module also makes it possible for instructors of introductory geology courses to modify module components to discuss related topics, such as climate, energy, and geologic hazards. This work, which will be available online as a free download, is a solid contribution toward increasing the available teaching resources focused on the deep biosphere for geoscience educators.

  10. Mapping vaccinia virus DNA replication origins at nucleotide level by deep sequencing.

    Science.gov (United States)

    Senkevich, Tatiana G; Bruno, Daniel; Martens, Craig; Porcella, Stephen F; Wolf, Yuri I; Moss, Bernard

    2015-09-01

    Poxviruses reproduce in the host cytoplasm and encode most or all of the enzymes and factors needed for expression and synthesis of their double-stranded DNA genomes. Nevertheless, the mode of poxvirus DNA replication and the nature and location of the replication origins remain unknown. A current but unsubstantiated model posits only leading strand synthesis starting at a nick near one covalently closed end of the genome and continuing around the other end to generate a concatemer that is subsequently resolved into unit genomes. The existence of specific origins has been questioned because any plasmid can replicate in cells infected by vaccinia virus (VACV), the prototype poxvirus. We applied directional deep sequencing of short single-stranded DNA fragments enriched for RNA-primed nascent strands isolated from the cytoplasm of VACV-infected cells to pinpoint replication origins. The origins were identified as the switching points of the fragment directions, which correspond to the transition from continuous to discontinuous DNA synthesis. Origins containing a prominent initiation point mapped to a sequence within the hairpin loop at one end of the VACV genome and to the same sequence within the concatemeric junction of replication intermediates. These findings support a model for poxvirus genome replication that involves leading and lagging strand synthesis and is consistent with the requirements for primase and ligase activities as well as earlier electron microscopic and biochemical studies implicating a replication origin at the end of the VACV genome.

  11. High-resolution AUV mapping and sampling of a deep hydrocarbon plume in the Gulf of Mexico

    Science.gov (United States)

    Ryan, J. P.; Zhang, Y.; Thomas, H.; Rienecker, E.; Nelson, R.; Cummings, S.

    2010-12-01

    During NOAA cruise GU-10-02 on the Ship Gordon Gunter, the Monterey Bay Aquarium Research Institute (MBARI) autonomous underwater vehicle (AUV) Dorado was deployed to map and sample a deep (900-1200 m) volume centered approximately seven nautical miles southwest of the Deepwater Horizon wellhead. Dorado was equipped to detect optical and chemical signals of hydrocarbons and to acquire targeted samples. The primary sensor reading used for hydrocarbon detection was colored dissolved organic matter (CDOM) fluorescence (CF). On June 2 and 3, ship cast and subsequent AUV surveys detected elevated CF in a layer between 1100 and 1200 m depth. While the deep volume was mapped in a series of parallel vertical sections, the AUV ran a peak-capture algorithm to target sample acquisition at layer signal peaks. Samples returned by ship CTD/CF rosette sampling and by AUV were preliminarily examined at sea, and they exhibited odor and fluorometric signal consistent with oil. More definitive and detailed results on these samples are forthcoming from shore-based laboratory analyses. During post-cruise analysis, all of the CF data were analyzed to objectively define and map the deep plume feature. Specifically, the maximum expected background CF over the depth range 1000-1200 m was extrapolated from a linear relationship between depth and maximum CF over the depth range 200 to 1000 m. Values exceeding the maximum expected background in the depth range 1000-1200 m were interpreted as signal from a hydrocarbon-enriched plume. Using this definition we examine relationships between CF and other AUV measurements within the plume, illustrate the three-dimensional structure of the plume boundary region that was mapped, describe small-scale layering on isopycnals, and examine short-term variations in plume depth, intensity and hydrographic relationships. Three-dimensional representation of part of a deep hydrocarbon plume mapped and sampled by AUV on June 2-3, 2010.

  12. Mapping For Literature Conceptual And Theoretical Framework And Methodology Case Of Hot Deep Mining Ventilation Engineering Evaluation And Design

    Directory of Open Access Journals (Sweden)

    Peter M. Lukonde

    2017-09-01

    Full Text Available The paper reports the layout of a mapping process for literature theoretical and conceptual framework and methodology for mining ventilation engineering evaluation design and methodology for a hot deep mine. The purpose of mine ventilation is to provide suitable environmental conditions in working places that promote comfort and efficiency as well as the safety and health of underground personnel. The objectives addressed in this paper include a evaluation of a current mine ventilation system for a hot deep-level mine taking into account the existing ventilation system infrastructure for building of a mine ventilation baseline parametric database for subsequent end of life mine ventilation design and b design of the extension end of mine life ventilation system taking into account increased production high geothermic gradient and subsequent increase in depth of mining. The methodology used in evaluating an existing underground mine ventilation system and designing the extension end of mine life ventilation system employed three stages i Literature mapping to identify authors titles and technical papers at global regional and nationaldistrict scales relevant to the research ii Conceptual and theoretical framework mapping to extract a kernel or core of concepts hypotheses and theories from the literature map to drive the formation of methods of implementation and iii Methodology and implementation mapping to direct and control the processes of data collection analysis and interpretation. A sample case study of a deep-level underground mine has been used in this paper to provide examples of data collection data analysis and interpretation key findings and results discussion and what is new conclusions and recommendations when the proposed mapping process is employed.

  13. Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation

    Science.gov (United States)

    Karargyros, Alex; Syeda-Mahmood, Tanveer

    2018-02-01

    Deep learning networks are gaining popularity in many medical image analysis tasks due to their generalized ability to automatically extract relevant features from raw images. However, this can make the learning problem unnecessarily harder requiring network architectures of high complexity. In case of anomaly detection, in particular, there is often sufficient regional difference between the anomaly and the surrounding parenchyma that could be easily highlighted through bottom-up saliency operators. In this paper we propose a new hybrid deep learning network using a combination of raw image and such regional maps to more accurately learn the anomalies using simpler network architectures. Specifically, we modify a deep learning network called U-Net using both the raw and pre-segmented images as input to produce joint encoding (contraction) and expansion paths (decoding) in the U-Net. We present results of successfully delineating subdural and epidural hematomas in brain CT imaging and liver hemangioma in abdominal CT images using such network.

  14. Mapping porosity of the deep critical zone in 3D using near-surface geophysics, rock physics modeling, and drilling

    Science.gov (United States)

    Flinchum, B. A.; Holbrook, W. S.; Grana, D.; Parsekian, A.; Carr, B.; Jiao, J.

    2017-12-01

    Porosity is generated by chemical, physical and biological processes that work to transform bedrock into soil. The resulting porosity structure can provide specifics about these processes and can improve understanding groundwater storage in the deep critical zone. Near-surface geophysical methods, when combined with rock physics and drilling, can be a tool used to map porosity over large spatial scales. In this study, we estimate porosity in three-dimensions (3D) across a 58 Ha granite catchment. Observations focus on seismic refraction, downhole nuclear magnetic resonance logs, downhole sonic logs, and samples of core acquired by push coring. We use a novel petrophysical approach integrating two rock physics models, a porous medium for the saprolite and a differential effective medium for the fractured rock, that drive a Bayesian inversion to calculate porosity from seismic velocities. The inverted geophysical porosities are within about 0.05 m3/m3 of lab measured values. We extrapolate the porosity estimates below seismic refraction lines to a 3D volume using ordinary kriging to map the distribution of porosity in 3D up to depths of 80 m. This study provides a unique map of porosity on scale never-before-seen in critical zone science. Estimating porosity on these large spatial scales opens the door for improving and understanding the processes that shape the deep critical zone.

  15. SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing.

    Science.gov (United States)

    Tsuchiya, Mariko; Amano, Kojiro; Abe, Masaya; Seki, Misato; Hase, Sumitaka; Sato, Kengo; Sakakibara, Yasubumi

    2016-06-15

    Deep sequencing of the transcripts of regulatory non-coding RNA generates footprints of post-transcriptional processes. After obtaining sequence reads, the short reads are mapped to a reference genome, and specific mapping patterns can be detected called read mapping profiles, which are distinct from random non-functional degradation patterns. These patterns reflect the maturation processes that lead to the production of shorter RNA sequences. Recent next-generation sequencing studies have revealed not only the typical maturation process of miRNAs but also the various processing mechanisms of small RNAs derived from tRNAs and snoRNAs. We developed an algorithm termed SHARAKU to align two read mapping profiles of next-generation sequencing outputs for non-coding RNAs. In contrast with previous work, SHARAKU incorporates the primary and secondary sequence structures into an alignment of read mapping profiles to allow for the detection of common processing patterns. Using a benchmark simulated dataset, SHARAKU exhibited superior performance to previous methods for correctly clustering the read mapping profiles with respect to 5'-end processing and 3'-end processing from degradation patterns and in detecting similar processing patterns in deriving the shorter RNAs. Further, using experimental data of small RNA sequencing for the common marmoset brain, SHARAKU succeeded in identifying the significant clusters of read mapping profiles for similar processing patterns of small derived RNA families expressed in the brain. The source code of our program SHARAKU is available at http://www.dna.bio.keio.ac.jp/sharaku/, and the simulated dataset used in this work is available at the same link. Accession code: The sequence data from the whole RNA transcripts in the hippocampus of the left brain used in this work is available from the DNA DataBank of Japan (DDBJ) Sequence Read Archive (DRA) under the accession number DRA004502. yasu@bio.keio.ac.jp Supplementary data are available

  16. Deep-tissue temperature mapping by multi-illumination photoacoustic tomography aided by a diffusion optical model: a numerical study

    Science.gov (United States)

    Zhou, Yuan; Tang, Eric; Luo, Jianwen; Yao, Junjie

    2018-01-01

    Temperature mapping during thermotherapy can help precisely control the heating process, both temporally and spatially, to efficiently kill the tumor cells and prevent the healthy tissues from heating damage. Photoacoustic tomography (PAT) has been used for noninvasive temperature mapping with high sensitivity, based on the linear correlation between the tissue's Grüneisen parameter and temperature. However, limited by the tissue's unknown optical properties and thus the optical fluence at depths beyond the optical diffusion limit, the reported PAT thermometry usually takes a ratiometric measurement at different temperatures and thus cannot provide absolute measurements. Moreover, ratiometric measurement over time at different temperatures has to assume that the tissue's optical properties do not change with temperatures, which is usually not valid due to the temperature-induced hemodynamic changes. We propose an optical-diffusion-model-enhanced PAT temperature mapping that can obtain the absolute temperature distribution in deep tissue, without the need of multiple measurements at different temperatures. Based on the initial acoustic pressure reconstructed from multi-illumination photoacoustic signals, both the local optical fluence and the optical parameters including absorption and scattering coefficients are first estimated by the optical-diffusion model, then the temperature distribution is obtained from the reconstructed Grüneisen parameters. We have developed a mathematic model for the multi-illumination PAT of absolute temperatures, and our two-dimensional numerical simulations have shown the feasibility of this new method. The proposed absolute temperature mapping method may set the technical foundation for better temperature control in deep tissue in thermotherapy.

  17. Seawater capacitance – a promising proxy for mapping and characterizing drifting hydrocarbon plumes in the deep ocean

    Directory of Open Access Journals (Sweden)

    J. A. Fleming

    2012-12-01

    Full Text Available Hydrocarbons released into the deep ocean are an inevitable consequence of natural seep, seafloor drilling, and leaking wellhead-to-collection-point pipelines. The Macondo 252 (Deepwater Horizon well blowout of 2010 was even larger than the Ixtoc event in the Gulf of Campeche in 1979. History suggests it will not be the last accidental release, as deepwater drilling expands to meet an ever-growing demand. For those who must respond to this kind of disaster, the first line of action should be to know what is going on. This includes knowing where an oil plume is at any given time, where and how fast it is moving, and how it is evolving or degrading. We have experimented in the laboratory with induced polarization as a method to track hydrocarbons in the seawater column and find that finely dispersed oil in seawater gives rise to a large distributed capacitance. From previous sea trials, we infer this could potentially be used to both map and characterize oil plumes, down to a ratio of less than 0.001 oil-to-seawater, drifting and evolving in the deep ocean. A side benefit demonstrated in some earlier sea trials is that this same approach in modified form can also map certain heavy placer minerals, as well as communication cables, pipelines, and wrecks buried beneath the seafloor.

  18. Mapping "Vital Effects": Unlocking the Archive of Deep Sea Stylasterid δ18O and δ13C

    Science.gov (United States)

    King, T. M.; Rosenheim, B. E.

    2017-12-01

    Deep sea coral skeletons are able to incorporate chemical and isotopic signals from the dissolved inorganic pool of the surrounding water mass, attributing them with continuous, high-resolution records that span centuries to millennia. Most importantly, they are sessile organisms and remain fixed to the seafloor with respect to fluctuating water mass boundaries. Stylasterid corals (order Anthoathecata) are abundant in the Southern Ocean but not as commonly used for paleoceanographic reconstructions as corals of the order Scleractinia. Little is known about stylasterid growth rate, skeletal structure, or their effects on chemical and isotopic signals from the surrounding environment. Here, we present stable isotope "heat maps" over cross sections of stylasterid corals (genus Errina) from the western Ross Sea and eastern Wilkes Land, Antarctica. Isotope heat maps are used to illustrate isotope variability over small spatial scales within different sections of the coral skeletons. These maps indicate that the central growth axis of the coral stem is subject to kinetic effects, whereas, the outer coral skeleton is precipitated nearer to equilibrium with the surrounding water mass. We present several maps of both live and dead-collected corals (spanning 40,000 years from present) in order to examine natural variability through time and to identify possible diagenetic effects. Our results begin to clarify stylasterid growth patterns so that we are able to optimize sampling plans of these corals. These results also provide us with a context in which to interpret radiocarbon records, and potentially independent radio chronologies, compiled from the same coral collection (King et al., in review; GRL).

  19. Mapping Deep Low Velocity Zones in Alaskan Arctic Coastal Permafrost using Seismic Surface Waves

    Science.gov (United States)

    Dou, S.; Ajo Franklin, J. B.; Dreger, D. S.

    2012-12-01

    Permafrost degradation may be an important amplifier of climate change; Thawing of near-surface sediments holds the potential of increasing greenhouse gas emissions due to microbial decomposition of preserved organic carbon. Recently, the characterization of "deep" carbon pools (several meters below the surface) in circumpolar frozen ground has increased the estimated amount of soil carbon to three times higher than what was previously thought. It is therefore potentially important to include the characteristics and processes of deeper permafrost strata (on the orders of a few to tens of meters below surface) in climate models for improving future predictions of accessible carbon and climate feedbacks. This extension is particularly relevant if deeper formations are not completely frozen and may harbor on-going microbial activity despite sub-zero temperatures. Unfortunately, the characterization of deep permafrost systems is non-trivial; logistics and drilling constraints often limit direct characterization to relatively shallow units. Geophysical measurements, either surface or airborne, are often the most effective tools for evaluating these regions. Of the available geophysical techniques, the analysis of seismic surface waves (e.g. MASW) has several unique advantages, mainly the ability to provide field-scale information with good depth resolution as well as penetration (10s to 100s of m with small portable sources). Surface wave methods are also able to resolve low velocity regions, a class of features that is difficult to characterize using traditional P-wave refraction methods. As part of the Department of Energy (DOE) Next-Generation Ecosystem Experiments (NGEE-Arctic) project, we conducted a three-day seismic field survey (May 12 - 14, 2012) at the Barrow Environmental Observatory, which is located within the Alaskan Arctic Coastal Plain. Even though permafrost at the study site is continuous, ice-rich and thick (>= 350m), our Multichannel Analysis of

  20. A Transcriptome Map of Actinobacillus pleuropneumoniae at Single-Nucleotide Resolution Using Deep RNA-Seq.

    Directory of Open Access Journals (Sweden)

    Zhipeng Su

    Full Text Available Actinobacillus pleuropneumoniae is the pathogen of porcine contagious pleuropneumoniae, a highly contagious respiratory disease of swine. Although the genome of A. pleuropneumoniae was sequenced several years ago, limited information is available on the genome-wide transcriptional analysis to accurately annotate the gene structures and regulatory elements. High-throughput RNA sequencing (RNA-seq has been applied to study the transcriptional landscape of bacteria, which can efficiently and accurately identify gene expression regions and unknown transcriptional units, especially small non-coding RNAs (sRNAs, UTRs and regulatory regions. The aim of this study is to comprehensively analyze the transcriptome of A. pleuropneumoniae by RNA-seq in order to improve the existing genome annotation and promote our understanding of A. pleuropneumoniae gene structures and RNA-based regulation. In this study, we utilized RNA-seq to construct a single nucleotide resolution transcriptome map of A. pleuropneumoniae. More than 3.8 million high-quality reads (average length ~90 bp from a cDNA library were generated and aligned to the reference genome. We identified 32 open reading frames encoding novel proteins that were mis-annotated in the previous genome annotations. The start sites for 35 genes based on the current genome annotation were corrected. Furthermore, 51 sRNAs in the A. pleuropneumoniae genome were discovered, of which 40 sRNAs were never reported in previous studies. The transcriptome map also enabled visualization of 5'- and 3'-UTR regions, in which contained 11 sRNAs. In addition, 351 operons covering 1230 genes throughout the whole genome were identified. The RNA-Seq based transcriptome map validated annotated genes and corrected annotations of open reading frames in the genome, and led to the identification of many functional elements (e.g. regions encoding novel proteins, non-coding sRNAs and operon structures. The transcriptional units

  1. Delving Deep into Multiscale Pedestrian Detection via Single Scale Feature Maps

    Directory of Open Access Journals (Sweden)

    Xinchuan Fu

    2018-04-01

    Full Text Available The standard pipeline in pedestrian detection is sliding a pedestrian model on an image feature pyramid to detect pedestrians of different scales. In this pipeline, feature pyramid construction is time consuming and becomes the bottleneck for fast detection. Recently, a method called multiresolution filtered channels (MRFC was proposed which only used single scale feature maps to achieve fast detection. However, there are two shortcomings in MRFC which limit its accuracy. One is that the receptive field correspondence in different scales is weak. Another is that the features used are not scale invariance. In this paper, two solutions are proposed to tackle with the two shortcomings respectively. Specifically, scale-aware pooling is proposed to make a better receptive field correspondence, and soft decision tree is proposed to relive scale variance problem. When coupled with efficient sliding window classification strategy, our detector achieves fast detecting speed at the same time with state-of-the-art accuracy.

  2. Geothermometry Mapping of Deep Hydrothermal Reservoirs in Southeastern Idaho: Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Mattson, Earl D. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Conrad, Mark [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Neupane, Ghanashayam [Idaho National Lab. (INL), Idaho Falls, ID (United States); McLing, Travis [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wood, Thomas [Univ. of Idaho, Moscow, ID (United States); Cannon, Cody [Univ. of Idaho, Moscow, ID (United States)

    2016-08-01

    The Eastern Snake River Plain (ESRP) in southern Idaho is a region of high heat flow. Sustained volcanic activities in the wake of the passage of Yellowstone Hotspot have turned this region into an area with great potential for geothermal resources. Numerous hot springs with temperatures up to 75 ºC are scattered along the margins of the plain. Similarly, several hot-water producing wells and few hot springs are also present within the plain. The geothermal reservoirs in the area are likely to be hosted at depth in the felsic volcanic rocks underneath the thick sequences of basalts within the plain and the Paleozoic rocks underneath both basalts and felsic volcanic rocks along the margins. The heat source to these geothermal resources is thought to be the mid-crustal sill complex which sustains high heat flow in the ESRP. Several thermal anomaly areas are believed to be associated with the local thermal perturbation because of the presence of favorable structural settings. However, it is hypothesized that the pervasive presence of an overlying groundwater aquifer in the region effectively masks thermal signatures of deep-seated geothermal resources. The dilution of deeper thermal water and re-equilibration at lower temperatures are significant challenges for the evaluation of potential resource areas in the ESRP. To address this issue, this project, led by the Idaho National Laboratory (INL), aimed at applying advanced geothermometry tools including temperature-dependent mineral and isotopic equilibria with mixing models that account for processes such as boiling and dilution with shallow groundwater that could affect calculated temperatures of underlying deep thermal waters. Over the past several years, we collected approximately 100 water samples from springs/wells for chemical analysis as well as assembled existing water chemistry data from literature. We applied several geothermometric and geochemical modeling tools to the compositions of ESRP water samples

  3. Effect of Deep Cryogenic treatment on AISI A8 Tool steel & Development of Wear Mechanism maps using Fuzzy Clustering

    Science.gov (United States)

    Pillai, Nandakumar; Karthikeyan, R., Dr.

    2018-04-01

    Tool steels are widely classified according to their constituents and type of thermal treatments carried out to obtain its properties. Viking a special purpose tool steel coming under AISI A8 cold working steel classification is widely used for heavy duty blanking and forming operations. The optimum combination of wear resistance and toughness as well as ease of machinability in pre-treated condition makes this material accepted in heavy cutting and non cutting tool manufacture. Air or vacuum hardening is recommended as the normal treatment procedure to obtain the desired mechanical and tribological properties for steels under this category. In this study, we are incorporating a deep cryogenic phase within the conventional treatment cycle both before and after tempering. The thermal treatments at sub zero temperatures up to -195°C using cryogenic chamber with liquid nitrogen as medium was conducted. Micro structural changes in its microstructure and the corresponding improvement in the tribological and physical properties are analyzed. The cryogenic treatment leads to more conversion of retained austenite to martensite and also formation of fine secondary carbides. The microstructure is studied using the micrographs taken using optical microscopy. The wear tests are conducted on DUCOM tribometer for different combinations of speed and load under normal temperature. The wear rates and coefficient of friction obtained from these experiments are used to developed wear mechanism maps with the help of fuzzy c means clustering and probabilistic neural network models. Fuzzy C means clustering is an effective algorithm to group data of similar patterns. The wear mechanisms obtained from the computationally developed maps are then compared with the SEM photographs taken and the improvement in properties due to this additional cryogenic treatment is validated.

  4. Connecting People to Place: Stories, Science, Deep Maps, and Geo-Quests for Place-Based Learning

    Science.gov (United States)

    Hagley, C. A.; Silbernagel, J.; Host, G.; Hart, D. A.; Axler, R.; Fortner, R. W.; Axler, M.; Smith, V.; Drewes, A.; Bartsch, W.; Danz, N.; Mathews, J.; Wagler, M.

    2016-02-01

    The St. Louis River Estuary project (stlouisriverestuary.org) is about connecting the stories with the science of this special place to enhance spatial awareness and stewardship of the estuary. The stories, or spatial narratives, are told through vignettes of local resource activities, framed by perspectives of local people. The spatial narratives, developed through interviews and research, target six key activities of the estuary. The science is based on stressor gradients research, incorporating factors such as population and road density, pollutant point source density, and land use. The stressor gradient developed based on these factors was used as a basis for sampling water quality and plant and macroinvertebrate communities, with the intent of quantifying relationships between land-based stressors and aquatic ecosystem indicators of condition. The stories and science are interwoven, located in place on a Deep Map, and played out in GeoQuests to illustrate the complexity and multiple perspectives within the estuary's social, economic and ecological systems. Students, decision-makers, and Lake Superior enthusiasts can engage more deeply in the complexity of the stories and science by challenging themselves with these GeoQuests played on mobile devices. We hope these place-based learning tools will be valuable in advancing spatial literacy and conversation around environmental sustainability in coastal communities.

  5. NOAA's efforts to map extent, health and condition of deep sea corals and sponges and their habitat on the banks and island slopes of Southern California

    Science.gov (United States)

    Etnoyer, P. J.; Salgado, E.; Stierhoff, K.; Wickes, L.; Nehasil, S.; Kracker, L.; Lauermann, A.; Rosen, D.; Caldow, C.

    2015-12-01

    Southern California's deep-sea corals are diverse and abundant, but subject to multiple stressors, including corallivory, ocean acidification, and commercial bottom fishing. NOAA has surveyed these habitats using a remotely operated vehicle (ROV) since 2003. The ROV was equipped with high-resolution cameras to document deep-water groundfish and their habitat in a series of research expeditions from 2003 - 2011. Recent surveys 2011-2015 focused on in-situ measures of aragonite saturation and habitat mapping in notable habitats identified in previous years. Surveys mapped abundance and diversity of fishes and corals, as well as commercial fisheries landings and frequency of fishing gear. A novel priority setting algorithm was developed to identify hotspots of diversity and fishing intensity, and to determine where future conservation efforts may be warranted. High density coral aggregations identified in these analyses were also used to guide recent multibeam mapping efforts. The maps suggest a large extent of unexplored and unprotected hard-bottom habitat in the mesophotic zone and deep-sea reaches of Channel Islands National Marine Sanctuary.

  6. Deep-water chemosynthetic ecosystem research during the census of marine life decade and beyond: a proposed deep-ocean road map.

    Directory of Open Access Journals (Sweden)

    Christopher R German

    Full Text Available The ChEss project of the Census of Marine Life (2002-2010 helped foster internationally-coordinated studies worldwide focusing on exploration for, and characterization of new deep-sea chemosynthetic ecosystem sites. This work has advanced our understanding of the nature and factors controlling the biogeography and biodiversity of these ecosystems in four geographic locations: the Atlantic Equatorial Belt (AEB, the New Zealand region, the Arctic and Antarctic and the SE Pacific off Chile. In the AEB, major discoveries include hydrothermal seeps on the Costa Rica margin, deepest vents found on the Mid-Cayman Rise and the hottest vents found on the Southern Mid-Atlantic Ridge. It was also shown that the major fracture zones on the MAR do not create barriers for the dispersal but may act as trans-Atlantic conduits for larvae. In New Zealand, investigations of a newly found large cold-seep area suggest that this region may be a new biogeographic province. In the Arctic, the newly discovered sites on the Mohns Ridge (71 °N showed extensive mats of sulfur-oxidisng bacteria, but only one gastropod potentially bears chemosynthetic symbionts, while cold seeps on the Haakon Mossby Mud Volcano (72 °N are dominated by siboglinid worms. In the Antarctic region, the first hydrothermal vents south of the Polar Front were located and biological results indicate that they may represent a new biogeographic province. The recent exploration of the South Pacific region has provided evidence for a sediment hosted hydrothermal source near a methane-rich cold-seep area. Based on our 8 years of investigations of deep-water chemosynthetic ecosystems worldwide, we suggest highest priorities for future research: (i continued exploration of the deep-ocean ridge-crest; (ii increased focus on anthropogenic impacts; (iii concerted effort to coordinate a major investigation of the deep South Pacific Ocean - the largest contiguous habitat for life within Earth's biosphere, but

  7. Deep-water chemosynthetic ecosystem research during the census of marine life decade and beyond: a proposed deep-ocean road map.

    Science.gov (United States)

    German, Christopher R; Ramirez-Llodra, Eva; Baker, Maria C; Tyler, Paul A

    2011-01-01

    The ChEss project of the Census of Marine Life (2002-2010) helped foster internationally-coordinated studies worldwide focusing on exploration for, and characterization of new deep-sea chemosynthetic ecosystem sites. This work has advanced our understanding of the nature and factors controlling the biogeography and biodiversity of these ecosystems in four geographic locations: the Atlantic Equatorial Belt (AEB), the New Zealand region, the Arctic and Antarctic and the SE Pacific off Chile. In the AEB, major discoveries include hydrothermal seeps on the Costa Rica margin, deepest vents found on the Mid-Cayman Rise and the hottest vents found on the Southern Mid-Atlantic Ridge. It was also shown that the major fracture zones on the MAR do not create barriers for the dispersal but may act as trans-Atlantic conduits for larvae. In New Zealand, investigations of a newly found large cold-seep area suggest that this region may be a new biogeographic province. In the Arctic, the newly discovered sites on the Mohns Ridge (71 °N) showed extensive mats of sulfur-oxidisng bacteria, but only one gastropod potentially bears chemosynthetic symbionts, while cold seeps on the Haakon Mossby Mud Volcano (72 °N) are dominated by siboglinid worms. In the Antarctic region, the first hydrothermal vents south of the Polar Front were located and biological results indicate that they may represent a new biogeographic province. The recent exploration of the South Pacific region has provided evidence for a sediment hosted hydrothermal source near a methane-rich cold-seep area. Based on our 8 years of investigations of deep-water chemosynthetic ecosystems worldwide, we suggest highest priorities for future research: (i) continued exploration of the deep-ocean ridge-crest; (ii) increased focus on anthropogenic impacts; (iii) concerted effort to coordinate a major investigation of the deep South Pacific Ocean - the largest contiguous habitat for life within Earth's biosphere, but also the

  8. Observations of the Hubble Deep Field with the Infrared Space Observatory .1. Data reduction, maps and sky coverage

    DEFF Research Database (Denmark)

    Serjeant, S.B.G.; Eaton, N.; Oliver, S.J.

    1997-01-01

    We present deep imaging at 6.7 and 15 mu m from the CAM instrument on the Infrared Space Observatory (ISO), centred on the Hubble Deep Field (HDF). These are the deepest integrations published to date at these wavelengths in any region of sky. We discuss the observational strategy and the data...... reduction. The observed source density appears to approach the CAM confusion limit at 15 mu m, and fluctuations in the 6.7-mu m sky background may be identifiable with similar spatial fluctuations in the HDF galaxy counts. ISO appears to be detecting comparable field galaxy populations to the HDF, and our...

  9. Intraoperative subcortical mapping of a language-associated deep frontal tract connecting the superior frontal gyrus to Broca's area in the dominant hemisphere of patients with glioma.

    Science.gov (United States)

    Fujii, Masazumi; Maesawa, Satoshi; Motomura, Kazuya; Futamura, Miyako; Hayashi, Yuichiro; Koba, Itsuko; Wakabayashi, Toshihiko

    2015-06-01

    The deep frontal pathway connecting the superior frontal gyrus to Broca's area, recently named the frontal aslant tract (FAT), is assumed to be associated with language functions, especially speech initiation and spontaneity. Injury to the deep frontal lobe is known to cause aphasia that mimics the aphasia caused by damage to the supplementary motor area. Although fiber dissection and tractography have revealed the existence of the tract, little is known about its function. The aim of this study was to determine the function of the FAT via electrical stimulation in patients with glioma who underwent awake surgery. The authors analyzed the data from subcortical mapping with electrical stimulation in 5 consecutive cases (3 males and 2 females, age range 40-54 years) with gliomas in the left frontal lobe. Diffusion tensor imaging (DTI) and tractography of the FAT were performed in all cases. A navigation system and intraoperative MRI were used in all cases. During the awake phase of the surgery, cortical mapping was performed to find the precentral gyrus and Broca's area, followed by tumor resection. After the cortical layer was removed, subcortical mapping was performed to assess language-associated fibers in the white matter. In all 5 cases, positive responses were obtained at the stimulation sites in the subcortical area adjacent to the FAT, which was visualized by the navigation system. Speech arrest was observed in 4 cases, and remarkably slow speech and conversation was observed in 1 case. The location of these sites was also determined on intraoperative MR images and estimated on preoperative MR images with DTI tractography, confirming the spatial relationships among the stimulation sites and white matter tracts. Tumor removal was successfully performed without damage to this tract, and language function did not deteriorate in any of the cases postoperatively. The authors identified the left FAT and confirmed that it was associated with language functions. This

  10. HIGH RESOLUTION NEAR-INFRARED SURVEY OF THE PIPE NEBULA. I. A DEEP INFRARED EXTINCTION MAP OF BARNARD 59

    International Nuclear Information System (INIS)

    Roman-Zuniga, Carlos G.; Alves, Joao F.; Lada, Charles J.

    2009-01-01

    We present our analysis of a fully sampled, high resolution dust extinction map of the Barnard 59 complex in the Pipe Nebula. The map was constructed with the infrared color excess technique applied to a photometric catalog that combines data from both ground and space based observations. The map resolves for the first time the high density center of the main core in the complex, which is associated with the formation of a small cluster of stars. We found that the central core in Barnard 59 shows an unexpected lack of significant substructure consisting of only two significant fragments. Overall, the material appears to be consistent with being a single, large core with a density profile that can be well fit by a King model. A series of NH 3 pointed observations toward the high column density center of the core appear to show that the core is still thermally dominated, with subsonic non-thermal motions. The stars in the cluster could be providing feedback to support the core against collapse, but the relatively narrow radio lines suggest that an additional source of support, for example, a magnetic field, may be required to stabilize the core. Outside the central core our observations reveal the structure of peripheral cores and resolve an extended filament into a handful of significant substructures whose spacing and masses appear to be consistent with Jeans fragmentation.

  11. THE ALMA SPECTROSCOPIC SURVEY IN THE HUBBLE ULTRA DEEP FIELD: IMPLICATIONS FOR SPECTRAL LINE INTENSITY MAPPING AT MILLIMETER WAVELENGTHS AND CMB SPECTRAL DISTORTIONS

    Energy Technology Data Exchange (ETDEWEB)

    Carilli, C. L.; Walter, F. [National Radio Astronomy Observatory, P.O. Box 0, Socorro, NM 87801 (United States); Chluba, J. [Jodrell Bank Centre for Astrophysics, University of Manchester, Oxford Road, M13 9PL (United Kingdom); Decarli, R. [Max-Planck Institute for Astronomy, D-69117 Heidelberg (Germany); Aravena, M. [Nucleo de Astronomia, Facultad de Ingenieria, Universidad Diego Portales, Av. Ejercito 441, Santiago (Chile); Wagg, J. [Square Kilometre Array Organisation, Lower Withington, Cheshire (United Kingdom); Popping, G. [European Southern Observatory, Karl-Schwarzschild-Strasse 2, D-85748, Garching (Germany); Cortes, P. [Joint ALMA Observatory—ESO, Av. Alonso de Cordova, 3104, Santiago (Chile); Hodge, J. [Leiden Observatory, Leiden University, Niels Bohrweg 2, NL2333 RA Leiden (Netherlands); Weiss, A. [Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, D-53121 Bonn (Germany); Bertoldi, F. [Argelander Institute for Astronomy, University of Bonn, Auf dem Hügel 71, D-53121 Bonn (Germany); Riechers, D., E-mail: ccarilli@aoc.nrao.edu [Cornell University, 220 Space Sciences Building, Ithaca, NY 14853 (United States)

    2016-12-10

    We present direct estimates of the mean sky brightness temperature in observing bands around 99 and 242 GHz due to line emission from distant galaxies. These values are calculated from the summed line emission observed in a blind, deep survey for spectral line emission from high redshift galaxies using ALMA (the ALMA spectral deep field observations “ASPECS” survey). In the 99 GHz band, the mean brightness will be dominated by rotational transitions of CO from intermediate and high redshift galaxies. In the 242 GHz band, the emission could be a combination of higher order CO lines, and possibly [C ii] 158 μ m line emission from very high redshift galaxies ( z  ∼ 6–7). The mean line surface brightness is a quantity that is relevant to measurements of spectral distortions of the cosmic microwave background, and as a potential tool for studying large-scale structures in the early universe using intensity mapping. While the cosmic volume and the number of detections are admittedly small, this pilot survey provides a direct measure of the mean line surface brightness, independent of conversion factors, excitation, or other galaxy formation model assumptions. The mean surface brightness in the 99 GHZ band is: T{sub B}  = 0.94 ± 0.09 μ K. In the 242 GHz band, the mean brightness is: T{sub B}  = 0.55 ± 0.033 μ K. These should be interpreted as lower limits on the average sky signal, since we only include lines detected individually in the blind survey, while in a low resolution intensity mapping experiment, there will also be the summed contribution from lower luminosity galaxies that cannot be detected individually in the current blind survey.

  12. CMOS MAPS in a Homogeneous 3D Process for Charged Particle Tracking

    CERN Document Server

    Manazza, A; Manghisoni, M; Re, V; Traversi, G; Bettarini, S; Forti, F; Morsani, F; Rizzo, G; 10.1109/TNS.2014.2299341

    2014-01-01

    This work presents the characterization of deep n-well (DNW) CMOS monolithic active pixel sensors (MAPS) fabricated in a 130 nm homogeneous, vertically integrated technology. An evaluation of the 3D MAPS device performance, designed for application of the experiments at the future high luminosity colliders, is provided through the characterization of the prototypes, including tests with infrared (IR) laser, 55Fe and 90Sr sources. The radiation hardness study of the technology will also be presented together with its impact on 3D DNW MAPS performance.

  13. Effects of deformable registration algorithms on the creation of statistical maps for preoperative targeting in deep brain stimulation procedures

    Science.gov (United States)

    Liu, Yuan; D'Haese, Pierre-Francois; Dawant, Benoit M.

    2014-03-01

    Deep brain stimulation, which is used to treat various neurological disorders, involves implanting a permanent electrode into precise targets deep in the brain. Accurate pre-operative localization of the targets on pre-operative MRI sequence is challenging as these are typically located in homogenous regions with poor contrast. Population-based statistical atlases can assist with this process. Such atlases are created by acquiring the location of efficacious regions from numerous subjects and projecting them onto a common reference image volume using some normalization method. In previous work, we presented results concluding that non-rigid registration provided the best result for such normalization. However, this process could be biased by the choice of the reference image and/or registration approach. In this paper, we have qualitatively and quantitatively compared the performance of six recognized deformable registration methods at normalizing such data in poor contrasted regions onto three different reference volumes using a unique set of data from 100 patients. We study various metrics designed to measure the centroid, spread, and shape of the normalized data. This study leads to a total of 1800 deformable registrations and results show that statistical atlases constructed using different deformable registration methods share comparable centroids and spreads with marginal differences in their shape. Among the six methods being studied, Diffeomorphic Demons produces the largest spreads and centroids that are the furthest apart from the others in general. Among the three atlases, one atlas consistently outperforms the other two with smaller spreads for each algorithm. However, none of the differences in the spreads were found to be statistically significant, across different algorithms or across different atlases.

  14. Three-dimensional optical micro-angiography maps directional blood perfusion deep within microcirculation tissue beds in vivo

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Ruikang K [Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR 97237 (United States)

    2007-12-07

    Optical micro-angiography (OMAG) is a recently developed method of imaging localized blood perfusion at capillary level resolution within microcirculatory beds. This paper reports that the OMAG is capable of directional blood perfusion mapping in vivo. This is achieved simply by translating the mirror located in the reference arm back and forth while 3D imaging is performed. The mirror which moves toward the incident beam gives the blood perfusion that flows away from the beam direction and vice versa. The approach is experimentally demonstrated by imaging of a flow phantom and then cerebro-vascular perfusion of a live mouse with cranium intact.

  15. Long-Term Annual Mapping of Four Cities on Different Continents by Applying a Deep Information Learning Method to Landsat Data

    Directory of Open Access Journals (Sweden)

    Haobo Lyu

    2018-03-01

    Full Text Available Urbanization is a substantial contributor to anthropogenic environmental change, and often occurs at a rapid pace that demands frequent and accurate monitoring. Time series of satellite imagery collected at fine spatial resolution using stable spectral bands over decades are most desirable for this purpose. In practice, however, temporal spectral variance arising from variations in atmospheric conditions, sensor calibration, cloud cover, and other factors complicates extraction of consistent information on changes in urban land cover. Moreover, the construction and application of effective training samples is time-consuming, especially at continental and global scales. Here, we propose a new framework for satellite-based mapping of urban areas based on transfer learning and deep learning techniques. We apply this method to Landsat observations collected during 1984–2016 and extract annual records of urban areas in four cities in the temperate zone (Beijing, New York, Melbourne, and Munich. The method is trained using observations of Beijing collected in 1999, and then used to map urban areas in all target cities for the entire 1984–2016 period. The method addresses two central challenges in long term detection of urban change: temporal spectral variance and a scarcity of training samples. First, we use a recurrent neural network to minimize seasonal urban spectral variance. Second, we introduce an automated transfer strategy to maximize information gain from limited training samples when applied to new target cities in similar climate zones. Compared with other state-of-the-art methods, our method achieved comparable or even better accuracy: the average change detection accuracy during 1984–2016 is 89% for Beijing, 94% for New York, 93% for Melbourne, and 89% for Munich, and the overall accuracy of single-year urban maps is approximately 96 ± 3% among the four target cities. The results demonstrate the practical potential and suitability

  16. Large-scale deep-water seafloor mapping from the Rockall to the Hatton basins, NE Atlantic

    Science.gov (United States)

    Monteys, X.; Thébaudeau, B.; Murcia, C.; Duncan, N.

    2016-02-01

    Multibeam data acquired in 2000 and 2001 during the Irish National Seabed Survey (INSS) are used for the first detailed investigation of the seabed geomorphology and sediment type in the Hatton-Rockall basin area of the North East Atlantic Ocean, covering an area of approximately 80,000 km². The original multibeam survey produced bathymetric and backscatter datasets that allowed the creation of a Digital Terrain Models of approximately 50 m in resolution in water depths between 500 and 3500 m. Near-surface sediments for the entire region haven been classified using features derived from multibeam angular backscatter data (12kHz) and robust unsupervised clustering techniques. Additionally, sub bottom data imaging the shallow stratigraphy and geomagnetic measurements collected at the time of the MBES survey are combined to further characterise some of the features identified. The features presented in detail include parts of the Hatton and Gardar contourite drifts, volcanic mounds identified by their morphology and magnetic signature, deep-water coral mounds, iceberg scours as well as canyons, gullies and escarpments along and down the slopes of the banks and mounds. This study highlights for the first time the variety and complexity of the seafloor present at the seabed in the Irish Hatton-Rockall basin area

  17. A Global Survey and Interactive Map Suite of Deep Underground Facilities; Examples of Geotechnical and Engineering Capabilities, Achievements, Challenges: (Mines, Shafts, Tunnels, Boreholes, Sites and Underground Facilities for Nuclear Waste and Physics R&D)

    Science.gov (United States)

    Tynan, M. C.; Russell, G. P.; Perry, F.; Kelley, R.; Champenois, S. T.

    2017-12-01

    This global survey presents a synthesis of some notable geotechnical and engineering information reflected in four interactive layer maps for selected: 1) deep mines and shafts; 2) existing, considered or planned radioactive waste management deep underground studies, sites, or disposal facilities; 3) deep large diameter boreholes, and 4) physics underground laboratories and facilities from around the world. These data are intended to facilitate user access to basic information and references regarding deep underground "facilities", history, activities, and plans. In general, the interactive maps and database [http://gis.inl.gov/globalsites/] provide each facility's approximate site location, geology, and engineered features (e.g.: access, geometry, depth, diameter, year of operations, groundwater, lithology, host unit name and age, basin; operator, management organization, geographic data, nearby cultural features, other). Although the survey is not all encompassing, it is a comprehensive review of many of the significant existing and historical underground facilities discussed in the literature addressing radioactive waste management and deep mined geologic disposal safety systems. The global survey is intended to support and to inform: 1) interested parties and decision makers; 2) radioactive waste disposal and siting option evaluations, and 3) safety case development as a communication tool applicable to any mined geologic disposal facility as a demonstration of historical and current engineering and geotechnical capabilities available for use in deep underground facility siting, planning, construction, operations and monitoring.

  18. Mapping deep aquifer salinity trends in the southern San Joaquin Valley using borehole geophysical data constrained by chemical analyses

    Science.gov (United States)

    Gillespie, J.; Shimabukuro, D.; Stephens, M.; Chang, W. H.; Ball, L. B.; Everett, R.; Metzger, L.; Landon, M. K.

    2016-12-01

    The California State Water Resources Control Board and the California Division of Oil, Gas and Geothermal Resources are collaborating with the U.S. Geological Survey to map groundwater resources near oil fields and to assess potential interactions between oil and gas development and groundwater resources. Groundwater resources having salinity less than 10,000 mg/L total dissolved solids may be classified as Underground Sources of Drinking Water (USDW) and subject to protection under the federal Safe Drinking Water Act. In this study, we use information from oil well borehole geophysical logs, oilfield produced water and groundwater chemistry data, and three-dimensional geologic surfaces to map the spatial distribution of salinity in aquifers near oil fields. Salinity in the southern San Joaquin Valley is controlled primarily by depth and location. The base of protected waters occurs at very shallow depths, often 1,500 meters, in the eastern part of the San Joaquin Valley where higher runoff from the western slopes of the Sierra Nevada provide relatively abundant aquifer recharge. Stratigraphy acts as a secondary control on salinity within these broader areas. Formations deposited in non-marine environments are generally fresher than marine deposits. Layers isolated vertically between confining beds and cut off from recharge sources may be more saline than underlying aquifers that outcrop in upland areas on the edge of the valley with more direct connection to regional recharge areas. The role of faulting is more ambiguous. In some areas, abrupt changes in salinity may be fault controlled but, more commonly, the faults serve as traps separating oil-bearing strata that are exempt from USDW regulations, from water-bearing strata that are not exempt.

  19. High-Resolution Seafloor Mapping at A Deep-Sea Methane Seep Field with an Autonomous Underwater Vehicle

    Science.gov (United States)

    Skarke, A. D.

    2017-12-01

    A growing body of research indicates that points of seafloor gas emission, known as cold-seeps, are a common feature along many continental margins. Results from recent exploration efforts show that benthic environments at cold-seeps are characterized by extensive authigenic carbonate crusts and complex chemosynthetic communities. The seafloor morphology and geophysical properties of these locations are heterogeneous and relatively complex due to the three-dimensional structure created by carbonate buildups and dense bivalve beds. Seeps are often found clustered and the spatial extent of associated seafloor crusts and beds can reach multiple square kilometers. Here, the results of a 1.25 km2 autonomous underwater vehicle (AUV) survey of a deep-sea methane seep field with 13 vents, at a nominal depth of 1400 m, located near Veatch Canyon on the US Atlantic margin are presented. Multibeam sonar, sidescan sonar, and a sub bottom profiler on the AUV were used to make high-resolution observations of seafloor bathymetry (resolution 1m2) as well as water column, seafloor, and subsurface acoustic backscatter intensity. Additionally, a downward oriented camera was used to collect seafloor imagery coincident with acoustic observations at select locations. Acoustic results indicated the location of discrete gas plumes as well as a continuous area of elevated seafloor roughness and backscatter intensity consistent with the presence of large scale authigenic rock outcrops and extensive mussel beds, which were visually confirmed with camera imagery. Additionally, a linear area of particularly elevated seafloor roughness and acoustic backscatter intensity that lies sub-parallel to an adjacent ridge was interpreted to be controlled by underlying geologic processes such as soft sediment faulting. Automated analysis of camera imagery and coincident acoustic backscatter and bathymetry data as well as derivative metrics (e.g. slope and rugosity) was used to segment and classify bed

  20. Quasar 3C351: VLA maps and a deep search for optical emission in the outer lobes

    International Nuclear Information System (INIS)

    Kronberg, P.P.; Clarke, J.N.; van den Bergh, S.

    1980-01-01

    VLA radio maps of the quasar 3C351 (z=0.371) at approx.2'' and 0.''4 resolution (a) show interaction with a relatively dense intergalactic medium, (b) show that there is electron acceleration within at least one of the radio lobes, and (c) imply that the intergalactic gas density is different on one side of the source than on the other. Striking similarities are found between the northern radio lobe of 3C351 and one of the outer hotspots of Cygnus A, and possibly other similar systems, in that the outer, on-axis hotspot is resolved and cusp-shaped, and the ''secondary'' off-axis hotspot is more compact. A search for optical emission in the outer lobes shows no emission stronger than 22/sup m/ in the J band and approx.21/sup m/ in the F band. There is also no evidence at these limits for a cluster of galaxies near the radio source, as is suggested by our conclusion that it is interacting with a medium of typical intracluster density

  1. Personalized mapping of the deep brain with a white matter attenuated inversion recovery (WAIR) sequence at 1.5-tesla: Experience based on a series of 156 patients.

    Science.gov (United States)

    Zerroug, A; Gabrillargues, J; Coll, G; Vassal, F; Jean, B; Chabert, E; Claise, B; Khalil, T; Sakka, L; Feschet, F; Durif, F; Boyer, L; Coste, J; Lemaire, J-J

    2016-08-01

    Deep brain mapping has been proposed for direct targeting in stereotactic functional surgery, aiming to personalize electrode implantation according to individual MRI anatomy without atlas or statistical template. We report our clinical experience of direct targeting in a series of 156 patients operated on using a dedicated Inversion Recovery Turbo Spin Echo sequence at 1.5-tesla, called White Matter Attenuated Inversion Recovery (WAIR). After manual contouring of all pertinent structures and 3D planning of trajectories, 312 DBS electrodes were implanted. Detailed anatomy of close neighbouring structures, whether gray nuclei or white matter regions, was identified during each planning procedure. We gathered the experience of these 312 deep brain mappings and elaborated consistent procedures of anatomical MRI mapping for pallidal, subthalamic and ventral thalamic regions. We studied the number of times the central track anatomically optimized was selected for implantation of definitive electrodes. WAIR sequence provided high-quality images of most common functional targets, successfully used for pure direct stereotactic targeting: the central track corresponding to the optimized primary anatomical trajectory was chosen for implantation of definitive electrodes in 90.38%. WAIR sequence is anatomically reliable, enabling precise deep brain mapping and direct stereotactic targeting under routine clinical conditions. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  2. Pro region engineering of nerve growth factor by deep mutational scanning enables a yeast platform for conformational epitope mapping of anti-NGF monoclonal antibodies.

    Science.gov (United States)

    Medina-Cucurella, Angélica V; Zhu, Yaqi; Bowen, Scott J; Bergeron, Lisa M; Whitehead, Timothy A

    2018-04-12

    Nerve growth factor (NGF) plays a central role in multiple chronic pain conditions. As such, anti-NGF monoclonal antibodies (mAbs) that function by antagonizing NGF downstream signaling are leading drug candidates for non-opioid pain relief. To evaluate anti-canine NGF (cNGF) mAbs we sought a yeast surface display platform of cNGF. Both mature cNGF and pro-cNGF displayed on the yeast surface but bound conformationally sensitive mAbs at most 2.5-fold in mean fluorescence intensity above background, suggesting that cNGF was mostly misfolded. To improve the amount of folded, displayed cNGF, we used comprehensive mutagenesis, FACS, and deep sequencing to identify point mutants in the pro-region of canine NGF that properly enhance the folded protein displayed on the yeast surface. Out of 1,737 tested single point mutants in the pro region, 49 increased the amount of NGF recognized by conformationally sensitive mAbs. These gain-of-function mutations cluster around residues A-61-P-26. Gain-of-function mutants were additive, and a construct containing three mutations increased amount of folded cNGF to 23- fold above background. Using this new cNGF construct, fine conformational epitopes for tanezumab and three anti-cNGF mAbs were evaluated. The epitope revealed by the yeast experiments largely overlapped with the tanezumab epitope previously determined by X-ray crystallography. The other mAbs showed site-specific differences with tanezumab. As the number of binding epitopes of functionally neutralizing anti-NGF mAbs on NGF are limited, subtle differences in the individual interacting residues on NGF that bind each mAb contribute to the understanding of each antibody and variations in its neutralizing activity. These results demonstrate the potential of deep sequencing-guided protein engineering to improve the production of folded surface-displayed protein, and the resulting cNGF construct provides a platform to map conformational epitopes for other anti-neurotrophin m

  3. 3D edge detection seismic attributes used to map potential conduits for water and methane in deep gold mines in the Witwatersrand basin, South Africa

    CSIR Research Space (South Africa)

    Manzi, MSD

    2012-09-01

    Full Text Available Inrushes of ground water and the ignition of flammable gases pose risks to workers in deep South African gold mines. Large volumes of water may be stored in solution cavities in dolomitic rocks that overlie the Black Reef (BLR) Formation, while...

  4. Mapping and quantifying groundwater inflows to Deep Creek (Maribyrnong catchment, SE Australia) using 222Rn, implications for protecting groundwater-dependant ecosystems

    International Nuclear Information System (INIS)

    Cartwright, Ian; Gilfedder, Benjamin

    2015-01-01

    Highlights: • Groundwater inflows in a chain-of-ponds river quantified. • Groundwater inflow vs. discharge relationship determined using Rn. • First long-term continuous Rn monitoring in a river indicates temporal changes to groundwater inflows. • Application to protection of groundwater-dependant ecosystems. - Abstract: Understanding groundwater inflows to rivers is important in managing connected groundwater and surface water systems and for protecting groundwater-dependant ecosystems. This study defines the distribution of gaining reaches and estimates groundwater inflows to a 62 km long section of Deep Creek (Maribyrnong catchment, Australia) using 222 Rn. During summer months, Deep Creek ceases to flow and comprises a chain of ponds that δ 18 O and δ 2 H values, major ion concentrations, and 222 Rn activities imply are groundwater fed. During the period where the river flows, the relative contribution of groundwater inflows to total river discharge ranges from ∼14% at high flow conditions to ∼100% at low flows. That the predicted groundwater inflows account for all of the increase in discharge at low flow conditions lends confidence to the mass balance calculations. Near-continuous 27 week 222 Rn monitoring at one location in the middle of the catchment confirms the inverse correlation between river discharge and relative groundwater inflows, and also implies that there are limited bank return flows. Variations in groundwater inflows are related to geology and topography. High groundwater inflows occur where the river is at the edge of its floodplain, adjacent to hills composed of basement rocks, or flowing through steep incised valleys. Understanding the distribution of groundwater inflows and quantifying the contribution of groundwater to Deep Creek is important for managing and protecting the surface water resources, which support the endangered Yarra pygmy perch

  5. Deep frying

    NARCIS (Netherlands)

    Koerten, van K.N.

    2016-01-01

    Deep frying is one of the most used methods in the food processing industry. Though practically any food can be fried, French fries are probably the most well-known deep fried products. The popularity of French fries stems from their unique taste and texture, a crispy outside with a mealy soft

  6. Deep learning

    CERN Document Server

    Goodfellow, Ian; Courville, Aaron

    2016-01-01

    Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

  7. A Global Survey of Deep Underground Facilities; Examples of Geotechnical and Engineering Capabilities, Achievements, Challenges (Mines, Shafts, Tunnels, Boreholes, Sites and Underground Facilities for Nuclear Waste and Physics R&D): A Guide to Interactive Global Map Layers, Table Database, References and Notes

    International Nuclear Information System (INIS)

    Tynan, Mark C.; Russell, Glenn P.; Perry, Frank V.; Kelley, Richard E.; Champenois, Sean T.

    2017-01-01

    These associated tables, references, notes, and report present a synthesis of some notable geotechnical and engineering information used to create four interactive layer maps for selected: 1) deep mines and shafts; 2) existing, considered or planned radioactive waste management deep underground studies or disposal facilities 3) deep large diameter boreholes, and 4) physics underground laboratories and facilities from around the world. These data are intended to facilitate user access to basic information and references regarding “deep underground” facilities, history, activities, and plans. In general, the interactive maps and database provide each facility’s approximate site location, geology, and engineered features (e.g.: access, geometry, depth, diameter, year of operations, groundwater, lithology, host unit name and age, basin; operator, management organization, geographic data, nearby cultural features, other). Although the survey is not comprehensive, it is representative of many of the significant existing and historical underground facilities discussed in the literature addressing radioactive waste management and deep mined geologic disposal safety systems. The global survey is intended to support and to inform: 1) interested parties and decision makers; 2) radioactive waste disposal and siting option evaluations, and 3) safety case development applicable to any mined geologic disposal facility as a demonstration of historical and current engineering and geotechnical capabilities available for use in deep underground facility siting, planning, construction, operations and monitoring.

  8. A Global Survey of Deep Underground Facilities; Examples of Geotechnical and Engineering Capabilities, Achievements, Challenges (Mines, Shafts, Tunnels, Boreholes, Sites and Underground Facilities for Nuclear Waste and Physics R&D): A Guide to Interactive Global Map Layers, Table Database, References and Notes

    Energy Technology Data Exchange (ETDEWEB)

    Tynan, Mark C. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Russell, Glenn P. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Perry, Frank V. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kelley, Richard E. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Champenois, Sean T. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2017-06-13

    These associated tables, references, notes, and report present a synthesis of some notable geotechnical and engineering information used to create four interactive layer maps for selected: 1) deep mines and shafts; 2) existing, considered or planned radioactive waste management deep underground studies or disposal facilities 3) deep large diameter boreholes, and 4) physics underground laboratories and facilities from around the world. These data are intended to facilitate user access to basic information and references regarding “deep underground” facilities, history, activities, and plans. In general, the interactive maps and database provide each facility’s approximate site location, geology, and engineered features (e.g.: access, geometry, depth, diameter, year of operations, groundwater, lithology, host unit name and age, basin; operator, management organization, geographic data, nearby cultural features, other). Although the survey is not comprehensive, it is representative of many of the significant existing and historical underground facilities discussed in the literature addressing radioactive waste management and deep mined geologic disposal safety systems. The global survey is intended to support and to inform: 1) interested parties and decision makers; 2) radioactive waste disposal and siting option evaluations, and 3) safety case development applicable to any mined geologic disposal facility as a demonstration of historical and current engineering and geotechnical capabilities available for use in deep underground facility siting, planning, construction, operations and monitoring.

  9. Using High-Resolution Swath Mapping Data and Other Underway Geophysical Measurements Collected during Transit Cruises of RV Isabu to Map Deep Sea Floor of the Pacific and Indian Oceans

    Science.gov (United States)

    Hong, G. H.; Lee, S. M.; Kim, D. J.; Lee, Y. H.; Kim, S. S.

    2017-12-01

    Detail images of the seafloor are often the first collection of clues that set one towards a path that leads to a new discovery. The mapping of unchartered seafloor is like exploring the surface of an unknown planet for the first time. The launch of new global-ocean-class RV Isabu operated by Korea Institute of Ocean Science and Technology (KIOST) in November 2016 has reinvigorated the ongoing open ocean research in Korea. The location of the KIOST research vessels can be found at http://www.kiost.net/. Here we present a new collaborative research and education program which utilizes onboard measurements taken during the transit cruises. The measurements include high-resolution swath mapping bathymetric data, underway geophysical measurements (3.5 kHz subbottom profile, sea surface gravity and magnetic field) which are gathered semi-automatically during a scientific operation. The acquisition of data alone is not sufficient for meaningful scientific knowledge as the initial measurements must be cleaned and processed during or after the cruise. As in any scientific endeavor, planning is important. Prior to the cruise, preliminary study will be carried out by carefully examining the previously collected data from various global databases. Whenever possible, a small offset will be made of the ship track lines crossing the region so that important new measurements can be obtained systematically over the years. We anticipate that the program will not only contribute to fill the gap in the high-resolution bathymetry in some part of the Indian Ocean and Pacific. The processed and analyzed data will be available to other scientific communities for further understanding via download from KIOST website.

  10. Advantages of a vertical integration process in the design of DNW MAPS

    International Nuclear Information System (INIS)

    Ratti, L.; Gaioni, L.; Manazza, A.; Manghisoni, M.; Re, V.; Traversi, G.

    2015-01-01

    This work discusses the main features of a CMOS Deep N-well (DNW) monolithic active pixel sensor (MAPS) fabricated in a vertically integrated technology, where two 130 nm CMOS homogeneous tiers are processed to obtain a 3D integrated circuit (3D-IC). The 3D CMOS MAPS, which was designed in view of vertexing applications to experiments at high luminosity colliders, features a 20 μm pitch for a point resolution of about 5 μm and data sparsification capabilities for high data rate systems. Results from the characterization of different test structures, including single pixels, 3×3 and 8×8 matrices, are presented. In particular, measurements have been performed with an infrared laser source to evaluate the charge collection properties of the proposed vertically integrated sensors

  11. Advantages of a vertical integration process in the design of DNW MAPS

    Energy Technology Data Exchange (ETDEWEB)

    Ratti, L. [Università di Pavia, Dipartimento di Elettronica, Via Ferrata 1, I-27100 Pavia (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Gaioni, L. [Università di Bergamo, Dipartimento di Ingegneria Industriale, Via Marconi 5, I-24044 Dalmine (Italy); Manazza, A. [INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy); Manghisoni, M.; Re, V.; Traversi, G. [Università di Bergamo, Dipartimento di Ingegneria Industriale, Via Marconi 5, I-24044 Dalmine (Italy); INFN, Sezione di Pavia, Via Bassi 6, I-27100 Pavia (Italy)

    2015-06-01

    This work discusses the main features of a CMOS Deep N-well (DNW) monolithic active pixel sensor (MAPS) fabricated in a vertically integrated technology, where two 130 nm CMOS homogeneous tiers are processed to obtain a 3D integrated circuit (3D-IC). The 3D CMOS MAPS, which was designed in view of vertexing applications to experiments at high luminosity colliders, features a 20 μm pitch for a point resolution of about 5 μm and data sparsification capabilities for high data rate systems. Results from the characterization of different test structures, including single pixels, 3×3 and 8×8 matrices, are presented. In particular, measurements have been performed with an infrared laser source to evaluate the charge collection properties of the proposed vertically integrated sensors.

  12. Mapping out Map Libraries

    Directory of Open Access Journals (Sweden)

    Ferjan Ormeling

    2008-09-01

    Full Text Available Discussing the requirements for map data quality, map users and their library/archives environment, the paper focuses on the metadata the user would need for a correct and efficient interpretation of the map data. For such a correct interpretation, knowledge of the rules and guidelines according to which the topographers/cartographers work (such as the kind of data categories to be collected, and the degree to which these rules and guidelines were indeed followed are essential. This is not only valid for the old maps stored in our libraries and archives, but perhaps even more so for the new digital files as the format in which we now have to access our geospatial data. As this would be too much to ask from map librarians/curators, some sort of web 2.0 environment is sought where comments about data quality, completeness and up-to-dateness from knowledgeable map users regarding the specific maps or map series studied can be collected and tagged to scanned versions of these maps on the web. In order not to be subject to the same disadvantages as Wikipedia, where the ‘communis opinio’ rather than scholarship, seems to be decisive, some checking by map curators of this tagged map use information would still be needed. Cooperation between map curators and the International Cartographic Association ( ICA map and spatial data use commission to this end is suggested.

  13. Deep Learning

    DEFF Research Database (Denmark)

    Jensen, Morten Bornø; Bahnsen, Chris Holmberg; Nasrollahi, Kamal

    2018-01-01

    I løbet af de sidste 10 år er kunstige neurale netværk gået fra at være en støvet, udstødt tekno-logi til at spille en hovedrolle i udviklingen af kunstig intelligens. Dette fænomen kaldes deep learning og er inspireret af hjernens opbygning.......I løbet af de sidste 10 år er kunstige neurale netværk gået fra at være en støvet, udstødt tekno-logi til at spille en hovedrolle i udviklingen af kunstig intelligens. Dette fænomen kaldes deep learning og er inspireret af hjernens opbygning....

  14. Deep geothermics

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    The hot-dry-rocks located at 3-4 km of depth correspond to low permeable rocks carrying a large amount of heat. The extraction of this heat usually requires artificial hydraulic fracturing of the rock to increase its permeability before water injection. Hot-dry-rocks geothermics or deep geothermics is not today a commercial channel but only a scientific and technological research field. The Soultz-sous-Forets site (Northern Alsace, France) is characterized by a 6 degrees per meter geothermal gradient and is used as a natural laboratory for deep geothermal and geological studies in the framework of a European research program. Two boreholes have been drilled up to 3600 m of depth in the highly-fractured granite massif beneath the site. The aim is to create a deep heat exchanger using only the natural fracturing for water transfer. A consortium of german, french and italian industrial companies (Pfalzwerke, Badenwerk, EdF and Enel) has been created for a more active participation to the pilot phase. (J.S.). 1 fig., 2 photos

  15. Deep smarts.

    Science.gov (United States)

    Leonard, Dorothy; Swap, Walter

    2004-09-01

    When a person sizes up a complex situation and rapidly comes to a decision that proves to be not just good but brilliant, you think, "That was smart." After you watch him do this a few times, you realize you're in the presence of something special. It's not raw brainpower, though that helps. It's not emotional intelligence, either, though that, too, is often involved. It's deep smarts. Deep smarts are not philosophical--they're not"wisdom" in that sense, but they're as close to wisdom as business gets. You see them in the manager who understands when and how to move into a new international market, in the executive who knows just what kind of talk to give when her organization is in crisis, in the technician who can track a product failure back to an interaction between independently produced elements. These are people whose knowledge would be hard to purchase on the open market. Their insight is based on know-how more than on know-what; it comprises a system view as well as expertise in individual areas. Because deep smarts are experienced based and often context specific, they can't be produced overnight or readily imported into an organization. It takes years for an individual to develop them--and no time at all for an organization to lose them when a valued veteran walks out the door. They can be taught, however, with the right techniques. Drawing on their forthcoming book Deep Smarts, Dorothy Leonard and Walter Swap say the best way to transfer such expertise to novices--and, on a larger scale, to make individual knowledge institutional--isn't through PowerPoint slides, a Web site of best practices, online training, project reports, or lectures. Rather, the sage needs to teach the neophyte individually how to draw wisdom from experience. Companies have to be willing to dedicate time and effort to such extensive training, but the investment more than pays for itself.

  16. The projective heat map

    CERN Document Server

    Schwartz, Richard Evan

    2017-01-01

    This book introduces a simple dynamical model for a planar heat map that is invariant under projective transformations. The map is defined by iterating a polygon map, where one starts with a finite planar N-gon and produces a new N-gon by a prescribed geometric construction. One of the appeals of the topic of this book is the simplicity of the construction that yet leads to deep and far reaching mathematics. To construct the projective heat map, the author modifies the classical affine invariant midpoint map, which takes a polygon to a new polygon whose vertices are the midpoints of the original. The author provides useful background which makes this book accessible to a beginning graduate student or advanced undergraduate as well as researchers approaching this subject from other fields of specialty. The book includes many illustrations, and there is also a companion computer program.

  17. DeepPy: Pythonic deep learning

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo

    This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly...... be able to understand and change the DeepPy codebase as it is mainly implemented using high-level NumPy primitives. Moreover, DeepPy supports complex network architectures by letting the user compose mathematical expressions as directed graphs. The latest version is available at http...

  18. Ploughing the deep sea floor.

    Science.gov (United States)

    Puig, Pere; Canals, Miquel; Company, Joan B; Martín, Jacobo; Amblas, David; Lastras, Galderic; Palanques, Albert

    2012-09-13

    Bottom trawling is a non-selective commercial fishing technique whereby heavy nets and gear are pulled along the sea floor. The direct impact of this technique on fish populations and benthic communities has received much attention, but trawling can also modify the physical properties of seafloor sediments, water–sediment chemical exchanges and sediment fluxes. Most of the studies addressing the physical disturbances of trawl gear on the seabed have been undertaken in coastal and shelf environments, however, where the capacity of trawling to modify the seafloor morphology coexists with high-energy natural processes driving sediment erosion, transport and deposition. Here we show that on upper continental slopes, the reworking of the deep sea floor by trawling gradually modifies the shape of the submarine landscape over large spatial scales. We found that trawling-induced sediment displacement and removal from fishing grounds causes the morphology of the deep sea floor to become smoother over time, reducing its original complexity as shown by high-resolution seafloor relief maps. Our results suggest that in recent decades, following the industrialization of fishing fleets, bottom trawling has become an important driver of deep seascape evolution. Given the global dimension of this type of fishery, we anticipate that the morphology of the upper continental slope in many parts of the world’s oceans could be altered by intensive bottom trawling, producing comparable effects on the deep sea floor to those generated by agricultural ploughing on land.

  19. Greedy Deep Dictionary Learning

    OpenAIRE

    Tariyal, Snigdha; Majumdar, Angshul; Singh, Richa; Vatsa, Mayank

    2016-01-01

    In this work we propose a new deep learning tool called deep dictionary learning. Multi-level dictionaries are learnt in a greedy fashion, one layer at a time. This requires solving a simple (shallow) dictionary learning problem, the solution to this is well known. We apply the proposed technique on some benchmark deep learning datasets. We compare our results with other deep learning tools like stacked autoencoder and deep belief network; and state of the art supervised dictionary learning t...

  20. Pathways to deep decarbonization - 2015 report

    International Nuclear Information System (INIS)

    Ribera, Teresa; Colombier, Michel; Waisman, Henri; Bataille, Chris; Pierfederici, Roberta; Sachs, Jeffrey; Schmidt-Traub, Guido; Williams, Jim; Segafredo, Laura; Hamburg Coplan, Jill; Pharabod, Ivan; Oury, Christian

    2015-12-01

    In September 2015, the Deep Decarbonization Pathways Project published the Executive Summary of the Pathways to Deep Decarbonization: 2015 Synthesis Report. The full 2015 Synthesis Report was launched in Paris on December 3, 2015, at a technical workshop with the Mitigation Action Plans and Scenarios (MAPS) program. The Deep Decarbonization Pathways Project (DDPP) is a collaborative initiative to understand and show how individual countries can transition to a low-carbon economy and how the world can meet the internationally agreed target of limiting the increase in global mean surface temperature to less than 2 degrees Celsius (deg. C). Achieving the 2 deg. C limit will require that global net emissions of greenhouse gases (GHG) approach zero by the second half of the century. In turn, this will require a profound transformation of energy systems by mid-century through steep declines in carbon intensity in all sectors of the economy, a transition we call 'deep decarbonization'

  1. Taoism and Deep Ecology.

    Science.gov (United States)

    Sylvan, Richard; Bennett, David

    1988-01-01

    Contrasted are the philosophies of Deep Ecology and ancient Chinese. Discusses the cosmology, morality, lifestyle, views of power, politics, and environmental philosophies of each. Concludes that Deep Ecology could gain much from Taoism. (CW)

  2. Trace maps for arbitrary substitution sequences

    International Nuclear Information System (INIS)

    Avishai, Y.

    1993-01-01

    The discovery of quasi-crystals and their 1-dimensional modeling have led to a deep mathematical study of Schroedinger operators with an arbitrary deterministic potential sequence. In this work we address this problem and find trace maps for an arbitrary substitution sequence. our trace maps have lower dimensionality than those of Kolar and Nori, which make them quite attractive for actual applications. (authors)

  3. Deep Incremental Boosting

    OpenAIRE

    Mosca, Alan; Magoulas, George D

    2017-01-01

    This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training time and improves generalisation. We draw inspiration from Transfer of Learning approaches to reduce the start-up time to training each incremental Ensemble member. We show a set of experiments that outlines some preliminary results on some common Deep Learning datasets and discuss the potential improvements Deep In...

  4. Deep Space Telecommunications

    Science.gov (United States)

    Kuiper, T. B. H.; Resch, G. M.

    2000-01-01

    The increasing load on NASA's deep Space Network, the new capabilities for deep space missions inherent in a next-generation radio telescope, and the potential of new telescope technology for reducing construction and operation costs suggest a natural marriage between radio astronomy and deep space telecommunications in developing advanced radio telescope concepts.

  5. Deep learning with Python

    CERN Document Server

    Chollet, Francois

    2018-01-01

    DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES • Practical code examples • In-depth introduction to Keras • Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural ...

  6. Deep learning evaluation using deep linguistic processing

    OpenAIRE

    Kuhnle, Alexander; Copestake, Ann

    2017-01-01

    We discuss problems with the standard approaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a complement to current practice. We demonstrate that with the help of existing 'deep' linguistic processing technology we are able to create challenging abstract datasets, which enable us to investigate the language understanding abilities of multimodal deep learning models in detail, as compared to a single performance value ...

  7. Topographic mapping

    Science.gov (United States)

    ,

    2008-01-01

    The U.S. Geological Survey (USGS) produced its first topographic map in 1879, the same year it was established. Today, more than 100 years and millions of map copies later, topographic mapping is still a central activity for the USGS. The topographic map remains an indispensable tool for government, science, industry, and leisure. Much has changed since early topographers traveled the unsettled West and carefully plotted the first USGS maps by hand. Advances in survey techniques, instrumentation, and design and printing technologies, as well as the use of aerial photography and satellite data, have dramatically improved mapping coverage, accuracy, and efficiency. Yet cartography, the art and science of mapping, may never before have undergone change more profound than today.

  8. Deep learning relevance

    DEFF Research Database (Denmark)

    Lioma, Christina; Larsen, Birger; Petersen, Casper

    2016-01-01

    train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....

  9. Participatory Maps

    DEFF Research Database (Denmark)

    Salovaara-Moring, Inka

    2016-01-01

    practice. In particular, mapping environmental damage, endangered species, and human-made disasters has become one focal point for environmental knowledge production. This type of digital map has been highlighted as a processual turn in critical cartography, whereas in related computational journalism...... of a geo-visualization within information mapping that enhances embodiment in the experience of the information. InfoAmazonia is defined as a digitally created map-space within which journalistic practice can be seen as dynamic, performative interactions between journalists, ecosystems, space, and species...

  10. Pathways to deep decarbonization - Interim 2014 Report

    International Nuclear Information System (INIS)

    2014-01-01

    The interim 2014 report by the Deep Decarbonization Pathways Project (DDPP), coordinated and published by IDDRI and the Sustainable Development Solutions Network (SDSN), presents preliminary findings of the pathways developed by the DDPP Country Research Teams with the objective of achieving emission reductions consistent with limiting global warming to less than 2 deg. C. The DDPP is a knowledge network comprising 15 Country Research Teams and several Partner Organizations who develop and share methods, assumptions, and findings related to deep decarbonization. Each DDPP Country Research Team has developed an illustrative road-map for the transition to a low-carbon economy, with the intent of taking into account national socio-economic conditions, development aspirations, infrastructure stocks, resource endowments, and other relevant factors. The interim 2014 report focuses on technically feasible pathways to deep decarbonization

  11. Latest results of the R and D on CMOS MAPS for the Layer0 of the SuperB SVT

    Energy Technology Data Exchange (ETDEWEB)

    Balestri, G. [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (Italy); Batignani, G. [Università degli Studi di Pisa (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (Italy); Beck, G. [School of Physics and Astronomy Queen Mary, University of London, London E1 4NS (United Kingdom); Bernardelli, A. [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (Italy); Berra, A. [Università dell' Insubria, Como (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Milano Bicocca (Italy); Bettarini, S. [Università degli Studi di Pisa (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (Italy); Bevan, A. [School of Physics and Astronomy Queen Mary, University of London, London E1 4NS (United Kingdom); Bombelli, L. [Politecnico di Milano (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Milano (Italy); Bosi, F. [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (Italy); Bosisio, L. [Università degli Studi di Trieste (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Trieste (Italy); Casarosa, G., E-mail: giulia.casarosa@pi.infn.it [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (Italy); Ceccanti, M. [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (Italy); Cenci, R. [University of Maryland (United States); Citterio, M.; Coelli, S. [Istituto Nazionale di Fisica Nucleare, Sezione di Milano (Italy); Comotti, D. [Università degli Studi di Bergamo (Italy); Dalla Betta, G.-F. [Università degli Studi di Trento (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Padova (Italy); Fabbri, L. [Università degli Studi di Bologna (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Bologna (Italy); and others

    2013-12-21

    Physics and high background conditions set very challenging requirements on readout speed, material budget and resolution for the innermost layer of the SuperB Silicon Vertex Tracker operated at the full luminosity. Monolithic Active Pixel Sensors (MAPS) are very appealing in this application since the thin sensitive region allows grinding the substrate to tens of microns. Deep N-Well MAPS, developed in the ST 130 nm CMOS technology, achieved in-pixel sparsification and fast time stamping. Further improvements are being explored with an intense R and D program, including both vertical integration and 2D MAPS with the INMAPS quadruple well. We present the results of the characterization with IR laser, radioactive sources and beam of several chips produced with the 3D (Chartered/Tezzaron) process. We have also studied prototypes exploiting the features of the quadruple well and the high resistivity epitaxial layer of the INMAPS 180 nm process. Promising results from an irradiation campaign with neutrons on small matrices and other test-structures, as well as the response of the sensors to high energy charged tracks are presented.

  12. Concept Mapping

    Science.gov (United States)

    Technology & Learning, 2005

    2005-01-01

    Concept maps are graphical ways of working with ideas and presenting information. They reveal patterns and relationships and help students to clarify their thinking, and to process, organize and prioritize. Displaying information visually--in concept maps, word webs, or diagrams--stimulates creativity. Being able to think logically teaches…

  13. Deep Vein Thrombosis

    African Journals Online (AJOL)

    OWNER

    Deep Vein Thrombosis: Risk Factors and Prevention in Surgical Patients. Deep Vein ... preventable morbidity and mortality in hospitalized surgical patients. ... the elderly.3,4 It is very rare before the age ... depends on the risk level; therefore an .... but also in the post-operative period. ... is continuing uncertainty regarding.

  14. Deep Echo State Network (DeepESN): A Brief Survey

    OpenAIRE

    Gallicchio, Claudio; Micheli, Alessio

    2017-01-01

    The study of deep recurrent neural networks (RNNs) and, in particular, of deep Reservoir Computing (RC) is gaining an increasing research attention in the neural networks community. The recently introduced deep Echo State Network (deepESN) model opened the way to an extremely efficient approach for designing deep neural networks for temporal data. At the same time, the study of deepESNs allowed to shed light on the intrinsic properties of state dynamics developed by hierarchical compositions ...

  15. Deep Learning: A Primer for Radiologists.

    Science.gov (United States)

    Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

    2017-01-01

    Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

  16. Mapping racism.

    Science.gov (United States)

    Moss, Donald B

    2006-01-01

    The author uses the metaphor of mapping to illuminate a structural feature of racist thought, locating the degraded object along vertical and horizontal axes. These axes establish coordinates of hierarchy and of distance. With the coordinates in place, racist thought begins to seem grounded in natural processes. The other's identity becomes consolidated, and parochialism results. The use of this kind of mapping is illustrated via two patient vignettes. The author presents Freud's (1905, 1927) views in relation to such a "mapping" process, as well as Adorno's (1951) and Baldwin's (1965). Finally, the author conceptualizes the crucial status of primitivity in the workings of racist thought.

  17. Deep learning in bioinformatics.

    Science.gov (United States)

    Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh

    2017-09-01

    In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  18. Deep subsurface microbial processes

    Science.gov (United States)

    Lovley, D.R.; Chapelle, F.H.

    1995-01-01

    Information on the microbiology of the deep subsurface is necessary in order to understand the factors controlling the rate and extent of the microbially catalyzed redox reactions that influence the geophysical properties of these environments. Furthermore, there is an increasing threat that deep aquifers, an important drinking water resource, may be contaminated by man's activities, and there is a need to predict the extent to which microbial activity may remediate such contamination. Metabolically active microorganisms can be recovered from a diversity of deep subsurface environments. The available evidence suggests that these microorganisms are responsible for catalyzing the oxidation of organic matter coupled to a variety of electron acceptors just as microorganisms do in surface sediments, but at much slower rates. The technical difficulties in aseptically sampling deep subsurface sediments and the fact that microbial processes in laboratory incubations of deep subsurface material often do not mimic in situ processes frequently necessitate that microbial activity in the deep subsurface be inferred through nonmicrobiological analyses of ground water. These approaches include measurements of dissolved H2, which can predict the predominant microbially catalyzed redox reactions in aquifers, as well as geochemical and groundwater flow modeling, which can be used to estimate the rates of microbial processes. Microorganisms recovered from the deep subsurface have the potential to affect the fate of toxic organics and inorganic contaminants in groundwater. Microbial activity also greatly influences 1 the chemistry of many pristine groundwaters and contributes to such phenomena as porosity development in carbonate aquifers, accumulation of undesirably high concentrations of dissolved iron, and production of methane and hydrogen sulfide. Although the last decade has seen a dramatic increase in interest in deep subsurface microbiology, in comparison with the study of

  19. Genetic Mapping

    Science.gov (United States)

    ... greatly advanced genetics research. The improved quality of genetic data has reduced the time required to identify a ... cases, a matter of months or even weeks. Genetic mapping data generated by the HGP's laboratories is freely accessible ...

  20. Okeanos Explorer (EX1706): Johnston Atoll (ROV/Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will include the use of the ship's deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, Knudsen 3260 chirp...

  1. Deep Water Survey Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The deep water biodiversity surveys explore and describe the biodiversity of the bathy- and bentho-pelagic nekton using Midwater and bottom trawls centered in the...

  2. Deep Space Habitat Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Deep Space Habitat was closed out at the end of Fiscal Year 2013 (September 30, 2013). Results and select content have been incorporated into the new Exploration...

  3. Deep Learning in Neuroradiology.

    Science.gov (United States)

    Zaharchuk, G; Gong, E; Wintermark, M; Rubin, D; Langlotz, C P

    2018-02-01

    Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applications to medical imaging. Because of the high volume and wealth of multimodal imaging information acquired in typical studies, neuroradiology is poised to be an early adopter of deep learning. Compelling deep learning research applications have been demonstrated, and their use is likely to grow rapidly. This review article describes the reasons, outlines the basic methods used to train and test deep learning models, and presents a brief overview of current and potential clinical applications with an emphasis on how they are likely to change future neuroradiology practice. Facility with these methods among neuroimaging researchers and clinicians will be important to channel and harness the vast potential of this new method. © 2018 by American Journal of Neuroradiology.

  4. Deep inelastic lepton scattering

    International Nuclear Information System (INIS)

    Nachtmann, O.

    1977-01-01

    Deep inelastic electron (muon) nucleon and neutrino nucleon scattering as well as electron positron annihilation into hadrons are reviewed from a theoretical point of view. The emphasis is placed on comparisons of quantum chromodynamics with the data. (orig.) [de

  5. Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, E; Augustine, C; Paul, S; Detorakis, G

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Back Propagation (BP) rule, often relies on the immediate availability of network-wide...

  6. Pathogenesis of deep endometriosis.

    Science.gov (United States)

    Gordts, Stephan; Koninckx, Philippe; Brosens, Ivo

    2017-12-01

    The pathophysiology of (deep) endometriosis is still unclear. As originally suggested by Cullen, change the definition "deeper than 5 mm" to "adenomyosis externa." With the discovery of the old European literature on uterine bleeding in 5%-10% of the neonates and histologic evidence that the bleeding represents decidual shedding, it is postulated/hypothesized that endometrial stem/progenitor cells, implanted in the pelvic cavity after birth, may be at the origin of adolescent and even the occasionally premenarcheal pelvic endometriosis. Endometriosis in the adolescent is characterized by angiogenic and hemorrhagic peritoneal and ovarian lesions. The development of deep endometriosis at a later age suggests that deep infiltrating endometriosis is a delayed stage of endometriosis. Another hypothesis is that the endometriotic cell has undergone genetic or epigenetic changes and those specific changes determine the development into deep endometriosis. This is compatible with the hereditary aspects, and with the clonality of deep and cystic ovarian endometriosis. It explains the predisposition and an eventual causal effect by dioxin or radiation. Specific genetic/epigenetic changes could explain the various expressions and thus typical, cystic, and deep endometriosis become three different diseases. Subtle lesions are not a disease until epi(genetic) changes occur. A classification should reflect that deep endometriosis is a specific disease. In conclusion the pathophysiology of deep endometriosis remains debated and the mechanisms of disease progression, as well as the role of genetics and epigenetics in the process, still needs to be unraveled. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  7. Why & When Deep Learning Works: Looking Inside Deep Learnings

    OpenAIRE

    Ronen, Ronny

    2017-01-01

    The Intel Collaborative Research Institute for Computational Intelligence (ICRI-CI) has been heavily supporting Machine Learning and Deep Learning research from its foundation in 2012. We have asked six leading ICRI-CI Deep Learning researchers to address the challenge of "Why & When Deep Learning works", with the goal of looking inside Deep Learning, providing insights on how deep networks function, and uncovering key observations on their expressiveness, limitations, and potential. The outp...

  8. Projective mapping

    DEFF Research Database (Denmark)

    Dehlholm, Christian; Brockhoff, Per B.; Bredie, Wender Laurentius Petrus

    2012-01-01

    by the practical testing environment. As a result of the changes, a reasonable assumption would be to question the consequences caused by the variations in method procedures. Here, the aim is to highlight the proven or hypothetic consequences of variations of Projective Mapping. Presented variations will include...... instructions and influence heavily the product placements and the descriptive vocabulary (Dehlholm et.al., 2012b). The type of assessors performing the method influences results with an extra aspect in Projective Mapping compared to more analytical tests, as the given spontaneous perceptions are much dependent......Projective Mapping (Risvik et.al., 1994) and its Napping (Pagès, 2003) variations have become increasingly popular in the sensory field for rapid collection of spontaneous product perceptions. It has been applied in variations which sometimes are caused by the purpose of the analysis and sometimes...

  9. Affective Maps

    DEFF Research Database (Denmark)

    Salovaara-Moring, Inka

    . In particular, mapping environmental damage, endangered species, and human made disasters has become one of the focal point of affective knowledge production. These ‘more-than-humangeographies’ practices include notions of species, space and territory, and movement towards a new political ecology. This type...... of digital cartographies has been highlighted as the ‘processual turn’ in critical cartography, whereas in related computational journalism it can be seen as an interactive and iterative process of mapping complex and fragile ecological developments. This paper looks at computer-assisted cartography as part...

  10. AFSC/RACE/GAP/Rooper: Deep sea coral and sponge distribution

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — As part of a series of ongoing research projects, the AFSC has been mapping and modeling the distribution of deep-sea coral and sponge communities throughout Alaska....

  11. Energetic map

    International Nuclear Information System (INIS)

    2012-01-01

    This report explains the energetic map of Uruguay as well as the different systems that delimits political frontiers in the region. The electrical system importance is due to the electricity, oil and derived , natural gas, potential study, biofuels, wind and solar energy

  12. Necklace maps

    NARCIS (Netherlands)

    Speckmann, B.; Verbeek, K.A.B.

    2010-01-01

    Statistical data associated with geographic regions is nowadays globally available in large amounts and hence automated methods to visually display these data are in high demand. There are several well-established thematic map types for quantitative data on the ratio-scale associated with regions:

  13. Participatory maps

    DEFF Research Database (Denmark)

    Salovaara-Moring, Inka

    towards a new political ecology. This type of digital cartographies has been highlighted as the ‘processual turn’ in critical cartography, whereas in related computational journalism it can be seen as an interactive and iterative process of mapping complex and fragile ecological developments. This paper...

  14. Auxiliary Deep Generative Models

    DEFF Research Database (Denmark)

    Maaløe, Lars; Sønderby, Casper Kaae; Sønderby, Søren Kaae

    2016-01-01

    Deep generative models parameterized by neural networks have recently achieved state-of-the-art performance in unsupervised and semi-supervised learning. We extend deep generative models with auxiliary variables which improves the variational approximation. The auxiliary variables leave...... the generative model unchanged but make the variational distribution more expressive. Inspired by the structure of the auxiliary variable we also propose a model with two stochastic layers and skip connections. Our findings suggest that more expressive and properly specified deep generative models converge...... faster with better results. We show state-of-the-art performance within semi-supervised learning on MNIST (0.96%), SVHN (16.61%) and NORB (9.40%) datasets....

  15. Deep Learning from Crowds

    DEFF Research Database (Denmark)

    Rodrigues, Filipe; Pereira, Francisco Camara

    Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the stateof-the-art in various domains. However, as the size of supervised artificial neural networks grows, typically so does the need for larger labeled datasets. Recently...... networks from crowds. We begin by describing an EM algorithm for jointly learning the parameters of the network and the reliabilities of the annotators. Then, a novel general-purpose crowd layer is proposed, which allows us to train deep neural networks end-to-end, directly from the noisy labels......, crowdsourcing has established itself as an efficient and cost-effective solution for labeling large sets of data in a scalable manner, but it often requires aggregating labels from multiple noisy contributors with different levels of expertise. In this paper, we address the problem of learning deep neural...

  16. Cognitive Implications of Deep Gray Matter Iron in Multiple Sclerosis.

    Science.gov (United States)

    Fujiwara, E; Kmech, J A; Cobzas, D; Sun, H; Seres, P; Blevins, G; Wilman, A H

    2017-05-01

    Deep gray matter iron accumulation is increasingly recognized in association with multiple sclerosis and can be measured in vivo with MR imaging. The cognitive implications of this pathology are not well-understood, especially vis-à-vis deep gray matter atrophy. Our aim was to investigate the relationships between cognition and deep gray matter iron in MS by using 2 MR imaging-based iron-susceptibility measures. Forty patients with multiple sclerosis (relapsing-remitting, n = 16; progressive, n = 24) and 27 healthy controls were imaged at 4.7T by using the transverse relaxation rate and quantitative susceptibility mapping. The transverse relaxation rate and quantitative susceptibility mapping values and volumes (atrophy) of the caudate, putamen, globus pallidus, and thalamus were determined by multiatlas segmentation. Cognition was assessed with the Brief Repeatable Battery of Neuropsychological Tests. Relationships between cognition and deep gray matter iron were examined by hierarchic regressions. Compared with controls, patients showed reduced memory ( P processing speed ( P = .02) and smaller putamen ( P deep gray matter iron accumulation in the current multiple sclerosis cohort. Atrophy and iron accumulation in deep gray matter both have negative but separable relationships to cognition in multiple sclerosis. © 2017 by American Journal of Neuroradiology.

  17. Deep boreholes; Tiefe Bohrloecher

    Energy Technology Data Exchange (ETDEWEB)

    Bracke, Guido [Gesellschaft fuer Anlagen- und Reaktorsicherheit gGmbH Koeln (Germany); Charlier, Frank [NSE international nuclear safety engineering gmbh, Aachen (Germany); Geckeis, Horst [Karlsruher Institut fuer Technologie (Germany). Inst. fuer Nukleare Entsorgung; and others

    2016-02-15

    The report on deep boreholes covers the following subject areas: methods for safe enclosure of radioactive wastes, requirements concerning the geological conditions of possible boreholes, reversibility of decisions and retrievability, status of drilling technology. The introduction covers national and international activities. Further chapters deal with the following issues: basic concept of the storage in deep bore holes, status of the drilling technology, safe enclosure, geomechanics and stability, reversibility of decisions, risk scenarios, compliancy with safe4ty requirements and site selection criteria, research and development demand.

  18. Deep Water Acoustics

    Science.gov (United States)

    2016-06-28

    the Deep Water project and participate in the NPAL Workshops, including Art Baggeroer (MIT), J. Beron- Vera (UMiami), M. Brown (UMiami), T...Kathleen E . Wage. The North Pacific Acoustic Laboratory deep-water acoustic propagation experiments in the Philippine Sea. J. Acoust. Soc. Am., 134(4...estimate of the angle α during PhilSea09, made from ADCP measurements at the site of the DVLA. Sim. A B1 B2 B3 C D E F Prof. # 0 4 4 4 5 10 16 20 α

  19. Okeanos Explorer (EX1607): CAPSTONE Wake Island PRI MNM (Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will include 24 hour/day mapping operations using the ship’s deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries...

  20. Deep Learning for Distribution Channels' Management

    Directory of Open Access Journals (Sweden)

    Sabina-Cristiana NECULA

    2017-01-01

    Full Text Available This paper presents an experiment of using deep learning models for distribution channel management. We present an approach that combines self-organizing maps with artificial neural network with multiple hidden layers in order to identify the potential sales that might be addressed for channel distribution change/ management. Our study aims to highlight the evolution of techniques from simple features/learners to more complex learners and feature engineering or sampling techniques. This paper will allow researchers to choose best suited techniques and features to prepare their churn prediction models.

  1. MAPPING INNOVATION

    DEFF Research Database (Denmark)

    Thuesen, Christian Langhoff; Koch, Christian

    2011-01-01

    By adopting a theoretical framework from strategic niche management research (SNM) this paper presents an analysis of the innovation system of the Danish Construction industry. The analysis shows a multifaceted landscape of innovation around an existing regime, built around existing ways of working...... and developed over generations. The regime is challenged from various niches and the socio-technical landscape through trends as globalization. Three niches (Lean Construction, BIM and System Deliveries) are subject to a detailed analysis showing partly incompatible rationales and various degrees of innovation...... potential. The paper further discusses how existing policymaking operates in a number of tensions one being between government and governance. Based on the concepts from SNM the paper introduces an innovation map in order to support the development of meta-governance policymaking. By mapping some...

  2. Mapping filmmaking

    DEFF Research Database (Denmark)

    Gilje, Øystein; Frølunde, Lisbeth; Lindstrand, Fredrik

    2010-01-01

    This chapter concerns mapping patterns in regards to how young filmmakers (age 15 – 20) in the Scandinavian countries learn about filmmaking. To uncover the patterns, we present portraits of four young filmmakers who participated in the Scandinavian research project Making a filmmaker. The focus ...... is on their learning practices and how they create ‘learning paths’ in relation to resources in diverse learning contexts, whether formal, non-formal and informal contexts.......This chapter concerns mapping patterns in regards to how young filmmakers (age 15 – 20) in the Scandinavian countries learn about filmmaking. To uncover the patterns, we present portraits of four young filmmakers who participated in the Scandinavian research project Making a filmmaker. The focus...

  3. Deep diode atomic battery

    International Nuclear Information System (INIS)

    Anthony, T.R.; Cline, H.E.

    1977-01-01

    A deep diode atomic battery is made from a bulk semiconductor crystal containing three-dimensional arrays of columnar and lamellar P-N junctions. The battery is powered by gamma rays and x-ray emission from a radioactive source embedded in the interior of the semiconductor crystal

  4. Deep Learning Policy Quantization

    NARCIS (Netherlands)

    van de Wolfshaar, Jos; Wiering, Marco; Schomaker, Lambertus

    2018-01-01

    We introduce a novel type of actor-critic approach for deep reinforcement learning which is based on learning vector quantization. We replace the softmax operator of the policy with a more general and more flexible operator that is similar to the robust soft learning vector quantization algorithm.

  5. Deep-sea fungi

    Digital Repository Service at National Institute of Oceanography (India)

    Raghukumar, C; Damare, S.R.

    significant in terms of carbon sequestration (5, 8). In light of this, the diversity, abundance, and role of fungi in deep-sea sediments may form an important link in the global C biogeochemistry. This review focuses on issues related to collection...

  6. Deep inelastic scattering

    International Nuclear Information System (INIS)

    Aubert, J.J.

    1982-01-01

    Deep inelastic lepton-nucleon interaction experiments are renewed. Singlet and non-singlet structure functions are measured and the consistency of the different results is checked. A detailed analysis of the scaling violation is performed in terms of the quantum chromodynamics predictions [fr

  7. Deep Vein Thrombosis

    Centers for Disease Control (CDC) Podcasts

    2012-04-05

    This podcast discusses the risk for deep vein thrombosis in long-distance travelers and ways to minimize that risk.  Created: 4/5/2012 by National Center for Emerging and Zoonotic Infectious Diseases (NCEZID).   Date Released: 4/5/2012.

  8. Deep Learning Microscopy

    KAUST Repository

    Rivenson, Yair; Gorocs, Zoltan; Gunaydin, Harun; Zhang, Yibo; Wang, Hongda; Ozcan, Aydogan

    2017-01-01

    regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably

  9. The deep universe

    CERN Document Server

    Sandage, AR; Longair, MS

    1995-01-01

    Discusses the concept of the deep universe from two conflicting theoretical viewpoints: firstly as a theory embracing the evolution of the universe from the Big Bang to the present; and secondly through observations gleaned over the years on stars, galaxies and clusters.

  10. Teaching for Deep Learning

    Science.gov (United States)

    Smith, Tracy Wilson; Colby, Susan A.

    2007-01-01

    The authors have been engaged in research focused on students' depth of learning as well as teachers' efforts to foster deep learning. Findings from a study examining the teaching practices and student learning outcomes of sixty-four teachers in seventeen different states (Smith et al. 2005) indicated that most of the learning in these classrooms…

  11. Deep Trawl Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Otter trawl (36' Yankee and 4-seam net deepwater gear) catches from mid-Atlantic slope and canyons at 200 - 800 m depth. Deep-sea (200-800 m depth) flat otter trawls...

  12. [Deep vein thrombosis prophylaxis.

    Science.gov (United States)

    Sandoval-Chagoya, Gloria Alejandra; Laniado-Laborín, Rafael

    2013-01-01

    Background: despite the proven effectiveness of preventive therapy for deep vein thrombosis, a significant proportion of patients at risk for thromboembolism do not receive prophylaxis during hospitalization. Our objective was to determine the adherence to thrombosis prophylaxis guidelines in a general hospital as a quality control strategy. Methods: a random audit of clinical charts was conducted at the Tijuana General Hospital, Baja California, Mexico, to determine the degree of adherence to deep vein thrombosis prophylaxis guidelines. The instrument used was the Caprini's checklist for thrombosis risk assessment in adult patients. Results: the sample included 300 patient charts; 182 (60.7 %) were surgical patients and 118 were medical patients. Forty six patients (15.3 %) received deep vein thrombosis pharmacologic prophylaxis; 27.1 % of medical patients received deep vein thrombosis prophylaxis versus 8.3 % of surgical patients (p < 0.0001). Conclusions: our results show that adherence to DVT prophylaxis at our hospital is extremely low. Only 15.3 % of our patients at risk received treatment, and even patients with very high risk received treatment in less than 25 % of the cases. We have implemented strategies to increase compliance with clinical guidelines.

  13. Probabilistic mapping of deep brain stimulation effects in essential tremor

    Directory of Open Access Journals (Sweden)

    Till A Dembek

    2017-01-01

    Discussion: Our results support the assumption, that the ZI might be a very effective target for tremor suppression. However stimulation inside the ZI and in its close vicinity was also related to the occurrence of stimulation-induced side-effects, so it remains unclear whether the VIM or the ZI is the overall better target. The study demonstrates the use of PSMs for target selection and evaluation. While their accuracy has to be carefully discussed, they can improve the understanding of DBS effects and can be of use for other DBS targets in the therapy of neurological or psychiatric disorders as well. Furthermore they provide a priori information about expected DBS effects in a certain region and might be helpful to clinicians in programming DBS devices in the future.

  14. Reionization Models Classifier using 21cm Map Deep Learning

    Science.gov (United States)

    Hassan, Sultan; Liu, Adrian; Kohn, Saul; Aguirre, James E.; La Plante, Paul; Lidz, Adam

    2018-05-01

    Next-generation 21cm observations will enable imaging of reionization on very large scales. These images will contain more astrophysical and cosmological information than the power spectrum, and hence providing an alternative way to constrain the contribution of different reionizing sources populations to cosmic reionization. Using Convolutional Neural Networks, we present a simple network architecture that is sufficient to discriminate between Galaxy-dominated versus AGN-dominated models, even in the presence of simulated noise from different experiments such as the HERA and SKA.

  15. Deep Mapping of Teuthivorous Whales and Their Prey Fields

    Science.gov (United States)

    2016-01-01

    components of this effort including Chad Waluk, David O’Gorman, Ian Robbins, John Calambokidas, Ari Friedlander, Peter Tyack, Patricia Arranz, and David...acoustic testing strand whales? Nature 392:29 Jochens AD, Biggs DC, Benoit-Bird KJ, Engelhaupt D, Gordon J, Hu C, Jaquet N, Johnson MP, Leben RR, Mate BR

  16. Mapping Resilience

    DEFF Research Database (Denmark)

    Carruth, Susan

    2015-01-01

    by planners when aiming to construct resilient energy plans. It concludes that a graphical language has the potential to be a significant tool, flexibly facilitating cross-disciplinary communication and decision-making, while emphasising that its role is to support imaginative, resilient planning rather than...... the relationship between resilience and energy planning, suggesting that planning in, and with, time is a core necessity in this domain. It then reviews four examples of graphically mapping with time, highlighting some of the key challenges, before tentatively proposing a graphical language to be employed...

  17. Deep inelastic scattering

    International Nuclear Information System (INIS)

    Zakharov, V.I.

    1977-01-01

    The present status of the quark-parton-gluon picture of deep inelastic scattering is reviewed. The general framework is mostly theoretical and covers investigations since 1970. Predictions of the parton model and of the asymptotically free field theories are compared with experimental data available. The valence quark approximation is concluded to be valid in most cases, but fails to account for the data on the total momentum transfer. On the basis of gluon corrections introduced to the parton model certain predictions concerning both the deep inelastic structure functions and form factors are made. The contributions of gluon exchanges and gluon bremsstrahlung are highlighted. Asymptotic freedom is concluded to be very attractive and provide qualitative explanation to some experimental observations (scaling violations, breaking of the Drell-Yan-West type relations). Lepton-nuclear scattering is pointed out to be helpful in probing the nature of nuclear forces and studying the space-time picture of the parton model

  18. Deep Energy Retrofit

    DEFF Research Database (Denmark)

    Zhivov, Alexander; Lohse, Rüdiger; Rose, Jørgen

    Deep Energy Retrofit – A Guide to Achieving Significant Energy User Reduction with Major Renovation Projects contains recommendations for characteristics of some of core technologies and measures that are based on studies conducted by national teams associated with the International Energy Agency...... Energy Conservation in Buildings and Communities Program (IEA-EBC) Annex 61 (Lohse et al. 2016, Case, et al. 2016, Rose et al. 2016, Yao, et al. 2016, Dake 2014, Stankevica et al. 2016, Kiatreungwattana 2014). Results of these studies provided a base for setting minimum requirements to the building...... envelope-related technologies to make Deep Energy Retrofit feasible and, in many situations, cost effective. Use of energy efficiency measures (EEMs) in addition to core technologies bundle and high-efficiency appliances will foster further energy use reduction. This Guide also provides best practice...

  19. Deep groundwater chemistry

    International Nuclear Information System (INIS)

    Wikberg, P.; Axelsen, K.; Fredlund, F.

    1987-06-01

    Starting in 1977 and up till now a number of places in Sweden have been investigated in order to collect the necessary geological, hydrogeological and chemical data needed for safety analyses of repositories in deep bedrock systems. Only crystalline rock is considered and in many cases this has been gneisses of sedimentary origin but granites and gabbros are also represented. Core drilled holes have been made at nine sites. Up to 15 holes may be core drilled at one site, the deepest down to 1000 m. In addition to this a number of boreholes are percussion drilled at each site to depths of about 100 m. When possible drilling water is taken from percussion drilled holes. The first objective is to survey the hydraulic conditions. Core drilled boreholes and sections selected for sampling of deep groundwater are summarized. (orig./HP)

  20. Mapping of

    Directory of Open Access Journals (Sweden)

    Sayed M. Arafat

    2014-06-01

    Full Text Available Land cover map of North Sinai was produced based on the FAO-Land Cover Classification System (LCCS of 2004. The standard FAO classification scheme provides a standardized system of classification that can be used to analyze spatial and temporal land cover variability in the study area. This approach also has the advantage of facilitating the integration of Sinai land cover mapping products to be included with the regional and global land cover datasets. The total study area is covering a total area of 20,310.4 km2 (203,104 hectare. The landscape classification was based on SPOT4 data acquired in 2011 using combined multispectral bands of 20 m spatial resolution. Geographic Information System (GIS was used to manipulate the attributed layers of classification in order to reach the maximum possible accuracy. GIS was also used to include all necessary information. The identified vegetative land cover classes of the study area are irrigated herbaceous crops, irrigated tree crops and rain fed tree crops. The non-vegetated land covers in the study area include bare rock, bare soils (stony, very stony and salt crusts, loose and shifting sands and sand dunes. The water bodies were classified as artificial perennial water bodies (fish ponds and irrigated canals and natural perennial water bodies as lakes (standing. The artificial surfaces include linear and non-linear features.

  1. Deep Reinforcement Fuzzing

    OpenAIRE

    Böttinger, Konstantin; Godefroid, Patrice; Singh, Rishabh

    2018-01-01

    Fuzzing is the process of finding security vulnerabilities in input-processing code by repeatedly testing the code with modified inputs. In this paper, we formalize fuzzing as a reinforcement learning problem using the concept of Markov decision processes. This in turn allows us to apply state-of-the-art deep Q-learning algorithms that optimize rewards, which we define from runtime properties of the program under test. By observing the rewards caused by mutating with a specific set of actions...

  2. Deep Visual Attention Prediction

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing

    2018-05-01

    In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

  3. DeepCotton: in-field cotton segmentation using deep fully convolutional network

    Science.gov (United States)

    Li, Yanan; Cao, Zhiguo; Xiao, Yang; Cremers, Armin B.

    2017-09-01

    Automatic ground-based in-field cotton (IFC) segmentation is a challenging task in precision agriculture, which has not been well addressed. Nearly all the existing methods rely on hand-crafted features. Their limited discriminative power results in unsatisfactory performance. To address this, a coarse-to-fine cotton segmentation method termed "DeepCotton" is proposed. It contains two modules, fully convolutional network (FCN) stream and interference region removal stream. First, FCN is employed to predict initially coarse map in an end-to-end manner. The convolutional networks involved in FCN guarantee powerful feature description capability, simultaneously, the regression analysis ability of neural network assures segmentation accuracy. To our knowledge, we are the first to introduce deep learning to IFC segmentation. Second, our proposed "UP" algorithm composed of unary brightness transformation and pairwise region comparison is used for obtaining interference map, which is executed to refine the coarse map. The experiments on constructed IFC dataset demonstrate that our method outperforms other state-of-the-art approaches, either in different common scenarios or single/multiple plants. More remarkable, the "UP" algorithm greatly improves the property of the coarse result, with the average amplifications of 2.6%, 2.4% on accuracy and 8.1%, 5.5% on intersection over union for common scenarios and multiple plants, separately.

  4. Deep Convolutional Generative Adversarial Network for Procedural 3D Landscape Generation Based on DEM

    OpenAIRE

    Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig; Billeskov, Jonas Aksel

    2018-01-01

    This paper proposes a novel framework for improving procedural generation of 3D landscapes using machine learning. We utilized a Deep Convolutional Generative Adversarial Network (DC-GAN) to generate heightmaps. The network was trained on a dataset consisting of Digital Elevation Maps (DEM) of the alps. During map generation, the batch size and learning rate were optimized for the most efficient and satisfying map production. The diversity of the final output was tested against Perlin noise u...

  5. Assessing Deep Sea Communities Through Seabed Imagery

    Science.gov (United States)

    Matkin, A. G.; Cross, K.; Milititsky, M.

    2016-02-01

    The deep sea still remains virtually unexplored. Human activity, such as oil and gas exploration and deep sea mining, is expanding further into the deep sea, increasing the need to survey and map extensive areas of this habitat in order to assess ecosystem health and value. The technology needed to explore this remote environment has been advancing. Seabed imagery can cover extensive areas of the seafloor and investigate areas where sampling with traditional coring methodologies is just not possible (e.g. cold water coral reefs). Remotely operated vehicles (ROVs) are an expensive option, so drop or towed camera systems can provide a more viable and affordable alternative, while still allowing for real-time control. Assessment of seabed imagery in terms of presence, abundance and density of particular species can be conducted by bringing together a variety of analytical tools for a holistic approach. Sixteen deep sea transects located offshore West Africa were investigated with a towed digital video telemetry system (DTS). Both digital stills and video footage were acquired. An extensive data set was obtained from over 13,000 usable photographs, allowing for characterisation of the different habitats present in terms of community composition and abundance. All observed fauna were identified to the lowest taxonomic level and enumerated when possible, with densities derived after the seabed area was calculated for each suitable photograph. This methodology allowed for consistent assessment of the different habitat types present, overcoming constraints, such as specific taxa that cannot be enumerated, such as sponges, corals or bryozoans, the presence of mobile and sessile species, or the level of taxonomic detail. Although this methodology will not enable a full characterisation of a deep sea community, in terms of species composition for instance, itt will allow a robust assessment of large areas of the deep sea in terms of sensitive habitats present and community

  6. Deep Red (Profondo Rosso)

    CERN Multimedia

    Cine Club

    2015-01-01

    Wednesday 29 April 2015 at 20:00 CERN Council Chamber    Deep Red (Profondo Rosso) Directed by Dario Argento (Italy, 1975) 126 minutes A psychic who can read minds picks up the thoughts of a murderer in the audience and soon becomes a victim. An English pianist gets involved in solving the murders, but finds many of his avenues of inquiry cut off by new murders, and he begins to wonder how the murderer can track his movements so closely. Original version Italian; English subtitles

  7. Reversible deep disposal

    International Nuclear Information System (INIS)

    2009-10-01

    This presentation, given by the national agency of radioactive waste management (ANDRA) at the meeting of October 8, 2009 of the high committee for the nuclear safety transparency and information (HCTISN), describes the concept of deep reversible disposal for high level/long living radioactive wastes, as considered by the ANDRA in the framework of the program law of June 28, 2006 about the sustainable management of radioactive materials and wastes. The document presents the social and political reasons of reversibility, the technical means considered (containers, disposal cavities, monitoring system, test facilities and industrial prototypes), the decisional process (progressive development and blocked off of the facility, public information and debate). (J.S.)

  8. Deep inelastic neutron scattering

    International Nuclear Information System (INIS)

    Mayers, J.

    1989-03-01

    The report is based on an invited talk given at a conference on ''Neutron Scattering at ISIS: Recent Highlights in Condensed Matter Research'', which was held in Rome, 1988, and is intended as an introduction to the techniques of Deep Inelastic Neutron Scattering. The subject is discussed under the following topic headings:- the impulse approximation I.A., scaling behaviour, kinematical consequences of energy and momentum conservation, examples of measurements, derivation of the I.A., the I.A. in a harmonic system, and validity of the I.A. in neutron scattering. (U.K.)

  9. [Deep mycoses rarely described].

    Science.gov (United States)

    Charles, D

    1986-01-01

    Beside deep mycoses very well known: histoplasmosis, candidosis, cryptococcosis, there are other mycoses less frequently described. Some of them are endemic in some countries: South American blastomycosis in Brazil, coccidioidomycosis in California; some others are cosmopolitan and may affect everyone: sporotrichosis, or may affect only immunodeficient persons: mucormycosis. They do not spare Africa, we may encounter basidiobolomycosis, rhinophycomycosis, dermatophytosis, sporotrichosis and, more recently reported, rhinosporidiosis. Important therapeutic progresses have been accomplished with amphotericin B and with antifungus imidazole compounds (miconazole and ketoconazole). Surgical intervention is sometime recommended in chromomycosis and rhinosporidiosis.

  10. Deep penetration calculations

    International Nuclear Information System (INIS)

    Thompson, W.L.; Deutsch, O.L.; Booth, T.E.

    1980-04-01

    Several Monte Carlo techniques are compared in the transport of neutrons of different source energies through two different deep-penetration problems each with two parts. The first problem involves transmission through a 200-cm concrete slab. The second problem is a 90 0 bent pipe jacketed by concrete. In one case the pipe is void, and in the other it is filled with liquid sodium. Calculations are made with two different Los Alamos Monte Carlo codes: the continuous-energy code MCNP and the multigroup code MCMG

  11. Star Maps History, Artistry, and Cartography

    CERN Document Server

    Kanas, Nick

    2012-01-01

    Star Maps captures the beauty and awe of the heavens through celestial prints and star atlases. It traces the history of celestial cartography and relates this history to the changing ideas of humanity's place in the universe. The text of this Second Edition is enriched with 263 photographs, 91 in color, showing images from actual antiquarian celestial books and atlases, each one with an explanation of its astronomical and cartographic features. This new edition of Star Maps: History, Artistry, and Cartography includes: - over 50 new pages of text and 44 new images (16 in color) - completely new sections on celestial frontispieces, deep-sky objects, playing card maps, additional cartographers, and modern computerized star maps - updated figures and text about celestial globes, volvelles, telescopes, and planets and asteroids - revised and updated text and illustrations throughout. The book focuses on the development of celestial cartography from ancient to modern times and describes the relationships between ...

  12. Deep Super Learner: A Deep Ensemble for Classification Problems

    OpenAIRE

    Young, Steven; Abdou, Tamer; Bener, Ayse

    2018-01-01

    Deep learning has become very popular for tasks such as predictive modeling and pattern recognition in handling big data. Deep learning is a powerful machine learning method that extracts lower level features and feeds them forward for the next layer to identify higher level features that improve performance. However, deep neural networks have drawbacks, which include many hyper-parameters and infinite architectures, opaqueness into results, and relatively slower convergence on smaller datase...

  13. Deep sea biophysics

    International Nuclear Information System (INIS)

    Yayanos, A.A.

    1982-01-01

    A collection of deep-sea bacterial cultures was completed. Procedures were instituted to shelter the culture collection from accidential warming. A substantial data base on the rates of reproduction of more than 100 strains of bacteria from that collection was obtained from experiments and the analysis of that data was begun. The data on the rates of reproduction were obtained under conditions of temperature and pressure found in the deep sea. The experiments were facilitated by inexpensively fabricated pressure vessels, by the streamlining of the methods for the study of kinetics at high pressures, and by computer-assisted methods. A polybarothermostat was used to study the growth of bacteria along temperature gradients at eight distinct pressures. This device should allow for the study of microbial processes in the temperature field simulating the environment around buried HLW. It is small enough to allow placement in a radiation field in future studies. A flow fluorocytometer was fabricated. This device will be used to determine the DNA content per cell in bacteria grown in laboratory culture and in microorganisms in samples from the ocean. The technique will be tested for its rapidity in determining the concentration of cells (standing stock of microorganisms) in samples from the ocean

  14. Deep Learning in Radiology.

    Science.gov (United States)

    McBee, Morgan P; Awan, Omer A; Colucci, Andrew T; Ghobadi, Comeron W; Kadom, Nadja; Kansagra, Akash P; Tridandapani, Srini; Auffermann, William F

    2018-03-29

    As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  15. Deep Learning Microscopy

    KAUST Repository

    Rivenson, Yair

    2017-05-12

    We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably better resolution, matching the performance of higher numerical aperture lenses, also significantly surpassing their limited field-of-view and depth-of-field. These results are transformative for various fields that use microscopy tools, including e.g., life sciences, where optical microscopy is considered as one of the most widely used and deployed techniques. Beyond such applications, our presented approach is broadly applicable to other imaging modalities, also spanning different parts of the electromagnetic spectrum, and can be used to design computational imagers that get better and better as they continue to image specimen and establish new transformations among different modes of imaging.

  16. Deep Transfer Metric Learning.

    Science.gov (United States)

    Junlin Hu; Jiwen Lu; Yap-Peng Tan; Jie Zhou

    2016-12-01

    Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption does not hold in many real visual recognition applications, especially when samples are captured across different data sets. In this paper, we propose a new deep transfer metric learning (DTML) method to learn a set of hierarchical nonlinear transformations for cross-domain visual recognition by transferring discriminative knowledge from the labeled source domain to the unlabeled target domain. Specifically, our DTML learns a deep metric network by maximizing the inter-class variations and minimizing the intra-class variations, and minimizing the distribution divergence between the source domain and the target domain at the top layer of the network. To better exploit the discriminative information from the source domain, we further develop a deeply supervised transfer metric learning (DSTML) method by including an additional objective on DTML, where the output of both the hidden layers and the top layer are optimized jointly. To preserve the local manifold of input data points in the metric space, we present two new methods, DTML with autoencoder regularization and DSTML with autoencoder regularization. Experimental results on face verification, person re-identification, and handwritten digit recognition validate the effectiveness of the proposed methods.

  17. Deep Reading and Learning

    Science.gov (United States)

    2017-10-01

    structured prediction. In search-based structured prediction, this mapping is constructed incrementally via heuristic search. We adapted several variations ...bad decision ( Goldberg and Elhadad 2010). We call this approach best good vs. best bad (BGBB). One problem with this update is that it ignores the...and Abelson, 1977). Scripts capture a stereotypical sequence of events that typically occur in a given context while allowing for variations . There

  18. MAPPING THE UNIVERSE: THE 2010 RUSSELL LECTURE

    International Nuclear Information System (INIS)

    Geller, Margaret J.; Kurtz, Michael J.; Diaferio, Antonaldo

    2011-01-01

    Redshift surveys are a powerful tool of modern cosmology. We discuss two aspects of their power to map the distribution of mass and light in the universe: (1) measuring the mass distribution extending into the infall regions of rich clusters and (2) applying deep redshift surveys to the selection of clusters of galaxies and to the identification of very large structures (Great Walls). We preview the HectoMAP project, a redshift survey with median redshift z = 0.34 covering 50 deg 2 to r = 21. We emphasize the importance and power of spectroscopy for exploring and understanding the nature and evolution of structure in the universe.

  19. Human Mind Maps

    Science.gov (United States)

    Glass, Tom

    2016-01-01

    When students generate mind maps, or concept maps, the maps are usually on paper, computer screens, or a blackboard. Human Mind Maps require few resources and little preparation. The main requirements are space where students can move around and a little creativity and imagination. Mind maps can be used for a variety of purposes, and Human Mind…

  20. Deep Reinforcement Learning: An Overview

    OpenAIRE

    Li, Yuxi

    2017-01-01

    We give an overview of recent exciting achievements of deep reinforcement learning (RL). We discuss six core elements, six important mechanisms, and twelve applications. We start with background of machine learning, deep learning and reinforcement learning. Next we discuss core RL elements, including value function, in particular, Deep Q-Network (DQN), policy, reward, model, planning, and exploration. After that, we discuss important mechanisms for RL, including attention and memory, unsuperv...

  1. Deep Feature Consistent Variational Autoencoder

    OpenAIRE

    Hou, Xianxu; Shen, Linlin; Sun, Ke; Qiu, Guoping

    2016-01-01

    We present a novel method for constructing Variational Autoencoder (VAE). Instead of using pixel-by-pixel loss, we enforce deep feature consistency between the input and the output of a VAE, which ensures the VAE's output to preserve the spatial correlation characteristics of the input, thus leading the output to have a more natural visual appearance and better perceptual quality. Based on recent deep learning works such as style transfer, we employ a pre-trained deep convolutional neural net...

  2. Deep learning for image classification

    Science.gov (United States)

    McCoppin, Ryan; Rizki, Mateen

    2014-06-01

    This paper provides an overview of deep learning and introduces the several subfields of deep learning including a specific tutorial of convolutional neural networks. Traditional methods for learning image features are compared to deep learning techniques. In addition, we present our preliminary classification results, our basic implementation of a convolutional restricted Boltzmann machine on the Mixed National Institute of Standards and Technology database (MNIST), and we explain how to use deep learning networks to assist in our development of a robust gender classification system.

  3. Learning Multimodal Deep Representations for Crowd Anomaly Event Detection

    Directory of Open Access Journals (Sweden)

    Shaonian Huang

    2018-01-01

    Full Text Available Anomaly event detection in crowd scenes is extremely important; however, the majority of existing studies merely use hand-crafted features to detect anomalies. In this study, a novel unsupervised deep learning framework is proposed to detect anomaly events in crowded scenes. Specifically, low-level visual features, energy features, and motion map features are simultaneously extracted based on spatiotemporal energy measurements. Three convolutional restricted Boltzmann machines are trained to model the mid-level feature representation of normal patterns. Then a multimodal fusion scheme is utilized to learn the deep representation of crowd patterns. Based on the learned deep representation, a one-class support vector machine model is used to detect anomaly events. The proposed method is evaluated using two available public datasets and compared with state-of-the-art methods. The experimental results show its competitive performance for anomaly event detection in video surveillance.

  4. A major QTL controlling deep rooting on rice chromosome 4.

    Science.gov (United States)

    Uga, Yusaku; Yamamoto, Eiji; Kanno, Noriko; Kawai, Sawako; Mizubayashi, Tatsumi; Fukuoka, Shuichi

    2013-10-24

    Drought is the most serious abiotic stress that hinders rice production under rainfed conditions. Breeding for deep rooting is a promising strategy to improve the root system architecture in shallow-rooting rice cultivars to avoid drought stress. We analysed the quantitative trait loci (QTLs) for the ratio of deep rooting (RDR) in three F₂ mapping populations derived from crosses between each of three shallow-rooting varieties ('ARC5955', 'Pinulupot1', and 'Tupa729') and a deep-rooting variety, 'Kinandang Patong'. In total, we detected five RDR QTLs on chromosomes 2, 4, and 6. In all three populations, QTLs on chromosome 4 were found to be located at similar positions; they explained from 32.0% to 56.6% of the total RDR phenotypic variance. This suggests that one or more key genetic factors controlling the root growth angle in rice is located in this region of chromosome 4.

  5. Maps & minds : mapping through the ages

    Science.gov (United States)

    ,

    1984-01-01

    Throughout time, maps have expressed our understanding of our world. Human affairs have been influenced strongly by the quality of maps available to us at the major turning points in our history. "Maps & Minds" traces the ebb and flow of a few central ideas in the mainstream of mapping. Our expanding knowledge of our cosmic neighborhood stems largely from a small number of simple but grand ideas, vigorously pursued.

  6. Fund Finder: A case study of database-to-ontology mapping

    OpenAIRE

    Barrasa Rodríguez, Jesús; Corcho, Oscar; Gómez-Pérez, A.

    2003-01-01

    The mapping between databases and ontologies is a basic problem when trying to "upgrade" deep web content to the semantic web. Our approach suggests the declarative definition of mappings as a way to achieve domain independency and reusability. A specific language (expressive enough to cover some real world mapping situations like lightly structured databases or not 1st normal form ones) is defined for this purpose. Along with this mapping description language, the ODEMapster processor is in ...

  7. Lunar Map Catalog

    Data.gov (United States)

    National Aeronautics and Space Administration — The Lunar Map Catalog includes various maps of the moon's surface, including Apollo landing sites; earthside, farside, and polar charts; photography index maps; zone...

  8. Baby Brain Map

    Science.gov (United States)

    ... a Member Home Resources & Services Professional Resource Baby Brain Map Mar 17, 2016 The Brain Map was adapted in 2006 by ZERO TO ... supports Adobe Flash Player. To view the Baby Brain Map, please visit this page on a browser ...

  9. Snapshots for Semantic Maps

    National Research Council Canada - National Science Library

    Nielsen, Curtis W; Ricks, Bob; Goodrich, Michael A; Bruemmer, David; Few, Doug; Walton, Miles

    2004-01-01

    .... Semantic maps are a relatively new approach to information presentation. Semantic maps provide more detail about an environment than typical maps because they are augmented by icons or symbols that provide meaning for places or objects of interest...

  10. Deep learning? What deep learning? | Fourie | South African ...

    African Journals Online (AJOL)

    In teaching generally over the past twenty years, there has been a move towards teaching methods that encourage deep, rather than surface approaches to learning. The reason for this being that students, who adopt a deep approach to learning are considered to have learning outcomes of a better quality and desirability ...

  11. Deep sea radionuclides

    International Nuclear Information System (INIS)

    Kanisch, G.; Vobach, M.

    1993-01-01

    Every year since 1979, either in sping or in summer, the fishing research vessel 'Walther Herwig' goes to the North Atlantic disposal areas of solid radioactive wastes, and, for comparative purposes, to other areas, in order to collect water samples, plankton and nekton, and, from the deep sea bed, sediment samples and benthos organisms. In addition to data on the radionuclide contents of various media, information about the plankton, nekton and benthos organisms living in those areas and about their biomasses could be gathered. The investigations are aimed at acquiring scientifically founded knowledge of the uptake of radioactive substances by microorganisms, and their migration from the sea bottom to the areas used by man. (orig.) [de

  12. Deep inelastic phenomena

    International Nuclear Information System (INIS)

    Aubert, J.J.

    1982-01-01

    The experimental situation of the deep inelastic scattering for electrons (muons) is reviewed. A brief history of experimentation highlights Mohr and Nicoll's 1932 experiment on electron-atom scattering and Hofstadter's 1950 experiment on electron-nucleus scattering. The phenomenology of electron-nucleon scattering carried out between 1960 and 1970 is described, with emphasis on the parton model, and scaling. Experiments at SLAC and FNAL since 1974 exhibit scaling violations. Three muon-nucleon scattering experiments at BFP, BCDMA, and EMA, currently producing new results in the high Q 2 domain suggest a rather flat behaviour of the structure function at fixed x as a function of Q 2 . It is seen that the structure measured in DIS can then be projected into a pure hadronic process to predict a cross section. Protonneutron difference, moment analysis, and Drell-Yan pairs are also considered

  13. Okeanos Explorer (EX1705): American Samoa, Kingman/Palmyra, Jarvis (ROV & Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will include the use of the ship's deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, Knudsen 3260 chirp...

  14. Okeanos Explorer (EX1703): Howland/Baker PRIMNM and PIPA (ROV/Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will include the use of the ship's deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, Knudsen 3260 chirp...

  15. Context and Deep Learning Design

    Science.gov (United States)

    Boyle, Tom; Ravenscroft, Andrew

    2012-01-01

    Conceptual clarification is essential if we are to establish a stable and deep discipline of technology enhanced learning. The technology is alluring; this can distract from deep design in a surface rush to exploit the affordances of the new technology. We need a basis for design, and a conceptual unit of organization, that are applicable across…

  16. Determinants of iron accumulation in deep grey matter of multiple sclerosis patients

    DEFF Research Database (Denmark)

    Ropele, Stefan; Kilsdonk, Iris D; Wattjes, Mike P

    2014-01-01

    BACKGROUND: Iron accumulation in deep grey matter (GM) structures is a consistent finding in multiple sclerosis (MS) patients. This study focused on the identification of independent determinants of iron accumulation using R2* mapping. SUBJECTS AND METHODS: Ninety-seven MS patients and 81 healthy...... controls were included in this multicentre study. R2* mapping was performed on 3T MRI systems. R2*in deep GM was corrected for age and was related to disease duration, disability, T2 lesion load and brain volume. RESULTS: Compared to controls, R2* was increased in all deep GM regions of MS patients except...... and the red nucleus. In lesions, R2* was inversely correlated with disease duration and higher total lesion load. CONCLUSION: Iron accumulation in deep GM of MS patients is most strongly and independently associated with duration and severity of the disease. Additional associations between cortical GM atrophy...

  17. Anisotropy in the deep Earth

    Science.gov (United States)

    Romanowicz, Barbara; Wenk, Hans-Rudolf

    2017-08-01

    Seismic anisotropy has been found in many regions of the Earth's interior. Its presence in the Earth's crust has been known since the 19th century, and is due in part to the alignment of anisotropic crystals in rocks, and in part to patterns in the distribution of fractures and pores. In the upper mantle, seismic anisotropy was discovered 50 years ago, and can be attributed for the most part, to the alignment of intrinsically anisotropic olivine crystals during large scale deformation associated with convection. There is some indication for anisotropy in the transition zone, particularly in the vicinity of subducted slabs. Here we focus on the deep Earth - the lower mantle and core, where anisotropy is not yet mapped in detail, nor is there consensus on its origin. Most of the lower mantle appears largely isotropic, except in the last 200-300 km, in the D″ region, where evidence for seismic anisotropy has been accumulating since the late 1980s, mostly from shear wave splitting measurements. Recently, a picture has been emerging, where strong anisotropy is associated with high shear velocities at the edges of the large low shear velocity provinces (LLSVPs) in the central Pacific and under Africa. These observations are consistent with being due to the presence of highly anisotropic MgSiO3 post-perovskite crystals, aligned during the deformation of slabs impinging on the core-mantle boundary, and upwelling flow within the LLSVPs. We also discuss mineral physics aspects such as ultrahigh pressure deformation experiments, first principles calculations to obtain information about elastic properties, and derivation of dislocation activity based on bonding characteristics. Polycrystal plasticity simulations can predict anisotropy but models are still highly idealized and neglect the complex microstructure of polyphase aggregates with strong and weak components. A promising direction for future progress in understanding the origin of seismic anisotropy in the deep mantle

  18. Workshop on ROVs and deep submergence

    Science.gov (United States)

    The deep-submergence community has an opportunity on March 6 to participate in a unique teleconferencing demonstration of a state-of-the-art, remotely operated underwater research vehicle known as the Jason-Medea System. Jason-Medea has been developed over the past decade by scientists, engineers, and technicians at the Deep Submergence Laboratory at Woods Hole Oceanographic Institution. The U.S. Navy, the Office of the Chief of Naval Research, and the National Science Foundation are sponsoring the workshop to explore the roles that modern computational, communications, and robotics technologies can play in deep-sea oceanographic research.Through the cooperation of Electronic Data Systems, Inc., the Jason Foundation, and Turner Broadcasting System, Inc., 2-1/2 hours of air time will be available from 3:00 to 5:30 PM EST on March 6. Twenty-seven satellite downlink sites will link one operating research vessel and the land-based operation with workshop participants in the United States, Canada, the United Kingdom, and Bermuda. The research ship Laney Chouest will be in the midst of a 3-week educational/research program in the Sea of Cortez, between Baja California and mainland Mexico. This effort is focused on active hydrothermal vents driven by heat flow from the volcanically active East Pacific Rise, which underlies the sediment-covered Guaymas Basin. The project combines into a single-operation, newly-developed robotic systems, state-of-the-art mapping and sampling tools, fiber-optic data transmission from the seafloor, instantaneous satellite communication from ship to shore, and a sophisticated array of computational and telecommunications networks. During the workshop, land-based scientists will observe and participate directly with their seagoing colleagues as they conduct seafloor research.

  19. Quantification of deep medullary veins at 7 T brain MRI

    Energy Technology Data Exchange (ETDEWEB)

    Kuijf, Hugo J.; Viergever, Max A.; Vincken, Koen L. [University Medical Center Utrecht, Image Sciences Institute, Utrecht (Netherlands); Bouvy, Willem H.; Razoux Schultz, Tom B.; Biessels, Geert Jan [University Medical Center Utrecht, Department of Neurology, Brain Center Rudolf Magnus, Utrecht (Netherlands); Zwanenburg, Jaco J.M. [University Medical Center Utrecht, Image Sciences Institute, Utrecht (Netherlands); University Medical Center Utrecht, Department of Radiology, Utrecht (Netherlands)

    2016-10-15

    Deep medullary veins support the venous drainage of the brain and may display abnormalities in the context of different cerebrovascular diseases. We present and evaluate a method to automatically detect and quantify deep medullary veins at 7 T. Five participants were scanned twice, to assess the robustness and reproducibility of manual and automated vein detection. Additionally, the method was evaluated on 24 participants to demonstrate its application. Deep medullary veins were assessed within an automatically created region-of-interest around the lateral ventricles, defined such that all veins must intersect it. A combination of vesselness, tubular tracking, and hysteresis thresholding located individual veins, which were quantified by counting and computing (3-D) density maps. Visual assessment was time-consuming (2 h/scan), with an intra-/inter-observer agreement on absolute vein count of ICC = 0.76 and 0.60, respectively. The automated vein detection showed excellent inter-scan reproducibility before (ICC = 0.79) and after (ICC = 0.88) visually censoring false positives. It had a positive predictive value of 71.6 %. Imaging at 7 T allows visualization and quantification of deep medullary veins. The presented method offers fast and reliable automated assessment of deep medullary veins. (orig.)

  20. Mapping the Heart

    Science.gov (United States)

    Hulse, Grace

    2012-01-01

    In this article, the author describes how her fourth graders made ceramic heart maps. The impetus for this project came from reading "My Map Book" by Sara Fanelli. This book is a collection of quirky, hand-drawn and collaged maps that diagram a child's world. There are maps of her stomach, her day, her family, and her heart, among others. The…

  1. Deep Learning Fluid Mechanics

    Science.gov (United States)

    Barati Farimani, Amir; Gomes, Joseph; Pande, Vijay

    2017-11-01

    We have developed a new data-driven model paradigm for the rapid inference and solution of the constitutive equations of fluid mechanic by deep learning models. Using generative adversarial networks (GAN), we train models for the direct generation of solutions to steady state heat conduction and incompressible fluid flow without knowledge of the underlying governing equations. Rather than using artificial neural networks to approximate the solution of the constitutive equations, GANs can directly generate the solutions to these equations conditional upon an arbitrary set of boundary conditions. Both models predict temperature, velocity and pressure fields with great test accuracy (>99.5%). The application of our framework for inferring and generating the solutions of partial differential equations can be applied to any physical phenomena and can be used to learn directly from experiments where the underlying physical model is complex or unknown. We also have shown that our framework can be used to couple multiple physics simultaneously, making it amenable to tackle multi-physics problems.

  2. Deep video deblurring

    KAUST Repository

    Su, Shuochen

    2016-11-25

    Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on aligning nearby frames. However, aligning images is a computationally expensive and fragile procedure, and methods that aggregate information must therefore be able to identify which regions have been accurately aligned and which have not, a task which requires high level scene understanding. In this work, we introduce a deep learning solution to video deblurring, where a CNN is trained end-to-end to learn how to accumulate information across frames. To train this network, we collected a dataset of real videos recorded with a high framerate camera, which we use to generate synthetic motion blur for supervision. We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baselines.

  3. Deep space telescopes

    CERN Multimedia

    CERN. Geneva

    2006-01-01

    The short series of seminars will address results and aims of current and future space astrophysics as the cultural framework for the development of deep space telescopes. It will then present such new tools, as they are currently available to, or imagined by, the scientific community, in the context of the science plans of ESA and of all major world space agencies. Ground-based astronomy, in the 400 years since Galileo’s telescope, has given us a profound phenomenological comprehension of our Universe, but has traditionally been limited to the narrow band(s) to which our terrestrial atmosphere is transparent. Celestial objects, however, do not care about our limitations, and distribute most of the information about their physics throughout the complete electromagnetic spectrum. Such information is there for the taking, from millimiter wavelengths to gamma rays. Forty years astronomy from space, covering now most of the e.m. spectrum, have thus given us a better understanding of our physical Universe then t...

  4. Deep inelastic final states

    International Nuclear Information System (INIS)

    Girardi, G.

    1980-11-01

    In these lectures we attempt to describe the final states of deep inelastic scattering as given by QCD. In the first section we shall briefly comment on the parton model and give the main properties of decay functions which are of interest for the study of semi-inclusive leptoproduction. The second section is devoted to the QCD approach to single hadron leptoproduction. First we recall basic facts on QCD log's and derive after that the evolution equations for the fragmentation functions. For this purpose we make a short detour in e + e - annihilation. The rest of the section is a study of the factorization of long distance effects associated with the initial and final states. We then show how when one includes next to leading QCD corrections one induces factorization breaking and describe the double moments useful for testing such effects. The next section contains a review on the QCD jets in the hadronic final state. We begin by introducing the notion of infrared safe variable and defining a few useful examples. Distributions in these variables are studied to first order in QCD, with some comments on the resummation of logs encountered in higher orders. Finally the last section is a 'gaullimaufry' of jet studies

  5. USGS Map Indices Overlay Map Service from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The USGS Map Indices service from The National Map (TNM) consists of 1x1 Degree, 30x60 Minute (100K), 15 Minute (63K), 7.5 Minute (24K), and 3.75 Minute grid...

  6. 7. Annex II: Maps

    OpenAIRE

    Aeberli, Annina

    2012-01-01

    Map 1: States of South Sudan UN OCHA (2012) Republic of South Sudan – States, as of 15 July 2012, Reliefweb http://reliefweb.int/map/south-sudan-republic/republic-south-sudan-states-15-july-2012-reference-map, accessed 31 July 2012. Map 2: Counties of South Sudan UN OCHA (2012) Republic of South Sudan – Counties, as of 16 July 2012, Reliefweb http://reliefweb.int/map/south-sudan-republic/republic-south-sudan-counties-16-july-2012-reference-map, accessed 31 July 2012. Map 3: Eastern Equato...

  7. Applicability of vulnerability maps

    International Nuclear Information System (INIS)

    Andersen, L.J.; Gosk, E.

    1989-01-01

    A number of aspects to vulnerability maps are discussed: the vulnerability concept, mapping purposes, possible users, and applicability of vulnerability maps. Problems associated with general-type vulnerability mapping, including large-scale maps, universal pollutant, and universal pollution scenario are also discussed. An alternative approach to vulnerability assessment - specific vulnerability mapping for limited areas, specific pollutant, and predefined pollution scenario - is suggested. A simplification of the vulnerability concept is proposed in order to make vulnerability mapping more objective and by this means more comparable. An extension of the vulnerability concept to the rest of the hydrogeological cycle (lakes, rivers, and the sea) is proposed. Some recommendations regarding future activities are given

  8. Differential maps, difference maps, interpolated maps, and long term prediction

    International Nuclear Information System (INIS)

    Talman, R.

    1988-06-01

    Mapping techniques may be thought to be attractive for the long term prediction of motion in accelerators, especially because a simple map can approximately represent an arbitrarily complicated lattice. The intention of this paper is to develop prejudices as to the validity of such methods by applying them to a simple, exactly solveable, example. It is shown that a numerical interpolation map, such as can be generated in the accelerator tracking program TEAPOT, predicts the evolution more accurately than an analytically derived differential map of the same order. Even so, in the presence of ''appreciable'' nonlinearity, it is shown to be impractical to achieve ''accurate'' prediction beyond some hundreds of cycles of oscillation. This suggests that the value of nonlinear maps is restricted to the parameterization of only the ''leading'' deviation from linearity. 41 refs., 6 figs

  9. The added value of semimicroelectrode recording in deep brain stimulation of the subthalamic nucleus for Parkinson disease

    NARCIS (Netherlands)

    Jonker, Pascal K. C.; van Dijk, J. Marc C.; van Hulzen, Arjen L. J.; van Laar, Teus; Staal, Michiel J.; Journee, H. Louis

    2013-01-01

    Object. Accurate placement of the leads is crucial in deep brain stimulation (DBS). To optimize the surgical positioning of the lead, a combination of anatomical targeting on MRI, electrophysiological mapping, and clinical testing is applied during the procedure. Electrophysiological mapping is

  10. Deep learning for computational chemistry.

    Science.gov (United States)

    Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

    2017-06-15

    The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  11. Deep learning for computational chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Goh, Garrett B. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Hodas, Nathan O. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Vishnu, Abhinav [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354

    2017-03-08

    The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.

  12. VEGETATION MAPPING IN WETLANDS

    Directory of Open Access Journals (Sweden)

    F. PEDROTTI

    2004-01-01

    Full Text Available The current work examines the main aspects of wetland vegetation mapping, which can be summarized as analysis of the ecological-vegetational (ecotone gradients; vegetation complexes; relationships between vegetation distribution and geomorphology; vegetation of the hydrographic basin lo which the wetland in question belongs; vegetation monitoring with help of four vegetation maps: phytosociological map of the real and potential vegetation, map of vegetation dynamical tendencies, map of vegetation series.

  13. DeepSimulator: a deep simulator for Nanopore sequencing

    KAUST Repository

    Li, Yu; Han, Renmin; Bi, Chongwei; Li, Mo; Wang, Sheng; Gao, Xin

    2017-01-01

    or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments

  14. Improving deep convolutional neural networks with mixed maxout units.

    Directory of Open Access Journals (Sweden)

    Hui-Zhen Zhao

    Full Text Available Motivated by insights from the maxout-units-based deep Convolutional Neural Network (CNN that "non-maximal features are unable to deliver" and "feature mapping subspace pooling is insufficient," we present a novel mixed variant of the recently introduced maxout unit called a mixout unit. Specifically, we do so by calculating the exponential probabilities of feature mappings gained by applying different convolutional transformations over the same input and then calculating the expected values according to their exponential probabilities. Moreover, we introduce the Bernoulli distribution to balance the maximum values with the expected values of the feature mappings subspace. Finally, we design a simple model to verify the pooling ability of mixout units and a Mixout-units-based Network-in-Network (NiN model to analyze the feature learning ability of the mixout models. We argue that our proposed units improve the pooling ability and that mixout models can achieve better feature learning and classification performance.

  15. Pseudo 2-transistor active pixel sensor using an n-well/gate-tied p-channel metal oxide semiconductor field eeffect transistor-type photodetector with built-in transfer gate

    Science.gov (United States)

    Seo, Sang-Ho; Seo, Min-Woong; Kong, Jae-Sung; Shin, Jang-Kyoo; Choi, Pyung

    2008-11-01

    In this paper, a pseudo 2-transistor active pixel sensor (APS) has been designed and fabricated by using an n-well/gate-tied p-channel metal oxide semiconductor field effect transistor (PMOSFET)-type photodetector with built-in transfer gate. The proposed sensor has been fabricated using a 0.35 μm 2-poly 4-metal standard complementary metal oxide semiconductor (CMOS) logic process. The pseudo 2-transistor APS consists of two NMOSFETs and one photodetector which can amplify the generated photocurrent. The area of the pseudo 2-transistor APS is 7.1 × 6.2 μm2. The sensitivity of the proposed pixel is 49 lux/(V·s). By using this pixel, a smaller pixel area and a higher level of sensitivity can be realized when compared with a conventional 3-transistor APS which uses a pn junction photodiode.

  16. Proposal and achievement of novel structure InN/GaN multiple quantum wells consisting of 1 ML and fractional monolayer InN wells inserted in GaN matrix

    International Nuclear Information System (INIS)

    Yoshikawa, A.; Che, S. B.; Yamaguchi, W.; Saito, H.; Wang, X. Q.; Ishitani, Y.; Hwang, E. S.

    2007-01-01

    The authors propose and demonstrate the fabrication of InN/GaN multiple quantum well (MQW) consisting of 1 ML and fractional monolayer InN well insertion in GaN matrix under In-polarity growth regime. Since the critical thickness of InN epitaxy on GaN is about 1 ML and the growth temperature for 1 ML InN insertion can be remarkably higher, the proposed MQW structure can avoid/reduce generation of misfit dislocation, resulting in higher quality MQW-structure nature in principle than former InN-based MQWs. The proposed InN/GaN MQWs are potentially applicable to room temperature operating excitonic devices working in short-wavelength visible colors

  17. Deep-sea coral research and technology program: Alaska deep-sea coral and sponge initiative final report

    Science.gov (United States)

    Rooper, Chris; Stone, Robert P.; Etnoyer, Peter; Conrath, Christina; Reynolds, Jennifer; Greene, H. Gary; Williams, Branwen; Salgado, Enrique; Morrison, Cheryl L.; Waller, Rhian G.; Demopoulos, Amanda W.J.

    2017-01-01

    Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska’s marine waters. In some places, such as the central and western Aleutian Islands, deep-sea coral and sponge resources can be extremely diverse and may rank among the most abundant deep-sea coral and sponge communities in the world. Many different species of fishes and invertebrates are associated with deep-sea coral and sponge communities in Alaska. Because of their biology, these benthic invertebrates are potentially impacted by climate change and ocean acidification. Deepsea coral and sponge ecosystems are also vulnerable to the effects of commercial fishing activities. Because of the size and scope of Alaska’s continental shelf and slope, the vast majority of the area has not been visually surveyed for deep-sea corals and sponges. NOAA’s Deep Sea Coral Research and Technology Program (DSCRTP) sponsored a field research program in the Alaska region between 2012–2015, referred to hereafter as the Alaska Initiative. The priorities for Alaska were derived from ongoing data needs and objectives identified by the DSCRTP, the North Pacific Fishery Management Council (NPFMC), and Essential Fish Habitat-Environmental Impact Statement (EFH-EIS) process.This report presents the results of 15 projects conducted using DSCRTP funds from 2012-2015. Three of the projects conducted as part of the Alaska deep-sea coral and sponge initiative included dedicated at-sea cruises and fieldwork spread across multiple years. These projects were the eastern Gulf of Alaska Primnoa pacifica study, the Aleutian Islands mapping study, and the Gulf of Alaska fish productivity study. In all, there were nine separate research cruises carried out with a total of 109 at-sea days conducting research. The remaining projects either used data and samples collected by the three major fieldwork projects or were piggy-backed onto existing research programs at the Alaska Fisheries Science Center (AFSC).

  18. Deep UV LEDs

    Science.gov (United States)

    Han, Jung; Amano, Hiroshi; Schowalter, Leo

    2014-06-01

    Deep ultraviolet (DUV) photons interact strongly with a broad range of chemical and biological molecules; compact DUV light sources could enable a wide range of applications in chemi/bio-sensing, sterilization, agriculture, and industrial curing. The much shorter wavelength also results in useful characteristics related to optical diffraction (for lithography) and scattering (non-line-of-sight communication). The family of III-N (AlGaInN) compound semiconductors offers a tunable energy gap from infrared to DUV. While InGaN-based blue light emitters have been the primary focus for the obvious application of solid state lighting, there is a growing interest in the development of efficient UV and DUV light-emitting devices. In the past few years we have witnessed an increasing investment from both government and industry sectors to further the state of DUV light-emitting devices. The contributions in Semiconductor Science and Technology 's special issue on DUV devices provide an up-to-date snapshot covering many relevant topics in this field. Given the expected importance of bulk AlN substrate in DUV technology, we are pleased to include a review article by Hartmann et al on the growth of AlN bulk crystal by physical vapour transport. The issue of polarization field within the deep ultraviolet LEDs is examined in the article by Braut et al. Several commercial companies provide useful updates in their development of DUV emitters, including Nichia (Fujioka et al ), Nitride Semiconductors (Muramoto et al ) and Sensor Electronic Technology (Shatalov et al ). We believe these articles will provide an excellent overview of the state of technology. The growth of AlGaN heterostructures by molecular beam epitaxy, in contrast to the common organo-metallic vapour phase epitaxy, is discussed by Ivanov et al. Since hexagonal boron nitride (BN) has received much attention as both a UV and a two-dimensional electronic material, we believe it serves readers well to include the

  19. DEEP INFILTRATING ENDOMETRIOSIS

    Directory of Open Access Journals (Sweden)

    Martina Ribič-Pucelj

    2018-02-01

    Full Text Available Background: Endometriosis is not considered a unified disease, but a disease encompassing three differ- ent forms differentiated by aetiology and pathogenesis: peritoneal endometriosis, ovarian endometriosis and deep infiltrating endometriosis (DIE. The disease is classified as DIE when the lesions penetrate 5 mm or more into the retroperitoneal space. The estimated incidence of endometriosis in women of reproductive age ranges from 10–15 % and that of DIE from 3–10 %, the highest being in infertile women and in those with chronic pelvic pain. The leading symptoms of DIE are chronic pelvic pain which increases with age and correlates with the depth of infiltration and infertility. The most important diagnostic procedures are patient’s history and proper gynecological examination. The diagnosis is confirmed with laparoscopy. DIE can affect, beside reproductive organs, also bowel, bladder and ureters, therefore adi- tional diagnostic procedures must be performed preopertively to confirm or to exclude the involvement of the mentioned organs. Endometriosis is hormon dependent disease, there- fore several hormonal treatment regims are used to supress estrogen production but the symptoms recurr soon after caesation of the treatment. At the moment, surgical treatment with excision of all lesions, including those of bowel, bladder and ureters, is the method of choice but requires frequently interdisciplinary approach. Surgical treatment significantly reduces pain and improves fertility in inferile patients. Conclusions: DIE is not a rare form of endometriosis characterized by chronic pelvic pain and infertility. Medical treatment is not efficient. The method of choice is surgical treatment with excision of all lesions. It significantly reduces pelvic pain and enables high spontaneus and IVF preg- nacy rates.Therefore such patients should be treated at centres with experience in treatment of DIE and with possibility of interdisciplinary approach.

  20. Telepresence for Deep Space Missions

    Data.gov (United States)

    National Aeronautics and Space Administration — Incorporating telepresence technologies into deep space mission operations can give the crew and ground personnel the impression that they are in a location at time...

  1. Hybrid mask for deep etching

    KAUST Repository

    Ghoneim, Mohamed T.

    2017-01-01

    Deep reactive ion etching is essential for creating high aspect ratio micro-structures for microelectromechanical systems, sensors and actuators, and emerging flexible electronics. A novel hybrid dual soft/hard mask bilayer may be deposited during

  2. Expanding Thurston maps

    CERN Document Server

    Bonk, Mario

    2017-01-01

    This monograph is devoted to the study of the dynamics of expanding Thurston maps under iteration. A Thurston map is a branched covering map on a two-dimensional topological sphere such that each critical point of the map has a finite orbit under iteration. It is called expanding if, roughly speaking, preimages of a fine open cover of the underlying sphere under iterates of the map become finer and finer as the order of the iterate increases. Every expanding Thurston map gives rise to a fractal space, called its visual sphere. Many dynamical properties of the map are encoded in the geometry of this visual sphere. For example, an expanding Thurston map is topologically conjugate to a rational map if and only if its visual sphere is quasisymmetrically equivalent to the Riemann sphere. This relation between dynamics and fractal geometry is the main focus for the investigations in this work.

  3. Deep Learning and Bayesian Methods

    OpenAIRE

    Prosper Harrison B.

    2017-01-01

    A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such meth...

  4. Density functionals from deep learning

    OpenAIRE

    McMahon, Jeffrey M.

    2016-01-01

    Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep learning is developed to approximate this functional. Deep learning allows computational models that are capable of naturally discovering intricate structure in large and/or high-dimensional data sets, with multiple levels of abstraction. As no assumptions are ...

  5. Multicenter R2* mapping in the healthy brain

    DEFF Research Database (Denmark)

    Ropele, Stefan; Wattjes, Mike P; Langkammer, Christian

    2014-01-01

    structures. METHODS: R2* mapping was performed in 81 healthy subjects in seven centers using different 3 T systems. R2* was calculated from a dual-echo gradient echo sequence and was assessed in several deep gray matter structures. The inter-scanner and inter-subject variability of R2* was calculated...

  6. Okeanos Explorer (EX1602): Mission System Shakedown/CAPSTONE Mapping

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will use the ship’s deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, Knudsen 3260 chirp sub-bottom...

  7. subsurface sequence delineation and saline water mapping of lagos

    African Journals Online (AJOL)

    A subsurface sequence delineation and saline water mapping of Lagos State was carried out. Ten (10) deep boreholes with average depth of 300 m were drilled within the sedimentary basin. The boreholes were lithologically and geophysically logged. The driller's lithological logs aided by gamma and resistivity logs, ...

  8. Okeanos Explorer (EX1701): Kingman/Palmyra, Jarvis (Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will include the use of the ship’s deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, ADCPs, and Knudsen...

  9. Deep Unfolding for Topic Models.

    Science.gov (United States)

    Chien, Jen-Tzung; Lee, Chao-Hsi

    2018-02-01

    Deep unfolding provides an approach to integrate the probabilistic generative models and the deterministic neural networks. Such an approach is benefited by deep representation, easy interpretation, flexible learning and stochastic modeling. This study develops the unsupervised and supervised learning of deep unfolded topic models for document representation and classification. Conventionally, the unsupervised and supervised topic models are inferred via the variational inference algorithm where the model parameters are estimated by maximizing the lower bound of logarithm of marginal likelihood using input documents without and with class labels, respectively. The representation capability or classification accuracy is constrained by the variational lower bound and the tied model parameters across inference procedure. This paper aims to relax these constraints by directly maximizing the end performance criterion and continuously untying the parameters in learning process via deep unfolding inference (DUI). The inference procedure is treated as the layer-wise learning in a deep neural network. The end performance is iteratively improved by using the estimated topic parameters according to the exponentiated updates. Deep learning of topic models is therefore implemented through a back-propagation procedure. Experimental results show the merits of DUI with increasing number of layers compared with variational inference in unsupervised as well as supervised topic models.

  10. Hot, deep origin of petroleum: deep basin evidence and application

    Science.gov (United States)

    Price, Leigh C.

    1978-01-01

    Use of the model of a hot deep origin of oil places rigid constraints on the migration and entrapment of crude oil. Specifically, oil originating from depth migrates vertically up faults and is emplaced in traps at shallower depths. Review of petroleum-producing basins worldwide shows oil occurrence in these basins conforms to the restraints of and therefore supports the hypothesis. Most of the world's oil is found in the very deepest sedimentary basins, and production over or adjacent to the deep basin is cut by or directly updip from faults dipping into the basin deep. Generally the greater the fault throw the greater the reserves. Fault-block highs next to deep sedimentary troughs are the best target areas by the present concept. Traps along major basin-forming faults are quite prospective. The structural style of a basin governs the distribution, types, and amounts of hydrocarbons expected and hence the exploration strategy. Production in delta depocenters (Niger) is in structures cut by or updip from major growth faults, and structures not associated with such faults are barren. Production in block fault basins is on horsts next to deep sedimentary troughs (Sirte, North Sea). In basins whose sediment thickness, structure and geologic history are known to a moderate degree, the main oil occurrences can be specifically predicted by analysis of fault systems and possible hydrocarbon migration routes. Use of the concept permits the identification of significant targets which have either been downgraded or ignored in the past, such as production in or just updip from thrust belts, stratigraphic traps over the deep basin associated with major faulting, production over the basin deep, and regional stratigraphic trapping updip from established production along major fault zones.

  11. Mapping in the cloud

    CERN Document Server

    Peterson, Michael P

    2014-01-01

    This engaging text provides a solid introduction to mapmaking in the era of cloud computing. It takes students through both the concepts and technology of modern cartography, geographic information systems (GIS), and Web-based mapping. Conceptual chapters delve into the meaning of maps and how they are developed, covering such topics as map layers, GIS tools, mobile mapping, and map animation. Methods chapters take a learn-by-doing approach to help students master application programming interfaces and build other technical skills for creating maps and making them available on the Internet. Th

  12. Mapping with Drupal

    CERN Document Server

    Palazzolo, Alan

    2011-01-01

    Build beautiful interactive maps on your Drupal website, and tell engaging visual stories with your data. This concise guide shows you how to create custom geographical maps from top to bottom, using Drupal 7 tools and out-of-the-box modules. You'll learn how mapping works in Drupal, with examples on how to use intuitive interfaces to map local events, businesses, groups, and other custom data. Although building maps with Drupal can be tricky, this book helps you navigate the system's complexities for creating sophisticated maps that match your site design. Get the knowledge and tools you ne

  13. Meso(topoclimatic maps and mapping

    Directory of Open Access Journals (Sweden)

    Ladislav Plánka

    2007-06-01

    Full Text Available The atmospheric characteristics can be studied from many points of view, most often we talk about time and spatial standpoint. Application of time standpoint leads either to different kinds of the synoptic and prognostic maps production, which presents actual state of atmosphere in short time section in the past or in the near future or to the climatic maps production which presents longterm weather regime. Spatial standpoint then differs map works according to natural phenomenon proportions, whereas the scale of their graphic presentation can be different. It depends on production purpose of each work.In the paper there are analysed methods of mapping and climatic maps production, which display longterm regime of chosen atmospheric features. These athmosphere features are formed in interaction with land surface and also have direct influence on people and their activities throughout the country. At the same time they’re influenced by anthropogenic intervention to the landscape.

  14. Prediction of visual saliency in video with deep CNNs

    Science.gov (United States)

    Chaabouni, Souad; Benois-Pineau, Jenny; Hadar, Ofer

    2016-09-01

    Prediction of visual saliency in images and video is a highly researched topic. Target applications include Quality assessment of multimedia services in mobile context, video compression techniques, recognition of objects in video streams, etc. In the framework of mobile and egocentric perspectives, visual saliency models cannot be founded only on bottom-up features, as suggested by feature integration theory. The central bias hypothesis, is not respected neither. In this case, the top-down component of human visual attention becomes prevalent. Visual saliency can be predicted on the basis of seen data. Deep Convolutional Neural Networks (CNN) have proven to be a powerful tool for prediction of salient areas in stills. In our work we also focus on sensitivity of human visual system to residual motion in a video. A Deep CNN architecture is designed, where we incorporate input primary maps as color values of pixels and magnitude of local residual motion. Complementary contrast maps allow for a slight increase of accuracy compared to the use of color and residual motion only. The experiments show that the choice of the input features for the Deep CNN depends on visual task:for th eintersts in dynamic content, the 4K model with residual motion is more efficient, and for object recognition in egocentric video the pure spatial input is more appropriate.

  15. Species distribution models of tropical deep-sea snappers.

    Directory of Open Access Journals (Sweden)

    Céline Gomez

    Full Text Available Deep-sea fisheries provide an important source of protein to Pacific Island countries and territories that are highly dependent on fish for food security. However, spatial management of these deep-sea habitats is hindered by insufficient data. We developed species distribution models using spatially limited presence data for the main harvested species in the Western Central Pacific Ocean. We used bathymetric and water temperature data to develop presence-only species distribution models for the commercially exploited deep-sea snappers Etelis Cuvier 1828, Pristipomoides Valenciennes 1830, and Aphareus Cuvier 1830. We evaluated the performance of four different algorithms (CTA, GLM, MARS, and MAXENT within the BIOMOD framework to obtain an ensemble of predicted distributions. We projected these predictions across the Western Central Pacific Ocean to produce maps of potential deep-sea snapper distributions in 32 countries and territories. Depth was consistently the best predictor of presence for all species groups across all models. Bathymetric slope was consistently the poorest predictor. Temperature at depth was a good predictor of presence for GLM only. Model precision was highest for MAXENT and CTA. There were strong regional patterns in predicted distribution of suitable habitat, with the largest areas of suitable habitat (> 35% of the Exclusive Economic Zone predicted in seven South Pacific countries and territories (Fiji, Matthew & Hunter, Nauru, New Caledonia, Tonga, Vanuatu and Wallis & Futuna. Predicted habitat also varied among species, with the proportion of predicted habitat highest for Aphareus and lowest for Etelis. Despite data paucity, the relationship between deep-sea snapper presence and their environments was sufficiently strong to predict their distribution across a large area of the Pacific Ocean. Our results therefore provide a strong baseline for designing monitoring programs that balance resource exploitation and

  16. Active Fire Mapping Program

    Science.gov (United States)

    Active Fire Mapping Program Current Large Incidents (Home) New Large Incidents Fire Detection Maps MODIS Satellite Imagery VIIRS Satellite Imagery Fire Detection GIS Data Fire Data in Google Earth ...

  17. Using maps in genealogy

    Science.gov (United States)

    ,

    2002-01-01

    In genealogical research, maps can provide clues to where our ancestors may have lived and where to look for written records about them. Beginners should master basic genealogical research techniques before starting to use topographic maps.

  18. NGS Survey Control Map

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NGS Survey Control Map provides a map of the US which allows you to find and display geodetic survey control points stored in the database of the National...

  19. National Pipeline Mapping System

    Data.gov (United States)

    Department of Transportation — The NPMS Public Map Viewer allows the general public to view maps of transmission pipelines, LNG plants, and breakout tanks in one selected county. Distribution and...

  20. NAIP Status Maps Gallery

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — NAIP Status Maps Gallery. These maps illustrate what aerial imagery collection is planned, whats been collected, when it is available and how it is available. These...

  1. Mapping Medicare Disparities Tool

    Data.gov (United States)

    U.S. Department of Health & Human Services — The CMS Office of Minority Health has designed an interactive map, the Mapping Medicare Disparities Tool, to identify areas of disparities between subgroups of...

  2. Recovery Action Mapping Tool

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Recovery Action Mapping Tool is a web map that allows users to visually interact with and query actions that were developed to recover species listed under the...

  3. Letter of Map Revision

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The National Flood Hazard Layer (NFHL) data incorporates all Digital Flood Insurance Rate Map(DFIRM) databases published by FEMA, and any Letters Of Map Revision...

  4. How Stressful Is "Deep Bubbling"?

    Science.gov (United States)

    Tyrmi, Jaana; Laukkanen, Anne-Maria

    2017-03-01

    Water resistance therapy by phonating through a tube into the water is used to treat dysphonia. Deep submersion (≥10 cm in water, "deep bubbling") is used for hypofunctional voice disorders. Using it with caution is recommended to avoid vocal overloading. This experimental study aimed to investigate how strenuous "deep bubbling" is. Fourteen subjects, half of them with voice training, repeated the syllable [pa:] in comfortable speaking pitch and loudness, loudly, and in strained voice. Thereafter, they phonated a vowel-like sound both in comfortable loudness and loudly into a glass resonance tube immersed 10 cm into the water. Oral pressure, contact quotient (CQ, calculated from electroglottographic signal), and sound pressure level were studied. The peak oral pressure P(oral) during [p] and shuttering of the outer end of the tube was measured to estimate the subglottic pressure P(sub) and the mean P(oral) during vowel portions to enable calculation of transglottic pressure P(trans). Sensations during phonation were reported with an open-ended interview. P(sub) and P(oral) were higher in "deep bubbling" and P(trans) lower than in loud syllable phonation, but the CQ did not differ significantly. Similar results were obtained for the comparison between loud "deep bubbling" and strained phonation, although P(sub) did not differ significantly. Most of the subjects reported "deep bubbling" to be stressful only for respiratory and lip muscles. No big differences were found between trained and untrained subjects. The CQ values suggest that "deep bubbling" may increase vocal fold loading. Further studies should address impact stress during water resistance exercises. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  5. Branched polynomial covering maps

    DEFF Research Database (Denmark)

    Hansen, Vagn Lundsgaard

    1999-01-01

    A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch...... set. Particular studies are made of branched polynomial covering maps arising from Riemann surfaces and from knots in the 3-sphere....

  6. Multi-moment maps

    DEFF Research Database (Denmark)

    Swann, Andrew Francis; Madsen, Thomas Bruun

    2012-01-01

    We introduce a notion of moment map adapted to actions of Lie groups that preserve a closed three-form. We show existence of our multi-moment maps in many circumstances, including mild topological assumptions on the underlying manifold. Such maps are also shown to exist for all groups whose second...

  7. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Fogh Olsen, Ole; Sporring, Jon

    2007-01-01

    . To address this problem we introduce a novel photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way we preserve the important illumination features......, while eliminating noise. We call our method diffusion based photon mapping....

  8. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Olsen, Ole Fogh; Sporring, Jon

    2006-01-01

    . To address this problem we introduce a novel photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way we preserve the important illumination features......, while eliminating noise. We call our method diffusion based photon mapping....

  9. On parabolic external maps

    DEFF Research Database (Denmark)

    Lomonaco, Luna; Petersen, Carsten Lunde; Shen, Weixiao

    2017-01-01

    We prove that any C1+BV degree d ≥ 2 circle covering h having all periodic orbits weakly expanding, is conjugate by a C1+BV diffeomorphism to a metrically expanding map. We use this to connect the space of parabolic external maps (coming from the theory of parabolic-like maps) to metrically expan...

  10. Digitised Maps in the Danish Map Collection

    OpenAIRE

    Annie Lenschau-Teglers; Vivi Gade Rønsberg

    2005-01-01

    As in the rest of the library world, The Royal Library in Copenhagen is in the process of digitising its collections. At the moment we are mainly working on the handwritten manual catalogue - but digitising the material is also a major working assignment. The Map Collection at The Royal Library has today divided the effort in digitising its materials into 3 groups: 1. Digitised maps as a vital addition to the records in our bibliographic database REX 2. Digitised maps presented as a Digital F...

  11. Magma Transport from Deep to Shallow Crust and Eruption

    Science.gov (United States)

    White, R. S.; Greenfield, T. S.; Green, R. G.; Brandsdottir, B.; Hudson, T.; Woods, J.; Donaldson, C.; Ágústsdóttir, T.

    2016-12-01

    We have mapped magma transport paths from the deep (20 km) to the shallow (6 km) crust and in two cases to eventual surface eruption under several Icelandic volcanoes (Askja, Bardarbunga, Eyjafjallajokull, Upptyppingar). We use microearthquakes caused by brittle fracture to map magma on the move and tomographic seismic studies of velocity perturbations beneath volcanoes to map the magma storage regions. High-frequency brittle failure earthquakes with magnitudes of typically 0-2 occur where melt is forcing its way through the country rock, or where previously frozen melt is repeatedly re-broken in conduits and dykes. The Icelandic crust on the rift zones where these earthquakes occur is ductile at depths greater than 7 km beneath the surface, so the occurrence of brittle failure seismicity at depths as great as 20 km is indicative of high strain rates, for which magma movement is the most likely explanation. We suggest that high volatile pressures caused by the exsolution of carbon dioxide in the deep crust is driving the magma movement and seismicity at depths of 15-20 km. Eruptions from shallow crustal storage areas are likewise driven by volatile exsolution, though additional volatiles, and in particular water are also involved in the shallow crust.

  12. Accelerating Deep Learning with Shrinkage and Recall

    OpenAIRE

    Zheng, Shuai; Vishnu, Abhinav; Ding, Chris

    2016-01-01

    Deep Learning is a very powerful machine learning model. Deep Learning trains a large number of parameters for multiple layers and is very slow when data is in large scale and the architecture size is large. Inspired from the shrinking technique used in accelerating computation of Support Vector Machines (SVM) algorithm and screening technique used in LASSO, we propose a shrinking Deep Learning with recall (sDLr) approach to speed up deep learning computation. We experiment shrinking Deep Lea...

  13. What Really is Deep Learning Doing?

    OpenAIRE

    Xiong, Chuyu

    2017-01-01

    Deep learning has achieved a great success in many areas, from computer vision to natural language processing, to game playing, and much more. Yet, what deep learning is really doing is still an open question. There are a lot of works in this direction. For example, [5] tried to explain deep learning by group renormalization, and [6] tried to explain deep learning from the view of functional approximation. In order to address this very crucial question, here we see deep learning from perspect...

  14. Mapping of wine industry

    OpenAIRE

    Віліна Пересадько; Надія Максименко; Катерина Біла

    2016-01-01

    Having reviewed a variety of approaches to understanding the essence of wine industry, having studied the modern ideas about the future of wine industry, having analyzed more than 50 maps from the Internet we have set the trends and special features of wine industry mapping in the world, such as: - the vast majority of maps displays the development of the industry at regional or national level, whereas there are practically no world maps; - wine-growing regions are represented on maps very un...

  15. Deep Learning and Bayesian Methods

    Directory of Open Access Journals (Sweden)

    Prosper Harrison B.

    2017-01-01

    Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.

  16. Deep Learning in Drug Discovery.

    Science.gov (United States)

    Gawehn, Erik; Hiss, Jan A; Schneider, Gisbert

    2016-01-01

    Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research by borrowing from the field of "deep learning". Compared with some of the other life sciences, their application in drug discovery is still limited. Here, we provide an overview of this emerging field of molecular informatics, present the basic concepts of prominent deep learning methods and offer motivation to explore these techniques for their usefulness in computer-assisted drug discovery and design. We specifically emphasize deep neural networks, restricted Boltzmann machine networks and convolutional networks. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Eric Davidson and deep time.

    Science.gov (United States)

    Erwin, Douglas H

    2017-10-13

    Eric Davidson had a deep and abiding interest in the role developmental mechanisms played in generating evolutionary patterns documented in deep time, from the origin of the euechinoids to the processes responsible for the morphological architectures of major animal clades. Although not an evolutionary biologist, Davidson's interests long preceded the current excitement over comparative evolutionary developmental biology. Here I discuss three aspects at the intersection between his research and evolutionary patterns in deep time: First, understanding the mechanisms of body plan formation, particularly those associated with the early diversification of major metazoan clades. Second, a critique of early claims about ancestral metazoans based on the discoveries of highly conserved genes across bilaterian animals. Third, Davidson's own involvement in paleontology through a collaborative study of the fossil embryos from the Ediacaran Doushantuo Formation in south China.

  18. Okeanos Explorer (EX1702): American Samoa Expedition: Suesuega o le Moana o Amerika Samoa (ROV/Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will include the use of the ship's deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, Knudsen 3260 chirp...

  19. Deep convolutional neural networks for dense non-uniform motion deblurring

    CSIR Research Space (South Africa)

    Cronje, J

    2015-11-01

    Full Text Available to form a dense non-uniform motion estimation map. Furthermore, a second CNN is trained to perform deblurring given a blurry image patch and the estimated motion vector. Combining the two trained networks result in a deep learning approach that can enhance...

  20. Deep far infrared ISOPHOT survey in "Selected Area 57" - I. Observations and source counts

    DEFF Research Database (Denmark)

    Linden-Vornle, M.J.D.; Nørgaard-Nielsen, Hans Ulrik; Jørgensen, H.E.

    2000-01-01

    We present here the results of a deep survey in a 0.4 deg(2) blank field in Selected Area 57 conducted with the ISOPHOT instrument aboard ESAs Infrared Space Observatory (ISO1) at both 60 mu m and 90 mu m. The resulting sky maps have a spatial resolution of 15 x 23 arcsrc(2) per pixel which is much...

  1. Scanning deep level transient spectroscopy using an MeV ion microprobe

    Energy Technology Data Exchange (ETDEWEB)

    Laird, J S; Bardos, R A; Saint, A; Moloney, G M; Legge, G F.J. [Melbourne Univ., Parkville, VIC (Australia)

    1994-12-31

    Traditionally the scanning ion microprobe has given little or no information regarding the electronic structure of materials in particular semiconductors. A new imaging technique called Scanning Ion Deep Level Transient Spectroscopy (SIDLTS) is presented which is able to spatially map alterations in the band gap structure of materials by lattice defects or impurities. 3 refs., 2 figs.

  2. Exploiting deep neural networks and head movements for binaural localisation of multiple speakers in reverberant conditions

    DEFF Research Database (Denmark)

    Ma, Ning; Brown, Guy J.; May, Tobias

    2015-01-01

    This paper presents a novel machine-hearing system that exploits deep neural networks (DNNs) and head movements for binaural localisation of multiple speakers in reverberant conditions. DNNs are used to map binaural features, consisting of the complete crosscorrelation function (CCF) and interaural...

  3. Scanning deep level transient spectroscopy using an MeV ion microprobe

    Energy Technology Data Exchange (ETDEWEB)

    Laird, J.S.; Bardos, R.A.; Saint, A.; Moloney, G.M.; Legge, G.F.J. [Melbourne Univ., Parkville, VIC (Australia)

    1993-12-31

    Traditionally the scanning ion microprobe has given little or no information regarding the electronic structure of materials in particular semiconductors. A new imaging technique called Scanning Ion Deep Level Transient Spectroscopy (SIDLTS) is presented which is able to spatially map alterations in the band gap structure of materials by lattice defects or impurities. 3 refs., 2 figs.

  4. Deep Learning in Gastrointestinal Endoscopy.

    Science.gov (United States)

    Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

    2016-01-01

    Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

  5. Branched polynomial covering maps

    DEFF Research Database (Denmark)

    Hansen, Vagn Lundsgaard

    2002-01-01

    A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch ...... set. Particular studies are made of branched polynomial covering maps arising from Riemann surfaces and from knots in the 3-sphere. (C) 2001 Elsevier Science B.V. All rights reserved.......A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch...

  6. Deep mycoses in Amazon region.

    Science.gov (United States)

    Talhari, S; Cunha, M G; Schettini, A P; Talhari, A C

    1988-09-01

    Patients with deep mycoses diagnosed in dermatologic clinics of Manaus (state of Amazonas, Brazil) were studied from November 1973 to December 1983. They came from the Brazilian states of Amazonas, Pará, Acre, and Rondônia and the Federal Territory of Roraima. All of these regions, with the exception of Pará, are situated in the western part of the Amazon Basin. The climatic conditions in this region are almost the same: tropical forest, high rainfall, and mean annual temperature of 26C. The deep mycoses diagnosed, in order of frequency, were Jorge Lobo's disease, paracoccidioidomycosis, chromomycosis, sporotrichosis, mycetoma, cryptococcosis, zygomycosis, and histoplasmosis.

  7. Producing deep-water hydrocarbons

    International Nuclear Information System (INIS)

    Pilenko, Thierry

    2011-01-01

    Several studies relate the history and progress made in offshore production from oil and gas fields in relation to reserves and the techniques for producing oil offshore. The intention herein is not to review these studies but rather to argue that the activities of prospecting and producing deep-water oil and gas call for a combination of technology and project management and, above all, of devotion and innovation. Without this sense of commitment motivating men and women in this industry, the human adventure of deep-water production would never have taken place

  8. Assessment of deep electrical conductivity features of Northern Victoria Land (Antarctica under other geophysical constraints

    Directory of Open Access Journals (Sweden)

    A. Caneva

    2000-06-01

    Full Text Available The lithospheric and crustal structure of the Victoria Land continental block (Antarctica has been studied by geological and geophysical surveys. Among them magnetovariational investigations (MV have been addressed to highlight the deep electrical conductivity patterns which contribute to the understanding of continental rifting and tectonic setting of the region. The hypothetical event map for H linearly polarized perpendicular to the coast indicates a possible broad coast parallel conductivity anomaly zone. Despite the coast effect, this feature could be related to the deep upper mantle thermal anomaly leading to Cenozoic uplift of the Transantarctic Mountains rift flank. However, both the hypothetic event map polarized parallel to the coast and the induction arrows suggest that the area of enhanced conductivity may be confined to the Deep Freeze Range crustal block along the western flank of the Mesozoic Rennick Graben. We also discuss the possible association between increased conductivity over the Southern Cross block and extensive Cenozoic alkaline plutonism.

  9. From Exploration to Exploitation? Opportunities and Imperatives in the Deep Sea

    KAUST Repository

    Van Dover, Cindy Lee

    2017-01-16

    We may think of the depths of the ocean as unseen, unfathomable, but there have been breakthroughs in technology that allow scientists access to the deep sea and that bring the deep sea directly to the public through live video feeds and data links. We can now map the seafloor to resolve features the size of a football and smaller using sound waves, while at the same time, sensors report to us the chemical nature of the surrounding environment. We will look at examples of robots and other assets that we use to explore the seafloor and at some of the discoveries that arise from our expanding capabilities. We will look at some of the blank places on the map and wonder what might be located there. And finally, we will explore the growing interest in mining the seabed and the potential for a Blue Economy in the deep ocean.

  10. Breast cancer molecular subtype classification using deep features: preliminary results

    Science.gov (United States)

    Zhu, Zhe; Albadawy, Ehab; Saha, Ashirbani; Zhang, Jun; Harowicz, Michael R.; Mazurowski, Maciej A.

    2018-02-01

    Radiogenomics is a field of investigation that attempts to examine the relationship between imaging characteris- tics of cancerous lesions and their genomic composition. This could offer a noninvasive alternative to establishing genomic characteristics of tumors and aid cancer treatment planning. While deep learning has shown its supe- riority in many detection and classification tasks, breast cancer radiogenomic data suffers from a very limited number of training examples, which renders the training of the neural network for this problem directly and with no pretraining a very difficult task. In this study, we investigated an alternative deep learning approach referred to as deep features or off-the-shelf network approach to classify breast cancer molecular subtypes using breast dynamic contrast enhanced MRIs. We used the feature maps of different convolution layers and fully connected layers as features and trained support vector machines using these features for prediction. For the feature maps that have multiple layers, max-pooling was performed along each channel. We focused on distinguishing the Luminal A subtype from other subtypes. To evaluate the models, 10 fold cross-validation was performed and the final AUC was obtained by averaging the performance of all the folds. The highest average AUC obtained was 0.64 (0.95 CI: 0.57-0.71), using the feature maps of the last fully connected layer. This indicates the promise of using this approach to predict the breast cancer molecular subtypes. Since the best performance appears in the last fully connected layer, it also implies that breast cancer molecular subtypes may relate to high level image features

  11. DeepSimulator: a deep simulator for Nanopore sequencing

    KAUST Repository

    Li, Yu

    2017-12-23

    Motivation: Oxford Nanopore sequencing is a rapidly developed sequencing technology in recent years. To keep pace with the explosion of the downstream data analytical tools, a versatile Nanopore sequencing simulator is needed to complement the experimental data as well as to benchmark those newly developed tools. However, all the currently available simulators are based on simple statistics of the produced reads, which have difficulty in capturing the complex nature of the Nanopore sequencing procedure, the main task of which is the generation of raw electrical current signals. Results: Here we propose a deep learning based simulator, DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83% to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection. Availability: The software can be accessed freely at: https://github.com/lykaust15/DeepSimulator.

  12. Stimulation Technologies for Deep Well Completions

    Energy Technology Data Exchange (ETDEWEB)

    None

    2003-09-30

    The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a study to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. An assessment of historical deep gas well drilling activity and forecast of future trends was completed during the first six months of the project; this segment of the project was covered in Technical Project Report No. 1. The second progress report covers the next six months of the project during which efforts were primarily split between summarizing rock mechanics and fracture growth in deep reservoirs and contacting operators about case studies of deep gas well stimulation.

  13. STIMULATION TECHNOLOGIES FOR DEEP WELL COMPLETIONS

    Energy Technology Data Exchange (ETDEWEB)

    Stephen Wolhart

    2003-06-01

    The Department of Energy (DOE) is sponsoring a Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a project to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. Phase 1 was recently completed and consisted of assessing deep gas well drilling activity (1995-2007) and an industry survey on deep gas well stimulation practices by region. Of the 29,000 oil, gas and dry holes drilled in 2002, about 300 were drilled in the deep well; 25% were dry, 50% were high temperature/high pressure completions and 25% were simply deep completions. South Texas has about 30% of these wells, Oklahoma 20%, Gulf of Mexico Shelf 15% and the Gulf Coast about 15%. The Rockies represent only 2% of deep drilling. Of the 60 operators who drill deep and HTHP wells, the top 20 drill almost 80% of the wells. Six operators drill half the U.S. deep wells. Deep drilling peaked at 425 wells in 1998 and fell to 250 in 1999. Drilling is expected to rise through 2004 after which drilling should cycle down as overall drilling declines.

  14. Deep Joint Rain Detection and Removal from a Single Image

    OpenAIRE

    Yang, Wenhan; Tan, Robby T.; Feng, Jiashi; Liu, Jiaying; Guo, Zongming; Yan, Shuicheng

    2016-01-01

    In this paper, we address a rain removal problem from a single image, even in the presence of heavy rain and rain streak accumulation. Our core ideas lie in the new rain image models and a novel deep learning architecture. We first modify an existing model comprising a rain streak layer and a background layer, by adding a binary map that locates rain streak regions. Second, we create a new model consisting of a component representing rain streak accumulation (where individual streaks cannot b...

  15. AlN/GaN Digital Alloy for Mid- and Deep-Ultraviolet Optoelectronics.

    Science.gov (United States)

    Sun, Wei; Tan, Chee-Keong; Tansu, Nelson

    2017-09-19

    The AlN/GaN digital alloy (DA) is a superlattice-like nanostructure formed by stacking ultra-thin ( ≤ 4 monolayers) AlN barriers and GaN wells periodically. Here we performed a comprehensive study on the electronics and optoelectronics properties of the AlN/GaN DA for mid- and deep-ultraviolet (UV) applications. Our numerical analysis indicates significant miniband engineering in the AlN/GaN DA by tuning the thicknesses of AlN barriers and GaN wells, so that the effective energy gap can be engineered from ~3.97 eV to ~5.24 eV. The band structure calculation also shows that the valence subbands of the AlN/GaN DA is properly rearranged leading to the heavy-hole (HH) miniband being the top valence subband, which results in the desired transverse-electric polarized emission. Furthermore, our study reveals that the electron-hole wavefunction overlaps in the AlN/GaN DA structure can be remarkably enhanced up to 97% showing the great potential of improving the internal quantum efficiency for mid- and deep-UV device application. In addition, the optical absorption properties of the AlN/GaN DA are analyzed with wide spectral coverage and spectral tunability in mid- and deep-UV regime. Our findings suggest the potential of implementing the AlN/GaN DA as a promising active region design for high efficiency mid- and deep-UV device applications.

  16. On palaeogeographic map

    Directory of Open Access Journals (Sweden)

    Zeng-Zhao Feng

    2016-01-01

    Full Text Available The palaeogeographic map is a graphic representation of physical geographical characteristics in geological history periods and human history periods. It is the most important result of palaeogeographic study. The author, as the Editor-in-Chief of Journal of Palaeogeography, Chinese Edition and English Edition, aimed at the problems of the articles submitted to and published in the Journal of Palaeogeography in recent years and the relevant papers and books of others, and integrated with his practice of palaeogeographic study and mapping, wrote this paper. The content mainly includes the data of palaeogeographic mapping, the problems of palaeogeographic mapping method, the “Single factor analysis and multifactor comprehensive mapping method —— Methodology of quantitative lithofacies palaeogeography”, i.e., the “4 steps mapping method”, the nomenclature of each palaeogeographic unit in palaeogeographic map, the explanation of each palaeogeographic unit in palaeogeographic map, the explanation of significance of palaeogeographic map and palaeogeographic article, the evaluative standards of palaeogeographic map and palaeogeographic article, and the self-evaluation. Criticisms and corrections are welcome.

  17. Mapping Urban Social Divisions

    Directory of Open Access Journals (Sweden)

    Susan Ball

    2010-05-01

    Full Text Available Against the background of increased levels of interest in space and images beyond the field of geography, this article (re- introduces earlier work on the semiotics of maps undertaken by geographers in the 1960s. The data limitations, purpose and cultural context in which a user interprets a map's codes and conventions are highlighted in this work, which remains relevant to the interpretation of maps—new and old—forty years later. By means of drawing on geography's contribution to the semiotics of maps, the article goes on to examine the concept of urban social divisions as represented in map images. Using a small number of map images, including two of the most widely known maps of urban social division in Europe and North America, the roles of context, data and purpose in the production and interpretation of maps are discussed. By presenting the examples chronologically the article shows that although advances in data collection and manipulation have allowed researchers to combine different social variables in maps of social division, and to interact with map images, work by geographers on the semiotics of maps is no less relevant today than when it was first proposed forty years ago. URN: urn:nbn:de:0114-fqs1002372

  18. Deep learning with convolutional neural networks for EEG decoding and visualization.

    Science.gov (United States)

    Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

    2017-11-01

    Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  19. Deep Space Climate Observatory (DSCOVR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Deep Space Climate ObserVatoRy (DSCOVR) satellite is a NOAA operated asset at the first Lagrange (L1) point. The primary space weather instrument is the PlasMag...

  20. FOSTERING DEEP LEARNING AMONGST ENTREPRENEURSHIP ...

    African Journals Online (AJOL)

    An important prerequisite for this important objective to be achieved is that lecturers ensure that students adopt a deep learning approach towards entrepreneurship courses been taught, as this will enable them to truly understand key entrepreneurial concepts and strategies and how they can be implemented in the real ...

  1. Deep Space Gateway "Recycler" Mission

    Science.gov (United States)

    Graham, L.; Fries, M.; Hamilton, J.; Landis, R.; John, K.; O'Hara, W.

    2018-02-01

    Use of the Deep Space Gateway provides a hub for a reusable planetary sample return vehicle for missions to gather star dust as well as samples from various parts of the solar system including main belt asteroids, near-Earth asteroids, and Mars moon.

  2. Deep freezers with heat recovery

    Energy Technology Data Exchange (ETDEWEB)

    Kistler, J.

    1981-09-02

    Together with space and water heating systems, deep freezers are the biggest energy consumers in households. The article investigates the possibility of using the waste heat for water heating. The design principle of such a system is presented in a wiring diagram.

  3. A Deep-Sea Simulation.

    Science.gov (United States)

    Montes, Georgia E.

    1997-01-01

    Describes an activity that simulates exploration techniques used in deep-sea explorations and teaches students how this technology can be used to take a closer look inside volcanoes, inspect hazardous waste sites such as nuclear reactors, and explore other environments dangerous to humans. (DDR)

  4. Barbabos Deep-Water Sponges

    NARCIS (Netherlands)

    Soest, van R.W.M.; Stentoft, N.

    1988-01-01

    Deep-water sponges dredged up in two locations off the west coast of Barbados are systematically described. A total of 69 species is recorded, among which 16 are new to science, viz. Pachymatisma geodiformis, Asteropus syringiferus, Cinachyra arenosa, Theonella atlantica. Corallistes paratypus,

  5. Deep learning for visual understanding

    NARCIS (Netherlands)

    Guo, Y.

    2017-01-01

    With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically. Deep learning, served as one of the most significant breakthroughs, has brought revolutionary success in diverse visual applications,

  6. Deep-Sky Video Astronomy

    CERN Document Server

    Massey, Steve

    2009-01-01

    A guide to using modern integrating video cameras for deep-sky viewing and imaging with the kinds of modest telescopes available commercially to amateur astronomers. It includes an introduction and a brief history of the technology and camera types. It examines the pros and cons of this unrefrigerated yet highly efficient technology

  7. DM Considerations for Deep Drilling

    OpenAIRE

    Dubois-Felsmann, Gregory

    2016-01-01

    An outline of the current situation regarding the DM plans for the Deep Drilling surveys and an invitation to the community to provide feedback on what they would like to see included in the data processing and visualization of these surveys.

  8. Lessons from Earth's Deep Time

    Science.gov (United States)

    Soreghan, G. S.

    2005-01-01

    Earth is a repository of data on climatic changes from its deep-time history. Article discusses the collection and study of these data to predict future climatic changes, the need to create national study centers for the purpose, and the necessary cooperation between different branches of science in climatic research.

  9. Digging Deeper: The Deep Web.

    Science.gov (United States)

    Turner, Laura

    2001-01-01

    Focuses on the Deep Web, defined as Web content in searchable databases of the type that can be found only by direct query. Discusses the problems of indexing; inability to find information not indexed in the search engine's database; and metasearch engines. Describes 10 sites created to access online databases or directly search them. Lists ways…

  10. Deep Learning and Music Adversaries

    DEFF Research Database (Denmark)

    Kereliuk, Corey Mose; Sturm, Bob L.; Larsen, Jan

    2015-01-01

    the minimal perturbation of the input image such that the system misclassifies it with high confidence. We adapt this approach to construct and deploy an adversary of deep learning systems applied to music content analysis. In our case, however, the system inputs are magnitude spectral frames, which require...

  11. Stimulation Technologies for Deep Well Completions

    Energy Technology Data Exchange (ETDEWEB)

    Stephen Wolhart

    2005-06-30

    The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies conducted a study to evaluate the stimulation of deep wells. The objective of the project was to review U.S. deep well drilling and stimulation activity, review rock mechanics and fracture growth in deep, high-pressure/temperature wells and evaluate stimulation technology in several key deep plays. This report documents results from this project.

  12. Data-driven discovery of Koopman eigenfunctions using deep learning

    Science.gov (United States)

    Lusch, Bethany; Brunton, Steven L.; Kutz, J. Nathan

    2017-11-01

    Koopman operator theory transforms any autonomous non-linear dynamical system into an infinite-dimensional linear system. Since linear systems are well-understood, a mapping of non-linear dynamics to linear dynamics provides a powerful approach to understanding and controlling fluid flows. However, finding the correct change of variables remains an open challenge. We present a strategy to discover an approximate mapping using deep learning. Our neural networks find this change of variables, its inverse, and a finite-dimensional linear dynamical system defined on the new variables. Our method is completely data-driven and only requires measurements of the system, i.e. it does not require derivatives or knowledge of the governing equations. We find a minimal set of approximate Koopman eigenfunctions that are sufficient to reconstruct and advance the system to future states. We demonstrate the method on several dynamical systems.

  13. A visual tracking method based on deep learning without online model updating

    Science.gov (United States)

    Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

    2018-02-01

    The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

  14. Localization noise in deep subwavelength plasmonic devices

    Science.gov (United States)

    Ghoreyshi, Ali; Victora, R. H.

    2018-05-01

    The grain shape dependence of absorption has been investigated in metal-insulator thin films. We demonstrate that randomness in the size and shape of plasmonic particles can lead to Anderson localization of polarization modes in the deep subwavelength regime. These localized modes can contribute to significant variation in the local field. In the case of plasmonic nanodevices, the effects of the localized modes have been investigated by mapping an electrostatic Hamiltonian onto the Anderson Hamiltonian in the presence of a random vector potential. We show that local behavior of the optical beam can be understood in terms of the weighted local density of the localized modes of the depolarization field. Optical nanodevices that operate on a length scale with high variation in the density of states of localized modes will experience a previously unidentified localized noise. This localization noise contributes uncertainty to the output of plasmonic nanodevices and limits their scalability. In particular, the resulting impact on heat-assisted magnetic recording is discussed.

  15. Mapping of wine industry

    Directory of Open Access Journals (Sweden)

    Віліна Пересадько

    2016-10-01

    Full Text Available Having reviewed a variety of approaches to understanding the essence of wine industry, having studied the modern ideas about the future of wine industry, having analyzed more than 50 maps from the Internet we have set the trends and special features of wine industry mapping in the world, such as: - the vast majority of maps displays the development of the industry at regional or national level, whereas there are practically no world maps; - wine-growing regions are represented on maps very unevenly; - all existing maps of the industry could be classified as analytical ascertaining inventory type; - the dominant ways of cartographic representation are area method and qualitative background method, sign method and collation maps are rarely used; - basically all the Internet maps have low quality as they are scanned images with poor resolution; - the special feature of maps published lately is lack of geographical basis (except for state borders and coastline. We created wine production and consumption world map «Wine Industry» in the scale of 1:60 000 000 with simple geographical basis (state names, state borders, major rivers, coastline. It was concluded that from the methodological point of view it is incorrect not to show geographical basis on maps of wine industry. Analysis of this map allowed us to identify areas of traditional wine-making, potential wine-making areas and countries which claim to be the world leaders in the field of wine production. We found disbalans between wine production and wine consumption - increasing wine production in South America, China and the United States and increasing wine consumption (mainly due to the import products in countries where the grape is not the primary agricultural product.

  16. Introduction to "Mapping Vietnameseness"

    OpenAIRE

    Hue-Tam Ho Tai

    2016-01-01

    Vietnam and China are currently engaged in a map war, with each country using ancient maps to buttress its claims to territorial sovereignty over some uninhabited islands in the South China Sea (in Chinese terminology), also known as the Eastern Sea (in Vietnamese). But what do maps in fact represent? What is meant by “territory”? How are territorial limits conceived? These questions were raised in a May 2015 workshop inspired by Thongchai Winichakul’s Siam Mapped: A History of the Geo-Body o...

  17. North America pipeline map

    International Nuclear Information System (INIS)

    Anon.

    2005-01-01

    This map presents details of pipelines currently in place throughout North America. Fifty-nine natural gas pipelines are presented, as well as 16 oil pipelines. The map also identifies six proposed natural gas pipelines. Major cities, roads and highways are included as well as state and provincial boundaries. The National Petroleum Reserve is identified, as well as the Arctic National Wildlife Refuge. The following companies placed advertisements on the map with details of the services they provide relating to pipeline management and construction: Ferus Gas Industries Trust; Proline; SulfaTreat Direct Oxidation; and TransGas. 1 map

  18. Open land use map

    OpenAIRE

    Mildorf, T.; Charvát, K.; Jezek, J.; Templer, Simon; Malewski, Christian

    2014-01-01

    Open Land Use Map is an initiative that has been started by the Plan4business project and that will be extended as part of the SDI4Apps project in the future. This service aims to create an improved worldwide land use map. The initial map will be prepared using the CORINE Land Cover, Global Cover dataset and Open Street Map. Contributors, mainly volunteers, will able to change the geometry and assign up-to-date land use according to the HILUCS specification. For certain regions more detailed ...

  19. The deep structure of the Sichuan basin and adjacent orogenic zones revealed by the aggregated deep seismic profiling datum

    Science.gov (United States)

    Xiong, X.; Gao, R.; Li, Q.; Wang, H.

    2012-12-01

    The sedimentary basin and the orogenic belt are the basic two tectonic units of the continental lithosphere, and form the basin-mountain coupling system, The research of which is the key element to the oil and gas exploration, the global tectonic theory and models and the development of the geological theory. The Sichuan basin and adjacent orogenic belts is one of the most ideal sites to research the issues above, in particular by the recent deep seismic profiling datum. From the 1980s to now, there are 11 deep seismic sounding profiles and 6 deep seismic reflection profiles and massive seismic broadband observation stations deployed around and crossed the Sichuan basin, which provide us a big opportunity to research the deep structure and other forward issues in this region. Supported by the National Natural Science Foundation of China (Grant No. 41104056) and the Fundamental Research Funds of the Institute of Geological Sciences, CAGS (No. J1119), we sampled the Moho depth and low-velocity zone depth and the Pn velocity of these datum, then formed the contour map of the Moho depth and Pn velocity by the interpolation of the sampled datum. The result shows the Moho depth beneath Sichuan basin ranges from 40 to 44 km, the sharp Moho offset appears in the western margin of the Sichuan basin, and there is a subtle Moho depression in the central southern part of the Sichuan basin; the P wave velocity can be 6.0 km/s at ca. 10 km deep, and increases gradually deeper, the average P wave velocity in this region is ca. 6.3 km/s; the Pn velocity is ca. 8.0-8.02 km/s in Sichuan basin, and 7.70-7.76 km/s in Chuan-Dian region; the low velocity zone appears in the western margin of the Sichuan basin, which maybe cause the cause of the earthquake.

  20. Deep Web and Dark Web: Deep World of the Internet

    OpenAIRE

    Çelik, Emine

    2018-01-01

    The Internet is undoubtedly still a revolutionary breakthrough in the history of humanity. Many people use the internet for communication, social media, shopping, political and social agenda, and more. Deep Web and Dark Web concepts not only handled by computer, software engineers but also handled by social siciensists because of the role of internet for the States in international arenas, public institutions and human life. By the moving point that very importantrole of internet for social s...

  1. DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

    Science.gov (United States)

    Wachinger, Christian; Reuter, Martin; Klein, Tassilo

    2018-04-15

    We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learning-based approach to brain segmentation that jointly learns an abstract feature representation and a multi-class classification. We propose a 3D patch-based approach, where we do not only predict the center voxel of the patch but also neighbors, which is formulated as multi-task learning. To address a class imbalance problem, we arrange two networks hierarchically, where the first one separates foreground from background, and the second one identifies 25 brain structures on the foreground. Since patches lack spatial context, we augment them with coordinates. To this end, we introduce a novel intrinsic parameterization of the brain volume, formed by eigenfunctions of the Laplace-Beltrami operator. As network architecture, we use three convolutional layers with pooling, batch normalization, and non-linearities, followed by fully connected layers with dropout. The final segmentation is inferred from the probabilistic output of the network with a 3D fully connected conditional random field, which ensures label agreement between close voxels. The roughly 2.7million parameters in the network are learned with stochastic gradient descent. Our results show that DeepNAT compares favorably to state-of-the-art methods. Finally, the purely learning-based method may have a high potential for the adaptation to young, old, or diseased brains by fine-tuning the pre-trained network with a small training sample on the target application, where the availability of larger datasets with manual annotations may boost the overall segmentation accuracy in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Deep Phenotyping: Deep Learning For Temporal Phenotype/Genotype Classification

    OpenAIRE

    Najafi, Mohammad; Namin, Sarah; Esmaeilzadeh, Mohammad; Brown, Tim; Borevitz, Justin

    2017-01-01

    High resolution and high throughput, genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. Complex developmental phenotypes are observed by imaging a variety of accessions in different environment conditions, however extracting the genetically heritable traits is challenging. In the recent years, deep learning techniques and in particular Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Long-Short Term Memories (LSTMs), h...

  3. Deep Neuromuscular Blockade Improves Laparoscopic Surgical Conditions

    DEFF Research Database (Denmark)

    Rosenberg, Jacob; Herring, W Joseph; Blobner, Manfred

    2017-01-01

    INTRODUCTION: Sustained deep neuromuscular blockade (NMB) during laparoscopic surgery may facilitate optimal surgical conditions. This exploratory study assessed whether deep NMB improves surgical conditions and, in doing so, allows use of lower insufflation pressures during laparoscopic cholecys...

  4. Joint Training of Deep Boltzmann Machines

    OpenAIRE

    Goodfellow, Ian; Courville, Aaron; Bengio, Yoshua

    2012-01-01

    We introduce a new method for training deep Boltzmann machines jointly. Prior methods require an initial learning pass that trains the deep Boltzmann machine greedily, one layer at a time, or do not perform well on classifi- cation tasks.

  5. DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

    Science.gov (United States)

    Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

    2017-07-18

    Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

  6. Building Program Vector Representations for Deep Learning

    OpenAIRE

    Mou, Lili; Li, Ge; Liu, Yuxuan; Peng, Hao; Jin, Zhi; Xu, Yan; Zhang, Lu

    2014-01-01

    Deep learning has made significant breakthroughs in various fields of artificial intelligence. Advantages of deep learning include the ability to capture highly complicated features, weak involvement of human engineering, etc. However, it is still virtually impossible to use deep learning to analyze programs since deep architectures cannot be trained effectively with pure back propagation. In this pioneering paper, we propose the "coding criterion" to build program vector representations, whi...

  7. Is Multitask Deep Learning Practical for Pharma?

    Science.gov (United States)

    Ramsundar, Bharath; Liu, Bowen; Wu, Zhenqin; Verras, Andreas; Tudor, Matthew; Sheridan, Robert P; Pande, Vijay

    2017-08-28

    Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks. Our work aims to resolve both of these barriers to adoption. We introduce a high-quality open-source implementation of multitask deep networks as part of the DeepChem open-source platform. Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models. We use our implementation to analyze the performance of multitask deep networks and related deep models on four collections of pharmaceutical data (three of which have not previously been analyzed in the literature). We split these data sets into train/valid/test using time and neighbor splits to test multitask deep learning performance under challenging conditions. Our results demonstrate that multitask deep networks are surprisingly robust and can offer strong improvement over random forests. Our analysis and open-source implementation in DeepChem provide an argument that multitask deep networks are ready for widespread use in commercial drug discovery.

  8. Evaluation of the DeepWind concept

    DEFF Research Database (Denmark)

    Schmidt Paulsen, Uwe; Borg, Michael; Gonzales Seabra, Luis Alberto

    The report describes the DeepWind 5 MW conceptual design as a baseline for results obtained in the scientific and technical work packages of the DeepWind project. A comparison of DeepWi nd with existing VAWTs and paper projects are carried out and the evaluation of the concept in terms of cost...

  9. Consolidated Deep Actor Critic Networks (DRAFT)

    NARCIS (Netherlands)

    Van der Laan, T.A.

    2015-01-01

    The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602, 2013.] and [Volodymyr et al. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 2015.] have demonstrated the power of combining deep neural networks with

  10. Simulator Studies of the Deep Stall

    Science.gov (United States)

    White, Maurice D.; Cooper, George E.

    1965-01-01

    Simulator studies of the deep-stall problem encountered with modern airplanes are discussed. The results indicate that the basic deep-stall tendencies produced by aerodynamic characteristics are augmented by operational considerations. Because of control difficulties to be anticipated in the deep stall, it is desirable that adequate safeguards be provided against inadvertent penetrations.

  11. TOPIC MODELING: CLUSTERING OF DEEP WEBPAGES

    OpenAIRE

    Muhunthaadithya C; Rohit J.V; Sadhana Kesavan; E. Sivasankar

    2015-01-01

    The internet is comprised of massive amount of information in the form of zillions of web pages.This information can be categorized into the surface web and the deep web. The existing search engines can effectively make use of surface web information.But the deep web remains unexploited yet. Machine learning techniques have been commonly employed to access deep web content.

  12. A Hybrid Vision-Map Method for Urban Road Detection

    Directory of Open Access Journals (Sweden)

    Carlos Fernández

    2017-01-01

    Full Text Available A hybrid vision-map system is presented to solve the road detection problem in urban scenarios. The standardized use of machine learning techniques in classification problems has been merged with digital navigation map information to increase system robustness. The objective of this paper is to create a new environment perception method to detect the road in urban environments, fusing stereo vision with digital maps by detecting road appearance and road limits such as lane markings or curbs. Deep learning approaches make the system hard-coupled to the training set. Even though our approach is based on machine learning techniques, the features are calculated from different sources (GPS, map, curbs, etc., making our system less dependent on the training set.

  13. On circle map coupled map lattice

    CERN Document Server

    Ahmed, E

    2002-01-01

    Circle map in one and two dimensions is studied. Both its stability, synchronization using bounded control and persistence is discussed. This work is expected to be applicable in ecology where spatial effects are known to be important. Also it will be relevant to systems where delay effects are not negligible.

  14. DeepFlavour in CMS

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Flavour-tagging of jets is an important task in collider based high energy physics and a field where machine learning tools are applied by all major experiments. A new tagger (DeepFlavour) was developed and commissioned in CMS that is based on an advanced machine learning procedure. A deep neural network is used to do multi-classification of jets that origin from a b-quark, two b-quarks, a c-quark, two c-quarks or light colored particles (u, d, s-quark or gluon). The performance was measured in both, data and simulation. The talk will also include the measured performance of all taggers in CMS. The different taggers and results will be discussed and compared with some focus on details of the newest tagger.

  15. Deep Learning for ECG Classification

    Science.gov (United States)

    Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

    2017-10-01

    The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

  16. Deep Space Habitat Concept Demonstrator

    Science.gov (United States)

    Bookout, Paul S.; Smitherman, David

    2015-01-01

    This project will develop, integrate, test, and evaluate Habitation Systems that will be utilized as technology testbeds and will advance NASA's understanding of alternative deep space mission architectures, requirements, and operations concepts. Rapid prototyping and existing hardware will be utilized to develop full-scale habitat demonstrators. FY 2014 focused on the development of a large volume Space Launch System (SLS) class habitat (Skylab Gen 2) based on the SLS hydrogen tank components. Similar to the original Skylab, a tank section of the SLS rocket can be outfitted with a deep space habitat configuration and launched as a payload on an SLS rocket. This concept can be used to support extended stay at the Lunar Distant Retrograde Orbit to support the Asteroid Retrieval Mission and provide a habitat suitable for human missions to Mars.

  17. Hybrid mask for deep etching

    KAUST Repository

    Ghoneim, Mohamed T.

    2017-08-10

    Deep reactive ion etching is essential for creating high aspect ratio micro-structures for microelectromechanical systems, sensors and actuators, and emerging flexible electronics. A novel hybrid dual soft/hard mask bilayer may be deposited during semiconductor manufacturing for deep reactive etches. Such a manufacturing process may include depositing a first mask material on a substrate; depositing a second mask material on the first mask material; depositing a third mask material on the second mask material; patterning the third mask material with a pattern corresponding to one or more trenches for transfer to the substrate; transferring the pattern from the third mask material to the second mask material; transferring the pattern from the second mask material to the first mask material; and/or transferring the pattern from the first mask material to the substrate.

  18. Mapping online consumer search

    NARCIS (Netherlands)

    Bronnenberg, B.J.; Kim, J.; Albuquerque, P.

    2011-01-01

    The authors propose a new method to visualize browsing behavior in so-called product search maps. Manufacturers can use these maps to understand how consumers search for competing products before choice, including how information acquisition and product search are organized along brands, product

  19. Map of Nasca Geoglyphs

    Science.gov (United States)

    Hanzalová, K.; Pavelka, K.

    2013-07-01

    The Czech Technical University in Prague in the cooperation with the University of Applied Sciences in Dresden (Germany) work on the Nasca Project. The cooperation started in 2004 and much work has been done since then. All work is connected with Nasca lines in southern Peru. The Nasca project started in 1995 and its main target is documentation and conservation of the Nasca lines. Most of the project results are presented as WebGIS application via Internet. In the face of the impending destruction of the soil drawings, it is possible to preserve this world cultural heritage for the posterity at least in a digital form. Creating of Nasca lines map is very useful. The map is in a digital form and it is also available as a paper map. The map contains planimetric component of the map, map lettering and altimetry. Thematic folder in this map is a vector layer of the geoglyphs in Nasca/Peru. Basis for planimetry are georeferenced satellite images, altimetry is created from digital elevation model. This map was created in ArcGis software.

  20. Mapping of Outdoor Classrooms.

    Science.gov (United States)

    Horvath, Victor G.

    Mapping symbols adopted by the Michigan Department of Natural Resources are presented with their explanations. In an effort to provide standardization and familiarity teachers and other school people involved in an outdoor education program are encouraged to utilize the same symbols in constructing maps. (DK)

  1. MAP OF NASCA GEOGLYPHS

    Directory of Open Access Journals (Sweden)

    K. Hanzalová

    2013-07-01

    Full Text Available The Czech Technical University in Prague in the cooperation with the University of Applied Sciences in Dresden (Germany work on the Nasca Project. The cooperation started in 2004 and much work has been done since then. All work is connected with Nasca lines in southern Peru. The Nasca project started in 1995 and its main target is documentation and conservation of the Nasca lines. Most of the project results are presented as WebGIS application via Internet. In the face of the impending destruction of the soil drawings, it is possible to preserve this world cultural heritage for the posterity at least in a digital form. Creating of Nasca lines map is very useful. The map is in a digital form and it is also available as a paper map. The map contains planimetric component of the map, map lettering and altimetry. Thematic folder in this map is a vector layer of the geoglyphs in Nasca/Peru. Basis for planimetry are georeferenced satellite images, altimetry is created from digital elevation model. This map was created in ArcGis software.

  2. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Sporring, Jon; Fogh Olsen, Ole

    2008-01-01

    . To address this problem, we introduce a photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way, we preserve important illumination features, while...

  3. Maps between Grassmann manifolds

    Indian Academy of Sciences (India)

    Parameswaran Sankaran Institute of Mathematical Sciences Chennai, India sankaran@imsc.res.in Indian Academy of Sciences Platinum Jubilee Meeting Hyderabad

    2009-07-02

    Jul 2, 2009 ... Classification of all manifolds (or maps between them) is an impossible task. The coarser, homotopical classification, is relatively easier–but only relatively! Homotopy is, roughly speaking, the study of properties of spaces and maps invariant under continuous deformations. Denote by [X, Y ] the set of all ...

  4. Constructing Maps Collaboratively.

    Science.gov (United States)

    Leinhardt, Gaea; Stainton, Catherine; Bausmith, Jennifer Merriman

    1998-01-01

    Summarizes a study that maintains that students who work together in small groups had a better understanding of map concepts. Discusses why making maps in groups can enhance students' conceptual geographic understanding and offers suggestions for improving geography instructions using small group configurations. Includes statistical and graphic…

  5. Algorithms for necklace maps

    NARCIS (Netherlands)

    Speckmann, B.; Verbeek, K.A.B.

    2015-01-01

    Necklace maps visualize quantitative data associated with regions by placing scaled symbols, usually disks, without overlap on a closed curve (the necklace) surrounding the map regions. Each region is projected onto an interval on the necklace that contains its symbol. In this paper we address the

  6. Text 2 Mind Map

    OpenAIRE

    Iona, John

    2017-01-01

    This is a review of the web resource 'Text 2 Mind Map' www.Text2MindMap.com. It covers what the resource is, and how it might be used in Library and education context, in particular for School Librarians.

  7. Formal genetic maps

    African Journals Online (AJOL)

    Mohammad Saad Zaghloul Salem

    2014-12-24

    Dec 24, 2014 ... ome/transcriptome/proteome, experimental induced maps that are intentionally designed and con- ... genetic maps imposed their application in nearly all fields of medical genetics including ..... or genes located adjacent to, or near, them. ...... types of markers, e.g., clinical markers (eye color), genomic.

  8. Soft-Deep Boltzmann Machines

    OpenAIRE

    Kiwaki, Taichi

    2015-01-01

    We present a layered Boltzmann machine (BM) that can better exploit the advantages of a distributed representation. It is widely believed that deep BMs (DBMs) have far greater representational power than its shallow counterpart, restricted Boltzmann machines (RBMs). However, this expectation on the supremacy of DBMs over RBMs has not ever been validated in a theoretical fashion. In this paper, we provide both theoretical and empirical evidences that the representational power of DBMs can be a...

  9. A deep learning framework for causal shape transformation.

    Science.gov (United States)

    Lore, Kin Gwn; Stoecklein, Daniel; Davies, Michael; Ganapathysubramanian, Baskar; Sarkar, Soumik

    2018-02-01

    Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information where the output is dependent on a sequence of inputs. However, in most considered problems, the dependencies typically lie in the latent domain which may not be suitable for applications involving the prediction of a step-wise transformation sequence that is dependent on the previous states only in the visible domain with a known terminal state. We propose a hybrid architecture of convolution neural networks (CNN) and stacked autoencoders (SAE) to learn a sequence of causal actions that nonlinearly transform an input visual pattern or distribution into a target visual pattern or distribution with the same support and demonstrated its practicality in a real-world engineering problem involving the physics of fluids. We solved a high-dimensional one-to-many inverse mapping problem concerning microfluidic flow sculpting, where the use of deep learning methods as an inverse map is very seldom explored. This work serves as a fruitful use-case to applied scientists and engineers in how deep learning can be beneficial as a solution for high-dimensional physical problems, and potentially opening doors to impactful advance in fields such as material sciences and medical biology where multistep topological transformations is a key element. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Evolving Deep Networks Using HPC

    Energy Technology Data Exchange (ETDEWEB)

    Young, Steven R. [ORNL, Oak Ridge; Rose, Derek C. [ORNL, Oak Ridge; Johnston, Travis [ORNL, Oak Ridge; Heller, William T. [ORNL, Oak Ridge; Karnowski, thomas P. [ORNL, Oak Ridge; Potok, Thomas E. [ORNL, Oak Ridge; Patton, Robert M. [ORNL, Oak Ridge; Perdue, Gabriel [Fermilab; Miller, Jonathan [Santa Maria U., Valparaiso

    2017-01-01

    While a large number of deep learning networks have been studied and published that produce outstanding results on natural image datasets, these datasets only make up a fraction of those to which deep learning can be applied. These datasets include text data, audio data, and arrays of sensors that have very different characteristics than natural images. As these “best” networks for natural images have been largely discovered through experimentation and cannot be proven optimal on some theoretical basis, there is no reason to believe that they are the optimal network for these drastically different datasets. Hyperparameter search is thus often a very important process when applying deep learning to a new problem. In this work we present an evolutionary approach to searching the possible space of network hyperparameters and construction that can scale to 18, 000 nodes. This approach is applied to datasets of varying types and characteristics where we demonstrate the ability to rapidly find best hyperparameters in order to enable practitioners to quickly iterate between idea and result.

  11. Deep Space Gateway Science Opportunities

    Science.gov (United States)

    Quincy, C. D.; Charles, J. B.; Hamill, Doris; Sidney, S. C.

    2018-01-01

    The NASA Life Sciences Research Capabilities Team (LSRCT) has been discussing deep space research needs for the last two years. NASA's programs conducting life sciences studies - the Human Research Program, Space Biology, Astrobiology, and Planetary Protection - see the Deep Space Gateway (DSG) as affording enormous opportunities to investigate biological organisms in a unique environment that cannot be replicated in Earth-based laboratories or on Low Earth Orbit science platforms. These investigations may provide in many cases the definitive answers to risks associated with exploration and living outside Earth's protective magnetic field. Unlike Low Earth Orbit or terrestrial locations, the Gateway location will be subjected to the true deep space spectrum and influence of both galactic cosmic and solar particle radiation and thus presents an opportunity to investigate their long-term exposure effects. The question of how a community of biological organisms change over time within the harsh environment of space flight outside of the magnetic field protection can be investigated. The biological response to the absence of Earth's geomagnetic field can be studied for the first time. Will organisms change in new and unique ways under these new conditions? This may be specifically true on investigations of microbial communities. The Gateway provides a platform for microbiology experiments both inside, to improve understanding of interactions between microbes and human habitats, and outside, to improve understanding of microbe-hardware interactions exposed to the space environment.

  12. Bodily maps of emotions.

    Science.gov (United States)

    Nummenmaa, Lauri; Glerean, Enrico; Hari, Riitta; Hietanen, Jari K

    2014-01-14

    Emotions are often felt in the body, and somatosensory feedback has been proposed to trigger conscious emotional experiences. Here we reveal maps of bodily sensations associated with different emotions using a unique topographical self-report method. In five experiments, participants (n = 701) were shown two silhouettes of bodies alongside emotional words, stories, movies, or facial expressions. They were asked to color the bodily regions whose activity they felt increasing or decreasing while viewing each stimulus. Different emotions were consistently associated with statistically separable bodily sensation maps across experiments. These maps were concordant across West European and East Asian samples. Statistical classifiers distinguished emotion-specific activation maps accurately, confirming independence of topographies across emotions. We propose that emotions are represented in the somatosensory system as culturally universal categorical somatotopic maps. Perception of these emotion-triggered bodily changes may play a key role in generating consciously felt emotions.

  13. Application of ecological mapping

    International Nuclear Information System (INIS)

    Sherk, J.A.

    1982-01-01

    The US Fish and Wildlife Service has initiated the production of a comprehensive ecological inventory map series for use as a major new planning tool. Important species data along with special land use designations are displayed on 1:250,000 scale topographic base maps. Sets of maps have been published for the Atlantic and Pacific coastal areas of the United States. Preparation of a map set for the Gulf of Mexico is underway at the present time. Potential application of ecological inventory map series information to a typical land disposal facility could occur during the narrowing of the number of possible disposal sites, the design of potential disposal site studies of ecological resources, the preparation of the environmental report, and the regulatory review of license applications. 3 figures, 3 tables

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

    Science.gov (United States)

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

    2017-12-01

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

  15. Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning

    Directory of Open Access Journals (Sweden)

    Yingfeng Cai

    2017-01-01

    Full Text Available Discriminative tracking methods use binary classification to discriminate between the foreground and background and have achieved some useful results. However, the use of labeled training samples is insufficient for them to achieve accurate tracking. Hence, discriminative classifiers must use their own classification results to update themselves, which may lead to feedback-induced tracking drift. To overcome these problems, we propose a semisupervised tracking algorithm that uses deep representation and transfer learning. Firstly, a 2D multilayer deep belief network is trained with a large amount of unlabeled samples. The nonlinear mapping point at the top of this network is subtracted as the feature dictionary. Then, this feature dictionary is utilized to transfer train and update a deep tracker. The positive samples for training are the tracked vehicles, and the negative samples are the background images. Finally, a particle filter is used to estimate vehicle position. We demonstrate experimentally that our proposed vehicle tracking algorithm can effectively restrain drift while also maintaining the adaption of vehicle appearance. Compared with similar algorithms, our method achieves a better tracking success rate and fewer average central-pixel errors.

  16. Diagnosis of deep venous thrombosis by radioisotopic phlebography

    International Nuclear Information System (INIS)

    Araujo, Antonio Luiz de

    1993-01-01

    The author studied 20 patients with deep venous thrombosis of members (one of them attacked on both arms), from various etiologies, by mean radioisotopic phlebography, in the Vascular Diseases, Radiology and Nuclear Medicine Services of Army Central Hospital (Rio de Janeiro, Brazil) from january 1988 to june 1990. The years old was 18 to 72. The cause most frequency of deep venous thrombosis was idiopathic (seven cases 33.3%). The presence of clot by radionuclide marker in all cases, 16 observations (76.2%) in the lower members and five in the upper extremities (23.9%); 17 cases (85%) also were a conventional venography and his images were confirmed. The diagnostic of deep venous thrombosis from 99m T c MAA (macro aggregate of albumin tagged with technetium) should always de complemented by pulmonary mapping, tracking possible silent emboli. Permit as well repetitions evolutionary until daily and using in patients with history of allergy to radiologic contrast because has not complication. (author)

  17. Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network

    Directory of Open Access Journals (Sweden)

    Yuexiang Li

    2018-02-01

    Full Text Available Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1, lesion dermoscopic feature extraction (task 2 and lesion classification (task 3. A deep learning framework consisting of two fully convolutional residual networks (FCRN is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.

  18. Deep sea mega-geomorphology: Progress and problems

    Science.gov (United States)

    Bryan, W. B.

    1985-01-01

    Historically, marine geologists have always worked with mega-scale morphology. This is a consequence both of the scale of the ocean basins and of the low resolution of the observational remote sensing tools available until very recently. In fact, studies of deep sea morphology have suffered from a serious gap in observational scale. Traditional wide-beam echo sounding gave images on a scale of miles, while deep sea photography has been limited to scales of a few tens of meters. Recent development of modern narrow-beam echo sounding coupled with computer-controlled swath mapping systems, and development of high-resolution deep-towed side-scan sonar, are rapidly filling in the scale gap. These technologies also can resolve morphologic detail on a scale of a few meters or less. As has also been true in planetary imaging projects, the ability to observe phenomena over a range of scales has proved very effective in both defining processes and in placing them in proper context.

  19. Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.

    Science.gov (United States)

    Li, Yuexiang; Shen, Linlin

    2018-02-11

    Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.

  20. Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network

    Science.gov (United States)

    2018-01-01

    Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved. PMID:29439500

  1. Deep SOMs for automated feature extraction and classification from big data streaming

    Science.gov (United States)

    Sakkari, Mohamed; Ejbali, Ridha; Zaied, Mourad

    2017-03-01

    In this paper, we proposed a deep self-organizing map model (Deep-SOMs) for automated features extracting and learning from big data streaming which we benefit from the framework Spark for real time streams and highly parallel data processing. The SOMs deep architecture is based on the notion of abstraction (patterns automatically extract from the raw data, from the less to more abstract). The proposed model consists of three hidden self-organizing layers, an input and an output layer. Each layer is made up of a multitude of SOMs, each map only focusing at local headmistress sub-region from the input image. Then, each layer trains the local information to generate more overall information in the higher layer. The proposed Deep-SOMs model is unique in terms of the layers architecture, the SOMs sampling method and learning. During the learning stage we use a set of unsupervised SOMs for feature extraction. We validate the effectiveness of our approach on large data sets such as Leukemia dataset and SRBCT. Results of comparison have shown that the Deep-SOMs model performs better than many existing algorithms for images classification.

  2. Deep UV Native Fluorescence Imaging of Antarctic Cryptoendolithic Communities

    Science.gov (United States)

    Storrie-Lombardi, M. C.; Douglas, S.; Sun, H.; McDonald, G. D.; Bhartia, R.; Nealson, K. H.; Hug, W. F.

    2001-01-01

    An interdisciplinary team at the Jet Propulsion Laboratory Center for Life Detection has embarked on a project to provide in situ chemical and morphological characterization of Antarctic cryptoendolithic microbial communities. We present here in situ deep ultraviolet (UV) native fluorescence and environmental scanning electron microscopy images transiting 8.5 mm into a sandstone sample from the Antarctic Dry Valleys. The deep ultraviolet imaging system employs 224.3, 248.6, and 325 nm lasers to elicit differential fluorescence and resonance Raman responses from biomolecules and minerals. The 224.3 and 248.6 nm lasers elicit a fluorescence response from the aromatic amino and nucleic acids. Excitation at 325 nm may elicit activity from a variety of biomolecules, but is more likely to elicit mineral fluorescence. The resultant fluorescence images provide in situ chemical and morphological maps of microorganisms and the associated organic matrix. Visible broadband reflectance images provide orientation against the mineral background. Environmental scanning electron micrographs provided detailed morphological information. The technique has made possible the construction of detailed fluorescent maps extending from the surface of an Antarctic sandstone sample to a depth of 8.5 mm. The images detect no evidence of microbial life in the superficial 0.2 mm crustal layer. The black lichen component between 0.3 and 0.5 mm deep absorbs all wavelengths of both laser and broadband illumination. Filamentous deep ultraviolet native fluorescent activity dominates in the white layer between 0.6 mm and 5.0 mm from the surface. These filamentous forms are fungi that continue into the red (iron-rich) region of the sample extending from 5.0 to 8.5 mm. Using differential image subtraction techniques it is possible to identify fungal nuclei. The ultraviolet response is markedly attenuated in this region, apparently from the absorption of ultraviolet light by iron-rich particles coating

  3. Deep water recycling through time.

    Science.gov (United States)

    Magni, Valentina; Bouilhol, Pierre; van Hunen, Jeroen

    2014-11-01

    We investigate the dehydration processes in subduction zones and their implications for the water cycle throughout Earth's history. We use a numerical tool that combines thermo-mechanical models with a thermodynamic database to examine slab dehydration for present-day and early Earth settings and its consequences for the deep water recycling. We investigate the reactions responsible for releasing water from the crust and the hydrated lithospheric mantle and how they change with subduction velocity ( v s ), slab age ( a ) and mantle temperature (T m ). Our results show that faster slabs dehydrate over a wide area: they start dehydrating shallower and they carry water deeper into the mantle. We parameterize the amount of water that can be carried deep into the mantle, W (×10 5 kg/m 2 ), as a function of v s (cm/yr), a (Myrs), and T m (°C):[Formula: see text]. We generally observe that a 1) 100°C increase in the mantle temperature, or 2) ∼15 Myr decrease of plate age, or 3) decrease in subduction velocity of ∼2 cm/yr all have the same effect on the amount of water retained in the slab at depth, corresponding to a decrease of ∼2.2×10 5 kg/m 2 of H 2 O. We estimate that for present-day conditions ∼26% of the global influx water, or 7×10 8 Tg/Myr of H 2 O, is recycled into the mantle. Using a realistic distribution of subduction parameters, we illustrate that deep water recycling might still be possible in early Earth conditions, although its efficiency would generally decrease. Indeed, 0.5-3.7 × 10 8 Tg/Myr of H 2 O could still be recycled in the mantle at 2.8 Ga. Deep water recycling might be possible even in early Earth conditions We provide a scaling law to estimate the amount of H 2 O flux deep into the mantle Subduction velocity has a a major control on the crustal dehydration pattern.

  4. Vision in the deep sea.

    Science.gov (United States)

    Warrant, Eric J; Locket, N Adam

    2004-08-01

    The deep sea is the largest habitat on earth. Its three great faunal environments--the twilight mesopelagic zone, the dark bathypelagic zone and the vast flat expanses of the benthic habitat--are home to a rich fauna of vertebrates and invertebrates. In the mesopelagic zone (150-1000 m), the down-welling daylight creates an extended scene that becomes increasingly dimmer and bluer with depth. The available daylight also originates increasingly from vertically above, and bioluminescent point-source flashes, well contrasted against the dim background daylight, become increasingly visible. In the bathypelagic zone below 1000 m no daylight remains, and the scene becomes entirely dominated by point-like bioluminescence. This changing nature of visual scenes with depth--from extended source to point source--has had a profound effect on the designs of deep-sea eyes, both optically and neurally, a fact that until recently was not fully appreciated. Recent measurements of the sensitivity and spatial resolution of deep-sea eyes--particularly from the camera eyes of fishes and cephalopods and the compound eyes of crustaceans--reveal that ocular designs are well matched to the nature of the visual scene at any given depth. This match between eye design and visual scene is the subject of this review. The greatest variation in eye design is found in the mesopelagic zone, where dim down-welling daylight and bio-luminescent point sources may be visible simultaneously. Some mesopelagic eyes rely on spatial and temporal summation to increase sensitivity to a dim extended scene, while others sacrifice this sensitivity to localise pinpoints of bright bioluminescence. Yet other eyes have retinal regions separately specialised for each type of light. In the bathypelagic zone, eyes generally get smaller and therefore less sensitive to point sources with increasing depth. In fishes, this insensitivity, combined with surprisingly high spatial resolution, is very well adapted to the

  5. The deep Canary poleward undercurrent

    Science.gov (United States)

    Velez-Belchi, P. J.; Hernandez-Guerra, A.; González-Pola, C.; Fraile, E.; Collins, C. A.; Machín, F.

    2012-12-01

    Poleward undercurrents are well known features in Eastern Boundary systems. In the California upwelling system (CalCEBS), the deep poleward flow has been observed along the entire outer continental shelf and upper-slope, using indirect methods based on geostrophic estimates and also using direct current measurements. The importance of the poleward undercurrents in the CalCEBS, among others, is to maintain its high productivity by means of the transport of equatorial Pacific waters all the way northward to Vancouver Island and the subpolar gyre but there is also concern about the low oxygen concentration of these waters. However, in the case of the Canary Current Eastern Boundary upwelling system (CanCEBS), there are very few observations of the poleward undercurrent. Most of these observations are short-term mooring records, or drifter trajectories of the upper-slope flow. Hence, the importance of the subsurface poleward flow in the CanCEBS has been only hypothesized. Moreover, due to the large differences between the shape of the coastline and topography between the California and the Canary Current system, the results obtained for the CalCEBS are not completely applicable to the CanCEBS. In this study we report the first direct observations of the continuity of the deep poleward flow of the Canary Deep Poleward undercurrent (CdPU) in the North-Africa sector of the CanCEBS, and one of the few direct observations in the North-Africa sector of the Canary Current eastern boundary. The results indicate that the Canary Island archipelago disrupts the deep poleward undercurrent even at depths where the flow is not blocked by the bathymetry. The deep poleward undercurrent flows west around the eastern-most islands and north east of the Conception Bank to rejoin the intermittent branch that follows the African slope in the Lanzarote Passage. This hypothesis is consistent with the AAIW found west of Lanzarote, as far as 17 W. But also, this hypothesis would be coherent

  6. The National Deep-Sea Coral and Sponge Database: A Comprehensive Resource for United States Deep-Sea Coral and Sponge Records

    Science.gov (United States)

    Dornback, M.; Hourigan, T.; Etnoyer, P.; McGuinn, R.; Cross, S. L.

    2014-12-01

    Research on deep-sea corals has expanded rapidly over the last two decades, as scientists began to realize their value as long-lived structural components of high biodiversity habitats and archives of environmental information. The NOAA Deep Sea Coral Research and Technology Program's National Database for Deep-Sea Corals and Sponges is a comprehensive resource for georeferenced data on these organisms in U.S. waters. The National Database currently includes more than 220,000 deep-sea coral records representing approximately 880 unique species. Database records from museum archives, commercial and scientific bycatch, and from journal publications provide baseline information with relatively coarse spatial resolution dating back as far as 1842. These data are complemented by modern, in-situ submersible observations with high spatial resolution, from surveys conducted by NOAA and NOAA partners. Management of high volumes of modern high-resolution observational data can be challenging. NOAA is working with our data partners to incorporate this occurrence data into the National Database, along with images and associated information related to geoposition, time, biology, taxonomy, environment, provenance, and accuracy. NOAA is also working to link associated datasets collected by our program's research, to properly archive them to the NOAA National Data Centers, to build a robust metadata record, and to establish a standard protocol to simplify the process. Access to the National Database is provided through an online mapping portal. The map displays point based records from the database. Records can be refined by taxon, region, time, and depth. The queries and extent used to view the map can also be used to download subsets of the database. The database, map, and website is already in use by NOAA, regional fishery management councils, and regional ocean planning bodies, but we envision it as a model that can expand to accommodate data on a global scale.

  7. What Will Science Gain From Mapping the World Ocean Floor?

    Science.gov (United States)

    Jakobsson, M.

    2017-12-01

    It is difficult to estimate how much of the World Ocean floor topography (bathymetry) that has been mapped. Estimates range from a few to more than ten percent of the World Ocean area. The most recent version of the bathymetric grid compiled by the General Bathymetric Chart of the Oceans (GEBCO) has bathymetric control points in 18% of the 30 x 30 arc second large grid cells. The depth values for the rest of the cells are obtained through interpolation guided by satellite altimetry in deep water. With this statistic at hand, it seems tenable to suggest that there are many scientific discoveries to be made from a complete high-resolution mapping of the World Ocean floor. In this presentation, some of our recent scientific discoveries based on modern multibeam bathymetric mapping will be highlighted and discussed. For example, how multibeam mapping provided evidence for a km-thick ice shelf covering the entire Arctic Ocean during peak glacial conditions, a hypothesis proposed nearly half a century ago, and how groundwater escape features are visible in high-resolution bathymetry in the Baltic Sea, with potential implications for the freshwater budget and distribution of nutrients and pollutants. Presented examples will be placed in the context of mapping resolution, systematic surveys versus mapping along transits, and scientific hypothesis driven mapping versus ocean exploration. The newly announced Nippon Foundation - GEBCO Seabed 2030 project has the vision to map 100% of the World Ocean floor mapped by 2030. Are there specific scientific areas where we can expect new discoveries from all mapping data collected through the Seabed 2030 project? Are there outstanding hypothesis that can be tested from a fully mapped World Ocean floor?

  8. Deep iCrawl: An Intelligent Vision-Based Deep Web Crawler

    OpenAIRE

    R.Anita; V.Ganga Bharani; N.Nityanandam; Pradeep Kumar Sahoo

    2011-01-01

    The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based app...

  9. Geoseq: a tool for dissecting deep-sequencing datasets

    Directory of Open Access Journals (Sweden)

    Homann Robert

    2010-10-01

    Full Text Available Abstract Background Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO, Sequence Read Archive (SRA hosted by the NCBI, or the DNA Data Bank of Japan (ddbj. Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Results Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Conclusions Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a identify differential isoform expression in mRNA-seq datasets, b identify miRNAs (microRNAs in libraries, and identify mature and star sequences in miRNAS and c to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool.

  10. USGS Topo Base Map from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The USGS Topographic Base Map from The National Map. This tile cached web map service combines the most current data services (Boundaries, Names, Transportation,...

  11. Analyzing thematic maps and mapping for accuracy

    Science.gov (United States)

    Rosenfield, G.H.

    1982-01-01

    Two problems which exist while attempting to test the accuracy of thematic maps and mapping are: (1) evaluating the accuracy of thematic content, and (2) evaluating the effects of the variables on thematic mapping. Statistical analysis techniques are applicable to both these problems and include techniques for sampling the data and determining their accuracy. In addition, techniques for hypothesis testing, or inferential statistics, are used when comparing the effects of variables. A comprehensive and valid accuracy test of a classification project, such as thematic mapping from remotely sensed data, includes the following components of statistical analysis: (1) sample design, including the sample distribution, sample size, size of the sample unit, and sampling procedure; and (2) accuracy estimation, including estimation of the variance and confidence limits. Careful consideration must be given to the minimum sample size necessary to validate the accuracy of a given. classification category. The results of an accuracy test are presented in a contingency table sometimes called a classification error matrix. Usually the rows represent the interpretation, and the columns represent the verification. The diagonal elements represent the correct classifications. The remaining elements of the rows represent errors by commission, and the remaining elements of the columns represent the errors of omission. For tests of hypothesis that compare variables, the general practice has been to use only the diagonal elements from several related classification error matrices. These data are arranged in the form of another contingency table. The columns of the table represent the different variables being compared, such as different scales of mapping. The rows represent the blocking characteristics, such as the various categories of classification. The values in the cells of the tables might be the counts of correct classification or the binomial proportions of these counts divided by

  12. Deep Corals, Deep Learning: Moving the Deep Net Towards Real-Time Image Annotation

    OpenAIRE

    Lea-Anne Henry; Sankha S. Mukherjee; Neil M. Roberston; Laurence De Clippele; J. Murray Roberts

    2016-01-01

    The mismatch between human capacity and the acquisition of Big Data such as Earth imagery undermines commitments to Convention on Biological Diversity (CBD) and Aichi targets. Artificial intelligence (AI) solutions to Big Data issues are urgently needed as these could prove to be faster, more accurate, and cheaper. Reducing costs of managing protected areas in remote deep waters and in the High Seas is of great importance, and this is a realm where autonomous technology will be transformative.

  13. Invited talk: Deep Learning Meets Physics

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Deep Learning has emerged as one of the most successful fields of machine learning and artificial intelligence with overwhelming success in industrial speech, text and vision benchmarks. Consequently it evolved into the central field of research for IT giants like Google, facebook, Microsoft, Baidu, and Amazon. Deep Learning is founded on novel neural network techniques, the recent availability of very fast computers, and massive data sets. In its core, Deep Learning discovers multiple levels of abstract representations of the input. The main obstacle to learning deep neural networks is the vanishing gradient problem. The vanishing gradient impedes credit assignment to the first layers of a deep network or to early elements of a sequence, therefore limits model selection. Major advances in Deep Learning can be related to avoiding the vanishing gradient like stacking, ReLUs, residual networks, highway networks, and LSTM. For Deep Learning, we suggested self-normalizing neural networks (SNNs) which automatica...

  14. Color on emergency mapping

    Science.gov (United States)

    Jiang, Lili; Qi, Qingwen; Zhang, An

    2007-06-01

    There are so many emergency issues in our daily life. Such as typhoons, tsunamis, earthquake, fires, floods, epidemics, etc. These emergencies made people lose their lives and their belongings. Every day, every hour, even every minute people probably face the emergency, so how to handle it and how to decrease its hurt are the matters people care most. If we can map it exactly before or after the emergencies; it will be helpful to the emergency researchers and people who live in the emergency place. So , through the emergency map, before emergency is occurring we can predict the situation, such as when and where the emergency will be happen; where people can refuge, etc. After disaster, we can also easily assess the lost, discuss the cause and make the lost less. The primary effect of mapping is offering information to the people who care about the emergency and the researcher who want to study it. Mapping allows the viewers to get a spatial sense of hazard. It can also provide the clues to study the relationship of the phenomenon in emergency. Color, as the basic element of the map, it can simplify and clarify the phenomenon. Color can also affects the general perceptibility of the map, and elicits subjective reactions to the map. It is to say, structure, readability, and the reader's psychological reactions can be affected by the use of color.

  15. Cognitive maps and attention.

    Science.gov (United States)

    Hardt, Oliver; Nadel, Lynn

    2009-01-01

    Cognitive map theory suggested that exploring an environment and attending to a stimulus should lead to its integration into an allocentric environmental representation. We here report that directed attention in the form of exploration serves to gather information needed to determine an optimal spatial strategy, given task demands and characteristics of the environment. Attended environmental features may integrate into spatial representations if they meet the requirements of the optimal spatial strategy: when learning involves a cognitive mapping strategy, cues with high codability (e.g., concrete objects) will be incorporated into a map, but cues with low codability (e.g., abstract paintings) will not. However, instructions encouraging map learning can lead to the incorporation of cues with low codability. On the other hand, if spatial learning is not map-based, abstract cues can and will be used to encode locations. Since exploration appears to determine what strategy to apply and whether or not to encode a cue, recognition memory for environmental features is independent of whether or not a cue is part of a spatial representation. In fact, when abstract cues were used in a way that was not map-based, or when they were not used for spatial navigation at all, they were nevertheless recognized as familiar. Thus, the relation between exploratory activity on the one hand and spatial strategy and memory on the other appears more complex than initially suggested by cognitive map theory.

  16. Quantitative Susceptibility Mapping in Parkinson's Disease.

    Science.gov (United States)

    Langkammer, Christian; Pirpamer, Lukas; Seiler, Stephan; Deistung, Andreas; Schweser, Ferdinand; Franthal, Sebastian; Homayoon, Nina; Katschnig-Winter, Petra; Koegl-Wallner, Mariella; Pendl, Tamara; Stoegerer, Eva Maria; Wenzel, Karoline; Fazekas, Franz; Ropele, Stefan; Reichenbach, Jürgen Rainer; Schmidt, Reinhold; Schwingenschuh, Petra

    2016-01-01

    Quantitative susceptibility mapping (QSM) and R2* relaxation rate mapping have demonstrated increased iron deposition in the substantia nigra of patients with idiopathic Parkinson's disease (PD). However, the findings in other subcortical deep gray matter nuclei are converse and the sensitivity of QSM and R2* for morphological changes and their relation to clinical measures of disease severity has so far been investigated only sparsely. The local ethics committee approved this study and all subjects gave written informed consent. 66 patients with idiopathic Parkinson's disease and 58 control subjects underwent quantitative MRI at 3T. Susceptibility and R2* maps were reconstructed from a spoiled multi-echo 3D gradient echo sequence. Mean susceptibilities and R2* rates were measured in subcortical deep gray matter nuclei and compared between patients with PD and controls as well as related to clinical variables. Compared to control subjects, patients with PD had increased R2* values in the substantia nigra. QSM also showed higher susceptibilities in patients with PD in substantia nigra, in the nucleus ruber, thalamus, and globus pallidus. Magnetic susceptibility of several of these structures was correlated with the levodopa-equivalent daily dose (LEDD) and clinical markers of motor and non-motor disease severity (total MDS-UPDRS, MDS-UPDRS-I and II). Disease severity as assessed by the Hoehn & Yahr scale was correlated with magnetic susceptibility in the substantia nigra. The established finding of higher R2* rates in the substantia nigra was extended by QSM showing superior sensitivity for PD-related tissue changes in nigrostriatal dopaminergic pathways. QSM additionally reflected the levodopa-dosage and disease severity. These results suggest a more widespread pathologic involvement and QSM as a novel means for its investigation, more sensitive than current MRI techniques.

  17. Analysis of ONKALO water leakage mapping results

    International Nuclear Information System (INIS)

    Ahokas, H.; Nummela, J; Turku, J.

    2014-04-01

    As part of the programme for the final disposal of spent nuclear fuel, an analysis has been compiled of water leakage mapping performed in ONKALO. Leakage mapping is part of the Olkiluoto Monitoring Programme (OMO) and the field work has been carried out by Posiva Oy. The main objective of the study is to analyse differences detected between mapping campaigns carried out typically twice a year in 2005-2012. Differences were estimated to be caused by the differences in groundwater conditions caused by seasonal effects or by differences between the years. The effect of technical changes like shotcreting, postgrouting, ventilation etc. on the results was also studied. The development of the visualisation of mapping results was also an objective of this work. Leakage mapping results have been reported yearly in the monitoring reports of Hydrology with some brief comments on the detected differences. In this study, the development of the total area and the number of different leakages as well as the correlation of changes with shotcreting and grouting operations were studied. In addition, traces of fractures on tunnel surfaces, and the location of rock bolts and drain pipes were illustrated together with leakage mapping. In water leakage mapping, the tunnel surfaces are visually mapped to five categories: dry, damp, wet, dripping and flowing. Major changes were detected in the total area of damp leakages. It is likely that the increase has been caused by the condensation of warm ventilation air on the tunnel surfaces and the corresponding decrease by the evaporation of moisture into the dry ventilation air. Shotcreting deep in ONKALO may also have decreased the total area of damp leakages. Changes in the total area and number of wet leakages correlate at least near the surface with differences in yearly precipitation. It is possible that strong rains have also caused a temporary increase in wet leakages. Dripping and wet leakages have been observed on average more

  18. Analysis of ONKALO water leakage mapping results

    Energy Technology Data Exchange (ETDEWEB)

    Ahokas, H.; Nummela, J; Turku, J. [Poeyry Finland Oy, Vantaa (Finland)

    2014-04-15

    As part of the programme for the final disposal of spent nuclear fuel, an analysis has been compiled of water leakage mapping performed in ONKALO. Leakage mapping is part of the Olkiluoto Monitoring Programme (OMO) and the field work has been carried out by Posiva Oy. The main objective of the study is to analyse differences detected between mapping campaigns carried out typically twice a year in 2005-2012. Differences were estimated to be caused by the differences in groundwater conditions caused by seasonal effects or by differences between the years. The effect of technical changes like shotcreting, postgrouting, ventilation etc. on the results was also studied. The development of the visualisation of mapping results was also an objective of this work. Leakage mapping results have been reported yearly in the monitoring reports of Hydrology with some brief comments on the detected differences. In this study, the development of the total area and the number of different leakages as well as the correlation of changes with shotcreting and grouting operations were studied. In addition, traces of fractures on tunnel surfaces, and the location of rock bolts and drain pipes were illustrated together with leakage mapping. In water leakage mapping, the tunnel surfaces are visually mapped to five categories: dry, damp, wet, dripping and flowing. Major changes were detected in the total area of damp leakages. It is likely that the increase has been caused by the condensation of warm ventilation air on the tunnel surfaces and the corresponding decrease by the evaporation of moisture into the dry ventilation air. Shotcreting deep in ONKALO may also have decreased the total area of damp leakages. Changes in the total area and number of wet leakages correlate at least near the surface with differences in yearly precipitation. It is possible that strong rains have also caused a temporary increase in wet leakages. Dripping and wet leakages have been observed on average more

  19. Deep learning with convolutional neural networks for EEG decoding and visualization

    Science.gov (United States)

    Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

    2017-01-01

    Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

  20. Crowdsourcing The National Map

    Science.gov (United States)

    McCartney, Elizabeth; Craun, Kari J.; Korris, Erin M.; Brostuen, David A.; Moore, Laurence R.

    2015-01-01

    Using crowdsourcing techniques, the US Geological Survey’s (USGS) Volunteered Geographic Information (VGI) project known as “The National Map Corps (TNMCorps)” encourages citizen scientists to collect and edit data about man-made structures in an effort to provide accurate and authoritative map data for the USGS National Geospatial Program’s web-based The National Map. VGI is not new to the USGS, but past efforts have been hampered by available technologies. Building on lessons learned, TNMCorps volunteers are successfully editing 10 different structure types in all 50 states as well as Puerto Rico and the US Virgin Islands.

  1. Region & Gateway Mapping

    OpenAIRE

    Schröter, Derik

    2007-01-01

    State-of-the-art robot mapping approaches are capable of acquiring impressively accurate 2D and 3D models of their environments. To the best of our knowledge, few of them represent structure or acquire models of task-relevant objects. In this work, a new approach to mapping of indoor environments is presented, in which the environment structure in terms of regions and gateways is automatically extracted, while the robot explores. Objects, both in 2D and 3D, are modeled explicitly in those map...

  2. MUTYH Associated Polyposis (MAP)

    DEFF Research Database (Denmark)

    Poulsen, Marie Louise Mølgaard; Bisgaard, M L

    2008-01-01

    Adenomatous Polyposis (FAP) and to a lesser extend Lynch Syndrome, which are caused by germline mutations in the APC and Mismatch Repair (MMR) genes, respectively.Here we review research findings regarding MUTYH interactions, genotypic and phenotypic characteristics of MAP, as well as surveillance......MUTYH Associated Polyposis (MAP), a Polyposis predisposition caused by biallelic mutations in the Base Excision Repair (BER) gene MUTYH, confers a marked risk of colorectal cancer (CRC). The MAP phenotype is difficult to distinguish from other hereditary CRC syndromes. Especially from Familial...

  3. Elevation data for floodplain mapping

    National Research Council Canada - National Science Library

    Committee on Floodplain Mapping Technologies; National Research Council; Division on Earth and Life Studies; National Research Council

    2007-01-01

    .... Elevation Data for Floodplain Mapping shows that there is sufficient two-dimensional base map imagery to meet FEMA's flood map modernization goals, but that the three-dimensional base elevation data...

  4. Northern Hemisphere Synoptic Weather Maps

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Daily Series of Synoptic Weather Maps. Part I consists of plotted and analyzed daily maps of sea-level and 500-mb maps for 0300, 0400, 1200, 1230, 1300, and 1500...

  5. DOT Official County Highway Map

    Data.gov (United States)

    Minnesota Department of Natural Resources — The County Highway Map theme is a scanned and rectified version of the original MnDOT County Highway Map Series. The cultural features on some of these maps may be...

  6. Tools for mapping ecosystem services

    Science.gov (United States)

    Palomo, Ignacio; Adamescu, Mihai; Bagstad, Kenneth J.; Cazacu, Constantin; Klug, Hermann; Nedkov, Stoyan; Burkhard, Benjamin; Maes, Joachim

    2017-01-01

    Mapping tools have evolved impressively in recent decades. From early computerised mapping techniques to current cloud-based mapping approaches, we have witnessed a technological evolution that has facilitated the democratisation of Geographic Information

  7. Deep Interior: Multiple-Rendezvous Prospecting of NEOs

    Science.gov (United States)

    Kakuda, R. Y.; Asphaug, E.; Belton, M. J. S.; Gulkis, S.; Huebner, W. F.

    2000-10-01

    This is an international multiple-rendezvous mission designed to prospect the deep interior and subsurface geophysical properties of diverse near-Earth objects, using reflection radar tomography, imaging, gravity, and explosions. What we learn will greatly influence future missions and guide strategies for the diversion, disruption, or utilization of potentially hazardous objects. Deep Interior. Low-frequency radar to determine internal variations of complex permittivity at resolutions approaching 20 m. Map inclusions or voids, fracture geometries, and compositional or structural boundaries. Subsurface. High-frequency radar to determine depth of regolith, existence and nature of cometary mantle, geology beneath and around craters, and subsurface expressions to surface geology. Topography and Geodesy. Stereogrammetric imaging with 1 m/pixel spatial resolution, supplemented by radar altimetry in shadowed regions, to determine detailed shape, volume, and spin state. Compare with radar sounding to learn how internal structure is manifested on the surface. Mass and Density. Total mass and lower moments of the internal mass distribution by mapping the exterior gravitational field. Look for mass concentrations. Surface microphysics and composition. Map color, albedo, and scattering properties of the surface over sunlit regions in six optical filters. Material properties. Deploy grenades to characterize the mechanics and dynamics of surface materials. Record 8 frame/sec, 20 cm/pixel videos of crater formation and ejecta dynamics, to enable simple and direct laboratory constraints on material density, cohesion and porosity. Dust. Look for dust lofted by surface waves propagating from the explosions, to constrain elastic properties and attenuation. Observe longer-term dynamics and optical properties of dust "atmosphere" generated by human activity. Cometary Activity. At comet 107P/Wilson-Harrington, look for expressions of past cometary activity, and for possible awakening

  8. Deep-water northern Gulf of Mexico hydrocarbon plays

    International Nuclear Information System (INIS)

    Peterson, R.H.; Cooke, D.W.

    1995-01-01

    The geologic setting in the deep-water (depths greater than 1,500 feet) Gulf of Mexico is very favorable for the existence of large, commercial hydrocarbon accumulations. These areas have active salt tectonics that create abundant traps, underlying mature Mesozoic source rocks that can be observed expelling oil and gas to the ocean surface, and good quality reservoirs provided by turbidite sand deposits. Despite the limited amount of drilling in the deep-water Gulf of Mexico, 11 deep-water accumulations have been discovered which, when developed, will rank in the top 100 largest fields in the Gulf of Mexico. Proved field discoveries (those with announced development plans) have added over 1 billion barrels of oil equivalent to Gulf of Mexico reserves, and unproved field discoveries may add to additional billion barrels of oil equivalent. The Minerals Management Service, United States Department of the Interior, has completed a gulf-wide review of over 1,086 oil and gas fields and placed every pay sand in each field into a hydrocarbon play (plays are defined by chronostratigraphy, lithostratigraph, structure, and production). Seven productive hydrocarbon plays were identified in the deep-water northern Gulf of Mexico. Regional maps illustrate the productive limits of each play. In addition, field data, dry holes, and wells with sub-economic pay were added to define the facies and structural limits for each play. Areas for exploration potential are identified for each hydrocarbon play. A type field for each play is chosen to demonstrate the play's characteristics

  9. Deep remission: a new concept?

    Science.gov (United States)

    Colombel, Jean-Frédéric; Louis, Edouard; Peyrin-Biroulet, Laurent; Sandborn, William J; Panaccione, Remo

    2012-01-01

    Crohn's disease (CD) is a chronic inflammatory disorder characterized by periods of clinical remission alternating with periods of relapse defined by recurrent clinical symptoms. Persistent inflammation is believed to lead to progressive bowel damage over time, which manifests with the development of strictures, fistulae and abscesses. These disease complications frequently lead to a need for surgical resection, which in turn leads to disability. So CD can be characterized as a chronic, progressive, destructive and disabling disease. In rheumatoid arthritis, treatment paradigms have evolved beyond partial symptom control alone toward the induction and maintenance of sustained biological remission, also known as a 'treat to target' strategy, with the goal of improving long-term disease outcomes. In CD, there is currently no accepted, well-defined, comprehensive treatment goal that entails the treatment of both clinical symptoms and biologic inflammation. It is important that such a treatment concept begins to evolve for CD. A treatment strategy that delays or halts the progression of CD to increasing damage and disability is a priority. As a starting point, a working definition of sustained deep remission (that includes long-term biological remission and symptom control) with defined patient outcomes (including no disease progression) has been proposed. The concept of sustained deep remission represents a goal for CD management that may still evolve. It is not clear if the concept also applies to ulcerative colitis. Clinical trials are needed to evaluate whether treatment algorithms that tailor therapy to achieve deep remission in patients with CD can prevent disease progression and disability. Copyright © 2012 S. Karger AG, Basel.

  10. Automated Plantation Mapping in Indonesia Using Remote Sensing Data

    Science.gov (United States)

    Karpatne, A.; Jia, X.; Khandelwal, A.; Kumar, V.

    2017-12-01

    Plantation mapping is critical for understanding and addressing deforestation, a key driver of climate change and ecosystem degradation. Unfortunately, most plantation maps are limited to small areas for specific years because they rely on visual inspection of imagery. In this work, we propose a data-driven approach which automatically generates yearly plantation maps for large regions using MODIS multi-spectral data. While traditional machine learning algorithms face manifold challenges in this task, e.g. imperfect training labels, spatio-temporal data heterogeneity, noisy and high-dimensional data, lack of evaluation data, etc., we introduce a novel deep learning-based framework that combines existing imperfect plantation products as training labels and models the spatio-temporal relationships of land covers. We also explores the post-processing steps based on Hidden Markov Model that further improve the detection accuracy. Then we conduct extensive evaluation of the generated plantation maps. Specifically, by randomly sampling and comparing with high-resolution Digital Globe imagery, we demonstrate that the generated plantation maps achieve both high precision and high recall. When compared with existing plantation mapping products, our detection can avoid both false positives and false negatives. Finally, we utilize the generated plantation maps in analyzing the relationship between forest fires and growth of plantations, which assists in better understanding the cause of deforestation in Indonesia.

  11. Topics in deep inelastic scattering

    International Nuclear Information System (INIS)

    Wandzura, S.M.

    1977-01-01

    Several topics in deep inelastic lepton--nucleon scattering are discussed, with emphasis on the structure functions appearing in polarized experiments. The major results are: infinite set of new sum rules reducing the number of independent spin dependent structure functions (for electroproduction) from two to one; the application of the techniques of Nachtmann to extract the coefficients appearing in the Wilson operator product expansion; and radiative corrections to the Wilson coefficients of free field theory. Also discussed are the use of dimensional regularization to simplify the calculation of these radiative corrections

  12. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  13. Haz-Map

    Data.gov (United States)

    U.S. Department of Health & Human Services — Haz-Map is an occupational health database designed for health and safety professionals and for consumers seeking information about the adverse effects of workplace...

  14. TOXMAP®: Environmental Health Maps

    Data.gov (United States)

    U.S. Department of Health & Human Services — TOXMAP® is a Geographic Information System (GIS) that uses maps of the United States and Canada to help users visually explore data primarily from the EPA's Toxics...

  15. The CPD Maps System

    Data.gov (United States)

    Department of Housing and Urban Development — CPD Maps includes data on the locations of existing CDBG, HOME, public housing and other HUD-funded community assets, so that users can view past investments...

  16. MetaMap

    Data.gov (United States)

    U.S. Department of Health & Human Services — MetaMap is a highly configurable application developed by the Lister Hill National Center for Biomedical Communications at the National Library of Medicine (NLM) to...

  17. FLOODPLAIN MAPPING, Bandera, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Floodplain Mapping/Redelineation study deliverables depict and quantify the flood risks for the study area. The primary risk classifications used are the...

  18. FLOODPLAIN MAPPING, Atascosa, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Floodplain Mapping/Redelineation study deliverables depict and quantify the flood risks for the study area. The primary risk classifications used are the...

  19. Public Waters Inventory Maps

    Data.gov (United States)

    Minnesota Department of Natural Resources — This theme is a scanned and rectified version of the Minnesota DNR - Division of Waters "Public Waters Inventory" (PWI) maps. DNR Waters utilizes a small scale...

  20. Daily Weather Maps

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Several different government offices have published the Daily weather maps over its history. The publication has also gone by different names over time. The U.S....

  1. Mapping Intermediality in Performance

    NARCIS (Netherlands)

    2010-01-01

    Mapping Intermediality in Performance benadert het vraagstuk van intermedialiteit met betrekking tot performance (vooral theater) vanuit vijf verschillende invalshoeken: performativiteit en lichaam; tijd en ruimte; digitale cultuur en posthumanisme; netwerken; pedagogiek en praxis. In deze boeiende

  2. Mapping the HISS Dipole

    International Nuclear Information System (INIS)

    McParland, C.; Bieser, F.

    1984-01-01

    The principal component of the Bevalac HISS facility is a large super-conducting 3 Tesla dipole. The facility's need for a large magnetic volume spectrometer resulted in a large gap geometry - a 2 meter pole tip diameter and a 1 meter pole gap. Obviously, the field required detailed mapping for effective use as a spectrometer. The mapping device was designed with several major features in mind. The device would measure field values on a grid which described a closed rectangular solid. The grid would be a regular with the exact measurement intervals adjustable by software. The device would function unattended over the long period of time required to complete a field map. During this time, the progress of the map could be monitored by anyone with access to the HISS VAX computer. Details of the mechanical, electrical, and control design follow

  3. NOS Bathymetric Maps

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This collection of bathymetric contour maps which represent the seafloor topography includes over 400 individual titles and covers US offshore areas including Hawaii...

  4. Survey on Ontology Mapping

    Science.gov (United States)

    Zhu, Junwu

    To create a sharable semantic space in which the terms from different domain ontology or knowledge system, Ontology mapping become a hot research point in Semantic Web Community. In this paper, motivated factors of ontology mapping research are given firstly, and then 5 dominating theories and methods, such as information accessing technology, machine learning, linguistics, structure graph and similarity, are illustrated according their technology class. Before we analyses the new requirements and takes a long view, the contributions of these theories and methods are summarized in details. At last, this paper suggest to design a group of semantic connector with the ability of migration learning for OWL-2 extended with constrains and the ontology mapping theory of axiom, so as to provide a new methodology for ontology mapping.

  5. Interest rates mapping

    Science.gov (United States)

    Kanevski, M.; Maignan, M.; Pozdnoukhov, A.; Timonin, V.

    2008-06-01

    The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a two-dimensional feature space-time and maturity. Exploratory data analysis includes a variety of tools widely used in econophysics and geostatistics. Geostatistical models and machine learning algorithms (multilayer perceptron and Support Vector Machines) were applied to produce interest rate maps. IR maps can be used for the visualisation and pattern perception purposes, to develop and to explore economical hypotheses, to produce dynamic asset-liability simulations and for financial risk assessments. The feasibility of an application of interest rates mapping approach for the IRC forecasting is considered as well.

  6. National Coastal Mapping Program

    Data.gov (United States)

    Army Corps of Engineers, Department of the Army, Department of Defense — The U. S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP) is designed to provide high-resolution elevation and imagery data along U.S....

  7. BaseMap

    Data.gov (United States)

    California Natural Resource Agency — The goal of this project is to provide a convenient base map that can be used as a starting point for CA projects. It's simple, but designed to work at a number of...

  8. Stochasticity in the Josephson map

    International Nuclear Information System (INIS)

    Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.

    1996-04-01

    The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)

  9. Deep Space Network Antenna Logic Controller

    Science.gov (United States)

    Ahlstrom, Harlow; Morgan, Scott; Hames, Peter; Strain, Martha; Owen, Christopher; Shimizu, Kenneth; Wilson, Karen; Shaller, David; Doktomomtaz, Said; Leung, Patrick

    2007-01-01

    The Antenna Logic Controller (ALC) software controls and monitors the motion control equipment of the 4,000-metric-ton structure of the Deep Space Network 70-meter antenna. This program coordinates the control of 42 hydraulic pumps, while monitoring several interlocks for personnel and equipment safety. Remote operation of the ALC runs via the Antenna Monitor & Control (AMC) computer, which orchestrates the tracking functions of the entire antenna. This software provides a graphical user interface for local control, monitoring, and identification of faults as well as, at a high level, providing for the digital control of the axis brakes so that the servo of the AMC may control the motion of the antenna. Specific functions of the ALC also include routines for startup in cold weather, controlled shutdown for both normal and fault situations, and pump switching on failure. The increased monitoring, the ability to trend key performance characteristics, the improved fault detection and recovery, the centralization of all control at a single panel, and the simplification of the user interface have all reduced the required workforce to run 70-meter antennas. The ALC also increases the antenna availability by reducing the time required to start up the antenna, to diagnose faults, and by providing additional insight into the performance of key parameters that aid in preventive maintenance to avoid key element failure. The ALC User Display (AUD) is a graphical user interface with hierarchical display structure, which provides high-level status information to the operation of the ALC, as well as detailed information for virtually all aspects of the ALC via drill-down displays. The operational status of an item, be it a function or assembly, is shown in the higher-level display. By pressing the item on the display screen, a new screen opens to show more detail of the function/assembly. Navigation tools and the map button allow immediate access to all screens.

  10. Invited Article: Deep Impact instrument calibration

    International Nuclear Information System (INIS)

    Klaasen, Kenneth P.; Mastrodemos, Nickolaos; A'Hearn, Michael F.; Farnham, Tony; Groussin, Olivier; Ipatov, Sergei; Li Jianyang; McLaughlin, Stephanie; Sunshine, Jessica; Wellnitz, Dennis; Baca, Michael; Delamere, Alan; Desnoyer, Mark; Thomas, Peter; Hampton, Donald; Lisse, Carey

    2008-01-01

    Calibration of NASA's Deep Impact spacecraft instruments allows reliable scientific interpretation of the images and spectra returned from comet Tempel 1. Calibrations of the four onboard remote sensing imaging instruments have been performed in the areas of geometric calibration, spatial resolution, spectral resolution, and radiometric response. Error sources such as noise (random, coherent, encoding, data compression), detector readout artifacts, scattered light, and radiation interactions have been quantified. The point spread functions (PSFs) of the medium resolution instrument and its twin impactor targeting sensor are near the theoretical minimum [∼1.7 pixels full width at half maximum (FWHM)]. However, the high resolution instrument camera was found to be out of focus with a PSF FWHM of ∼9 pixels. The charge coupled device (CCD) read noise is ∼1 DN. Electrical cross-talk between the CCD detector quadrants is correctable to <2 DN. The IR spectrometer response nonlinearity is correctable to ∼1%. Spectrometer read noise is ∼2 DN. The variation in zero-exposure signal level with time and spectrometer temperature is not fully characterized; currently corrections are good to ∼10 DN at best. Wavelength mapping onto the detector is known within 1 pixel; spectral lines have a FWHM of ∼2 pixels. About 1% of the IR detector pixels behave badly and remain uncalibrated. The spectrometer exhibits a faint ghost image from reflection off a beamsplitter. Instrument absolute radiometric calibration accuracies were determined generally to <10% using star imaging. Flat-field calibration reduces pixel-to-pixel response differences to ∼0.5% for the cameras and <2% for the spectrometer. A standard calibration image processing pipeline is used to produce archival image files for analysis by researchers.

  11. Invited Article: Deep Impact instrument calibration.

    Science.gov (United States)

    Klaasen, Kenneth P; A'Hearn, Michael F; Baca, Michael; Delamere, Alan; Desnoyer, Mark; Farnham, Tony; Groussin, Olivier; Hampton, Donald; Ipatov, Sergei; Li, Jianyang; Lisse, Carey; Mastrodemos, Nickolaos; McLaughlin, Stephanie; Sunshine, Jessica; Thomas, Peter; Wellnitz, Dennis

    2008-09-01

    Calibration of NASA's Deep Impact spacecraft instruments allows reliable scientific interpretation of the images and spectra returned from comet Tempel 1. Calibrations of the four onboard remote sensing imaging instruments have been performed in the areas of geometric calibration, spatial resolution, spectral resolution, and radiometric response. Error sources such as noise (random, coherent, encoding, data compression), detector readout artifacts, scattered light, and radiation interactions have been quantified. The point spread functions (PSFs) of the medium resolution instrument and its twin impactor targeting sensor are near the theoretical minimum [ approximately 1.7 pixels full width at half maximum (FWHM)]. However, the high resolution instrument camera was found to be out of focus with a PSF FWHM of approximately 9 pixels. The charge coupled device (CCD) read noise is approximately 1 DN. Electrical cross-talk between the CCD detector quadrants is correctable to <2 DN. The IR spectrometer response nonlinearity is correctable to approximately 1%. Spectrometer read noise is approximately 2 DN. The variation in zero-exposure signal level with time and spectrometer temperature is not fully characterized; currently corrections are good to approximately 10 DN at best. Wavelength mapping onto the detector is known within 1 pixel; spectral lines have a FWHM of approximately 2 pixels. About 1% of the IR detector pixels behave badly and remain uncalibrated. The spectrometer exhibits a faint ghost image from reflection off a beamsplitter. Instrument absolute radiometric calibration accuracies were determined generally to <10% using star imaging. Flat-field calibration reduces pixel-to-pixel response differences to approximately 0.5% for the cameras and <2% for the spectrometer. A standard calibration image processing pipeline is used to produce archival image files for analysis by researchers.

  12. Ogallala Aquifer Mapping Program

    International Nuclear Information System (INIS)

    1984-10-01

    A computerized data file has been established which can be used efficiently by the contour-plotting program SURFACE II to produce maps of the Ogallala aquifer in 17 counties of the Texas Panhandle. The data collected have been evaluated and compiled into three sets, from which SURFACE II can generate maps of well control, aquifer thickness, saturated thickness, water level, and the difference between virgin (pre-1942) and recent (1979 to 1981) water levels. 29 figures, 1 table

  13. Maps for the future.

    Directory of Open Access Journals (Sweden)

    Cristina D’Alessandro-Scarpari

    2005-05-01

    Full Text Available Geographers’ relations with maps have a long story of attraction and repulsion. The map has always fascinated Geographers (even before the institutionalization of the discipline as a powerful tool, able to demarcate territories, to produce different visions of them and to transform them by the actions they may cause or influence. Sometimes for strategic reasons Geographers have also denigrated cartography as a secondary and technical form of knowledge, a tool merely for understanding and ...

  14. Dynamics of exponential maps

    OpenAIRE

    Rempe, Lasse

    2003-01-01

    This thesis contains several new results about the dynamics of exponential maps $z\\mapsto \\exp(z)+\\kappa$. In particular, we prove that periodic external rays of exponential maps with nonescaping singular value always land. This is an analog of a theorem of Douady and Hubbard for polynomials. We also answer a question of Herman, Baker and Rippon by showing that the boundary of an unbounded exponential Siegel disk always contains the singular value. In addition to the presentation of new resul...

  15. Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures.

    Science.gov (United States)

    Trullo, Roger; Petitjean, Caroline; Nie, Dong; Shen, Dinggang; Ruan, Su

    2017-09-01

    Computed Tomography (CT) is the standard imaging technique for radiotherapy planning. The delineation of Organs at Risk (OAR) in thoracic CT images is a necessary step before radiotherapy, for preventing irradiation of healthy organs. However, due to low contrast, multi-organ segmentation is a challenge. In this paper, we focus on developing a novel framework for automatic delineation of OARs. Different from previous works in OAR segmentation where each organ is segmented separately, we propose two collaborative deep architectures to jointly segment all organs, including esophagus, heart, aorta and trachea. Since most of the organ borders are ill-defined, we believe spatial relationships must be taken into account to overcome the lack of contrast. The aim of combining two networks is to learn anatomical constraints with the first network, which will be used in the second network, when each OAR is segmented in turn. Specifically, we use the first deep architecture, a deep SharpMask architecture, for providing an effective combination of low-level representations with deep high-level features, and then take into account the spatial relationships between organs by the use of Conditional Random Fields (CRF). Next, the second deep architecture is employed to refine the segmentation of each organ by using the maps obtained on the first deep architecture to learn anatomical constraints for guiding and refining the segmentations. Experimental results show superior performance on 30 CT scans, comparing with other state-of-the-art methods.

  16. The National Map - Orthoimagery

    Science.gov (United States)

    Mauck, James; Brown, Kim; Carswell, William J.

    2009-01-01

    Orthorectified digital aerial photographs and satellite images of 1-meter (m) pixel resolution or finer make up the orthoimagery component of The National Map. The process of orthorectification removes feature displacements and scale variations caused by terrain relief and sensor geometry. The result is a combination of the image characteristics of an aerial photograph or satellite image and the geometric qualities of a map. These attributes allow users to: *Measure distance *Calculate areas *Determine shapes of features *Calculate directions *Determine accurate coordinates *Determine land cover and use *Perform change detection *Update maps The standard digital orthoimage is a 1-m or finer resolution, natural color or color infra-red product. Most are now produced as GeoTIFFs and accompanied by a Federal Geographic Data Committee (FGDC)-compliant metadata file. The primary source for 1-m data is the National Agriculture Imagery Program (NAIP) leaf-on imagery. The U.S. Geological Survey (USGS) utilizes NAIP imagery as the image layer on its 'Digital- Map' - a new generation of USGS topographic maps (http://nationalmap.gov/digital_map). However, many Federal, State, and local governments and organizations require finer resolutions to meet a myriad of needs. Most of these images are leaf-off, natural-color products at resolutions of 1-foot (ft) or finer.

  17. MAPS of Cancer

    Science.gov (United States)

    Gray, Lincoln

    1998-01-01

    Our goal was to produce an interactive visualization from a mathematical model that successfully predicts metastases from head and neck cancer. We met this goal early in the project. The visualization is available for the public to view. Our work appears to fill a need for more information about this deadly disease. The idea of this project was to make an easily interpretable visualization based on what we call "functional maps" of disease. A functional map is a graphic summary of medical data, where distances between parts of the body are determined by the probability of disease, not by anatomical distances. Functional maps often beat little resemblance to anatomical maps, but they can be used to predict the spread of disease. The idea of modeling the spread of disease in an abstract multidimensional space is difficult for many people. Our goal was to make the important predictions easy to see. NASA must face this problem frequently: how to help laypersons and professionals see important trends in abstract, complex data. We took advantage of concepts perfected in NASA's graphics libraries. As an analogy, consider a functional map of early America. Suppose we choose travel times, rather than miles, as our measures of inter-city distances. For Abraham Lincoln, travel times would have been the more meaningful measure of separation between cities. In such a map New Orleans would be close to Memphis because of the Mississippi River. St. Louis would be close to Portland because of the Oregon Trail. Oklahoma City would be far from Little Rock because of the Cheyenne. Such a map would look puzzling to those of us who have always seen physical maps, but the functional map would be more useful in predicting the probabilities of inter-site transit. Continuing the analogy, we could predict the spread of social diseases such as gambling along the rivers and cattle rustling along the trails. We could simply print the functional map of America, but it would be more interesting

  18. Deep groundwater flow at Palmottu

    International Nuclear Information System (INIS)

    Niini, H.; Vesterinen, M.; Tuokko, T.

    1993-01-01

    Further observations, measurements, and calculations aimed at determining the groundwater flow regimes and periodical variations in flow at deeper levels were carried out in the Lake Palmottu (a natural analogue study site for radioactive waste disposal in southwestern Finland) drainage basin. These water movements affect the migration of radionuclides from the Palmottu U-Th deposit. The deep water flow is essentially restricted to the bedrock fractures which developed under, and are still affected by, the stress state of the bedrock. Determination of the detailed variations was based on fracture-tectonic modelling of the 12 most significant underground water-flow channels that cross the surficial water of the Palmottu area. According to the direction of the hydraulic gradient the deep water flow is mostly outwards from the Palmottu catchment but in the westernmost section it is partly towards the centre. Estimation of the water flow through the U-Th deposit by the water-balance method is still only approximate and needs continued observation series and improved field measurements

  19. Deep ocean model penetrator experiments

    International Nuclear Information System (INIS)

    Freeman, T.J.; Burdett, J.R.F.

    1986-01-01

    Preliminary trials of experimental model penetrators in the deep ocean have been conducted as an international collaborative exercise by participating members (national bodies and the CEC) of the Engineering Studies Task Group of the Nuclear Energy Agency's Seabed Working Group. This report describes and gives the results of these experiments, which were conducted at two deep ocean study areas in the Atlantic: Great Meteor East and the Nares Abyssal Plain. Velocity profiles of penetrators of differing dimensions and weights have been determined as they free-fell through the water column and impacted the sediment. These velocity profiles are used to determine the final embedment depth of the penetrators and the resistance to penetration offered by the sediment. The results are compared with predictions of embedment depth derived from elementary models of a penetrator impacting with a sediment. It is tentatively concluded that once the resistance to penetration offered by a sediment at a particular site has been determined, this quantity can be used to sucessfully predict the embedment that penetrators of differing sizes and weights would achieve at the same site

  20. Academic Training: Deep Space Telescopes

    CERN Multimedia

    Françoise Benz

    2006-01-01

    2005-2006 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 20, 21, 22, 23, 24 February from 11:00 to 12:00 - Council Chamber on 20, 21, 23, 24 February, TH Auditorium, bldg 4 - 3-006, on 22 February Deep Space Telescopes G. BIGNAMI / CNRS, Toulouse, F & Univ. di Pavia, I The short series of seminars will address results and aims of current and future space astrophysics as the cultural framework for the development of deep space telescopes. It will then present such new tools, as they are currently available to, or imagined by, the scientific community, in the context of the science plans of ESA and of all major world space agencies. Ground-based astronomy, in the 400 years since Galileo's telescope, has given us a profound phenomenological comprehension of our Universe, but has traditionally been limited to the narrow band(s) to which our terrestrial atmosphere is transparent. Celestial objects, however, do not care about our limitations, and distribute most of the information about their physics thro...

  1. Near-bottom Multibeam Survey Capabilities in the US National Deep Submergence Facility (Invited)

    Science.gov (United States)

    Yoerger, D. R.; McCue, S. J.; Jason; Sentry Operations Groups

    2010-12-01

    The US National Deep Submergence Facility (NDSF) provides near-bottom multibeam mapping capabilities from the autonomous underwater vehicle Sentry and the remotely operated vehicle Jason. These vehicles can be used to depths of 4500 and 6500m respectively. Both vehicles are equipped with Reson 7125 400khz multibeam sonars as well as compatible navigation equipment (inertial navigation systems, doppler velocity logs, and acoustic navigation systems). These vehicles have produced maps of rugged Mid-Ocean Ridge terrain in the Galapagos Rift, natural oil and gas seeps off the coast of Southern California, deep coral sites in the Gulf of Mexico, and sites for the Ocean Observing Initiative off the coast of Oregon. Multibeam surveys are conducted from heights between 20 and 80 meters, allowing the scientific user to select the tradeoff between resolution and coverage rate. In addition to conventional bathymetric mapping, the systems have used to image methane bubble plumes from natural seeps. This talk will provide summaries of these mapping efforts and describe the data processing pipeline used to produce maps shortly after each dive. Development efforts to reduce navigational errors and reconcile discrepancies between adjacent swaths will also be described.

  2. Image Captioning with Deep Bidirectional LSTMs

    OpenAIRE

    Wang, Cheng; Yang, Haojin; Bartz, Christian; Meinel, Christoph

    2016-01-01

    This work presents an end-to-end trainable deep bidirectional LSTM (Long-Short Term Memory) model for image captioning. Our model builds on a deep convolutional neural network (CNN) and two separate LSTM networks. It is capable of learning long term visual-language interactions by making use of history and future context information at high level semantic space. Two novel deep bidirectional variant models, in which we increase the depth of nonlinearity transition in different way, are propose...

  3. Deep inelastic processes and the parton model

    International Nuclear Information System (INIS)

    Altarelli, G.

    The lecture was intended as an elementary introduction to the physics of deep inelastic phenomena from the point of view of theory. General formulae and facts concerning inclusive deep inelastic processes in the form: l+N→l'+hadrons (electroproduction, neutrino scattering) are first recalled. The deep inelastic annihilation e + e - →hadrons is then envisaged. The light cone approach, the parton model and their relation are mainly emphasized

  4. Deep inelastic electron and muon scattering

    International Nuclear Information System (INIS)

    Taylor, R.E.

    1975-07-01

    From the review of deep inelastic electron and muon scattering it is concluded that the puzzle of deep inelastic scattering versus annihilation was replaced with the challenge of the new particles, that the evidence for the simplest quark-algebra models of deep inelastic processes is weaker than a year ago. Definite evidence of scale breaking was found but the specific form of that scale breaking is difficult to extract from the data. 59 references

  5. Fast, Distributed Algorithms in Deep Networks

    Science.gov (United States)

    2016-05-11

    shallow networks, additional work will need to be done in order to allow for the application of ADMM to deep nets. The ADMM method allows for quick...Quock V Le, et al. Large scale distributed deep networks. In Advances in Neural Information Processing Systems, pages 1223–1231, 2012. [11] Ken-Ichi...A TRIDENT SCHOLAR PROJECT REPORT NO. 446 Fast, Distributed Algorithms in Deep Networks by Midshipman 1/C Ryan J. Burmeister, USN

  6. Learning Transferable Features with Deep Adaptation Networks

    OpenAIRE

    Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

    2015-01-01

    Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

  7. Dynamic map labeling.

    Science.gov (United States)

    Been, Ken; Daiches, Eli; Yap, Chee

    2006-01-01

    We address the problem of filtering, selecting and placing labels on a dynamic map, which is characterized by continuous zooming and panning capabilities. This consists of two interrelated issues. The first is to avoid label popping and other artifacts that cause confusion and interrupt navigation, and the second is to label at interactive speed. In most formulations the static map labeling problem is NP-hard, and a fast approximation might have O(nlogn) complexity. Even this is too slow during interaction, when the number of labels shown can be several orders of magnitude less than the number in the map. In this paper we introduce a set of desiderata for "consistent" dynamic map labeling, which has qualities desirable for navigation. We develop a new framework for dynamic labeling that achieves the desiderata and allows for fast interactive display by moving all of the selection and placement decisions into the preprocessing phase. This framework is general enough to accommodate a variety of selection and placement algorithms. It does not appear possible to achieve our desiderata using previous frameworks. Prior to this paper, there were no formal models of dynamic maps or of dynamic labels; our paper introduces both. We formulate a general optimization problem for dynamic map labeling and give a solution to a simple version of the problem. The simple version is based on label priorities and a versatile and intuitive class of dynamic label placements we call "invariant point placements". Despite these restrictions, our approach gives a useful and practical solution. Our implementation is incorporated into the G-Vis system which is a full-detail dynamic map of the continental USA. This demo is available through any browser.

  8. An overview of latest deep water technologies

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    The 8th Deep Offshore Technology Conference (DOT VIII, Rio de Janeiro, October 30 - November 3, 1995) has brought together renowned specialists in deep water development projects, as well as managers from oil companies and engineering/service companies to discuss state-of-the-art technologies and ongoing projects in the deep offshore. This paper is a compilation of the session summaries about sub sea technologies, mooring and dynamic positioning, floaters (Tension Leg Platforms (TLP) and Floating Production Storage and Off loading (FPSO)), pipelines and risers, exploration and drilling, and other deep water techniques. (J.S.)

  9. Deep learning in neural networks: an overview.

    Science.gov (United States)

    Schmidhuber, Jürgen

    2015-01-01

    In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.

  10. The deep ocean under climate change

    Science.gov (United States)

    Levin, Lisa A.; Le Bris, Nadine

    2015-11-01

    The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems.

  11. Docker Containers for Deep Learning Experiments

    OpenAIRE

    Gerke, Paul K.

    2017-01-01

    Deep learning is a powerful tool to solve problems in the area of image analysis. The dominant compute platform for deep learning is Nvidia’s proprietary CUDA, which can only be used together with Nvidia graphics cards. The nivida-docker project allows exposing Nvidia graphics cards to docker containers and thus makes it possible to run deep learning experiments in docker containers.In our department, we use deep learning to solve problems in the area of medical image analysis and use docker ...

  12. Deep Brain Stimulation for Parkinson's Disease

    Science.gov (United States)

    ... about the BRAIN initiative, see www.nih.gov/science/brain . Show More Show Less Search Disorders SEARCH SEARCH Definition Treatment Prognosis Clinical Trials Organizations Publications Definition Deep ...

  13. Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study.

    Science.gov (United States)

    Betancur, Julian; Commandeur, Frederic; Motlagh, Mahsaw; Sharir, Tali; Einstein, Andrew J; Bokhari, Sabahat; Fish, Mathews B; Ruddy, Terrence D; Kaufmann, Philipp; Sinusas, Albert J; Miller, Edward J; Bateman, Timothy M; Dorbala, Sharmila; Di Carli, Marcelo; Germano, Guido; Otaki, Yuka; Tamarappoo, Balaji K; Dey, Damini; Berman, Daniel S; Slomka, Piotr J

    2018-03-12

    The study evaluated the automatic prediction of obstructive disease from myocardial perfusion imaging (MPI) by deep learning as compared with total perfusion deficit (TPD). Deep convolutional neural networks trained with a large multicenter population may provide improved prediction of per-patient and per-vessel coronary artery disease from single-photon emission computed tomography MPI. A total of 1,638 patients (67% men) without known coronary artery disease, undergoing stress 99m Tc-sestamibi or tetrofosmin MPI with new generation solid-state scanners in 9 different sites, with invasive coronary angiography performed within 6 months of MPI, were studied. Obstructive disease was defined as ≥70% narrowing of coronary arteries (≥50% for left main artery). Left ventricular myocardium was segmented using clinical nuclear cardiology software and verified by an expert reader. Stress TPD was computed using sex- and camera-specific normal limits. Deep learning was trained using raw and quantitative polar maps and evaluated for prediction of obstructive stenosis in a stratified 10-fold cross-validation procedure. A total of 1,018 (62%) patients and 1,797 of 4,914 (37%) arteries had obstructive disease. Area under the receiver-operating characteristic curve for disease prediction by deep learning was higher than for TPD (per patient: 0.80 vs. 0.78; per vessel: 0.76 vs. 0.73: p deep learning threshold set to the same specificity as TPD, per-patient sensitivity improved from 79.8% (TPD) to 82.3% (deep learning) (p deep learning) (p Deep learning has the potential to improve automatic interpretation of MPI as compared with current clinical methods. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  14. Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

    Science.gov (United States)

    Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

    2017-12-01

    State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with

  15. Cultivating the Deep Subsurface Microbiome

    Science.gov (United States)

    Casar, C. P.; Osburn, M. R.; Flynn, T. M.; Masterson, A.; Kruger, B.

    2017-12-01

    Subterranean ecosystems are poorly understood because many microbes detected in metagenomic surveys are only distantly related to characterized isolates. Cultivating microorganisms from the deep subsurface is challenging due to its inaccessibility and potential for contamination. The Deep Mine Microbial Observatory (DeMMO) in Lead, SD however, offers access to deep microbial life via pristine fracture fluids in bedrock to a depth of 1478 m. The metabolic landscape of DeMMO was previously characterized via thermodynamic modeling coupled with genomic data, illustrating the potential for microbial inhabitants of DeMMO to utilize mineral substrates as energy sources. Here, we employ field and lab based cultivation approaches with pure minerals to link phylogeny to metabolism at DeMMO. Fracture fluids were directed through reactors filled with Fe3O4, Fe2O3, FeS2, MnO2, and FeCO3 at two sites (610 m and 1478 m) for 2 months prior to harvesting for subsequent analyses. We examined mineralogical, geochemical, and microbiological composition of the reactors via DNA sequencing, microscopy, lipid biomarker characterization, and bulk C and N isotope ratios to determine the influence of mineralogy on biofilm community development. Pre-characterized mineral chips were imaged via SEM to assay microbial growth; preliminary results suggest MnO2, Fe3O4, and Fe2O3 were most conducive to colonization. Solid materials from reactors were used as inoculum for batch cultivation experiments. Media designed to mimic fracture fluid chemistry was supplemented with mineral substrates targeting metal reducers. DNA sequences and microscopy of iron oxide-rich biofilms and fracture fluids suggest iron oxidation is a major energy source at redox transition zones where anaerobic fluids meet more oxidizing conditions. We utilized these biofilms and fluids as inoculum in gradient cultivation experiments targeting microaerophilic iron oxidizers. Cultivation of microbes endemic to DeMMO, a system

  16. Deep learning in mammography and breast histology, an overview and future trends.

    Science.gov (United States)

    Hamidinekoo, Azam; Denton, Erika; Rampun, Andrik; Honnor, Kate; Zwiggelaar, Reyer

    2018-07-01

    Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promising results reported by deep learning based methods in breast imaging, an overview of the recent state-of-the-art deep learning based CAD systems developed for mammography and breast histopathology images is presented. In this study, the relationship between mammography and histopathology phenotypes is described, which takes biological aspects into account. We propose a computer based breast cancer modelling approach: the Mammography-Histology-Phenotype-Linking-Model, which develops a mapping of features/phenotypes between mammographic abnormalities and their histopathological representation. Challenges are discussed along with the potential contribution of such a system to clinical decision making and treatment management. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

  17. Introduction to "Mapping Vietnameseness"

    Directory of Open Access Journals (Sweden)

    Hue-Tam Ho Tai

    2016-09-01

    Full Text Available Vietnam and China are currently engaged in a map war, with each country using ancient maps to buttress its claims to territorial sovereignty over some uninhabited islands in the South China Sea (in Chinese terminology, also known as the Eastern Sea (in Vietnamese. But what do maps in fact represent? What is meant by “territory”? How are territorial limits conceived? These questions were raised in a May 2015 workshop inspired by Thongchai Winichakul’s Siam Mapped: A History of the Geo-Body of a Nation (1994, a groundbreaking book that traces the transformation of Thai geographical consciousness as a result of Siam’s encounter with Western powers in the nineteenth century. While many of Thongchai’s insights apply to the Vietnamese case, as the first of the three articles included in this special issue of Cross-Currents shows, some of the 2015 workshop participants’ conclusions departed from his, especially regarding the formation of a Vietnamese geographical consciousness before the colonial period.[i] This is true of the other two papers, which focus specifically on the construction of borders and the associated production of maps in the nineteenth century before French colonial conquest... Notes 1 Thanks are due to the Max Planck Institute for the Study of Religious and Ethnic Change in Gottingen, Germany, for its gracious hosting and generous funding of the conference, together with the Asia Center of Harvard University.

  18. Mapping sequences by parts

    Directory of Open Access Journals (Sweden)

    Guziolowski Carito

    2007-09-01

    Full Text Available Abstract Background: We present the N-map method, a pairwise and asymmetrical approach which allows us to compare sequences by taking into account evolutionary events that produce shuffled, reversed or repeated elements. Basically, the optimal N-map of a sequence s over a sequence t is the best way of partitioning the first sequence into N parts and placing them, possibly complementary reversed, over the second sequence in order to maximize the sum of their gapless alignment scores. Results: We introduce an algorithm computing an optimal N-map with time complexity O (|s| × |t| × N using O (|s| × |t| × N memory space. Among all the numbers of parts taken in a reasonable range, we select the value N for which the optimal N-map has the most significant score. To evaluate this significance, we study the empirical distributions of the scores of optimal N-maps and show that they can be approximated by normal distributions with a reasonable accuracy. We test the functionality of the approach over random sequences on which we apply artificial evolutionary events. Practical Application: The method is illustrated with four case studies of pairs of sequences involving non-standard evolutionary events.

  19. Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

    OpenAIRE

    Plessen, Mogens Graf

    2017-01-01

    Within the context of autonomous vehicles, classical model-based control methods suffer from the trade-off between model complexity and computational burden required for the online solution of expensive optimization or search problems at every short sampling time. These methods include sampling-based algorithms, lattice-based algorithms and algorithms based on model predictive control (MPC). Recently, end-to-end trained deep neural networks were proposed to map camera images directly to steer...

  20. Assessment and Methods for Supply-Following Loads in Modern Electricity Grids with Deep Renewables Penetration

    Science.gov (United States)

    2013-12-18

    today. Following the course of this trend, grids with deep renewables penetration present a CHAPTER 1. INTRODUCTION 2 family of new challenges and...maps the demand curve. Coal is operated as an intermediate resource, turned on for the course of the day, but turned off at night; this represents a...Internet access and a data storage entity, recording data samples into a MySQL database. Having all of the sensors on a network was important for

  1. Velocity and Attenuation Profiles in the Monterey Deep-Sea Fan

    Science.gov (United States)

    1987-12-01

    a. 11 o n i n and depth. Sol ’^ a 11 e i"i u a 11 o >) a i::> 1 n Ci sediment for each of the f i...i. n c t ion o f f r e q u e n c; y...estimate of sea floor depth was obtained from an oceano - graphic map of the Monterey fan (’Oceanographic Data of the Monterey Deep Sea Fan’, 1st

  2. Deep inelastic scattering and disquarks

    International Nuclear Information System (INIS)

    Anselmino, M.

    1993-01-01

    The most comprehensive and detailed analyses of the existing data on the structure function F 2 (x, Q 2 ) of free nucleons, from the deep inelastic scattering (DIS) of charged leptons on hydrogen and deuterium targets, have proved beyond any doubt that higher twist, 1/Q 2 corrections are needed in order to obtain a perfect agreement between perturbative QCD predictions and the data. These higher twist corrections take into account two quark correlations inside the nucleon; it is then natural to try to model them in the quark-diquark model of the proton. In so doing all interactions between the two quarks inside the diquark, both perturbative and non perturbative, are supposed to be taken into account. (orig./HSI)

  3. Detector for deep well logging

    International Nuclear Information System (INIS)

    1976-01-01

    A substantial improvement in the useful life and efficiency of a deep-well scintillation detector is achieved by a unique construction wherein the steel cylinder enclosing the sodium iodide scintillation crystal is provided with a tapered recess to receive a glass window which has a high transmittance at the critical wavelength and, for glass, a high coefficient of thermal expansion. A special high-temperature epoxy adhesive composition is employed to form a relatively thick sealing annulus which keeps the glass window in the tapered recess and compensates for the differences in coefficients of expansion between the container and glass so as to maintain a hermetic seal as the unit is subjected to a wide range of temperature

  4. Deep borehole disposal of plutonium

    International Nuclear Information System (INIS)

    Gibb, F. G. F.; Taylor, K. J.; Burakov, B. E.

    2008-01-01

    Excess plutonium not destined for burning as MOX or in Generation IV reactors is both a long-term waste management problem and a security threat. Immobilisation in mineral and ceramic-based waste forms for interim safe storage and eventual disposal is a widely proposed first step. The safest and most secure form of geological disposal for Pu yet suggested is in very deep boreholes and we propose here that the key to successful combination of these immobilisation and disposal concepts is the encapsulation of the waste form in small cylinders of recrystallized granite. The underlying science is discussed and the results of high pressure and temperature experiments on zircon, depleted UO 2 and Ce-doped cubic zirconia enclosed in granitic melts are presented. The outcomes of these experiments demonstrate the viability of the proposed solution and that Pu could be successfully isolated from its environment for many millions of years. (authors)

  5. Automatic Differentiation and Deep Learning

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Statistical learning has been getting more and more interest from the particle-physics community in recent times, with neural networks and gradient-based optimization being a focus. In this talk we shall discuss three things: automatic differention tools: tools to quickly build DAGs of computation that are fully differentiable. We shall focus on one such tool "PyTorch".  Easy deployment of trained neural networks into large systems with many constraints: for example, deploying a model at the reconstruction phase where the neural network has to be integrated into CERN's bulk data-processing C++-only environment Some recent models in deep learning for segmentation and generation that might be useful for particle physics problems.

  6. Jets in deep inelastic scattering

    International Nuclear Information System (INIS)

    Joensson, L.

    1995-01-01

    Jet production in deep inelastic scattering provides a basis for the investigation of various phenomena related to QCD. Two-jet production at large Q 2 has been studied and the distributions with respect to the partonic scaling variables have been compared to models and to next to leading order calculations. The first observations of azimuthal asymmetries of jets produced in first order α s processes have been obtained. The gluon initiated boson-gluon fusion process permits a direct determination of the gluon density of the proton from an analysis of the jets produced in the hard scattering process. A comparison of these results with those from indirect extractions of the gluon density provides an important test of QCD. (author)

  7. NESTOR Deep Sea Neutrino Telescope

    International Nuclear Information System (INIS)

    Aggouras, G.; Anassontzis, E.G.; Ball, A.E.; Bourlis, G.; Chinowsky, W.; Fahrun, E.; Grammatikakis, G.; Green, C.; Grieder, P.; Katrivanos, P.; Koske, P.; Leisos, A.; Markopoulos, E.; Minkowsky, P.; Nygren, D.; Papageorgiou, K.; Przybylski, G.; Resvanis, L.K.; Siotis, I.; Sopher, J.; Staveris-Polikalas, A.; Tsagli, V.; Tsirigotis, A.; Tzamarias, S.; Zhukov, V.A.

    2006-01-01

    One module of NESTOR, the Mediterranean deep-sea neutrino telescope, was deployed at a depth of 4000m, 14km off the Sapienza Island, off the South West coast of Greece. The deployment site provides excellent environmental characteristics. The deployed NESTOR module is constructed as a hexagonal star like latticed titanium star with 12 Optical Modules and an one-meter diameter titanium sphere which houses the electronics. Power and data were transferred through a 30km electro-optical cable to the shore laboratory. In this report we describe briefly the detector and the detector electronics and discuss the first physics data acquired and give the zenith angular distribution of the reconstructed muons

  8. Deep Borehole Disposal Safety Analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Freeze, Geoffrey A. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Stein, Emily [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Price, Laura L. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); MacKinnon, Robert J. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Tillman, Jack Bruce [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

    2016-10-01

    This report presents a preliminary safety analysis for the deep borehole disposal (DBD) concept, using a safety case framework. A safety case is an integrated collection of qualitative and quantitative arguments, evidence, and analyses that substantiate the safety, and the level of confidence in the safety, of a geologic repository. This safety case framework for DBD follows the outline of the elements of a safety case, and identifies the types of information that will be required to satisfy these elements. At this very preliminary phase of development, the DBD safety case focuses on the generic feasibility of the DBD concept. It is based on potential system designs, waste forms, engineering, and geologic conditions; however, no specific site or regulatory framework exists. It will progress to a site-specific safety case as the DBD concept advances into a site-specific phase, progressing through consent-based site selection and site investigation and characterization.

  9. DeepRT: deep learning for peptide retention time prediction in proteomics

    OpenAIRE

    Ma, Chunwei; Zhu, Zhiyong; Ye, Jun; Yang, Jiarui; Pei, Jianguo; Xu, Shaohang; Zhou, Ruo; Yu, Chang; Mo, Fan; Wen, Bo; Liu, Siqi

    2017-01-01

    Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction. DeepRT automatically learns features directly from the peptide sequences using the deep convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model, which eliminates the need to use hand-crafted features or rules. After the feature learning, pr...

  10. Dro1, a major QTL involved in deep rooting of rice under upland field conditions.

    Science.gov (United States)

    Uga, Yusaku; Okuno, Kazutoshi; Yano, Masahiro

    2011-05-01

    Developing a deep root system is an important strategy for avoiding drought stress in rice. Using the 'basket' method, the ratio of deep rooting (RDR; the proportion of total roots that elongated through the basket bottom) was calculated to evaluate deep rooting. A new major quantitative trait locus (QTL) controlling RDR was detected on chromosome 9 by using 117 recombinant inbred lines (RILs) derived from a cross between the lowland cultivar IR64, with shallow rooting, and the upland cultivar Kinandang Patong (KP), with deep rooting. This QTL explained 66.6% of the total phenotypic variance in RDR in the RILs. A BC(2)F(3) line homozygous for the KP allele of the QTL had an RDR of 40.4%, compared with 2.6% for the homozygous IR64 allele. Fine mapping of this QTL was undertaken using eight BC(2)F(3) recombinant lines. The RDR QTL Dro1 (Deeper rooting 1) was mapped between the markers RM24393 and RM7424, which delimit a 608.4 kb interval in the reference cultivar Nipponbare. To clarify the influence of Dro1 in an upland field, the root distribution in different soil layers was quantified by means of core sampling. A line homozygous for the KP allele of Dro1 (Dro1-KP) and IR64 did not differ in root dry weight in the shallow soil layers (0-25 cm), but root dry weight of Dro1-KP in deep soil layers (25-50 cm) was significantly greater than that of IR64, suggesting that Dro1 plays a crucial role in increased deep rooting under upland field conditions.

  11. Predicted deep-sea coral habitat suitability for the U.S. West coast.

    Directory of Open Access Journals (Sweden)

    John M Guinotte

    Full Text Available Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington. Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH and identify suitable habitat within U.S. National Marine Sanctuaries (NMS. Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled.

  12. The evolving Alaska mapping program.

    Science.gov (United States)

    Brooks, P.D.; O'Brien, T. J.

    1986-01-01

    This paper describes the development of mapping in Alaska, the current status of the National Mapping Program, and future plans for expanding and improving the mapping coverage. Research projects with Landsat Multispectral Scanner and Return Vidicon imagery and real- and synthetic-aperture radar; image mapping programs; digital mapping; remote sensing projects; the Alaska National Interest Lands Conservation Act; and the Alaska High-Altitude Aerial Photography Program are also discussed.-from Authors

  13. Ergodicity of polygonal slap maps

    International Nuclear Information System (INIS)

    Del Magno, Gianluigi; Pedro Gaivão, José; Lopes Dias, João; Duarte, Pedro

    2014-01-01

    Polygonal slap maps are piecewise affine expanding maps of the interval obtained by projecting the sides of a polygon along their normals onto the perimeter of the polygon. These maps arise in the study of polygonal billiards with non-specular reflection laws. We study the absolutely continuous invariant probabilities (acips) of the slap maps for several polygons, including regular polygons and triangles. We also present a general method for constructing polygons with slap maps with more than one ergodic acip. (paper)

  14. Preoperative percutaneous cranial nerve mapping in head and neck surgery.

    Science.gov (United States)

    Park, Jung I

    2003-01-01

    To identify and map the course of the peripheral branches of the cranial nerve preoperatively and percutaneously. Prospective study. Preoperative percutaneous nerve mapping performed prior to the operation under deep sedation or general anesthesia without muscle paralysis. Private office surgery suite, freestanding surgery center, and regional medical centers. A total of 142 patients undergoing head and neck surgery and facial plastic surgery between August 1994 and July 1999. Monopolar probe was used for nerve stimulation. Electromyographic reading was done through intramuscular bipolar recording electrodes. The equipment used was a nerve monitor. The mandibular divisions were tested in 142 cases, the frontal division in 60 cases, the accessory nerve in 12 cases, and the hypoglossal nerve in 3 cases. Satisfactory mappings were obtained in 115 cases of the mandibular division, 49 cases of the frontal division, 8 cases of the accessory division, and 1 case of the hypoglossal nerve. Preoperative percutaneous nerve mapping is a new method of identifying the location of the peripheral branches of the cranial nerves. Identifying and mapping the course of peripheral branches of the cranial nerves safely assists the head and neck surgeon in the placement of incisions in a favorable location and in the dissection of the area involving the nerves. Mapping alerts the surgeon to an area containing a nerve and allows the surgeon to avoid just the specific area where a nerve is present, preventing large-scale abandonment of unmapped areas for fear of potential nerve damage.

  15. Mapping Unknown Knowns

    DEFF Research Database (Denmark)

    Diogo de Andrade Silva, Elisa; Lanng, Ditte Bendix; Wind, Simon

    representative dimensions of travellers’ embodied ‘dwelling-in-motion’ (Urry, 2007) and experiences. The paper foregrounds a ‘Mapping-in-Motion’ graphic example, an experimental urban design student assignment aiming to map some of the less representative dimensions of journeys between A and B in Berlin...... in relation to analysis, representation, exploration and design of everyday travelling in the city. Such ‘mobilities design’ (Jensen and Lanng 2017) concerns routes, sites and artefacts of mobilities, e.g., road networks, train stations, and bike parking facilities. Some dimensions of these structures...

  16. Learning Bing maps API

    CERN Document Server

    Sinani, Artan

    2013-01-01

    This is a practical, hands-on guide with illustrative examples, which will help you explore the vast universe of Bing maps.If you are a developer who wants to learn how to exploit the numerous features of Bing Maps then this book is ideal for you. It can also be useful for more experienced developers who wish to explore other areas of the APIs. It is assumed that you have some knowledge of JavaScript, HTML, and CSS. For some chapters a working knowledge of .Net and Visual Studio is also needed.

  17. Graphene Conductance Uniformity Mapping

    DEFF Research Database (Denmark)

    Buron, Jonas Christian Due; Petersen, Dirch Hjorth; Bøggild, Peter

    2012-01-01

    We demonstrate a combination of micro four-point probe (M4PP) and non-contact terahertz time-domain spectroscopy (THz-TDS) measurements for centimeter scale quantitative mapping of the sheet conductance of large area chemical vapor deposited graphene films. Dual configuration M4PP measurements......, demonstrated on graphene for the first time, provide valuable statistical insight into the influence of microscale defects on the conductance, while THz-TDS has potential as a fast, non-contact metrology method for mapping of the spatially averaged nanoscopic conductance on wafer-scale graphene with scan times......, dominating the microscale conductance of the investigated graphene film....

  18. Equivalent drawbead performance in deep drawing simulations

    NARCIS (Netherlands)

    Meinders, Vincent T.; Geijselaers, Hubertus J.M.; Huetink, Han

    1999-01-01

    Drawbeads are applied in the deep drawing process to improve the control of the material flow during the forming operation. In simulations of the deep drawing process these drawbeads can be replaced by an equivalent drawbead model. In this paper the usage of an equivalent drawbead model in the

  19. Is deep dreaming the new collage?

    Science.gov (United States)

    Boden, Margaret A.

    2017-10-01

    Deep dreaming (DD) can combine and transform images in surprising ways. But, being based in deep learning (DL), it is not analytically understood. Collage is an art form that is constrained along various dimensions. DD will not be able to generate collages until DL can be guided in a disciplined fashion.

  20. Deep web search: an overview and roadmap

    NARCIS (Netherlands)

    Tjin-Kam-Jet, Kien; Trieschnigg, Rudolf Berend; Hiemstra, Djoerd

    2011-01-01

    We review the state-of-the-art in deep web search and propose a novel classification scheme to better compare deep web search systems. The current binary classification (surfacing versus virtual integration) hides a number of implicit decisions that must be made by a developer. We make these

  1. Research Proposal for Distributed Deep Web Search

    NARCIS (Netherlands)

    Tjin-Kam-Jet, Kien

    2010-01-01

    This proposal identifies two main problems related to deep web search, and proposes a step by step solution for each of them. The first problem is about searching deep web content by means of a simple free-text interface (with just one input field, instead of a complex interface with many input

  2. Development of Hydro-Mechanical Deep Drawing

    DEFF Research Database (Denmark)

    Zhang, Shi-Hong; Danckert, Joachim

    1998-01-01

    The hydro-mechanical deep-drawing process is reviewed in this article. The process principles and features are introduced and the developments of the hydro-mechanical deep-drawing process in process performances, in theory and in numerical simulation are described. The applications are summarized....... Some other related hydraulic forming processes are also dealt with as a comparison....

  3. Stable architectures for deep neural networks

    Science.gov (United States)

    Haber, Eldad; Ruthotto, Lars

    2018-01-01

    Deep neural networks have become invaluable tools for supervised machine learning, e.g. classification of text or images. While often offering superior results over traditional techniques and successfully expressing complicated patterns in data, deep architectures are known to be challenging to design and train such that they generalize well to new data. Critical issues with deep architectures are numerical instabilities in derivative-based learning algorithms commonly called exploding or vanishing gradients. In this paper, we propose new forward propagation techniques inspired by systems of ordinary differential equations (ODE) that overcome this challenge and lead to well-posed learning problems for arbitrarily deep networks. The backbone of our approach is our interpretation of deep learning as a parameter estimation problem of nonlinear dynamical systems. Given this formulation, we analyze stability and well-posedness of deep learning and use this new understanding to develop new network architectures. We relate the exploding and vanishing gradient phenomenon to the stability of the discrete ODE and present several strategies for stabilizing deep learning for very deep networks. While our new architectures restrict the solution space, several numerical experiments show their competitiveness with state-of-the-art networks.

  4. Temperature impacts on deep-sea biodiversity.

    Science.gov (United States)

    Yasuhara, Moriaki; Danovaro, Roberto

    2016-05-01

    Temperature is considered to be a fundamental factor controlling biodiversity in marine ecosystems, but precisely what role temperature plays in modulating diversity is still not clear. The deep ocean, lacking light and in situ photosynthetic primary production, is an ideal model system to test the effects of temperature changes on biodiversity. Here we synthesize current knowledge on temperature-diversity relationships in the deep sea. Our results from both present and past deep-sea assemblages suggest that, when a wide range of deep-sea bottom-water temperatures is considered, a unimodal relationship exists between temperature and diversity (that may be right skewed). It is possible that temperature is important only when at relatively high and low levels but does not play a major role in the intermediate temperature range. Possible mechanisms explaining the temperature-biodiversity relationship include the physiological-tolerance hypothesis, the metabolic hypothesis, island biogeography theory, or some combination of these. The possible unimodal relationship discussed here may allow us to identify tipping points at which on-going global change and deep-water warming may increase or decrease deep-sea biodiversity. Predicted changes in deep-sea temperatures due to human-induced climate change may have more adverse consequences than expected considering the sensitivity of deep-sea ecosystems to temperature changes. © 2014 Cambridge Philosophical Society.

  5. Deep underground exploration in the Asse salt mine

    International Nuclear Information System (INIS)

    Steinberg, S.; Schmidt, M.W.

    1992-01-01

    The activities reported here under the project task entitled ''Deep underground exploration up to the 925 m level'' opened up depths and salt formations in the Asse salt mine which are intended sites for R and D work for investigating and determining the conditions of radioactive waste disposal in a repository of the Gorleben type. The newly developed experimental levels will thus allow to directly apply research results obtained in the Asse mine to the Gorleben project. The activities reported included among other tasks work for increasing the depth of exploration in the Asse mine 2 down to 950 m, using a newly developed cutting method. The work was performed in cooperation with a mining corporation specializing in this sort of tasks. (orig.) With 18 maps [de

  6. Towards deep learning with segregated dendrites.

    Science.gov (United States)

    Guerguiev, Jordan; Lillicrap, Timothy P; Richards, Blake A

    2017-12-05

    Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning algorithm that utilizes multi-compartment neurons might help us to understand how the neocortex optimizes cost functions. Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments. Thanks to this segregation, neurons in different layers of the network can coordinate synaptic weight updates. As a result, the network learns to categorize images better than a single layer network. Furthermore, we show that our algorithm takes advantage of multilayer architectures to identify useful higher-order representations-the hallmark of deep learning. This work demonstrates that deep learning can be achieved using segregated dendritic compartments, which may help to explain the morphology of neocortical pyramidal neurons.

  7. 2004 Alaska Lidar Mapping

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The data sets are generated using the OPTECH ALTM 70 kHz LIDAR system mounted onboard AeroMap's twin-engine Cessna 320 aircraft. Classified data sets such as this...

  8. Ramachandran and his Map

    Indian Academy of Sciences (India)

    Ramachandran map, detailed in this article. His current interests are peptide, cyclic peptide and protein conforma- tions, energetics, data analysis, computer modeling as well as development of new algorithms useful for the conformational studies. C Ramakrishnan. Introduction. Professor G N Ramachandran was one of the ...

  9. Photogrammetry and Digital Mapping

    DEFF Research Database (Denmark)

    Frederiksen, Poul

    1998-01-01

    Technical tour to Lithuania, Poland and Estonia for 13 technical staff and managers of State Land Service, HQ, Latvia. Focus on technical aspects and management of geographical data for map production and administration. Visits to state and local government organisations and newly established...

  10. Mapping World Hunger.

    Science.gov (United States)

    Van Vliet, Lucille W.

    1988-01-01

    Describes a lesson designed to involve students in grades 6 through 8 in learning how geography was affected the problem of world hunger. Emphasis is placed on using maps, globes, atlases, and geographic dictionaries, as well as books, magazines, and other resources. (MES)

  11. Fluence map segmentation

    International Nuclear Information System (INIS)

    Rosenwald, J.-C.

    2008-01-01

    The lecture addressed the following topics: 'Interpreting' the fluence map; The sequencer; Reasons for difference between desired and actual fluence map; Principle of 'Step and Shoot' segmentation; Large number of solutions for given fluence map; Optimizing 'step and shoot' segmentation; The interdigitation constraint; Main algorithms; Conclusions on segmentation algorithms (static mode); Optimizing intensity levels and monitor units; Sliding window sequencing; Synchronization to avoid the tongue-and-groove effect; Accounting for physical characteristics of MLC; Importance of corrections for leaf transmission and offset; Accounting for MLC mechanical constraints; The 'complexity' factor; Incorporating the sequencing into optimization algorithm; Data transfer to the treatment machine; Interface between R and V and accelerator; and Conclusions on fluence map segmentation (Segmentation is part of the overall inverse planning procedure; 'Step and Shoot' and 'Dynamic' options are available for most TPS (depending on accelerator model; The segmentation phase tends to come into the optimization loop; The physical characteristics of the MLC have a large influence on final dose distribution; The IMRT plans (MU and relative dose distribution) must be carefully validated). (P.A.)

  12. Mapping the Heavens

    Indian Academy of Sciences (India)

    results of astrophysical mapping along multi- ple dimensions of space and time that deter- mine the distribution ... discipline, the book evocatively charts out the enormous impact of these advances on human culture, in that our ... And her evocative writing skills make the de- scriptions of these various discoveries come alive.

  13. Bike Map Lines

    Data.gov (United States)

    Town of Chapel Hill, North Carolina — Chapel Hill Bike Map Lines from KMZ file.This data came from the wiki comment board for the public, not an “official map” showing the Town of Chapel Hill's plans or...

  14. Copenhagen Sonic Experience Map

    DEFF Research Database (Denmark)

    Kreutzfeldt, Jacob

    2011-01-01

    In the wake of present European interest for mapping urban noise, it seems increasingly relevant to investigate the multiple ways in which sound intersects with the everyday experiences of urban citizens. Focusing on the polluting effects of infrastructural noise, the EU-initiated project of asse...

  15. Extending Lipschitz mappings continuously

    Czech Academy of Sciences Publication Activity Database

    Kopecká, Eva

    2012-01-01

    Roč. 18, č. 2 (2012), s. 167-177 ISSN 1425-6908 Institutional support: RVO:67985840 Keywords : Lipschitz mapping * Hilbert space * extension Subject RIV: BA - General Mathematics http://www.degruyter.com/view/j/jaa.2012.18.issue-2/jaa-2012-0011/jaa-2012-0011. xml

  16. STOCHASTIC FLOWS OF MAPPINGS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.

  17. Mapping the Literature

    DEFF Research Database (Denmark)

    Boulus-Rødje, Nina

    2012-01-01

    As the utilization of various e-voting technologies has notably increased in the past few years, so has the amount of publications on experiences with these technologies. This article, will, therefore map the literature while highlighting some of the important topics discussed within the field of e...

  18. eMAPS

    CERN Document Server

    Human Resources Department

    2005-01-01

    Starting with the 2005 performance appraisal and advancement exercise (MAPS), the paper version of the annual appraisal report has been replaced by an electronic EDH version - eMAPS (see Weekly Bulletin 48/2004). As announced in Weekly Bulletin 2/2005, information sessions to explain the features of eMAPS using EDH have been arranged as follows: 18 January 2005: Main Auditorium (500-1-001) from 14:00 to 15:30. 20 January 2005: AB Auditorium II (864-1-D02) from 14:00 to 15:30. 24 January 2005: AT Auditorium (30-7-018) from 10:00 to 11:30. The changeover to an electronic appraisal report is designed to reduce the administrative workload involving, e.g. photocopying, tracing and filing paper copies, while allowing staff members and their hierarchy access to the report form at the appropriate times. There is no change in the procedure for the annual interview and the advancement exercise, though Administrative Circular No 26 (Rev. 5) has been updated to take account of the introduction of eMAPS. The content...

  19. Mapping functional connectivity

    Science.gov (United States)

    Peter Vogt; Joseph R. Ferrari; Todd R. Lookingbill; Robert H. Gardner; Kurt H. Riitters; Katarzyna Ostapowicz

    2009-01-01

    An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible,...

  20. Historical Topographic Map Collection bookmark

    Science.gov (United States)

    Fishburn, Kristin A.; Allord, Gregory J.

    2017-06-29

    The U.S. Geological Survey (USGS) National Geospatial Program is scanning published USGS 1:250,000-scale and larger topographic maps printed between 1884, the inception of the topographic mapping program, and 2006. The goal of this project, which began publishing the historical scanned maps in 2011, is to provide a digital repository of USGS topographic maps, available to the public at no cost. For more than 125 years, USGS topographic maps have accurately portrayed the complex geography of the Nation. The USGS is the Nation’s largest producer of printed topographic maps, and prior to 2006, USGS topographic maps were created using traditional cartographic methods and printed using a lithographic printing process. As the USGS continues the release of a new generation of topographic maps (US Topo) in electronic form, the topographic map remains an indispensable tool for government, science, industry, land management planning, and leisure.

  1. Deep-sea benthic footprint of the deepwater horizon blowout.

    Directory of Open Access Journals (Sweden)

    Paul A Montagna

    Full Text Available The Deepwater Horizon (DWH accident in the northern Gulf of Mexico occurred on April 20, 2010 at a water depth of 1525 meters, and a deep-sea plume was detected within one month. Oil contacted and persisted in parts of the bottom of the deep-sea in the Gulf of Mexico. As part of the response to the accident, monitoring cruises were deployed in fall 2010 to measure potential impacts on the two main soft-bottom benthic invertebrate groups: macrofauna and meiofauna. Sediment was collected using a multicorer so that samples for chemical, physical and biological analyses could be taken simultaneously and analyzed using multivariate methods. The footprint of the oil spill was identified by creating a new variable with principal components analysis where the first factor was indicative of the oil spill impacts and this new variable mapped in a geographic information system to identify the area of the oil spill footprint. The most severe relative reduction of faunal abundance and diversity extended to 3 km from the wellhead in all directions covering an area about 24 km(2. Moderate impacts were observed up to 17 km towards the southwest and 8.5 km towards the northeast of the wellhead, covering an area 148 km(2. Benthic effects were correlated to total petroleum hydrocarbon, polycyclic aromatic hydrocarbons and barium concentrations, and distance to the wellhead; but not distance to hydrocarbon seeps. Thus, benthic effects are more likely due to the oil spill, and not natural hydrocarbon seepage. Recovery rates in the deep sea are likely to be slow, on the order of decades or longer.

  2. A deep belief network with PLSR for nonlinear system modeling.

    Science.gov (United States)

    Qiao, Junfei; Wang, Gongming; Li, Wenjing; Li, Xiaoli

    2017-10-31

    Nonlinear system modeling plays an important role in practical engineering, and deep learning-based deep belief network (DBN) is now popular in nonlinear system modeling and identification because of the strong learning ability. However, the existing weights optimization for DBN is based on gradient, which always leads to a local optimum and a poor training result. In this paper, a DBN with partial least square regression (PLSR-DBN) is proposed for nonlinear system modeling, which focuses on the problem of weights optimization for DBN using PLSR. Firstly, unsupervised contrastive divergence (CD) algorithm is used in weights initialization. Secondly, initial weights derived from CD algorithm are optimized through layer-by-layer PLSR modeling from top layer to bottom layer. Instead of gradient method, PLSR-DBN can determine the optimal weights using several PLSR models, so that a better performance of PLSR-DBN is achieved. Then, the analysis of convergence is theoretically given to guarantee the effectiveness of the proposed PLSR-DBN model. Finally, the proposed PLSR-DBN is tested on two benchmark nonlinear systems and an actual wastewater treatment system as well as a handwritten digit recognition (nonlinear mapping and modeling) with high-dimension input data. The experiment results show that the proposed PLSR-DBN has better performances of time and accuracy on nonlinear system modeling than that of other methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Deep convolutional neural network for mammographic density segmentation

    Science.gov (United States)

    Wei, Jun; Li, Songfeng; Chan, Heang-Ping; Helvie, Mark A.; Roubidoux, Marilyn A.; Lu, Yao; Zhou, Chuan; Hadjiiski, Lubomir; Samala, Ravi K.

    2018-02-01

    Breast density is one of the most significant factors for cancer risk. In this study, we proposed a supervised deep learning approach for automated estimation of percentage density (PD) on digital mammography (DM). The deep convolutional neural network (DCNN) was trained to estimate a probability map of breast density (PMD). PD was calculated as the ratio of the dense area to the breast area based on the probability of each pixel belonging to dense region or fatty region at a decision threshold of 0.5. The DCNN estimate was compared to a feature-based statistical learning approach, in which gray level, texture and morphological features were extracted from each ROI and the least absolute shrinkage and selection operator (LASSO) was used to select and combine the useful features to generate the PMD. The reference PD of each image was provided by two experienced MQSA radiologists. With IRB approval, we retrospectively collected 347 DMs from patient files at our institution. The 10-fold cross-validation results showed a strong correlation r=0.96 between the DCNN estimation and interactive segmentation by radiologists while that of the feature-based statistical learning approach vs radiologists' segmentation had a correlation r=0.78. The difference between the segmentation by DCNN and by radiologists was significantly smaller than that between the feature-based learning approach and radiologists (p approach has the potential to replace radiologists' interactive thresholding in PD estimation on DMs.

  4. Large deep neural networks for MS lesion segmentation

    Science.gov (United States)

    Prieto, Juan C.; Cavallari, Michele; Palotai, Miklos; Morales Pinzon, Alfredo; Egorova, Svetlana; Styner, Martin; Guttmann, Charles R. G.

    2017-02-01

    Multiple sclerosis (MS) is a multi-factorial autoimmune disorder, characterized by spatial and temporal dissemination of brain lesions that are visible in T2-weighted and Proton Density (PD) MRI. Assessment of lesion burden and is useful for monitoring the course of the disease, and assessing correlates of clinical outcomes. Although there are established semi-automated methods to measure lesion volume, most of them require human interaction and editing, which are time consuming and limits the ability to analyze large sets of data with high accuracy. The primary objective of this work is to improve existing segmentation algorithms and accelerate the time consuming operation of identifying and validating MS lesions. In this paper, a Deep Neural Network for MS Lesion Segmentation is implemented. The MS lesion samples are extracted from the Partners Comprehensive Longitudinal Investigation of Multiple Sclerosis (CLIMB) study. A set of 900 subjects with T2, PD and a manually corrected label map images were used to train a Deep Neural Network and identify MS lesions. Initial tests using this network achieved a 90% accuracy rate. A secondary goal was to enable this data repository for big data analysis by using this algorithm to segment the remaining cases available in the CLIMB repository.

  5. Generalized Smooth Transition Map Between Tent and Logistic Maps

    Science.gov (United States)

    Sayed, Wafaa S.; Fahmy, Hossam A. H.; Rezk, Ahmed A.; Radwan, Ahmed G.

    There is a continuous demand on novel chaotic generators to be employed in various modeling and pseudo-random number generation applications. This paper proposes a new chaotic map which is a general form for one-dimensional discrete-time maps employing the power function with the tent and logistic maps as special cases. The proposed map uses extra parameters to provide responses that fit multiple applications for which conventional maps were not enough. The proposed generalization covers also maps whose iterative relations are not based on polynomials, i.e. with fractional powers. We introduce a framework for analyzing the proposed map mathematically and predicting its behavior for various combinations of its parameters. In addition, we present and explain the transition map which results in intermediate responses as the parameters vary from their values corresponding to tent map to those corresponding to logistic map case. We study the properties of the proposed map including graph of the map equation, general bifurcation diagram and its key-points, output sequences, and maximum Lyapunov exponent. We present further explorations such as effects of scaling, system response with respect to the new parameters, and operating ranges other than transition region. Finally, a stream cipher system based on the generalized transition map validates its utility for image encryption applications. The system allows the construction of more efficient encryption keys which enhances its sensitivity and other cryptographic properties.

  6. Okeanos Explorer (EX1606): CAPSTONE Wake Island Unit PRIMNM (ROV & Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will use the ship’s deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, ADCPs, and Knudsen 3260 chirp...

  7. Okeanos Explorer (EX1605L2): CAPSTONE CNMI and Mariana Trench MNM (Mapping)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operations will use the ship’s deep water mapping systems (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, ADCPs, and Knudsen 3260 chirp...

  8. Analyses of the deep borehole drilling status for a deep borehole disposal system

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jong Youl; Choi, Heui Joo; Lee, Min Soo; Kim, Geon Young; Kim, Kyung Su [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    The purpose of disposal for radioactive wastes is not only to isolate them from humans, but also to inhibit leakage of any radioactive materials into the accessible environment. Because of the extremely high level and long-time scale radioactivity of HLW(High-level radioactive waste), a mined deep geological disposal concept, the disposal depth is about 500 m below ground, is considered as the safest method to isolate the spent fuels or high-level radioactive waste from the human environment with the best available technology at present time. Therefore, as an alternative disposal concept, i.e., deep borehole disposal technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general status of deep drilling technologies was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, very preliminary applicability of deep drilling technology for deep borehole disposal analyzed. In this paper, as one of key technologies of deep borehole disposal system, the general status of deep drilling technologies in oil industry, geothermal industry and geo scientific field was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, the very preliminary applicability of deep drilling technology for deep borehole disposal such as relation between depth and diameter, drilling time and feasibility classification was analyzed.

  9. Status and prospects of exploration and exploitation key technologies of the deep petroleum resources in onshore China

    Directory of Open Access Journals (Sweden)

    Genshun Yao

    2018-02-01

    Full Text Available In recent years, China's deep oil and gas exploration and exploitation have developed rapidly. Technological advancements have played an important role in the rapid exploration and highly efficient development. Aimed at the complex engineering geological environment of deep oil and gas in China, this paper has combined the four technological systems that have made significant progress, mainly including: (1 seismic imaging and reservoir prediction techniques for deep–burial complex structures, includign “2W1S” technique (wide-band, wide azimuth, and small bin, RTM (Reverse Time Migration, integrated modeling technology for complex structures and variable velocity mapping technique, improving structural interpretation accuracy, ensuring high precision ofimaging, and prediction for deep geological bodies; (2 deep speed raising and efficiency drilling technology series, which significantly improved the drilling speed, in turn reduced the drilling cost and drilling risk; (3 development of a deep high-temperature and high-pressure logging technology series, which provided a guarantee for the accurate identification of reservoir properties and fluid properties; (4 the efficient development technology for deep reservoirs, especially the development and maturity of the reconstruction volume technology, improve the production of single well and the benefit of deep oil and gas development. This paper further points out the improvement direction of the four major technology series of deep oil based on the analysis of the current development of the four major technological systems. Moreover, the development of applicability and economy for technical system is the key to realize high efficiency and low-cost exploration and development of deep oil and gas. Keywords: Deep oil & gas, Exploration and exploitation technologies, Seismic, Logging, Drilling, Petroleum reservoir stimulation

  10. Changes in brain glucose metabolism in subthalamic nucleus deep brain stimulation for advanced Parkinson's disease.

    Science.gov (United States)

    Volonté, M A; Garibotto, V; Spagnolo, F; Panzacchi, A; Picozzi, P; Franzin, A; Giovannini, E; Leocani, L; Cursi, M; Comi, G; Perani, D

    2012-07-01

    Despite its large clinical application, our understanding about the mechanisms of action of deep brain stimulation of the subthalamic nucleus is still limited. Aim of the present study was to explore cortical and subcortical metabolic modulations measured by Positron Emission Tomography associated with improved motor manifestations after deep brain stimulation in Parkinson disease, comparing the ON and OFF conditions. Investigations were performed in the stimulator off- and on-conditions in 14 parkinsonian patients and results were compared with a group of matched healthy controls. The results were also used to correlate metabolic changes with the clinical effectiveness of the procedure. The comparisons using Statistical parametric mapping revealed a brain metabolic pattern typical of advanced Parkinson disease. The direct comparison in ON vs OFF condition showed mainly an increased metabolism in subthalamic regions, corresponding to the deep brain stimulation site. A positive correlation exists between neurostimulation clinical effectiveness and metabolic differences in ON and OFF state, including the primary sensorimotor, premotor and parietal cortices, anterior cingulate cortex. Deep brain stimulation seems to operate modulating the neuronal network rather than merely exciting or inhibiting basal ganglia nuclei. Correlations with Parkinson Disease cardinal features suggest that the improvement of specific motor signs associated with deep brain stimulation might be explained by the functional modulation, not only in the target region, but also in surrounding and remote connecting areas, resulting in clinically beneficial effects. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters

    Directory of Open Access Journals (Sweden)

    Yongyang Xu

    2018-01-01

    Full Text Available Very high resolution (VHR remote sensing imagery has been used for land cover classification, and it tends to a transition from land-use classification to pixel-level semantic segmentation. Inspired by the recent success of deep learning and the filter method in computer vision, this work provides a segmentation model, which designs an image segmentation neural network based on the deep residual networks and uses a guided filter to extract buildings in remote sensing imagery. Our method includes the following steps: first, the VHR remote sensing imagery is preprocessed and some hand-crafted features are calculated. Second, a designed deep network architecture is trained with the urban district remote sensing image to extract buildings at the pixel level. Third, a guided filter is employed to optimize the classification map produced by deep learning; at the same time, some salt-and-pepper noise is removed. Experimental results based on the Vaihingen and Potsdam datasets demonstrate that our method, which benefits from neural networks and guided filtering, achieves a higher overall accuracy when compared with other machine learning and deep learning methods. The method proposed shows outstanding performance in terms of the building extraction from diversified objects in the urban district.

  12. MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

    Science.gov (United States)

    Fang, Chao; Shang, Yi; Xu, Dong

    2018-05-01

    Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

  13. Overview of deep learning in medical imaging.

    Science.gov (United States)

    Suzuki, Kenji

    2017-09-01

    The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a

  14. Analytic mappings: a new approach in particle production by accelerated observers

    International Nuclear Information System (INIS)

    Sanchez, N.

    1982-01-01

    This is a summary of the authors recent results about physical consequences of analytic mappings in the space-time. Classically, the mapping defines an accelerated frame. At the quantum level it gives rise to particle production. Statistically, the real singularities of the mapping have associated temperatures. This concerns a new approach in Q.F.T. as formulated in accelerated frames. It has been considered as a first step in the understanding of the deep connection that could exist between the structure (geometry and topology) of the space-time and thermodynamics, mainly motivated by the works of Hawking since 1975. (Auth.)

  15. USGS Imagery Only Base Map Service from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images...

  16. Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

    Directory of Open Access Journals (Sweden)

    Joel Saltz

    2018-04-01

    Full Text Available Summary: Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment. : Tumor-infiltrating lymphocytes (TILs were identified from standard pathology cancer images by a deep-learning-derived “computational stain” developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles. Keywords: digital pathology, immuno-oncology, machine learning, lymphocytes, tumor microenvironment, deep learning, tumor-infiltrating lymphocytes, artificial intelligence, bioinformatics, computer vision

  17. WFIRST: Science from Deep Field Surveys

    Science.gov (United States)

    Koekemoer, Anton; Foley, Ryan; WFIRST Deep Field Working Group

    2018-01-01

    WFIRST will enable deep field imaging across much larger areas than those previously obtained with Hubble, opening up completely new areas of parameter space for extragalactic deep fields including cosmology, supernova and galaxy evolution science. The instantaneous field of view of the Wide Field Instrument (WFI) is about 0.3 square degrees, which would for example yield an Ultra Deep Field (UDF) reaching similar depths at visible and near-infrared wavelengths to that obtained with Hubble, over an area about 100-200 times larger, for a comparable investment in time. Moreover, wider fields on scales of 10-20 square degrees could achieve depths comparable to large HST surveys at medium depths such as GOODS and CANDELS, and would enable multi-epoch supernova science that could be matched in area to LSST Deep Drilling fields or other large survey areas. Such fields may benefit from being placed on locations in the sky that have ancillary multi-band imaging or spectroscopy from other facilities, from the ground or in space. The WFIRST Deep Fields Working Group has been examining the science considerations for various types of deep fields that may be obtained with WFIRST, and present here a summary of the various properties of different locations in the sky that may be considered for future deep fields with WFIRST.

  18. Deep Learning and Its Applications in Biomedicine.

    Science.gov (United States)

    Cao, Chensi; Liu, Feng; Tan, Hai; Song, Deshou; Shu, Wenjie; Li, Weizhong; Zhou, Yiming; Bo, Xiaochen; Xie, Zhi

    2018-02-01

    Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning applications, including medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. Finally, we offer our perspectives for the future directions in the field of deep learning. Copyright © 2018. Production and hosting by Elsevier B.V.

  19. The deep lymphatic anatomy of the hand.

    Science.gov (United States)

    Ma, Chuan-Xiang; Pan, Wei-Ren; Liu, Zhi-An; Zeng, Fan-Qiang; Qiu, Zhi-Qiang

    2018-04-03

    The deep lymphatic anatomy of the hand still remains the least described in medical literature. Eight hands were harvested from four nonembalmed human cadavers amputated above the wrist. A small amount of 6% hydrogen peroxide was employed to detect the lymphatic vessels around the superficial and deep palmar vascular arches, in webs from the index to little fingers, the thenar and hypothenar areas. A 30-gauge needle was inserted into the vessels and injected with a barium sulphate compound. Each specimen was dissected, photographed and radiographed to demonstrate deep lymphatic distribution of the hand. Five groups of deep collecting lymph vessels were found in the hand: superficial palmar arch lymph vessel (SPALV); deep palmar arch lymph vessel (DPALV); thenar lymph vessel (TLV); hypothenar lymph vessel (HTLV); deep finger web lymph vessel (DFWLV). Each group of vessels drained in different directions first, then all turned and ran towards the wrist in different layers. The deep lymphatic drainage of the hand has been presented. The results will provide an anatomical basis for clinical management, educational reference and scientific research. Copyright © 2018 Elsevier GmbH. All rights reserved.

  20. Concept Mapping for Higher Order Thinking

    Directory of Open Access Journals (Sweden)

    Susan Marie Zvacek

    2013-02-01

    Full Text Available Engineering education is facing a changing world in which how one thinks is becoming more important than what one thinks; that is, our course content is important but constantly changing and we need to help students learn how to think about that content.Today’s students have grown accustomed to immediate rewards, multi-channel stimuli, and rapid-fire communications.  As a result, they are often impatient and suffer a lack of focus. When reflection is called for in the learning process - a time consuming practice - students may find it difficult to overcome the conflict between their typically speedy management of priorities and the focused, time-intensive thinking required to acquire a strong foundation of declarative knowledge.Therefore, the exploration of tools to facilitate the formation of deep knowledge structures is essential. One instructional strategy that shows promise is the use of concept mapping, a learning activity that requires students to explain their understanding of important ideas and the relationships among those ideas.  This paper describes a pilot project to integrate concept mapping into a Mechanical Engineering Course and the preliminary results of that project.This project has been established within the Working Group of “Tools for Developing High Order Thinking Skills”, of the Portuguese Society for Engineering Education, in which the first author is the leader and the other two co-authors, are working group members

  1. A Physics-Based Deep Learning Approach to Shadow Invariant Representations of Hyperspectral Images.

    Science.gov (United States)

    Windrim, Lloyd; Ramakrishnan, Rishi; Melkumyan, Arman; Murphy, Richard J

    2018-02-01

    This paper proposes the Relit Spectral Angle-Stacked Autoencoder, a novel unsupervised feature learning approach for mapping pixel reflectances to illumination invariant encodings. This work extends the Spectral Angle-Stacked Autoencoder so that it can learn a shadow-invariant mapping. The method is inspired by a deep learning technique, Denoising Autoencoders, with the incorporation of a physics-based model for illumination such that the algorithm learns a shadow invariant mapping without the need for any labelled training data, additional sensors, a priori knowledge of the scene or the assumption of Planckian illumination. The method is evaluated using datasets captured from several different cameras, with experiments to demonstrate the illumination invariance of the features and how they can be used practically to improve the performance of high-level perception algorithms that operate on images acquired outdoors.

  2. Hello World Deep Learning in Medical Imaging.

    Science.gov (United States)

    Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

    2018-05-03

    There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

  3. Deep Generative Models for Molecular Science

    DEFF Research Database (Denmark)

    Jørgensen, Peter Bjørn; Schmidt, Mikkel Nørgaard; Winther, Ole

    2018-01-01

    Generative deep machine learning models now rival traditional quantum-mechanical computations in predicting properties of new structures, and they come with a significantly lower computational cost, opening new avenues in computational molecular science. In the last few years, a variety of deep...... generative models have been proposed for modeling molecules, which differ in both their model structure and choice of input features. We review these recent advances within deep generative models for predicting molecular properties, with particular focus on models based on the probabilistic autoencoder (or...

  4. Harnessing the Deep Web: Present and Future

    OpenAIRE

    Madhavan, Jayant; Afanasiev, Loredana; Antova, Lyublena; Halevy, Alon

    2009-01-01

    Over the past few years, we have built a system that has exposed large volumes of Deep-Web content to Google.com users. The content that our system exposes contributes to more than 1000 search queries per-second and spans over 50 languages and hundreds of domains. The Deep Web has long been acknowledged to be a major source of structured data on the web, and hence accessing Deep-Web content has long been a problem of interest in the data management community. In this paper, we report on where...

  5. Desalination Economic Evaluation Program (DEEP). User's manual

    International Nuclear Information System (INIS)

    2000-01-01

    DEEP (formerly named ''Co-generation and Desalination Economic Evaluation'' Spreadsheet, CDEE) has been developed originally by General Atomics under contract, and has been used in the IAEA's feasibility studies. For further confidence in the software, it was validated in March 1998. After that, a user friendly version has been issued under the name of DEEP at the end of 1998. DEEP output includes the levelised cost of water and power, a breakdown of cost components, energy consumption and net saleable power for each selected option. Specific power plants can be modelled by adjustment of input data including design power, power cycle parameters and costs

  6. Zooplankton at deep Red Sea brine pools

    KAUST Repository

    Kaartvedt, Stein

    2016-03-02

    The deep-sea anoxic brines of the Red Sea comprise unique, complex and extreme habitats. These environments are too harsh for metazoans, while the brine–seawater interface harbors dense microbial populations. We investigated the adjacent pelagic fauna at two brine pools using net tows, video records from a remotely operated vehicle and submerged echosounders. Waters just above the brine pool of Atlantis II Deep (2000 m depth) appeared depleted of macrofauna. In contrast, the fauna appeared to be enriched at the Kebrit Deep brine–seawater interface (1466 m).

  7. Letters of Map Change (LOMC)

    Data.gov (United States)

    Department of Homeland Security — Documents, including different types of Letters of MAP Revision (LOMR) and Letters of Map Amendment (LOMA), which are issued by FEMA to revise or amend the flood...

  8. NEPR Geographic Zone Map 2015

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This geographic zone map was created by interpreting satellite and aerial imagery, seafloor topography (bathymetry model), and the new NEPR Benthic Habitat Map...

  9. NEPR Benthic Habitat Map 2015

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This benthic habitat map was created from a semi-automated habitat mapping process, using a combination of bathymetry, satellite imagery, aerial imagery and...

  10. Map Usage in Virtual Environments

    National Research Council Canada - National Science Library

    Cevik, Helsin

    1998-01-01

    ... of map representation as an aid in performing navigation tasks. The approach taken was first to determine and then investigate the parameters that affect virtual map representation through an experiment designed specifically for this thesis...

  11. q-Deformed nonlinear maps

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics; Volume 64; Issue 3 ... Keywords. Nonlinear dynamics; logistic map; -deformation; Tsallis statistics. ... As a specific example, a -deformation procedure is applied to the logistic map. Compared ...

  12. The Europa Global Geologic Map

    Science.gov (United States)

    Leonard, E. J.; Patthoff, D. A.; Senske, D. A.; Collins, G. C.

    2018-06-01

    The Europa Global Geologic Map reveals three periods in Europa's surface history as well as an interesting distribution of microchaos. We will discuss the mapping and the interesting implications of our analysis of Europa's surface.

  13. Map projections cartographic information systems

    CERN Document Server

    Grafarend, Erik W; Syffus, Rainer

    2014-01-01

    This book offers a timely review of map projections including sphere, ellipsoid, rotational surfaces, and geodetic datum transformations. Coverage includes computer vision, and remote sensing space projective mappings in photogrammetry.

  14. Map projections cartographic information systems

    CERN Document Server

    Grafarend, Erik W

    2006-01-01

    In the context of Geographical Information Systems (GIS) the book offers a timely review of map projections (sphere, ellipsoid, rotational surfaces) and geodetic datum transformations. For the needs of photogrammetry, computer vision, and remote sensing space projective mappings are reviewed.

  15. Universal map for cellular automata

    International Nuclear Information System (INIS)

    García-Morales, V.

    2012-01-01

    A universal map is derived for all deterministic 1D cellular automata (CAs) containing no freely adjustable parameters and valid for any alphabet size and any neighborhood range (including non-symmetrical neighborhoods). The map can be extended to an arbitrary number of dimensions and topologies and to arbitrary order in time. Specific CA maps for the famous Conway's Game of Life and Wolfram's 256 elementary CAs are given. An induction method for CAs, based in the universal map, allows mathematical expressions for the orbits of a wide variety of elementary CAs to be systematically derived. -- Highlights: ► A universal map is derived for all deterministic 1D cellular automata (CA). ► The map is generalized to 2D for Von Neumann, Moore and hexagonal neighborhoods. ► A map for all Wolfram's 256 elementary CAs is derived. ► A map for Conway's “Game of Life” is obtained.

  16. North America Synoptic Weather Maps

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Series of Synoptic Weather Maps. Maps contains a surface analysis comprised of plotted weather station observations, isobars indicating low and high-pressure...

  17. Associators in generalized octonionic maps

    International Nuclear Information System (INIS)

    Griffin, C.J.; Joshi, G.C.

    1994-01-01

    Generalizing previous work, it is shown that structural transitions are a general property of a large class of octonionic maps. They can thus be used as an indicator of non-associativity in an octonionic map. 7 refs., ills

  18. Mapping earthworm communities in Europe

    NARCIS (Netherlands)

    Rutgers, M.; Orgiazzi, A.; Gardi, C.; Römbke, J.; Jansch, S.; Keith, A.; Neilson, R.; Boag, B.; Schmidt, O.; Murchie, A.K.; Blackshaw, R.P.; Pérès, G.; Cluzeau, D.; Guernion, M.; Briones, M.J.I.; Rodeiro, J.; Pineiro, R.; Diaz Cosin, D.J.; Sousa, J.P.; Suhadolc, M.; Kos, I.; Krogh, P.H.; Faber, J.H.; Mulder, C.; Bogte, J.J.; Wijnen, van H.J.; Schouten, A.J.; Zwart, de D.

    2016-01-01

    Existing data sets on earthworm communities in Europe were collected, harmonized, collated, modelled and depicted on a soil biodiversity map. Digital Soil Mapping was applied using multiple regressions relating relatively low density earthworm community data to soil characteristics, land use,

  19. Map Usage in Virtual Environments

    National Research Council Canada - National Science Library

    Cevik, Helsin

    1998-01-01

    .... Instead, we can determine the parameters that affect virtual map representation and that help to construct a mental map, and then manipulate these parameters in order to increase the effectiveness...

  20. Quicksilver: Fast predictive image registration - A deep learning approach.

    Science.gov (United States)

    Yang, Xiao; Kwitt, Roland; Styner, Martin; Niethammer, Marc

    2017-09-01

    This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver registration for image-pairs works by patch-wise prediction of a deformation model based directly on image appearance. A deep encoder-decoder network is used as the prediction model. While the prediction strategy is general, we focus on predictions for the Large Deformation Diffeomorphic Metric Mapping (LDDMM) model. Specifically, we predict the momentum-parameterization of LDDMM, which facilitates a patch-wise prediction strategy while maintaining the theoretical properties of LDDMM, such as guaranteed diffeomorphic mappings for sufficiently strong regularization. We also provide a probabilistic version of our prediction network which can be sampled during the testing time to calculate uncertainties in the predicted deformations. Finally, we introduce a new correction network which greatly increases the prediction accuracy of an already existing prediction network. We show experimental results for uni-modal atlas-to-image as well as uni-/multi-modal image-to-image registrations. These experiments demonstrate that our method accurately predicts registrations obtained by numerical optimization, is very fast, achieves state-of-the-art registration results on four standard validation datasets, and can jointly learn an image similarity measure. Quicksilver is freely available as an open-source software. Copyright © 2017 Elsevier Inc. All rights reserved.